Sequential Differentiation of Embryonic Stem Cells into Neural Epithelial-Like Stem Cells and Oligodendrocyte Progenitor Cells

<div><p>Background</p><p>Recent advances in stem cell technology afford an unlimited source of neural progenitors and glial cells for cell based therapy in central nervous system (CNS) disorders. However, current differentiation strategies still need to be improved due to time-consuming processes, poorly defined culture conditions, and low yield of target cell populations.</p><p>Methodology/Principle Findings</p><p>This study aimed to provide a precise sequential differentiation to capture two transient stages: neural epithelia-like stem cells (NESCs) and oligodendrocytes progenitor cells (OPCs) derived from mouse embryonic stem cells (ESCs). CHIR99021, a glycogen synthase kinase 3 (GSK-3) inhibitor, in combination with dual SMAD inhibitors, could induce ESCs to rapidly differentiate into neural rosette-like colonies, which facilitated robust generation of NESCs that had a high self-renewal capability and stable neuronal and glial differentiation potentials. Furthermore, SHH combined with FGF-2 and PDGF-AA could induce NESCs to differentiate into highly expandable OPCs. These OPCs not only robustly differentiated into oligodendrocytes, but also displayed an increased migratory activity <i>in vitro</i>.</p><p>Conclusions/Significance</p><p>We developed a precise and reliable strategy for sequential differentiation to capture NESCs and OPCs derived from ESCs, thus providing unlimited cell source for cell transplantation and drug screening towards CNS repair.</p></div

Comparison of NSCs and NESCs.

<p>(A) Phase contrast of NSCs isolated from mouse embryo cortex and NESCs derived from ESCs, which were both at p1. (B) RT-PCR analysis of NSCs and NESCs at P1 with representative NSC markers (C) According to the expression of representative genes in NESCs and NSCs, as determined by RT-PCR, NESCs shared similar markers as NSCs such as Pax6, Neurod4, Ncam1, Nestin, and Rarb. (D) Immunocytochemistry of NSCs and NESCs at P1 revealed that they shared similar NSC markers such as Sox1, Pax6, Sox9 and CD133. Scale bar, 200 μm in A, and 50 μm in D.</p

Rapid and robust differentiation of ESCs into NESCs.

<p>(A) Phase-contrast and fluorescence images of mouse ESCs, which express Oct3/4 and SSEA1. (B) Under defined differentiation conditions by adding SB431542, Dorsomorphin, Noggin, and CHIR99021, ESCs made transitions into neural rosette-like colonies expressing Pax6 and Sox1. (C) ESCs-derived-NESCs differentiated into neuroepithelial-like stem cells (NESCs) expressing Pax6 and Sox1. (D) Cumulative curve showing ESCs-derived NESCs could be expanded over 20 passages (Passage denoted P1-P20). *<i>p</i><0.05, passage 20 (P20) versus all other passages. (E, F) qPCR of representative markers during neural differentiation from ESCs to patterned neural rosettes-like colonies (NR) and NESCs showing a rapid downregulation in pluripotency genes such as Oct4 and Nanog and upregulation in genes specific to NR and NESCs such as Pax6 and Nestin. (G) Representative confocal image showing NESCs were highly pure as the percentage of PLZF-positive cells in total cell population was 97% ± 1%, the values significantly higher than those for negative control (cell population stained only with secondary antibody). Nuclei counterstained with Ho (Hoechst 33342 blue). Data were expressed as means ± SEM from 4 chosen fields per slide. Scale bar, 200 μm in phase contrast images and 50 μm in fluorescence images of A, B, C; and scale bar, 25μm in F. *<i>p</i><0.05.</p

Efficient differentiation of NESCs-derived OPCs into OLs.

<p>(A) phase contrast image (left) and fluorescence images (right) by marker MBP for OLs. The percentage of MBP positive population among the differentiated OLs was significantly higher than negative control (cell population stained only with secondary antibody) (B) RT-PCR analysis compared NESCs, OPCs, and OLs with representative markers for each population. (C) qPCR profiling, performed during the transition of NESCs-derived OPCs to OLs, showing a rapid down regulation of OPCs genes and up regulation of genes specific to OLs. (D) Phase contrast (left) and immunofluorescence image (right) of astrocytes marked with GFAP differentiated from OPCs, and quantitative analysis revealed that there was significant different between the percentage of GFAP positive astrocytes and negative control marked only with 2° antibody. (p<0.05) (E) Immunofluorescence image of neurons derived from NESCs with a marker of β-tubulin III. Also shown (at the right half) is a magnification of the boxed area in the left half. Scale bar, 100 μm in (A), 200 μm in (D), 100 μm in the left half of (E), and 50 μm in the right half of (E). *<i>p</i><0.05.</p

Schematic diagram showing step-by-step differentiation of ESCs into OLs under influences of a series of developmental signals.

