Self-renewal of single mouse hematopoietic stem cells is reduced by JAK2V617F without compromising progenitor cell expansion

Recent descriptions of significant heterogeneity in normal stem cells and cancers have altered our understanding of tumorigenesis, emphasizing the need to understand how single stem cells are subverted to cause tumors. Human myeloproliferative neoplasms (MPNs) are thought to reflect transformation of a hematopoietic stem cell (HSC) and the majority harbor an acquired V617F mutation in the JAK2 tyrosine kinase, making them a paradigm for studying the early stages of tumor establishment and progression. The consequences of activating tyrosine kinase mutations for stem and progenitor cell behavior are unclear. In this article, we identify a distinct cellular mechanism operative in stem cells. By using conditional knock-in mice, we show that the HSC defect resulting from expression of heterozygous human JAK2V617F is both quantitative (reduced HSC numbers) and qualitative (lineage biases and reduced self-renewal per HSC). The defect is intrinsic to individual HSCs and their progeny are skewed toward proliferation and differentiation as evidenced by single cell and transplantation assays. Aged JAK2V617F show a more pronounced defect as assessed by transplantation, but mice that transform reacquire competitive self-renewal ability. Quantitative analysis of HSC-derived clones was used to model the fate choices of normal and JAK2-mutant HSCs and indicates that JAK2V617F reduces self-renewal of individual HSCs but leaves progenitor expansion intact. This conclusion is supported by paired daughter cell analyses, which indicate that JAK2-mutant HSCs more often give rise to two differentiated daughter cells. Together these data suggest that acquisition of JAK2V617F alone is insufficient for clonal expansion and disease progression and causes eventual HSC exhaustion. Moreover, our results show that clonal expansion of progenitor cells provides a window in which collaborating mutations can accumulate to drive disease progression. Characterizing the mechanism(s) of JAK2V617F subclinical clonal expansions and the transition to overt MPNs will illuminate the earliest stages of tumor establishment and subclone competition, fundamentally shifting the way we treat and manage cancers

Click-correlative light and electron microscopy (click-AT-CLEM) for imaging and tracking azido-functionalized sphingolipids in bacteria

Sphingolipids, including ceramides, are a diverse group of structurally related lipids composed of a sphingoid base backbone coupled to a fatty acid side chain and modified terminal hydroxyl group. Recently, it has been shown that sphingolipids show antimicrobial activity against a broad range of pathogenic microorganisms. The antimicrobial mechanism, however, remains so far elusive. Here, we introduce 'click-AT-CLEM', a labeling technique for correlated light and electron microscopy (CLEM) based on the super-resolution array tomography (srAT) approach and bio-orthogonal click chemistry for imaging of azido-tagged sphingolipids to directly visualize their interaction with the model Gram-negative bacterium Neisseria meningitidis at subcellular level. We observed ultrastructural damage of bacteria and disruption of the bacterial outer membrane induced by two azido-modified sphingolipids by scanning electron microscopy and transmission electron microscopy. Click-AT-CLEM imaging and mass spectrometry clearly revealed efficient incorporation of azido-tagged sphingolipids into the outer membrane of Gram-negative bacteria as underlying cause of their antimicrobial activity

Single-cell approaches identify the molecular network driving malignant hematopoietic stem cell self-renewal.

