Striatin plays a major role in angiotensin II-induced cardiomyocyte and cardiac hypertrophy in mice in vivo.

The three striatins (STRN, STRN3, STRN4) form the core of STRiatin-Interacting Phosphatase and Kinase (STRIPAK) complexes. These place protein phosphatase 2A (PP2A) in proximity to protein kinases thereby restraining kinase activity and regulating key cellular processes. Our aim was to establish if striatins play a significant role in cardiac remodelling associated with cardiac hypertrophy and heart failure.

Differences in 5'untranslated regions highlight the importance of translational regulation of dosage sensitive genes.

Background: Untranslated regions (UTRs) are important mediators of post-transcriptional regulation. The length of UTRs and the composition of regulatory elements within them are known to vary substantially across genes, but little is known about the reasons for this variation in humans. Here, we set out to determine whether this variation, specifically in 5'UTRs, correlates with gene dosage sensitivity.

Discovering microproteins: making the most of ribosome profiling data.

Building a reference set of protein-coding open reading frames (ORFs) has revolutionized biological process discovery and understanding. Traditionally, gene models have been confirmed using cDNA sequencing and encoded translated regions inferred using sequence-based detection of start and stop combinations longer than 100 amino-acids to prevent false positives. This has led to small ORFs (smORFs) and their encoded proteins left un-annotated.

Transient naive reprogramming corrects hiPS cells functionally and epigenetically.

Cells undergo a major epigenome reconfiguration when reprogrammed to human induced pluripotent stem cells (hiPS cells). However, the epigenomes of hiPS cells and human embryonic stem (hES) cells differ significantly, which affects hiPS cell function. These differences include epigenetic memory and aberrations that emerge during reprogramming, for which the mechanisms remain unknown.

Single cell analysis in head and neck cancer reveals potential immune evasion mechanisms during early metastasis.

Profiling tumors at single-cell resolution provides an opportunity to understand complexities underpinning lymph-node metastases in head and neck squamous-cell carcinoma. Single-cell RNAseq (scRNAseq) analysis of cancer-cell trajectories identifies a subpopulation of pre-metastatic cells, driven by actionable pathways including AXL and AURK. Blocking these two proteins blunts tumor invasion in patient-derived cultures.

A single-cell atlas identifies pretreatment features of primary imatinib resistance in chronic myeloid leukemia.

Primary resistance to tyrosine kinase inhibitors (TKIs) is a significant barrier to optimal outcomes in chronic myeloid leukemia (CML), but factors contributing to response heterogeneity remain unclear. Using single-cell RNA (scRNA) sequencing, we identified 8 statistically significant features in pretreatment bone marrow, which correlated with either sensitivity (major molecular response or MMR) or extreme resistance to imatinib (eventual blast crisis [BC] transformation). Employing machine-learning, we identified leukemic stem cell (LSC) and natural killer (NK) cell gene expression profiles predicting imatinib response with >80% accuracy, including no false positives for predicting BC.

Deep learning models will shape the future of stem cell research.

Our ability to understand and control stem cell biology is being augmented by developments on two fronts, our ability to collect more data describing cell state and our capability to comprehend these data using deep learning models. Here we consider the impact deep learning will have in the future of stem cell research. We explore the importance of generating data suitable for these methods, the requirement for close collaboration between experimental and computational researchers, and the challenges we face to do this fairly and effectively.

A novel network pharmacology approach for leukaemia differentiation therapy using Mogrify.

Acute myeloid leukaemia (AML) is a rapidly fatal blood cancer that is characterised by the accumulation of immature myeloid cells in the blood and bone marrow as a result of blocked differentiation. Methods which identify master transcriptional regulators of AML subtype-specific leukaemia cell states and their combinations could be critical for discovering novel differentiation-inducing therapies. In this proof-of-concept study, we demonstrate a novel utility of the Mogrify algorithm in identifying combinations of transcription factors (TFs) and drugs, which recapitulate granulocytic differentiation of the NB4 acute promyelocytic leukaemia (APL) cell line, using two different approaches.

PKN2 deficiency leads both to prenatal 'congenital' cardiomyopathy and defective angiotensin II stress responses.

The protein kinase PKN2 is required for embryonic development and PKN2 knockout mice die as a result of failure in the expansion of mesoderm, cardiac development and neural tube closure. In the adult, cardiomyocyte PKN2 and PKN1 (in combination) are required for cardiac adaptation to pressure-overload. The specific role of PKN2 in contractile cardiomyocytes during development and its role in the adult heart remain to be fully established.

Intestinal stem cell aging signature reveals a reprogramming strategy to enhance regenerative potential.

The impact of aging on intestinal stem cells (ISCs) has not been fully elucidated. In this study, we identified widespread epigenetic and transcriptional alterations in old ISCs. Using a reprogramming algorithm, we identified a set of key transcription factors (Egr1, Irf1, FosB) that drives molecular and functional differences between old and young states.

