While AI holds the potential to revolutionize space life sciences, realizing this promise is contingent upon the systematic restructuring of heterogeneous spaceflight biological data into machine-actionable, AI-ready forms. Even though open access principles support human reuse and scientific reproducibility, this does not necessarily enable AI systems to access and analyze such a diverse set of scientific datasets. In addition, the growing array of AI approaches places distinct demands on data structure, metadata, and access interfaces. In order to respond to such growing changes we propose a three-tier approach, proceeding from FAIR to AI-ready to space-ready data. We discuss existing infrastructures and how they can be improved to close the AI access gap. We conclude by proposing a neutral international coordinating body as the governance backbone for the trustworthy, agent-accessible space biology infrastructure that deep space biological research will require.

Expression Atlas (https://www.ebi.ac.uk/gxa/home) is EMBL-EBI's comprehensive knowledgebase for gene and protein expression across tissues, cell types, conditions, and multiple species. Since our last update, Expression Atlas has expanded substantially in both content and functionality, now comprising >4500 studies from 67 species, with increased proteomics coverage and updated Genotype-Tissue Expression (GTEx) tissue profiles. The resource also includes hundreds of single-cell RNA-seq experiments spanning 21 species, among them externally analysed community datasets such as Tabula Sapiens and GTEx single-nucleus profiles, allowing exploration of curated atlases while maintaining their original analytical framework. Key methodological advances include a new marker gene analysis module for bulk baseline experiments, alongside workflow updates that improve reproducibility. Expression Atlas data are integrated into EMBL-EBI resources such as Ensembl, UniProt, and Europe PMC and disseminated through collaboration with model organism communities such as FlyBase and Gramene. The resource also supports translational research through the European Diagnostic Transcriptomic Library and integration with the Open Targets platform. Future directions include modernizing analysis pipelines, enhancing programmatic access, and delivering AI-ready data formats, strengthening Expression Atlas as a findable, accessible, interoperable, and reusable (FAIR) community-driven resource for both fundamental and translational discovery.

RNAcentral was founded in 2014 to serve as a comprehensive database of non-coding RNA sequences. It began by providing a single unified interface to more specialised resources, and now contains 45 million sequences. It has grown beyond providing a single interface to many specialised resources and now provides several services and analyses. These include secondary structure prediction with R2DT, sequence search, and analysis with Rfam. Since its last publication in 2021, RNAcentral has developed two major features. First, literature integration with the development of LitScan and LitSumm. LitScan automatically identifies and links relevant publications to RNA entries, while LitSumm uses natural language processing to generate functional summaries from the literature. Together, these tools address the critical challenge of connecting sequence data with scattered functional knowledge across thousands of publications. Secondly, RNAcentral has created gene level entries. Gene level entries represent a large structural change to RNAcentral. While RNAcentral previously organized data exclusively at the sequence level, we now group related transcripts into gene-centric views. This allows researchers to explore all isoforms, splice variants, and related sequences for a gene in a unified interface, better reflecting biological organization and facilitating comparative analyses. RNAcentral is freely available at: https://rnacentral.org .

Expression Atlas (www.ebi.ac.uk/gxa) and its newest counterpart the Single Cell Expression Atlas (www.ebi.ac.uk/gxa/sc) are EMBL-EBI's knowledgebases for gene and protein expression and localisation in bulk and at single cell level. These resources aim to allow users to investigate their expression in normal tissue (baseline) or in response to perturbations such as disease or changes to genotype (differential) across multiple species. Users are invited to search for genes or metadata terms across species or biological conditions in a standardised consistent interface. Alongside these data, new features in Single Cell Expression Atlas allow users to query metadata through our new cell type wheel search. At the experiment level data can be explored through two types of dimensionality reduction plots, t-distributed Stochastic Neighbor Embedding (tSNE) and Uniform Manifold Approximation and Projection (UMAP), overlaid with either clustering or metadata information to assist users' understanding. Data are also visualised as marker gene heatmaps identifying genes that help confer cluster identity. For some data, additional visualisations are available as interactive cell level anatomograms and cell type gene expression heatmaps.

Many datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While biospecimen and experimental information is often captured, detailed metadata standards related to data matrices and analysis workflows are currently lacking. To address this, we develop the matrix and analysis metadata standards (MAMS) to serve as a resource for data centers, repositories, and tool developers. We define metadata fields for matrices and parameters commonly utilized in analytical workflows and developed the rmams package to extract MAMS from single-cell objects. Overall, MAMS promotes the harmonization, integration, and reproducibility of single-cell data across platforms.

