Cell lineage specification during development of the anterior lateral plate mesoderm and forelimb field

The lateral plate mesoderm (LPM) is a transient embryonic tissue that gives rise to a diverse range of mature cell types, including the cardiovascular system, the urogenital system, endoskeleton of the limbs, and mesenchyme of the gut. While the genetic processes that drive development of these tissues are well defined, the early cell fate choices underlying LPM development and specification are poorly understood. In this study, we utilize single-cell transcriptomics to define cell lineage specification during development of the anterior LPM and the forelimb field in the chicken embryo. We identify the molecular pathways directing differentiation of the aLPM towards a somatic or splanchnic cell fate, and subsequent emergence of the forelimb mesenchyme. We establish the first transcriptional atlas of progenitor, transitional and mature cell types throughout the early forelimb field and uncover the global signalling pathways which are active during LPM differentiation and forelimb initiation. Specification of the somatic and splanchnic LPM from undifferentiated mesoderm utilizes distinct signalling pathways and involves shared repression of early mesodermal markers, followed by activation of lineage-specific gene modules. We identify rapid activation of the transcription factor TWIST1 in the somatic LPM preceding activation of known limb initiation genes, such as TBX5, which plays a likely role in epithelial-to-mesenchyme transition of the limb bud mesenchyme. Furthermore, development of the somatic LPM and limb is dependent on ectodermal BMP signalling, where BMP antagonism reduces expression of key somatic LPM and limb genes to inhibit formation of the limb bud mesenchyme. Together, these findings provide new insights into molecular mechanisms that drive fate cell choices during specification of the aLPM and forelimb initiation.

Oncogenes, Proto-Oncogenes, and Lineage Restriction of Cancer Stem Cells

In principle, an oncogene is a cellular gene (proto-oncogene) that is dysfunctional, due to mutation and fusion with another gene or overexpression. Generally, oncogenes are viewed as deregulating cell proliferation or suppressing apoptosis in driving cancer. The cancer stem cell theory states that most, if not all, cancers are a hierarchy of cells that arises from a transformed tissue-specific stem cell. These normal counterparts generate various cell types of a tissue, which adds a new dimension to how oncogenes might lead to the anarchic behavior of cancer cells. It is that stem cells, such as hematopoietic stem cells, replenish mature cell types to meet the demands of an organism. Some oncogenes appear to deregulate this homeostatic process by restricting leukemia stem cells to a single cell lineage. This review examines whether cancer is a legacy of stem cells that lose their inherent versatility, the extent that proto-oncogenes play a role in cell lineage determination, and the role that epigenetic events play in regulating cell fate and tumorigenesis.

Intestine-enriched apolipoprotein b orthologs regulate stem cell differentiation and regeneration in planarians

Little is known about how lipid mobilization and utilization are modulated during stem-cell-driven tissue growth during regeneration. Planarian flatworms can regenerate all missing tissues in 10 days due to the proliferation and differentiation of pluripotent somatic stem cells called neoblasts. In planarians, diet-derived neutral lipids are stored in the intestine. Here, we identify two intestine-enriched paralogs of apolipoprotein b, apob-1 and apob-2, that are required for regeneration. Consistent with apolipoproteins' known roles regulating neutral lipid (NL) transport in lipoprotein particles (LPs), NLs increased in the intestine upon simultaneous dsRNA-mediated knockdown of apob-1 and apob-2, but were depleted in neoblasts and their progeny. apob knockdown reduced regeneration blastema morphogenesis, and delayed re-establishment of axial polarity and regeneration of multiple organs. Using flow cytometry, we found that neoblast progeny accumulated in apob(RNAi) animals, with minimal effects on neoblast maintenance or proliferation. In addition, ApoB reduction primarily dysregulated expression of transcripts enriched in neoblast progeny and mature cell types, compared to cycling neoblasts. Together, our results provide evidence that intestine-derived lipids serve as a source of metabolites required for neoblast differentiation. In addition, these findings demonstrate that planarians are a tractable model for elucidating specialized mechanisms by which lipid metabolism must be regulated during animal regeneration.

A Quantitative Hematopoietic Stem Cell Reconstitution Protocol: Accounting for Recipient Variability, Tissue Distribution and Cell Half-Lives

Hematopoietic stem and progenitor cell (HSPC) transplantation is the paradigm for stem cell therapies. The protocol described here enables quantitative assessment of the body-wide HSPC reconstitution of different mature hematopoietic cells in mice based on their presence in circulating blood. The method determines donor-derived mature cell populations per mouse, over time, by quantitatively obtaining their absolute numbers in the peripheral blood and utilizing previously assessed tissue-distribution factors. A Markov-based birth/death computational model accounts for the drastic differences in mature cell half-lives. By quantifying the number of cells produced and eliminating host variability, the protocol can be used to directly compare the lineage output of different types of HSPCs on a per cell basis, thereby clarifying the lineage potential and expansion capacity of different cell populations. These protocols were developed for hematopoiesis, but can readily be extended to other contexts by simply replacing the cell types and distributions.HighlightsQuantitative assessment of stem and progenitor cell reconstitution capacityElimination of cell-specific recipient variability for accurate donor cell potentialDirectly comparable lineage output within and between stem and progenitor cellsBlood-based absolute quantification of whole-body repopulation over timeMarkov modelling-based consideration of differential mature cell half-lives