CLIPreg: constructing translational regulatory networks from CLIP-, Ribo- and RNA-seq.

Motivation: The creation and analysis of gene regulatory networks have been the focus of bioinformatics research and underpins much of what is known about gene regulation. However, as a result of a bias in the availability of data types that are collected, the vast majority of gene regulatory network resources and tools have focused on either transcriptional regulation or protein-protein interactions. This has left other areas of regulation, for instance, translational regulation, vastly underrepresented despite them having been shown to play a critical role in both health and disease.

Cardiomyocyte BRAF and type 1 RAF inhibitors promote cardiomyocyte and cardiac hypertrophy in mice in vivo.

The extracellular signal-regulated kinase 1/2 (ERK1/2) cascade promotes cardiomyocyte hypertrophy and is cardioprotective, with the three RAF kinases forming a node for signal integration. Our aims were to determine if BRAF is relevant for human heart failure, whether BRAF promotes cardiomyocyte hypertrophy, and if Type 1 RAF inhibitors developed for cancer (that paradoxically activate ERK1/2 at low concentrations: the 'RAF paradox') may have the same effect. BRAF was up-regulated in heart samples from patients with heart failure compared with normal controls.

Transcriptional signature in microglia associated with Aβ plaque phagocytosis.

The role of microglia cells in Alzheimer's disease (AD) is well recognized, however their molecular and functional diversity remain unclear. Here, we isolated amyloid plaque-containing (using labelling with methoxy-XO4, XO4) and non-containing (XO4) microglia from an AD mouse model. Transcriptomics analysis identified different transcriptional trajectories in ageing and AD mice.

Coding and non-coding roles of MOCCI (C15ORF48) coordinate to regulate host inflammation and immunity.

Mito-SEPs are small open reading frame-encoded peptides that localize to the mitochondria to regulate metabolism. Motivated by an intriguing negative association between mito-SEPs and inflammation, here we screen for mito-SEPs that modify inflammatory outcomes and report a mito-SEP named "Modulator of cytochrome C oxidase during Inflammation" (MOCCI) that is upregulated during inflammation and infection to promote host-protective resolution. MOCCI, a paralog of the NDUFA4 subunit of cytochrome C oxidase (Complex IV), replaces NDUFA4 in Complex IV during inflammation to lower mitochondrial membrane potential and reduce ROS production, leading to cyto-protection and dampened immune response.

ShinyCell: simple and sharable visualization of single-cell gene expression data.

Motivation: As the generation of complex single-cell RNA sequencing datasets becomes more commonplace it is the responsibility of researchers to provide access to these data in a way that can be easily explored and shared. Whilst it is often the case that data is deposited for future bioinformatic analysis many studies do not release their data in a way that is easy to explore by non-computational researchers.

Results: In order to help address this we have developed ShinyCell, an R package that converts single-cell RNA sequencing datasets into explorable and shareable interactive interfaces.

Modelling human blastocysts by reprogramming fibroblasts into iBlastoids.

Human pluripotent and trophoblast stem cells have been essential alternatives to blastocysts for understanding early human development. However, these simple culture systems lack the complexity to adequately model the spatiotemporal cellular and molecular dynamics that occur during early embryonic development. Here we describe the reprogramming of fibroblasts into in vitro three-dimensional models of the human blastocyst, termed iBlastoids.

Evaluating Capture Sequence Performance for Single-Cell CRISPR Activation Experiments.

The combination of single-cell RNA sequencing with CRISPR inhibition/activation provides a high-throughput approach to simultaneously study the effects of hundreds if not thousands of gene perturbations in a single experiment. One recent development in CRISPR-based single-cell techniques introduces a feature barcoding technology that allows for the simultaneous capture of mRNA and guide RNA (gRNA) from the same cell. This is achieved by introducing a capture sequence, whose complement can be incorporated into each gRNA and that can be used to amplify these features prior to sequencing.

Challenges for Computational Stem Cell Biology: A Discussion for the Field.

The first meetup for Computational Stem Cell Biologists was held at the 2020 annual meeting of the International Society for Stem Cell Research. The discussions highlighted opportunities and barriers to computational stem cell research that require coordinated action across the stem cell sector.

Computational Stem Cell Biology: Open Questions and Guiding Principles.

Computational biology is enabling an explosive growth in our understanding of stem cells and our ability to use them for disease modeling, regenerative medicine, and drug discovery. We discuss four topics that exemplify applications of computation to stem cell biology: cell typing, lineage tracing, trajectory inference, and regulatory networks. We use these examples to articulate principles that have guided computational biology broadly and call for renewed attention to these principles as computation becomes increasingly important in stem cell biology.

EpiMogrify Models H3K4me3 Data to Identify Signaling Molecules that Improve Cell Fate Control and Maintenance.

The need to derive and culture diverse cell or tissue types in vitro has prompted investigations on how changes in culture conditions affect cell states. However, the identification of the optimal conditions (e.g.