Loss-of-function mutations in the gene encoding the acetyltransferase CREBBP have been reported in numerous cancers but are particularly frequent in lymphoid malignancies. However, the functional significance of CREBBP loss in transformation and disease progression, most likely through cooperation with secondary genetic hits, has not yet been fully unravelled. Similarly, the contribution of the initial cell population sustaining CREBBP loss in the course of disease remains elusive. Here, we developed a new lymphoma mouse model integrating Crebbp loss at various stages of B cell development with a transposon-based insertional mutagenesis system. We demonstrated that Crebbp loss from the HSPC compartment resulted in an aggressive DLBCL-like disease, recapitulating well-characterised histological and molecular features of the human disease, as well as the recently described enhanced CD24 expression. More importantly, we identified candidate genes functionally equivalent to patient mutated genes. Those genes, mainly related to B cell development and cellular signalling, may represent novel therapeutic targets. Overall, this new model provides a powerful resource in which to conduct future mechanistic and therapeutic studies.### Competing Interest StatementThe authors have declared no competing interest.

Hematopoietic stem cells (HSCs) accumulate somatic mutations over time, some conferring a fitness advantage that can lead to clonal hematopoiesis (CH). Mutations in DNMT3A , particularly at hotspot R882, are the most prevalent in CH and carry an increased risk of acute myeloid leukemia (AML). Although DNMT3A R882 mutations are linked to global DNA hypomethylation, the mechanisms underlying their selective advantage remain unclear. Here, we show that Dnmt3a-R882H mutant HSCs exhibit resilience under inflammatory and genotoxic stress. During IL-1β-induced emergency granulopoiesis, Dnmt3aR882H/+ HSCs uncouple increased proliferation from stem cell exhaustion. In contrast, wild-type HSCs rapidly progress to terminal differentiation. We link this phenotype to a delayed activation of the p53-p21-DREAM axis, that allows mutant HSCs to avoid attrition, despite increased replication stress. Similarly, mutant HSCs exhibit delayed Trp53 activation following irradiation, but eventually recover a physiological Trp53 response. Analysis of patient data reveals shared phenotypic features between DNMT3A and monoallelic TP53 mutations in CH and myeloid neoplasms, highlighting potential functional similarities. Collectively, these findings suggest that the expansion of DNMT3A -mutant clones is affected by impaired TP53 signaling, which confers resilience against stressors. Therapeutic strategies targeting inflammatory pathways or the p53-p21-DREAM axis may reduce DNMT3A -CH expansion and/or progression and its associated risks. ### Competing Interest Statement The authors have declared no competing interest.

Stem cells undergo cellular division during their differentiation to produce daughter cells with a new cellular identity. However, the epigenetic events and molecular mechanisms occurring between consecutive cell divisions have been insufficiently studied due to technical limitations. Here, using the FUCCI reporter we developed a cell-cycle synchronised human pluripotent stem cell (hPSC) differentiation system for uncovering epigenome and transcriptome dynamics during the first two divisions leading to definitive endoderm. We observed that transcription of key differentiation markers occurs before cell division, while chromatin accessibility analyses revealed the early inhibition of alternative cell fates. We found that Activator protein-1 members controlled by p38/MAPK signalling are necessary for inducing endoderm while blocking cell fate shifting toward mesoderm, and that enhancers are rapidly established and decommissioned between different cell divisions. Our study has practical biomedical utility for producing hPSC-derived patient-specific cell types since p38/MAPK induction increased the differentiation efficiency of insulin-producing pancreatic beta-cells.

Resistance to standard and novel therapies remains the main obstacle to cure in acute myeloid leukaemia (AML) and is often driven by metabolic adaptations which are therapeutically actionable. Here we identify inhibition of mannose-6-phosphate isomerase (MPI), the first enzyme in the mannose metabolism pathway, as a sensitizer to both cytarabine and FLT3 inhibitors across multiple AML models. Mechanistically, we identify a connection between mannose metabolism and fatty acid metabolism, that is mediated via preferential activation of the ATF6 arm of the unfolded protein response (UPR). This in turn leads to cellular accumulation of polyunsaturated fatty acids, lipid peroxidation and ferroptotic cell death in AML cells. Our findings provide further support to the role of rewired metabolism in AML therapy resistance, unveil a connection between two apparently independent metabolic pathways and support further efforts to achieve eradication of therapy-resistant AML cells by sensitizing them to ferroptotic cell death.

