Microbes interact with humans in complex ways and understanding how they respond to the spaceflight environment is important to the success of future manned spaceflight missions. The BRIC-23 mission was designed to measure the response of Bacillus subtilis and Staphylococcus aureus to the spaceflight environment. This experiment aimed to produce high quality omics data from B. subtilis and S. aureus grown aboard the International Space Station (ISS) to allow comparison to matched ground controls. There were two primary objectives for this experiment: (1) Demonstrate all post-flight processes and operations required for successful completion of GeneLab Reference Missions conducted on ISS, and (2) Generate high quality GeneLab Reference Mission omics data sets for two prokaryotic model organisms, Bacillus subtilis and Staphylococcus aureus. Freezing Control Experiment: The BRIC hardware has significant thermal inertia, thus the freezing rate of samples placed at -80 C is quite slow. This could affect RNA-sequencing, proteomic and metabolic data sets. In an effort to understand how slow freezing could affect these data sets, a control experiment was designed in which B. subtilis and S. aureus were grown in petri plates and either slow frozen to -80 C at a rate matching the BRIC-23 spaceflight samples or processed immediately to harvest RNA and protein. S. aureus omics data is deposited in GLDS-145.

,Using the SHIME (an in vitro simulator of the human gut microbiome) we tracked the fate of the probiotic Lacticaseibacillus rhamnosus GG (LGG) over time and across colonic regions. Using fecal inoculum from three healthy human donors, reactors were established representing three colonic regions and both the luminal and mucosal microbiome in those regions. Community composition before, during, and after inoculation of the reactors with LGG as well as short chain fatty acid concentrations representing microbiome metabolic outputs. This dataset includes short-chain fatty acid concentrations and qPCR-based cell concentrations. Raw 16S rRNA amplicon sequencing of the V1-V2 regions can be found in the NCBI Sequence Read Archive associated with BioProject PRJNA893635: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA893635.,Resources in this dataset:,

,Data collected from Phenotypic Microarray (PM) plates PM01 and PM02, using an Omnilog system for the characterization of four species of Levilactobacillus brevis autochthonous to commercial cucumber fermentations and two ATCC reference strains, ATCC14869 and ATCC367. Each PM plate was duplicated for each isolate and the cells were prepared as suggested by the manufacturer. Omnilog data is the result of a screening and phenotypes should be confirmed using conditions that mimic the habitat of interest. This dataset was generated for scientific research purpose only. The Levilactobacillus brevis isolates included in this dataset have publicly available genome sequences described in the Microbiology Resource Announcement peer reviewed journal.,Resources in this dataset:,

RR-1 is a validation flight to evaluate the hardware operational and science capabilities of the Rodent Research Project on the ISS. RNA DNA and protein were purified from liver tissues from RR-1 mice (female C57BL/6J 16wk old at time of launch). From each group two liver samples were collected and frozen immediately after euthanasia. The rest of the liver samples from each group were collected from frozen carcasses dissected post-flight. RNA-Seq whole genome and RNA BS-Seq (bisulfite sequencing) and proteomic expression profiling were performed. xc2 xa0RNA extracted from these tissues was re-sequenced; these data are available as part of GLDS-168 (https://genelab-data.ndc.nasa.gov/genelab/accession/GLDS-168). xc2 xa0

The data is in the form of genomic sequences deposited in a public database, growth curves, and bioinformatic analysis of sequences. This dataset is associated with the following publication: Henson, M., J. Santodomingo , P. Kourtev, R. Jensen, and D. Learman. Metabolic and genomic analysis elucidates strain-level variation in Microbacterium spp. isolated from chromate contaminated sediment. PeerJ. PeerJ Inc., Corte Madera, CA, USA, e1395, (2015).

A comprehensive, integrated, non-redundant, well-annotated set of reference sequences including genomic, transcript, and protein.

To assess the variability of low-abundance oligonucleotide detection across sample matrices, we spiked DNA reference standards (meta sequins) into replicate wastewater DNA extracts at logarithmically decreasing mass-to-mass percentages (m/m%) and deeply sequenced them on the Illumina platform. This dataset summarizes the experimental conditions and results of the detection frequencies of those oligonucleotides as well as detailed descriptions of the DNA reference standards used. This dataset is associated with the following publication: Davis, B., P. Vikesland, and A. Pruden. Evaluating Quantitative Metagenomics for Environmental Monitoring of Antibiotic Resistance and Establishing Detection Limits. ENVIRONMENTAL SCIENCE & TECHNOLOGY. American Chemical Society, Washington, DC, USA, 59(12): 6192-6202, (2025).

Saccharomyces cerevisiae flocculation occurs when fermentable sugars are limiting and is therefore considered as a way to enhance the survival chance of Flo-expressing yeast cells. In this paper the role of Flo1p in mating was demonstrated by showing that the mating efficiency which contributes to the increased survival rate as well by generating genetic variability is increased when cells flocculate. This was revealed by liquid growth experiments in a low shear environment and differential transcriptome analysis of FLO1 expressing cells compared to the non-flocculent wild-type cells. The results show that a floc provides a uniquely organized multicellular ultrastructure that provides a suitable microenvironment to induce and perform cell conjugation. S. cerevisiae strains BY4742 WT BY4742::FLO8 and BY4742 [FLO1] were grown in microgravity and 1-g. A transcriptomic analysis was performed and the transcriptome data were integrated with the high quality protein-protein interaction networks. The identified high score sub-networks (qvalue < 0.001) were considered and further evaluated concerning their GO enrichment using a hypogeometric test. The data were from the Ying B-1 experiment.