Handy, D. | Search bioRxiv

bioRxiv2026

Growth and molecular responses of potato to lunar regolith simulants

BackgroundOn-site food production will be required to achieve NASAs goal of a sustainable Lunar habitat. Toward this end, the use of fine, soil-like material on the Lunar surface, known as regolith, has been proposed as a plant growth substrate. However, how this substrate may affect plant growth is not well understood. Lunar regolith is devoid of the organic materials that make soils on earth fertile for plant growth, and has been weathered by solar winds, cosmic rays, and micrometeorite impacts. Additionally, regolith at certain lunar sites may contain heavy metals. These metal ions may leech, thus posing challenges with accumulation in plant material. To address and verify the efficacy of regolith-based crop production, we used lunar regolith simulants (LRS). We investigated the effects of LRS on potato (Solanum tuberosum cv Modoc) plant and tuber development, gene expression, and nutrition profiles. ResultsGrowth in LRS negatively impacted the potato plant size and tuber yield. While the degree of impact differed between simulants, all plants grown in LRS were statistically significantly shorter in height than plants grown in control soil. Further experiments with the lunar mare simulant 1E (LMS-1E) show that these effects can be ameliorated through the addition of vermicompost, an organic component, with a 70:30 v/v ratio of LMS-1E to compost being virtually indistinguishable from controls. Changes in gene expression profiles also differed between simulants, with genes related to photosynthesis, biotic and abiotic stress responses, signaling, and terpenes and flavonoids metabolism being commonly altered. Despite these observed differences in transcription, broad changes in metabolite profiles were not observed. ConclusionsLRS are clearly stressful on plants. However, amendment of the substrate with composted materials appears to be a viable strategy to alleviate stress. Given these observations, regolith-based agriculture may not be viable for very early food production when organic matter content is low. However, this would improve over time with continual incorporation of organic matter to regolith. As such, we believe regolith-based agriculture is a viable long-term strategy.

plant biology↗

bioRxiv2024

DREAMER: Exploring Common Mechanisms of Adverse Drug Reactions and Disease Phenotypes through Network-Based Analysis

Adverse drug reactions (ADRs) are a major concern in clinical healthcare, significantly affecting patient safety and drug development. The need for a deeper understanding of ADR mechanisms is crucial for improving drug safety profiles in drug design and drug repurposing. This study introduces DREAMER (Drug adverse REAction Mechanism ExplaineR), a novel network-based method for exploring the mechanisms underlying adverse drug reactions and disease phenotypes at a molecular level by leveraging a comprehensive knowledge graph obtained from various datasets. By considering drugs and diseases that cause similar phenotypes, and investigating their commonalities regarding their impact on specific modules of the protein-protein interaction network, DREAMER can robustly identify protein sets associated with the biological mechanisms underlying ADRs and unravel the causal relationships that contribute to the observed clinical outcomes. Applying DREAMER to 649 ADRs, we identified proteins associated with the mechanism of action for 67 ADRs across multiple organ systems, e.g., ventricular arrhythmia, metabolic acidosis, and interstitial pneumonitis. In particular, DREAMER highlights the importance of GABAergic signaling and proteins of the coagulation pathways for personality disorders and intracranial hemorrhage, respectively. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol (targeting KCNH2), ranolazine (targeting SCN5A, currently under clinical trial), and diltiazem (indicated drug targeting CACNA1C and SCN3A) as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.

systems biology↗