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Space Algae: Understanding the Genomic Impacts on Microalgae After Growth in the International Space Station

Plants and microbes can be used for biological support of crewed space missions. The radiation and microgravity environment of spaceflight is expected to increase genetic mutation of all organisms. It is essential to understand how spaceflight impacts mutation rates in photosynthetic organisms to enable appropriate countermeasures and ensure productivity during long duration and deep space missions. The Space Algae flight experiments to the International Space Station (ISS) are studying the genomic stability of microalgae that could potentially be used in biological life support systems. Space Algae-1 grew ultraviolet light mutagenized Chlamydomonas reinhardtii in the VEGGIE plant growth chamber for approximately 40 mitotic generations over one month on the ISS. Whole genome sequencing from pooled cell samples every 10 generations revealed that spaceflight cultures had an ~50% increase in DNA polymorphisms relative to ground controls. These mutations had a novel base substitution signature and suggested a risk that microalgae may be unstable for long-term production in space. Space Algae-2 is focusing on the edible cyanobacterium Arthrospira platensis, commonly known as Spirulina. This experiment seeks to grow serial cultures to allow the organism to evolve in long-term spaceflight. Biological responses of the cells to spaceflight will be assessed with multi-omics analyses to determine mutation load, gene/protein expression, metabolic/nutritional composition, and cell morphology.

Algae↗

NASA NTRSDate not supplied

Space Algae: Understanding the Genomic Impacts on Microalgae After Growth in the International Space Station

Plants and microbes can be used for biological support of crewed space missions. The radiation and microgravity environment of spaceflight is expected to increase genetic mutation of all organisms. It is essential to understand how spaceflight impacts mutation rates in photosynthetic organisms to enable appropriate countermeasures and ensure productivity during long duration and deep space missions. The Space Algae flight experiments to the International Space Station (ISS) are studying the genomic stability of microalgae that could potentially be used in biological life support systems. Space Algae-1 grew ultraviolet light mutagenized Chlamydomonas reinhardtii in the VEGGIE plant growth chamber for approximately 40 mitotic generations over one month on the ISS. Whole genome sequencing from pooled cell samples every 10 generations revealed that spaceflight cultures had an ~50% increase in DNA polymorphisms relative to ground controls. These mutations had a novel base substitution signature and suggested a risk that microalgae may be unstable for long-term production in space. Space Algae-2 is focusing on the edible cyanobacterium Arthrospira platensis, commonly known as Spirulina. This experiment seeks to grow serial cultures to allow the organism to evolve in long-term spaceflight. Biological responses of the cells to spaceflight will be assessed with multi-omics analyses to determine mutation load, gene/protein expression, metabolic/nutritional composition, and cell morphology.

Algae↗

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Benchmarking Computational Tools for Calling SNPs and Indels in Complex Microbial Populations

The NASA BioNutrients missions seek to understand the suitability of microorganisms for bioproduction during space flight. One topic of interest is the stability of microbial genomes during long-term ambient storage and subsequent rehydration and growth. To address these questions, samples from 8 species were flown to ISS for 5 years of desiccated storage at ambient temperature (Stasis Packs) and 2 species were packaged along with powdered media inside a bioreactor system to allow hydration and growth in microgravity (Production Packs). For both systems, Whole Genome Sequencing (WGS) of the DNA extracted from the returned samples and paired ground controls will be conducted to identify changes in genome stability due to time, storage conditions and growth in space. Across the technical replicates, ground controls, 10 timepoints, and multiple experimental conditions, ~300 samples have been selected for initial analysis with WGS sequencing to 100x coverage. A flexible and resource efficient mutation calling pipeline is needed to process this large dataset and allow for comparisons between species. Many bioinformatics tools for calling Indels and Single Nucleotide Variants (SNVs) are designed for use with pure isolates, where true variations from the reference genome are expected to dominate the reads aligning to the location of mutation. In contrast, DNA from the Stasis Pack (SP) samples was collected directly after recovery from desiccated storage and the Production Pack (PP) samples were collected after fermentation. In this context, reads with mutations are expected to be less frequent than reads that align with the reference genome, as each sample will include multiple lines of cells. Thus, BioNutrients samples are expected to be similar to samples from cancer cell or “pooled” sequencing approaches. In preparation for the analysis of the BioNutrients samples, we have tested three mutation calling tools (GATK for Microbes, BreSeq and DiscoSNP) designed for complex samples. A challenge of validating mutation identification pipelines is a lack of “Ground Truth” datasets, especially for complex samples. To compare these three tools, we sought to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO as part of the Space Algae-1 mission. Here we present a summary of these tools against the analysis originally conducted using the CRISP tool. Critical metrics are compared such as runtime, the number of SNPs, the number and size of Indels, and patterns of transversion and transitions identified by each tool are reported. By sharing these benchmarking results collected in support of the BioNutrients mission, we aim to guide others seeking to identify SNVs in similarly complex microbial samples.

Biology↗

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Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