Blood stem cell PU.1 upregulation is a consequence of differentiation without fast autoregulation.

Transcription factors (TFs) regulate cell fates, and their expression must be tightly regulated. Autoregulation is assumed to regulate many TFs' own expression to control cell fates. Here, we manipulate and quantify the (auto)regulation of PU.1, a TF controlling hematopoietic stem and progenitor cells (HSPCs), and correlate it to their future fates. We generate transgenic mice allowing both inducible activation of PU.1 and noninvasive quantification of endogenous PU.1 protein expression. The quantified HSPC PU.1 dynamics show that PU.1 up-regulation occurs as a consequence of hematopoietic differentiation independently of direct fast autoregulation. In contrast, inflammatory signaling induces fast PU.1 up-regulation, which does not require PU.1 expression or its binding to its own autoregulatory enhancer. However, the increased PU.1 levels induced by inflammatory signaling cannot be sustained via autoregulation after removal of the signaling stimulus. We conclude that PU.1 overexpression induces HSC differentiation before PU.1 up-regulation, only later generating cell types with intrinsically higher PU.1.

A Novel GATA2 Protein Reporter Mouse Reveals Hematopoietic Progenitor Cell Types.

The transcription factor (TF) GATA2 plays a key role in organ development and cell fate control in the central nervous, urogenital, respiratory, and reproductive systems, and in primitive and definitive hematopoiesis. Here, we generate a knockin protein reporter mouse line expressing a GATA2VENUS fusion from the endogenous Gata2 genomic locus, with correct expression and localization of GATA2VENUS in different organs. GATA2VENUS expression is heterogeneous in different hematopoietic stem and progenitor cell populations (HSPCs), identifies functionally distinct subsets, and suggests a novel monocyte and mast cell lineage bifurcation point. GATA2 levels further correlate with proliferation and lineage outcome of hematopoietic progenitors. The GATA2VENUS mouse line improves the identification of specific live cell types during embryonic and adult development and will be crucial for analyzing GATA2 protein dynamics in TF networks.

Publisher Correction: Asymmetric lysosome inheritance predicts activation of haematopoietic stem cells.

An Amendment to this paper has been published and can be accessed via a link at the top of the paper.

Asymmetric lysosome inheritance predicts activation of haematopoietic stem cells.

Haematopoietic stem cells self-renew and differentiate into all blood lineages throughout life, and can repair damaged blood systems upon transplantation. Asymmetric cell division has previously been suspected to be a regulator of haematopoietic-stem-cell fate, but its existence has not directly been shown1. In asymmetric cell division, asymmetric fates of future daughter cells are prospectively determined by a mechanism that is linked to mitosis. This can be mediated by asymmetric inheritance of cell-extrinsic niche signals by, for example, orienting the divisional plane, or by the asymmetric inheritance of cell-intrinsic fate determinants. Observations of asymmetric inheritance or of asymmetric daughter-cell fates alone are not sufficient to demonstrate asymmetric cell division2. In both cases, sister-cell fates could be controlled by mechanisms that are independent of division. Here we demonstrate that the cellular degradative machinery-including lysosomes, autophagosomes, mitophagosomes and the protein NUMB-can be asymmetrically inherited into haematopoietic-stem-cell daughter cells. This asymmetric inheritance predicts the asymmetric future metabolic and translational activation and fates of haematopoietic-stem-cell daughter cells and their offspring. Therefore, our studies provide evidence for the existence of asymmetric cell division in haematopoietic stem cells.

Inflammatory signals directly instruct PU.1 in HSCs via TNF.

