A New Era for Space Life Science: International Standards for Space Omics Processing

Space agencies have announced plans for human missions to the Moon to prepare for Mars. However, the space environment presents stressors that include radiation, microgravity, and isolation. Understanding how these factors affect biology is crucial for safe and effective crewed space exploration. There is a need to develop countermeasures, to adapt plants and microbes for nutrient sources and bioregenerative life support, and to limit pathogen infection. Scientists across the world are conducting space omics experiments on model organisms and, more recently, on humans. Optimal extraction of actionable scientific discoveries from these precious datasets will only occur at the collective level with improved standardization. To address this shortcoming, we established ISSOP (International Standards for Space Omics Processing), an international consortium of scientists who aim to enhance standard guidelines between space biologists at a global level. Here we introduce our consortium and share past lessons learned and future challenges related to spaceflight omics.

JAXA protein crystallization in space: ongoing improvements for growing high-quality crystals

The Japan Aerospace Exploration Agency (JAXA) started a high-quality protein crystal growth project, now called JAXA PCG, on the International Space Station (ISS) in 2002. Using the counter-diffusion technique, 14 sessions of experiments have been performed as of 2012 with 580 proteins crystallized in total. Over the course of these experiments, a user-friendly interface framework for high accessibility has been constructed and crystallization techniques improved; devices to maximize the use of the microgravity environment have been designed, resulting in some high-resolution crystal growth. If crystallization conditions were carefully fixed in ground-based experiments, high-quality protein crystals grew in microgravity in many experiments on the ISS, especially when a highly homogeneous protein sample and a viscous crystallization solution were employed. In this article, the current status of JAXA PCG is discussed, and a rational approach to high-quality protein crystal growth in microgravity based on numerical analyses is explained.

Estimation of malaria incidence in northern Namibia in 2009 using Bayesian conditional-autoregressive spatial-temporal models

As malaria transmission declines, it becomes increasingly important to monitor changes in malaria incidence rather than prevalence. Here, a spatio-temporal model was used to identify constituencies with high malaria incidence to guide malaria control. Malaria cases were assembled across all age groups along with several environmental covariates. A Bayesian conditional-autoregressive model was used to model the spatial and temporal variation of incidence after adjusting for test positivity rates and health facility utilisation. Of the 144,744 malaria cases recorded in Namibia in 2009, 134,851 were suspected and 9893 were parasitologically confirmed. The mean annual incidence based on the Bayesian model predictions was 13 cases per 1000 population with the highest incidence predicted for constituencies bordering Angola and Zambia. The smoothed maps of incidence highlight trends in disease incidence. For Namibia, the 2009 maps provide a baseline for monitoring the targets of pre-elimination.