Recent advances in single-cell technologies have permitted the investigation of heterogeneous cell populations at previously unattainable resolution. Here we apply such approaches to resolve the molecular mechanisms driving disease in mouse hematopoietic stem cells (HSCs), using JAK2V617F mutant myeloproliferative neoplasms (MPNs) as a model. Single-cell gene expression and functional assays identified a subset of JAK2V617F mutant HSCs that display defective self-renewal. This defect is rescued at the single HSC level by crossing JAK2V617F mice with mice lacking TET2, the most commonly comutated gene in patients with MPN. Single-cell gene expression profiling of JAK2V617F-mutant HSCs revealed a loss of specific regulator genes, some of which were restored to normal levels in single TET2/JAK2 mutant HSCs. Of these, Bmi1 and, to a lesser extent, Pbx1 and Meis1 overexpression in JAK2-mutant HSCs could drive a disease phenotype and retain durable stem cell self-renewal in functional assays. Together, these single-cell approaches refine the molecules involved in clonal expansion of MPNs and have broad implications for deconstructing the molecular network of normal and malignant stem cells.MS is the recipient of a BBSRC Industrial CASE PhD Studentship, and CAO and JF are recipients of Wellcome Trust PhD Studentships. Work in the Kent lab is supported by a Bloodwise Bennett Fellowship (15008), a European Hematology Association Non-Clinical Advanced Research Fellowship, and an ERC Starting Grant (ERC-2016-STG–715371). Work in the Green Lab is supported by the Wellcome Trust, Bloodwise, Cancer Research UK, the Kay Kendall Leukaemia Fund, and the Leukemia and Lymphoma Society of America. Dr. Kent, Professor Göttgens, and Professor Green are all supported by a core support grant from the Wellcome Trust and MRC to the Wellcome Trust – Medical Research Council Cambridge Stem Cell Institute the National Institute for Health Research Cambridge Biomedical Research Centre, the Cambridge Experimental Cancer Medicine Centre

Tracing oncogene-driven remodelling of the intestinal stem cell niche.

Interactions between tumour cells and the surrounding microenvironment contribute to tumour progression, metastasis and recurrence1-3. Although mosaic analyses in Drosophila have advanced our understanding of such interactions4,5, it has been difficult to engineer parallel approaches in vertebrates. Here we present an oncogene-associated, multicolour reporter mouse model-the Red2Onco system-that allows differential tracing of mutant and wild-type cells in the same tissue. By applying this system to the small intestine, we show that oncogene-expressing mutant crypts alter the cellular organization of neighbouring wild-type crypts, thereby driving accelerated clonal drift. Crypts that express oncogenic KRAS or PI3K secrete BMP ligands that suppress local stem cell activity, while changes in PDGFRloCD81+ stromal cells induced by crypts with oncogenic PI3K alter the WNT signalling environment. Together, these results show how oncogene-driven paracrine remodelling creates a niche environment that is detrimental to the maintenance of wild-type tissue, promoting field transformation dominated by oncogenic clones.Royal Societ

Defining the Identity and Dynamics of Adult Gastric Isthmus Stem Cells.

The gastric corpus epithelium is the thickest part of the gastrointestinal tract and is rapidly turned over. Several markers have been proposed for gastric corpus stem cells in both isthmus and base regions. However, the identity of isthmus stem cells (IsthSCs) and the interaction between distinct stem cell populations is still under debate. Here, based on unbiased genetic labeling and biophysical modeling, we show that corpus glands are compartmentalized into two independent zones, with slow-cycling stem cells maintaining the base and actively cycling stem cells maintaining the pit-isthmus-neck region through a process of "punctuated" neutral drift dynamics. Independent lineage tracing based on Stmn1 and Ki67 expression confirmed that rapidly cycling IsthSCs maintain the pit-isthmus-neck region. Finally, single-cell RNA sequencing (RNA-seq) analysis is used to define the molecular identity and lineage relationship of a single, cycling, IsthSC population. These observations define the identity and functional behavior of IsthSCs.Wellcome Trust Royal Societ

