Expression Atlas update: insights from sequencing data at both bulk and single cell level.

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.

The SMAD2/3 interactome reveals that TGFß controls m6A mRNA methylation in pluripotency.

The TGFß pathway has essential roles in embryonic development, organ homeostasis, tissue repair and disease. These diverse effects are mediated through the intracellular effectors SMAD2 and SMAD3 (hereafter SMAD2/3), whose canonical function is to control the activity of target genes by interacting with transcriptional regulators. Therefore, a complete description of the factors that interact with SMAD2/3 in a given cell type would have broad implications for many areas of cell biology. Here we describe the interactome of SMAD2/3 in human pluripotent stem cells. This analysis reveals that SMAD2/3 is involved in multiple molecular processes in addition to its role in transcription. In particular, we identify a functional interaction with the METTL3-METTL14-WTAP complex, which mediates the conversion of adenosine to N6-methyladenosine (m6A) on RNA. We show that SMAD2/3 promotes binding of the m6A methyltransferase complex to a subset of transcripts involved in early cell fate decisions. This mechanism destabilizes specific SMAD2/3 transcriptional targets, including the pluripotency factor gene NANOG, priming them for rapid downregulation upon differentiation to enable timely exit from pluripotency. Collectively, these findings reveal the mechanism by which extracellular signalling can induce rapid cellular responses through regulation of the epitranscriptome. These aspects of TGFß signalling could have far-reaching implications in many other cell types and in diseases such as cancer.

Initiation of stem cell differentiation involves cell cycle-dependent regulation of developmental genes by Cyclin D.

Coordination of differentiation and cell cycle progression represents an essential process for embryonic development and adult tissue homeostasis. These mechanisms ultimately determine the quantities of specific cell types that are generated. Despite their importance, the precise molecular interplays between cell cycle machinery and master regulators of cell fate choice remain to be fully uncovered. Here, we demonstrate that cell cycle regulators Cyclin D1-3 control cell fate decisions in human pluripotent stem cells by recruiting transcriptional corepressors and coactivator complexes onto neuroectoderm, mesoderm, and endoderm genes. This activity results in blocking the core transcriptional network necessary for endoderm specification while promoting neuroectoderm factors. The genomic location of Cyclin Ds is determined by their interactions with the transcription factors SP1 and E2Fs, which result in the assembly of cell cycle-controlled transcriptional complexes. These results reveal how the cell cycle orchestrates transcriptional networks and epigenetic modifiers to instruct cell fate decisions.

Activin/nodal signaling and NANOG orchestrate human embryonic stem cell fate decisions by controlling the H3K4me3 chromatin mark.

Stem cells can self-renew and differentiate into multiple cell types. These characteristics are maintained by the combination of specific signaling pathways and transcription factors that cooperate to establish a unique epigenetic state. Despite the broad interest of these mechanisms, the precise molecular controls by which extracellular signals organize epigenetic marks to confer multipotency remain to be uncovered. Here, we use human embryonic stem cells (hESCs) to show that the Activin-SMAD2/3 signaling pathway cooperates with the core pluripotency factor NANOG to recruit the DPY30-COMPASS histone modifiers onto key developmental genes. Functional studies demonstrate the importance of these interactions for correct histone 3 Lys4 trimethylation and also self-renewal and differentiation. Finally, genetic studies in mice show that Dpy30 is also necessary to maintain pluripotency in the pregastrulation embryo, thereby confirming the existence of similar regulations in vivo during early embryonic development. Our results reveal the mechanisms by which extracellular factors coordinate chromatin status and cell fate decisions in hESCs.

Functional data analysis for computational biology.

SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Divergence of regulatory networks governed by the orthologous transcription factors FLC and PEP1 in Brassicaceae species.

Genome-wide landscapes of transcription factor (TF) binding sites (BSs) diverge during evolution, conferring species-specific transcriptional patterns. The rate of divergence varies in different metazoan lineages but has not been widely studied in plants. We identified the BSs and assessed the effects on transcription of FLOWERING LOCUS C (FLC) and PERPETUAL FLOWERING 1 (PEP1), two orthologous MADS-box TFs that repress flowering and confer vernalization requirement in the Brassicaceae species Arabidopsis thaliana and Arabis alpina, respectively. We found that only 14% of their BSs were conserved in both species and that these contained a CArG-box that is recognized by MADS-box TFs. The CArG-box consensus at conserved BSs was extended compared with the core motif. By contrast, species-specific BSs usually lacked the CArG-box in the other species. Flowering-time genes were highly overrepresented among conserved targets, and their CArG-boxes were widely conserved among Brassicaceae species. Cold-regulated (COR) genes were also overrepresented among targets, but the cognate BSs and the identity of the regulated genes were usually different in each species. In cold, COR gene transcript levels were increased in flc and pep1-1 mutants compared with WT, and this correlated with reduced growth in pep1-1 Therefore, FLC orthologs regulate a set of conserved target genes mainly involved in reproductive development and were later independently recruited to modulate stress responses in different Brassicaceae lineages. Analysis of TF BSs in these lineages thus distinguishes widely conserved targets representing the core function of the TF from those that were recruited later in evolution.