The molecular mechanisms governing the transition from hematopoietic stem cells (HSCs) to lineage-committed progenitors remain poorly understood. Transcription factors (TFs) are powerful cell intrinsic regulators of differentiation and lineage commitment, while cytokine signaling has been shown to instruct the fate of progenitor cells. However, the direct regulation of differentiation-inducing hematopoietic TFs by cell extrinsic signals remains surprisingly difficult to establish. PU.1 is a master regulator of hematopoiesis and promotes myeloid differentiation. Here we report that tumor necrosis factor (TNF) can directly and rapidly upregulate PU.1 protein in HSCs in vitro and in vivo. We demonstrate that in vivo, niche-derived TNF is the principal PU.1 inducing signal in HSCs and is both sufficient and required to relay signals from inflammatory challenges to HSCs.

Inductive and Selective Effects of GSK3 and MEK Inhibition on Nanog Heterogeneity in Embryonic Stem Cells.

Embryonic stem cells (ESCs) display heterogeneous expression of pluripotency factors such as Nanog when cultured with serum and leukemia inhibitory factor (LIF). In contrast, dual inhibition of the signaling kinases GSK3 and MEK (2i) converts ESC cultures into a state with more uniform and high Nanog expression. However, it is so far unclear whether 2i acts through an inductive or selective mechanism. Here, we use continuous time-lapse imaging to quantify the dynamics of death, proliferation, and Nanog expression in mouse ESCs after 2i addition. We show that 2i has a dual effect: it both leads to increased cell death of Nanog low ESCs (selective effect) and induces and maintains high Nanog levels (inductive effect) in single ESCs. Genetic manipulation further showed that presence of NANOG protein is important for cell viability in 2i medium. This demonstrates complex Nanog-dependent effects of 2i treatment on ESC cultures.

Mouse and human HSPC immobilization in liquid culture by CD43- or CD44-antibody coating.

Keeping track of individual cell identifications is imperative to the study of dynamic single-cell behavior over time. Highly motile hematopoietic stem and progenitor cells (HSPCs) migrate quickly and do not adhere, and thus must be imaged very frequently to keep cell identifications. Even worse, they are also flushed away during medium exchange. To overcome these limitations, we tested antibody coating for reducing HSPC motility in vitro. Anti-CD43- and anti-CD44-antibody coating reduced the cell motility of mouse and human HSPCs in a concentration-dependent manner. This enables 2-dimensional (2D) colony formation without cell mixing in liquid cultures, massively increases time-lapse imaging throughput, and also maintains cell positions during media exchange. Anti-CD43 but not anti-CD44 coating reduces mouse HSPC proliferation with increasing concentrations. No relevant effects on cell survival or myeloid and megakaryocyte differentiation of hematopoietic stem cells and multipotent progenitors 1-5 were detected. Human umbilical cord hematopoietic CD34+ cell survival, proliferation, and differentiation were not affected by either coating. This approach both massively simplifies and accelerates continuous analysis of suspension cells, and enables the study of their behavior in dynamic rather than static culture conditions over time.

fastER: a user-friendly tool for ultrafast and robust cell segmentation in large-scale microscopy.

MOTIVATION: Quantitative large-scale cell microscopy is widely used in biological and medical research. Such experiments produce huge amounts of image data and thus require automated analysis. However, automated detection of cell outlines (cell segmentation) is typically challenging due to, e.g. high cell densities, cell-to-cell variability and low signal-to-noise ratios. RESULTS: Here, we evaluate accuracy and speed of various state-of-the-art approaches for cell segmentation in light microscopy images using challenging real and synthetic image data. The results vary between datasets and show that the tested tools are either not robust enough or computationally expensive, thus limiting their application to large-scale experiments. We therefore developed fastER, a trainable tool that is orders of magnitude faster while producing state-of-the-art segmentation quality. It supports various cell types and image acquisition modalities, but is easy-to-use even for non-experts: it has no parameters and can be adapted to specific image sets by interactively labelling cells for training. As a proof of concept, we segment and count cells in over 200 000 brightfield images (1388 × 1040 pixels each) from a six day time-lapse microscopy experiment; identification of over 46 000 000 single cells requires only about two and a half hours on a desktop computer. AVAILABILITY AND IMPLEMENTATION: C ++ code, binaries and data at https://www.bsse.ethz.ch/csd/software/faster.html . CONTACT: oliver.hilsenbeck@bsse.ethz.ch or timm.schroeder@bsse.ethz.ch. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prospective identification of hematopoietic lineage choice by deep learning.