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders

A Federated Database for Obesity Research:An IMI-SOPHIA Study

Obesity is considered by many as a lifestyle choice rather than a chronic progressive disease. The Innovative Medicines Initiative (IMI) SOPHIA (Stratification of Obesity Phenotypes to Optimize Future Obesity Therapy) project is part of a momentum shift aiming to provide better tools for the stratification of people with obesity according to disease risk and treatment response. One of the challenges to achieving these goals is that many clinical cohorts are siloed, limiting the potential of combined data for biomarker discovery. In SOPHIA, we have addressed this challenge by setting up a federated database building on open-source DataSHIELD technology. The database currently federates 16 cohorts that are accessible via a central gateway. The database is multi-modal, including research studies, clinical trials, and routine health data, and is accessed using the R statistical programming environment where statistical and machine learning analyses can be performed at a distance without any disclosure of patient-level data. We demonstrate the use of the database by providing a proof-of-concept analysis, performing a federated linear model of BMI and systolic blood pressure, pooling all data from 16 studies virtually without any analyst seeing individual patient-level data. This analysis provided similar point estimates compared to a meta-analysis of the 16 individual studies. Our approach provides a benchmark for reproducible, safe federated analyses across multiple study types provided by multiple stakeholders.</p

Frequent expression loss of Inter-alpha-trypsin inhibitor heavy chain (ITIH) genes in multiple human solid tumors: A systematic expression analysis

<p>Abstract</p> <p>Background</p> <p>The inter-alpha-trypsin inhibitors (ITI) are a family of plasma protease inhibitors, assembled from a light chain – bikunin, encoded by <it>AMBP </it>– and five homologous heavy chains (encoded by <it>ITIH1</it>, <it>ITIH2</it>, <it>ITIH3</it>, <it>ITIH4</it>, and <it>ITIH5</it>), contributing to extracellular matrix stability by covalent linkage to hyaluronan. So far, ITIH molecules have been shown to play a particularly important role in inflammation and carcinogenesis.</p> <p>Methods</p> <p>We systematically investigated differential gene expression of the <it>ITIH </it>gene family, as well as <it>AMBP </it>and the interacting partner <it>TNFAIP6 </it>in 13 different human tumor entities (of breast, endometrium, ovary, cervix, stomach, small intestine, colon, rectum, lung, thyroid, prostate, kidney, and pancreas) using cDNA dot blot analysis (Cancer Profiling Array, CPA), semiquantitative RT-PCR and immunohistochemistry.</p> <p>Results</p> <p>We found that <it>ITIH </it>genes are clearly downregulated in multiple human solid tumors, including breast, colon and lung cancer. Thus, <it>ITIH </it>genes may represent a family of putative tumor suppressor genes that should be analyzed in greater detail in the future. For an initial detailed analysis we chose <it>ITIH2 </it>expression in human breast cancer. Loss of <it>ITIH2 </it>expression in 70% of cases (n = 50, CPA) could be confirmed by real-time PCR in an additional set of breast cancers (n = 36). Next we studied ITIH2 expression on the protein level by analyzing a comprehensive tissue micro array including 185 invasive breast cancer specimens. We found a strong correlation (p < 0.001) between ITIH2 expression and estrogen receptor (ER) expression indicating that ER may be involved in the regulation of this ECM molecule.</p> <p>Conclusion</p> <p>Altogether, this is the first systematic analysis on the differential expression of <it>ITIH </it>genes in human cancer, showing frequent downregulation that may be associated with initiation and/or progression of these malignancies.</p

One-step generation of conditional and reversible gene knockouts

Loss-of-function studies are key for investigating gene function, and CRISPR technology has made genome editing widely accessible in model organisms and cells. However, conditional gene inactivation in diploid cells is still difficult to achieve. Here, we present CRISPR-FLIP, a strategy that provides an efficient, rapid and scalable method for biallelic conditional gene knockouts in diploid or aneuploid cells, such as pluripotent stem cells, 3D organoids and cell lines, by co-delivery of CRISPR-Cas9 and a universal conditional intronic cassette.A.A.-R. and K.T. are supported by the Medical Research Council, A.M. is supported by Wntsapp, Marie Curie ITN. J.F. and J.C.R.S. are supported by the Wellcome Trust. W.C.S. received core grant support from the Wellcome Trust to the Wellcome Trust Sanger Institute. B.-K.K. and R.C.M. are supported by a Sir Henry Dale Fellowship from the Wellcome Trust and the Royal Society (101241/Z/13/Z) and receive a core support grant from the Wellcome Trust and MRC to the WT–MRC Cambridge Stem Cell Institute