Lineage tracing on transcriptional landscapes links state to fate during differentiation

A challenge in biology is to associate molecular differences among progenitor cells with their capacity to generate mature cell types. Here, we used expressed DNA barcodes to clonally trace transcriptomes over time and applied this to study fate determination in hematopoiesis. We identified states of primed fate potential and located them on a continuous transcriptional landscape. We identified two routes of monocyte differentiation that leave an imprint on mature cells. Analysis of sister cells also revealed cells to have intrinsic fate biases not detectable by single-cell RNA sequencing. Finally, we benchmarked computational methods of dynamic inference from single-cell snapshots, showing that fate choice occurs earlier than is detected by state-of the-art algorithms and that cells progress steadily through pseudotime with precise and consistent dynamics.

Uncovering the activities, biological roles, and regulation of bacterial cell wall hydrolases and tailoring enzymes

Bacteria account for 1000-fold more biomass than humans. They vary widely in shape and size. The morphological diversity of bacteria is due largely to the different peptidoglycan-based cell wall structures that encase bacterial cells. Although the basic structure of peptidoglycan is highly conserved, consisting of long glycan strands that are cross-linked by short peptide chains, the mature cell wall is chemically diverse. Peptidoglycan hydrolases and cell wall–tailoring enzymes that regulate glycan strand length, the degree of cross-linking, and the addition of other modifications to peptidoglycan are central in determining the final architecture of the bacterial cell wall. Historically, it has been difficult to biochemically characterize these enzymes that act on peptidoglycan because suitable peptidoglycan substrates were inaccessible. In this review, we discuss fundamental aspects of bacterial cell wall synthesis, describe the regulation and diverse biochemical and functional activities of peptidoglycan hydrolases, and highlight recently developed methods to make and label defined peptidoglycan substrates. We also review how access to these substrates has now enabled biochemical studies that deepen our understanding of how bacterial cell wall enzymes cooperate to build a mature cell wall. Such improved understanding is critical to the development of new antibiotics that disrupt cell wall biogenesis, a process essential to the survival of bacteria.

Clinical Evidence Against the Continuum of Low-Primed Uncommitted Hematopoietic and Progenitor Cells (CLOUD-HSPC) Concept for Hematopoiesis

Introduction: The classical model of blood stem cell differentiation is branch-like linear HSPC progression from progenitor multi/oligo potent stem cells to differentiated mature cell types. An alternative model, referred to as CLOUD-HSPC, proposes bone marrow (BM) HSPCs continuous and direct differentiation into unipotent cells of myeloid lineage (neutrophils (N), basophils (B), eosinophils (E), monocytes (M), mast cells, megakaryocytes (platelets) and erythrocytes without linear stem cell commitment (Velten Nat Cell Biol 2017). Pegfilgrastim (Peg), and the non-colony stimulating agent Plinabulin (Plin) prevent chemotherapy (chemo) induced neutropenia (CIN) in cancer patients (pts), and both exert BM effects leading to CD34+ cell mobilization (Blayney ASH 2017, 2018). In mice, Plin enhances LSK (Lin-Sca+cKit3+) cell differentiation in BM (Ghosh, AACR 2018). Here we clinically validated the CLOUD-HSPC concept by analyzing peripheral blood mononuclear cell (PBMC) counts derived from two bifurcating progenitor cells 1. Granulocyte-Monocyte Progenitor (GMP) producing N,M,E and B and 2. Common Lymphoid Progenitor (CLP) producing lymphocytes (L), after exposure to Peg or Plin in a CIN setting. With linear stem cell commitment, increase in the differentiated mature cell counts would positively inter-correlate, and with CLOUD-HSPC, they would not. Methods: In the Phase 3 portion of study BPI-2358-105 (NCT03102606), pts with NSCLC, BC or HRPC received pre-medication with dexamethasone (Dex) on day (D) -1,0, and 1 and docetaxel (Doc) on day (D) 1. Pts were randomized 1:1 to either Plin 40 mg (n=52), given 30 min after Doc infusion D1, or Peg 6 mg (n=53), D2. Central laboratory (Covance Laboratory) PBMC counts were obtained at screening, D 1,2, 6,7,8,9,10, 15 in Cycle 1, and correlated with each other at a pre-planned interim analysis. D1 and D2 data points were omitted due to confounding effects of Dex and demargination. Data of Plin and Peg were combined, since both drugs exert BM effects leading to increased N cell counts and showed similar correlation trends. Results: Maximum increases in % from screening value on D5-D15 of each N,M,E,B and L counts correlated with each other. Pearson correlation coefficients (r) after linear regression and corresponding p-value are summarized below. Conclusions: There is a linear and positive inter-correlation between differentiated mature cells derived from the GMP and CLP lineage, proving strong clinical evidence against CLOUD-HSPC, but in favor of the classical linear commitment model. Table Disclosures Mohanlal: BeyondSpring Pharmaceuticals: Employment. Blayney:BeyondSpring Pharmaceuticals: Research Funding. Huang:BeyondSpring Pharmaceuticals: Employment.