Following on from the NASA twins' study, there has been a tremendous interest in the use of omics techniques in spaceflight. Individual space agencies, NASA's GeneLab, JAXA's ibSLS, and the ESA-funded Space Omics Topical Team and the International Standards for Space Omics Processing (ISSOP) groups have established several initiatives to support this growth. Here, we present recommendations from the Space Omics Topical Team to promote standard application of space omics in Europe. We focus on four main themes: i) continued participation in and coordination with international omics endeavors, ii) strengthening of the European space omics infrastructure including workforce and facilities, iii) capitalizing on the emerging opportunities in the commercial space sector, and iv) capitalizing on the emerging opportunities in human subjects research.

Resistance to standard and novel therapies remains the main obstacle to cure in acute myeloid leukemia (AML) and is often driven by metabolic adaptations which are therapeutically actionable. Here we identify inhibition of mannose-6-phosphate isomerase (MPI), the first enzyme in the mannose metabolism pathway, as a sensitizer to both cytarabine and FLT3 inhibitors across multiple AML models. Mechanistically, we identify a connection between mannose metabolism and fatty acid metabolism, that is mediated via preferential activation of the ATF6 arm of the unfolded protein response (UPR). This in turn leads to cellular accumulation of polyunsaturated fatty acids, lipid peroxidation and ferroptotic cell death in AML cells. Our findings provide further support to the role of rewired metabolism in AML therapy resistance, unveil a novel connection between two apparently independent metabolic pathways and support further efforts to achieve eradication of therapy-resistant AML cells by sensitizing them to ferroptotic cell death.

Single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) have experienced rapid development in recent years. The findings of spaceflight-based scRNA-seq and SRT investigations are likely to improve our understanding of life in space and our comprehension of gene expression in various cell systems and tissue dynamics. However, compared to their Earth-based counterparts, gene expression experiments conducted in spaceflight have not experienced the same pace of development. Out of the hundreds of spaceflight gene expression datasets available, only a few used scRNA-seq and SRT. In this perspective piece, we explore the growing importance of scRNA-seq and SRT in space biology and discuss the challenges and considerations relevant to robust experimental design to enable growth of these methods in the field.

The purpose of the Maleth Program, also known as Project Maleth, is Malta's first space program to evaluate human skin tissue microbiome changes in type 2 diabetes mellitus (T2DM) patients afflicted with diabetic foot ulcers (DFU). This was carried out in both ground-based models and spaceflight. The first mission (Maleth I) under this program was carried out to uncover the effects of spaceflight, microgravity and radiation on human skin tissue microbiome samples from six T2DM patients recruited into the study. Each patient human skin tissue sample was split in three, with one section processed immediately for genomic profiling by 16S typing and the rest were processed for longer term ground-control and spaceflight experiments. Ground-control and spaceflight human skin tissue samples were also processed for genomic profiling upon mission re-entry and completion. Maleth I's overall objective was achieved, as human skin tissue samples with their microbiomes travelled to space and back yielding positive results by both standard microbiology techniques and genetic typing using 16S rRNA amplicon sequencing. Preliminary findings of this mission are discussed in light of its innovative approach at DFU microbiome research, and the clinical implications that may emerge from this and other future similar studies.

ABSTRACT Background Antimicrobial Resistance (AMR) has a detrimental impact on human health on Earth and it is equally concerning in other environments such as space due to microgravity, radiation and confinement, especially for long-distance space travel. The International Space Station (ISS) is ideal for investigating microbial diversity and virulence. The shotgun metagenomics data of the ISS generated during the Microbial Tracking – 1 (MT-1) project and resulting metagenome-assembled genomes (MAGs) across three flights in eight different locations during 12 months were used in this study. The objective of this study was to identify the AMR genes associated with whole genomes of 227 cultivable strains, 21 shotgun metagenome sequences, and 24 MAGs retrieved from the ISS environmental samples that were treated with propidium monoazide (PMA; viable microbes). Results We have analyzed the data using a deep learning model, allowing us to go beyond traditional cut-offs based only on high DNA sequence similarity and extending the catalog of AMR genes. Our results in PMA treated samples revealed AMR dominance in the last flight for Kalamiella piersonii , a bacteria related to urinary tract infection in humans. The analysis of 227 pure strains isolated from the MT-1 project revealed hundreds of antibiotic resistance genes from many isolates, including two top-ranking species that corresponded to strains of Enterobacter bugandensis and Bacillus cereus . Computational predictions were experimentally validated by antibiotic resistance profiles in these two species, showing a high degree of concordance. Specifically, disc assay data confirmed the high resistance of these two pathogens to various beta-lactam antibiotics. Conclusion Overall, our computational predictions and validation analyses demonstrate the advantages of machine learning to uncover concealed AMR determinants in metagenomics datasets, expanding the understanding of the ISS environmental microbiomes and their pathogenic potential in humans.