Efficacy and safety of pop-titrated versus fixed-energy trans-scleral diode laser cyclophotocoagulation for refractory glaucoma.

PURPOSE: To compare the efficacy and safety of pop-titrated versus fixed-energy diode laser trans-scleral cyclophotocoagulation (DLTSC) for refractory glaucoma. METHODS: This is a prospective, interventional, longitudinal, and comparative case-control study. Patients with refractory glaucoma treated with pop-titrated DLTSC were compared to a fixed-energy DLTSC control group. Variables analyzed included: age, gender, diagnosis, pre- and post-treatment intraocular pressure (IOP). Success rate, anti-glaucoma medications reduction, and complications were analyzed at day 90 post-treatment. Primary success criterion consisted of eyes with a postoperative IOP ≤ 22 mmHg or a 30% reduction of pre-treatment IOP and managed with topical anti-glaucoma medications only. RESULTS: A total of 68 eyes from 67 patients were included for analysis: 30 in the pop-titrated group and 38 in the fixed-energy group. Therapeutic success was achieved in 56-72% of the pop-titrated group versus 47-52% in the fixed-energy group considering the 3 different criteria analyzed (p = 0.23-0.4). There was a 22% (from 4.1 to 3.2 drugs) reduction of anti-glaucoma medications in the pop-titrated group, compared to 32% (from 3.5 to 2.4 drugs) in the fixed-energy group (p = 0.42). Five eyes (13.1%) developed hypotony, all of which belonged to the fixed-energy group (p = 0.048). CONCLUSIONS: Pop-titrated DLTSC represents an effective and safe option for the management of refractory glaucoma. We found no statistically significant difference in success rates among both groups. However, there was a significantly higher risk of hypotony in eyes treated with the fixed-energy protocol.

hiPSC hepatocyte model demonstrates the role of unfolded protein response and inflammatory networks in α1-antitrypsin deficiency.

BACKGROUND & AIMS: α1-Antitrypsin deficiency (A1ATD) is an autosomal recessive disorder caused by mutations in the SERPINA1 gene. Individuals with the Z variant (Gly342Lys) retain polymerised protein in the endoplasmic reticulum (ER) of their hepatocytes, predisposing them to liver disease. The concomitant lack of circulating A1AT also causes lung emphysema. Greater insight into the mechanisms that link protein misfolding to liver injury will facilitate the design of novel therapies. METHODS: Human-induced pluripotent stem cell (hiPSC)-derived hepatocytes provide a novel approach to interrogate the molecular mechanisms of A1ATD because of their patient-specific genetic architecture and reflection of human physiology. To that end, we utilised patient-specific hiPSC hepatocyte-like cells (ZZ-HLCs) derived from an A1ATD (ZZ) patient, which faithfully recapitulated key aspects of the disease at the molecular and cellular level. Subsequent functional and "omics" comparisons of these cells with their genetically corrected isogenic-line (RR-HLCs) and primary hepatocytes/human tissue enabled identification of new molecular markers and disease signatures. RESULTS: Our studies showed that abnormal A1AT polymer processing (immobilised ER components, reduced luminal protein mobility and disrupted ER cisternae) occurred heterogeneously within hepatocyte populations and was associated with disrupted mitochondrial structure, presence of the oncogenic protein AKR1B10 and two upregulated molecular clusters centred on members of inflammatory (IL-18 and Caspase-4) and unfolded protein response (Calnexin and Calreticulin) pathways. These results were validated in a second patient-specific hiPSC line. CONCLUSIONS: Our data identified novel pathways that potentially link the expression of Z A1AT polymers to liver disease. These findings could help pave the way towards identification of new therapeutic targets for the treatment of A1ATD. LAY SUMMARY: This study compared the gene expression and protein profiles of healthy liver cells and those affected by the inherited disease α1-antitrypsin deficiency. This approach identified specific factors primarily present in diseased samples which could provide new targets for drug development. This study also demonstrates the interest of using hepatic cells generated from human-induced pluripotent stem cells to model liver disease in vitro for uncovering new mechanisms with clinical relevance.

fCCAC: functional canonical correlation analysis to evaluate covariance between nucleic acid sequencing datasets.

Summary: Computational evaluation of variability across DNA or RNA sequencing datasets is a crucial step in genomic science, as it allows both to evaluate reproducibility of biological or technical replicates, and to compare different datasets to identify their potential correlations. Here we present fCCAC, an application of functional canonical correlation analysis to assess covariance of nucleic acid sequencing datasets such as chromatin immunoprecipitation followed by deep sequencing (ChIP-seq). We show how this method differs from other measures of correlation, and exemplify how it can reveal shared covariance between histone modifications and DNA binding proteins, such as the relationship between the H3K4me3 chromatin mark and its epigenetic writers and readers. Availability and Implementation: An R/Bioconductor package is available at http://bioconductor.org/packages/fCCAC/ . Contact: pmb59@cam.ac.uk. Supplementary information: Supplementary data are available at Bioinformatics online.

