Dirk Loeffler

Inflammation-Induced Emergency Megakaryopoiesis Driven by Hematopoietic Stem Cell-like Megakaryocyte Progenitors

Infections are associated with extensive platelet consumption, representing a high risk for health. However, the mechanism coordinating the rapid regeneration of the platelet pool during such stress conditions remains unclear. Here, we report that the phenotypic hematopoietic stem cell (HSC) compartment contains stem-like megakaryocyte-committed progenitors (SL-MkPs), a cell population that shares many features with multipotent HSCs and serves as a lineage-restricted emergency pool for inflammatory insults. During homeostasis, SL-MkPs are maintained in a primed but quiescent state, thus contributing little to steady-state megakaryopoiesis. Even though lineage-specific megakaryocyte transcripts are expressed, protein synthesis is suppressed. In response to acute inflammation, SL-MkPs become activated, resulting in megakaryocyte protein production from pre-existing transcripts and a maturation of SL-MkPs and other megakaryocyte progenitors. This results in an efficient replenishment of platelets that are lost during inflammatory insult. Thus, our study reveals an emergency machinery that counteracts life-threatening platelet depletions during acute inflammation.

Chronic interleukin-1 exposure drives haematopoietic stem cells towards precocious myeloid differentiation at the expense of self-renewal.

Haematopoietic stem cells (HSCs) maintain lifelong blood production and increase blood cell numbers in response to chronic and acute injury. However, the mechanism(s) by which inflammatory insults are communicated to HSCs and their consequences for HSC activity remain largely unknown. Here, we demonstrate that interleukin-1 (IL-1), which functions as a key pro-inflammatory ‘emergency’ signal, directly accelerates cell division and myeloid differentiation of HSCs through precocious activation of a PU.1-dependent gene program. Although this effect is essential for rapid myeloid recovery following acute injury to the bone marrow, chronic IL-1 exposure restricts HSC lineage output, severely erodes HSC self-renewal capacity, and primes IL-1-exposed HSCs to fail massive replicative challenges such as transplantation. Importantly, these damaging effects are transient and fully reversible on IL-1 withdrawal. Our results identify a critical regulatory circuit that tailors HSC responses to acute needs, and is likely to underlie deregulated blood homeostasis in chronic inflammation conditions.

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.

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.

Software tools for single-cell tracking and quantification of cellular and molecular properties

Software tools for single-cell tracking and quantification of cellular and molecular properties

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.

Advances in tracking hematopoiesis at the single-cell level.

Purpose of reviewStudying heterogeneous populations, such as hematopoietic stem cells (HSCs), requires continuous long-term observation of living cells at the single-cell level. The purpose of this review is to discuss recent advances in technologies required for continuous single-cell analysis and the contribution of this approach to find answers in hematopoiesis research. Recent findingsContinuous long-term imaging at the single-cell level still requires custom-made hardware, software and manual in-depth analysis of large amounts of data. Despite these technical difficulties, continuous time-lapse imaging and single-cell tracking are increasingly used in hematopoiesis research. It has already contributed to answering decades-old questions. SummaryContinuous long-term single-cell analysis is indispensable for a comprehensive analysis of dynamic processes in heterogeneous cell populations. Despite many remaining technological hurdles, this approach is increasingly used in hematopoiesis research.

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.

HSC-Explorer: A Curated Database for Hematopoietic Stem Cells

HSC-Explorer (http://mips.helmholtz-muenchen.de/HSC/) is a publicly available, integrative database containing detailed information about the early steps of hematopoiesis. The resource aims at providing fast and easy access to relevant information, in particular to the complex network of interacting cell types and molecules, from the wealth of publications in the field through visualization interfaces. It provides structured information on more than 7000 experimentally validated interactions between molecules, bioprocesses and environmental factors. Information is manually derived by critical reading of the scientific literature from expert annotators. Hematopoiesis-relevant interactions are accompanied with context information such as model organisms and experimental methods for enabling assessment of reliability and relevance of experimental results. Usage of established vocabularies facilitates downstream bioinformatics applications and to convert the results into complex networks. Several predefined datasets (Selected topics) offer insights into stem cell behavior, the stem cell niche and signaling processes supporting hematopoietic stem cell maintenance. HSC-Explorer provides a versatile web-based resource for scientists entering the field of hematopoiesis enabling users to inspect the associated biological processes through interactive graphical presentation.

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.