Master annotations in GFF3 format of 226 bacterial isolates obtained from the International Space Station (ISS) during Microbial Tracking-1 flight experiments. The analysis was performed with Prokka v1.14.5 (Seemann, 2014). Raw sequencing data and sequence assemblies in FASTA format can be downloaded from the NASA GeneLab repository https://genelab.nasa.gov, the first comprehensive space-related omics database.

Single-cell RNA sequencing (scRNA-seq) and spatially resolved transcriptomics (SRT) have experienced rapid development in recent years. The findings of spaceflight-based scRNA-seq and SRT investigations are likely to improve our understanding of life in space and our comprehension of gene expression in various cell systems and tissue dynamics. However, compared to their Earth-based counterparts, gene expression experiments conducted in spaceflight have not experienced the same pace of development. Out of the hundreds of spaceflight gene expression datasets available, only five used scRNA-seq and two used SRT. One principal factor driving this disparity are the special considerations in tissue preservation that are essential for collecting high-quality data. Advancing cell and tissue preservation protocols during spaceflight can increase the quality of data obtained and enable further scRNA-seq and SRT experiments. Additionally, the growing spectrum of computational tools for SRT can help inform which SRT method is optimal for experiment goals and can assist the selection of preservation methods to use during flight. In this paper we explore the growing importance of scRNA-seq and SRT in space biology and present investigators with the challenges and considerations relevant to robust experimental design.

Altered transcription is a cardinal feature of acute myeloid leukemia (AML); however, exactly how mutations synergize to remodel the epigenetic landscape and rewire three-dimensional DNA topology is unknown. Here, we apply an integrated genomic approach to a murine allelic series that models the two most common mutations in AML: Flt3-ITD and Npm1c. We then deconvolute the contribution of each mutation to alterations of the epigenetic landscape and genome organization, and infer how mutations synergize in the induction of AML. Our studies demonstrate that Flt3-ITD signals to chromatin to alter the epigenetic environment and synergizes with mutations in Npm1c to alter gene expression and drive leukemia induction. These analyses also allow the identification of long-range cis-regulatory circuits, including a previously unknown superenhancer of Hoxa locus, as well as larger and more detailed gene-regulatory networks, driven by transcription factors including PU.1 and IRF8, whose importance we demonstrate through perturbation of network members. Mice bearing mutations in Flt3-ITD and Npm1c, which are commonly found in acute myeloid leukemia, are used to characterize the cooperative effects of these cancer drivers on the cellular epigenome and three-dimensional genome conformation during tumor development.