Practical guidelines for the comprehensive analysis of ChIP-seq data.

Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the Encyclopedia of DNA Elements (ENCODE) Project. To this end, chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is the standard methodology. Mapping such protein-DNA interactions in vivo using ChIP-seq presents multiple challenges not only in sample preparation and sequencing but also for computational analysis. Here, we present step-by-step guidelines for the computational analysis of ChIP-seq data. We address all the major steps in the analysis of ChIP-seq data: sequencing depth selection, quality checking, mapping, data normalization, assessment of reproducibility, peak calling, differential binding analysis, controlling the false discovery rate, peak annotation, visualization, and motif analysis. At each step in our guidelines we discuss some of the software tools most frequently used. We also highlight the challenges and problems associated with each step in ChIP-seq data analysis. We present a concise workflow for the analysis of ChIP-seq data in Figure 1 that complements and expands on the recommendations of the ENCODE and modENCODE projects. Each step in the workflow is described in detail in the following sections.

MAMS: matrix and analysis metadata standards to facilitate harmonization and reproducibility of single-cell data.

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.

Epigenetic and transcriptional regulations prime cell fate before division during human pluripotent stem cell differentiation.

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.

Matrix and analysis metadata standards (MAMS) to facilitate harmonization and reproducibility of single-cell data.

A large number of genomic and imaging datasets are being produced by consortia that seek to characterize healthy and disease tissues at single-cell resolution. While much effort has been devoted to capturing information related to biospecimen information and experimental procedures, the metadata standards that describe data matrices and the analysis workflows that produced them are relatively lacking. Detailed metadata schema related to data analysis are needed to facilitate sharing and interoperability across groups and to promote data provenance for reproducibility. To address this need, we developed the Matrix and Analysis Metadata Standards (MAMS) to serve as a resource for data coordinating centers and tool developers. We first curated several simple and complex "use cases" to characterize the types of feature-observation matrices (FOMs), annotations, and analysis metadata produced in different workflows. Based on these use cases, metadata fields were defined to describe the data contained within each matrix including those related to processing, modality, and subsets. Suggested terms were created for the majority of fields to aid in harmonization of metadata terms across groups. Additional provenance metadata fields were also defined to describe the software and workflows that produced each FOM. Finally, we developed a simple list-like schema that can be used to store MAMS information and implemented in multiple formats. Overall, MAMS can be used as a guide to harmonize analysis-related metadata which will ultimately facilitate integration of datasets across tools and consortia. MAMS specifications, use cases, and examples can be found at https://github.com/single-cell-mams/mams/.

Mannose metabolism inhibition sensitizes acute myeloid leukaemia cells to therapy by driving ferroptotic cell death.

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.

Enhancing European capabilities for application of multi-omics studies in biology and biomedicine space research.

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.

Machine learning algorithm to characterize antimicrobial resistance associated with the International Space Station surface microbiome.

BACKGROUND: Antimicrobial resistance (AMR) has a detrimental impact on human health on Earth and it is equally concerning in other environments such as space habitat 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 associated with spaceflight. 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 226 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 226 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. Video Abstract.

The Maleth program: Malta's first space mission discoveries on the microbiome of diabetic foot ulcers.

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.

Challenges and considerations for single-cell and spatially resolved transcriptomics sample collection during spaceflight.

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.

MULTIMODAL IMAGING IN A CASE OF CENTRAL RETINAL ARTERY OCCLUSION IN THE PRESENCE OF TYPE 2 MACULAR TELANGIECTASIA.

PURPOSE: To report a case of central retinal artery occlusion in a patient with macular telangiectasia Type 2 using multimodal imaging. METHODS: Observational case report. RESULTS: A 58-year-old woman who presented with acute painless unilateral vision loss was diagnosed with central retinal artery occlusion in her right eye with macular telangiectasia Type 2 findings in both eyes. Fundus examination revealed retinal whitening with unusual cherry-red spot plus small crystalline deposits in the temporal macula. Surprisingly, spectral domain optical coherence tomography of the contralateral eye showed characteristically intraretinal hyporreflective spaces, whereas optical coherence tomography angiography exhibited microvascular abnormalities in the deep capillary plexus. At follow-up, a pseudolamellar macular hole was noticed in the affected eye with no recovery of best-corrected visual acuity. CONCLUSION: This case describes an onset of central artery occlusion in a patient with underlying macular telangiectasia Type 2 and suggests that it had a possible role in the acceleration of its natural course. The utility of multimodal imaging lies on better accuracy in diagnosis as well as prognosis, management, and monitoring of the disease.

Modeling HNF1B-associated monogenic diabetes using human iPSCs reveals an early stage impairment of the pancreatic developmental program.

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 ß-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.