Differentiation alters molecular properties of stem and progenitor cells, leading to changes in their shape and movement characteristics. We present a deep neural network that prospectively predicts lineage choice in differentiating primary hematopoietic progenitors using image patches from brightfield microscopy and cellular movement. Surprisingly, lineage choice can be detected up to three generations before conventional molecular markers are observable. Our approach allows identification of cells with differentially expressed lineage-specifying genes without molecular labeling.

CSF-1-induced Src signaling can instruct monocytic lineage choice.

Controlled regulation of lineage decisions is imperative for hematopoiesis. Yet, the molecular mechanisms underlying hematopoietic lineage choices are poorly defined. Colony-stimulating factor 1 (CSF-1), the cytokine acting as the principal regulator of monocyte/macrophage (M) development, has been shown to be able to instruct the lineage choice of uncommitted granulocyte M (GM) progenitors toward an M fate. However, the intracellular signaling pathways involved are unknown. CSF-1 activates a multitude of signaling pathways resulting in a pleiotropic cellular response. The precise role of individual pathways within this complex and redundant signaling network is dependent on cellular context, and is not well understood. Here, we address which CSF-1-activated pathways are involved in transmitting the lineage-instructive signal in primary bone marrow-derived GM progenitors. Although its loss is compensated for by alternative signaling activation mechanisms, Src family kinase (SFK) signaling is sufficient to transmit the CSF-1 lineage instructive signal. Moreover, c-Src activity is sufficient to drive M fate, even in nonmyeloid cells.

Challenges in long-term imaging and quantification of single-cell dynamics.

Continuous analysis of single cells, over several cell divisions and for up to weeks at a time, is crucial to deciphering rare, dynamic and heterogeneous cell responses, which would otherwise be missed by population or single-cell snapshot analysis. Although the field of long-term single-cell imaging, tracking and analysis is constantly advancing, several technical challenges continue to hinder wider implementation of this important approach. This is a particular problem for mammalian cells, where in vitro observation usually remains the only possible option for uninterrupted long-term, single-cell observation. Efforts must focus not only on identifying and maintaining culture conditions that support normal cellular behavior while allowing high-resolution imaging over time, but also on developing computational methods that enable semiautomatic analysis of the data. Solutions in microscopy hard- and software, computer vision and specialized theoretical methods for analysis of dynamic single-cell data will enable important discoveries in biology and beyond.

Early myeloid lineage choice is not initiated by random PU.1 to GATA1 protein ratios.

The mechanisms underlying haematopoietic lineage decisions remain disputed. Lineage-affiliated transcription factors with the capacity for lineage reprogramming, positive auto-regulation and mutual inhibition have been described as being expressed in uncommitted cell populations. This led to the assumption that lineage choice is cell-intrinsically initiated and determined by stochastic switches of randomly fluctuating cross-antagonistic transcription factors. However, this hypothesis was developed on the basis of RNA expression data from snapshot and/or population-averaged analyses. Alternative models of lineage choice therefore cannot be excluded. Here we use novel reporter mouse lines and live imaging for continuous single-cell long-term quantification of the transcription factors GATA1 and PU.1 (also known as SPI1). We analyse individual haematopoietic stem cells throughout differentiation into megakaryocytic-erythroid and granulocytic-monocytic lineages. The observed expression dynamics are incompatible with the assumption that stochastic switching between PU.1 and GATA1 precedes and initiates megakaryocytic-erythroid versus granulocytic-monocytic lineage decision-making. Rather, our findings suggest that these transcription factors are only executing and reinforcing lineage choice once made. These results challenge the current prevailing model of early myeloid lineage choice.