Abstract Introduction The development of resistance to standard and novel therapies remains the main obstacle to cure in acute myeloid leukemia (AML). Metabolic rewiring has emerged as a therapeutically actionable vulnerability in AML, where specific metabolic adaptations arising as a result of driver mutations or in response to therapy have been reported. Mannose phosphoisomerase (MPI) is the first enzyme in the mannose metabolism (MM) pathway, that leads to the production of GDP-Mannose, a key sugar donor for N-glycosylation reactions. MPI was amongst the top drop-out genes in our published CRISPR-Cas9 screen aiming to identify sensitizers to FLT3 tyrosine kinase inhibitors (TKI) in AML carrying activating FLT3 internal tandem duplication (ITD) mutations (Gallipoli et al., Blood 2018). Moreover, analysis of published genomic datasets indicates that MPI expression levels are higher in AML compared to normal samples, correlate with patient outcome (A) and further increase in paired relapsed to diagnosis samples. We therefore hypothesized that MM and MPI inhibition sensitize AML cells to both FLT3-TKI and standard chemotherapy and tested this in preclinical models. Methods Experiments were performed in human AML cell lines, primary AML mononuclear cells and normal CD34 + stem/progenitor cells. Liquid chromatography coupled to mass spectrometry and oxygen consumption/extracellular acidification rate as measured by a Seahorse analyser were employed to assess metabolic changes. Gene-expression was measured by RNA-sequencing and confirmed by RT-qPCR. Viability, surface protein expression and lipid peroxidation were assessed by flow-cytometry. Protein expression and localisation was measured by western blot and immunofluorescence. Gene silencing was performed using CRISPR-Cas9 gene editing and inducible short hairpin RNA interference. Results We show that genetic and chemical MPI inhibition sensitizes FLT3 WT and FLT3 ITD AML cell lines in vitro to standard cytarabine chemotherapy and FLT3-TKI respectively and these effects are rescued by the addition of MPI downstream product mannose. We validate these findings in vivo using MPI knock-out (KO) cell line xenografts and in vitro using primary AML samples following MPI knock-down (B). We also demonstrate a lack of toxicity to normal CD34 + cells. Surprisingly, global metabolomic analysis show that MPI KO cells accumulate fatty acids and particularly polyunsaturated fatty acids (PUFA) (C), due to both increased uptake and reduced fatty acid oxidation (FAO). MPI KO cells downregulate several FAO metabolism genes and this is corroborated by the strong positive correlation of MPI expression levels with multiple genes involved in FAO across multiple primary AML datasets. Metabolic profiling demonstrates that MPI KO cells have reduced oxidative phosphorylation metabolism and in particular are unable to oxidise palmitate, an effect rescued by mannose or the FAO activator fenofibrate (D). We link this metabolic defect to the specific activation of the ATF6 arm of the unfolded protein response (UPR) due to a reduction in protein glycosylation in MPI KO cells. We validate this by demonstrating that activating or inhibiting ATF6 respectively phenocopies or rescues the effects of MPI KO (E) and show this to be secondary to ATF6 driving FAO inhibition, via transcriptional downregulation of PPARα, a master regulator of lipid catabolism. Finally, we show that accumulation of PUFA in MPI KO cells is accompanied by reduced cysteine levels and increased markers of oxidative stress and lipid peroxidation, such as 4-hydroxynonenal (4-HNE), all features associated with ferroptosis (F). We validate this by showing that combining FLT3-TKI with MPI KO leads to ferroptotic cell death in AML cells, which can be rescued by the radical-trapping antioxidant ferrostatin. Conclusions We provide further evidence to support the role of metabolic rewiring in driving therapy resistance in AML and show for the first time that targeting MPI and MM sensitizes AML cells to cytarabine and FLT3-TKI. Mechanistically we unveil a novel connection between MM and fatty acid metabolism, via activation of the ATF6 arm of the UPR, leading to cellular PUFA accumulation, lipid peroxidation and ferroptotic cell death. Finally, our findings also suggest that triggering ferroptosis can be leveraged as a therapeutically actionable mechanism driving cell death in therapy-resistant AML cells. Figure 1 Figure 1. Disclosures Vassiliou: Kymab Ltd: Divested equity in a private or publicly-traded company in the past 24 months; STRM.BIO: Consultancy; Astrazeneca: Consultancy.

Heterozygous mutations in HNF1B in humans result in a multisystem disorder, including pancreatic hypoplasia and diabetes mellitus. Here we used a well-controlled human induced pluripotent stem cell pancreatic differentiation model to elucidate the molecular mechanisms underlying HNF1B-associated diabetes. Our results show that lack of HNF1B blocks specification of pancreatic fate from the foregut progenitor (FP) stage, but HNF1B haploinsufficiency allows differentiation of multipotent pancreatic progenitor cells (MPCs) and insulin-secreting β-like cells. We show that HNF1B haploinsufficiency impairs cell proliferation in FPs and MPCs. This could be attributed to impaired induction of key pancreatic developmental genes, including SOX11, ROBO2, and additional TEAD1 target genes whose function is associated with MPC self-renewal. In this work we uncover an exhaustive list of potential HNF1B gene targets during human pancreas organogenesis whose downregulation might underlie HNF1B-associated diabetes onset in humans, thus providing an important resource to understand the pathogenesis of this disease.