Identification of factors promoting ex vivo maintenance of mouse hematopoietic stem cells by long-term single-cell quantification.

The maintenance of hematopoietic stem cells (HSCs) during ex vivo culture is an important prerequisite for their therapeutic manipulation. However, despite intense research, culture conditions for robust maintenance of HSCs are still missing. Cultured HSCs are quickly lost, preventing their improved analysis and manipulation. Identification of novel factors supporting HSC ex vivo maintenance is therefore necessary. Coculture with the AFT024 stroma cell line is capable of maintaining HSCs ex vivo long-term, but the responsible molecular players remain unknown. Here, we use continuous long-term single-cell observation to identify the HSC behavioral signature under supportive or nonsupportive stroma cocultures. We report early HSC survival as a major characteristic of HSC-maintaining conditions. Behavioral screening after manipulation of candidate molecules revealed that the extracellular matrix protein dermatopontin (Dpt) is involved in HSC maintenance. DPT knockdown in supportive stroma impaired HSC survival, whereas ectopic expression of the Dpt gene or protein in nonsupportive conditions restored HSC survival. Supplementing defined stroma- and serum-free culture conditions with recombinant DPT protein improved HSC clonogenicity. These findings illustrate a previously uncharacterized role of Dpt in maintaining HSCs ex vivo.

Network plasticity of pluripotency transcription factors in embryonic stem cells.

Transcription factor (TF) networks are thought to regulate embryonic stem cell (ESC) pluripotency. However, TF expression dynamics and regulatory mechanisms are poorly understood. We use reporter mouse ESC lines allowing non-invasive quantification of Nanog or Oct4 protein levels and continuous long-term single-cell tracking and quantification over many generations to reveal diverse TF protein expression dynamics. For cells with low Nanog expression, we identified two distinct colony types: one re-expressed Nanog in a mosaic pattern, and the other did not re-express Nanog over many generations. Although both expressed pluripotency markers, they exhibited differences in their TF protein correlation networks and differentiation propensities. Sister cell analysis revealed that differences in Nanog levels are not necessarily accompanied by differences in the expression of other pluripotency factors. Thus, regulatory interactions of pluripotency TFs are less stringently implemented in individual self-renewing ESCs than assumed at present.

An automatic method for robust and fast cell detection in bright field images from high-throughput microscopy.

BACKGROUND: In recent years, high-throughput microscopy has emerged as a powerful tool to analyze cellular dynamics in an unprecedentedly high resolved manner. The amount of data that is generated, for example in long-term time-lapse microscopy experiments, requires automated methods for processing and analysis. Available software frameworks are well suited for high-throughput processing of fluorescence images, but they often do not perform well on bright field image data that varies considerably between laboratories, setups, and even single experiments. RESULTS: In this contribution, we present a fully automated image processing pipeline that is able to robustly segment and analyze cells with ellipsoid morphology from bright field microscopy in a high-throughput, yet time efficient manner. The pipeline comprises two steps: (i) Image acquisition is adjusted to obtain optimal bright field image quality for automatic processing. (ii) A concatenation of fast performing image processing algorithms robustly identifies single cells in each image. We applied the method to a time-lapse movie consisting of ∼315,000 images of differentiating hematopoietic stem cells over 6 days. We evaluated the accuracy of our method by comparing the number of identified cells with manual counts. Our method is able to segment images with varying cell density and different cell types without parameter adjustment and clearly outperforms a standard approach. By computing population doubling times, we were able to identify three growth phases in the stem cell population throughout the whole movie, and validated our result with cell cycle times from single cell tracking. CONCLUSIONS: Our method allows fully automated processing and analysis of high-throughput bright field microscopy data. The robustness of cell detection and fast computation time will support the analysis of high-content screening experiments, on-line analysis of time-lapse experiments as well as development of methods to automatically track single-cell genealogies.