<p>Schematic diagram showing step-by-step differentiation of ESCs into OLs under influences of a series of developmental signals.</p

Comparison of NESCs at different passages.

<p>(A) Phase contrast of NESCs at P1 and P10. (B) Flow cytometry analysis revealed that percentage of NESC population positive for Nestin and PLZF are over 90% at both p1 and p10. (C) Immunocytochemistry of NESC showed that NESCs at P10 still expressed neuroepithelial stem cell markers, such as Sox1, Sox2, Dach1, PLZF and ZO-1 as in P1. Scale bar, 200 μm in A, and 50 μm in C.</p

Differentiation of ESCs-derived NESCs into expandable OPCs.

<p>(A) Phase contrast image of mESC-derived NESCs differentiated into OPCs with bipolar morphology under defined medium containing FGF2, PDGF-AA and SAG on matri-gel coated plate. Also shown (inset) is a magnification of the boxed area in (A). (B) Cumulative growth curve of NESCs-derived OPCs divide over eight passages (P1-P8). *p<0.05, P6, P7, or P8 versus P1-P5 respectively. (C) qPCR analysis showed that during the transition of NESCs into OPCs, the genes specific to NESCs such as Nestin and Pax6 were down-regulated, while the genes specific to OPCs such as Nkx2.2, Sox10, and PDGFRα were up-regulated. (D) Immunostaining of OPCs showed they were nearly homogenous expressing transcription factors Olig2 and Sox10, (E) The percentages of Olig2- and Sox10-positive cells in total cell population were 91 ± 2% and 94 ± 3%, respectively, the values significantly higher than those for negative control (cell population stained only with secondary antibody). *p<0.05. (F) NESCs displayed a 5–6 fold increase in migratory activity in response to FGF2, PDGF and SHH treatment comparing to the basal medium. Data were expressed as means ± SEM and derived from 2–4 independent experiments, *p<0.05. Scale bar, 200 μm in (A) and 100 μm in (D) or in the inset of (A).</p

Graphene oxide-coated stir bar sorptive extraction of trace aflatoxins from soy milk followed by high performance liquid chromatography-laser-induced fluorescence detection

<p>Mycotoxins are potential food pollutants produced by fungi. Among them, aflatoxins (AFs) are the most toxic. Therefore, AFs were selected as models, and a sensitive, simple and green graphene oxide (GO)-based stir bar sorptive extraction (SBSE) method was developed for extraction and determination of AFs with high performance liquid chromatography-laser-induced fluorescence detector (HPLC-LIF). This method improved the sensitivity of AFs detection and solved the deposition difficulty of the direct use of GO as adsorbent. Several parameters including a spiked amount of NaCl, stirring rate, extraction time and desorption time were investigated. Under optimal conditions, the quantitative method had low limits of detection of 2.4–8.0 pg/mL, which were better than some reported AFs analytical methods. The developed method has been applied to soy milk samples with good recoveries ranging from 80.5 to 102.3%. The prepared GO-based SBSE can be used as a sensitive screening technique for detecting AFs in soy milk.</p

DataSheet_1_Single-cell sequencing reveals the landscape of the tumor microenvironment in a skeletal undifferentiated pleomorphic sarcoma patient.pdf

Skeletal undifferentiated pleomorphic sarcoma (SUPS) is an invasive pleomorphic soft tissue sarcoma with a high degree of malignancy and poor prognosis. It is prone to recur and metastasize. The tumor microenvironment (TME) and the pathophysiology of SUPS are barely described. Single-cell RNA sequencing (scRNA-seq) provides an opportunity to dissect the landscape of human diseases at an unprecedented resolution, particularly in diseases lacking animal models, such as SUPS. We performed scRNA-seq to analyze tumor tissues and paracancer tissues from a SUPS patient. We identified the cell types and the corresponding marker genes in this SUPS case. We further showed that CD8+ exhausted T cells and Tregs highly expressed PDCD1, CTLA4 and TIGIT. Thus, PDCD1, CTLA4 and TIGIT were identified as potential targets in this case. We applied copy number karyotyping of aneuploid tumors (CopyKAT) to distinguish malignant cells from normal cells in fibroblasts. Our study identified eight malignant fibroblast subsets in SUPS with distinct gene expression profiles. C1-malignant Fibroblast and C6-malignant Fibroblast in the TME play crucial roles in tumor growth, angiogenesis, metastasis and immune response. Hence, targeting malignant fibroblasts could represent a potential strategy for this SUPS therapy. Intervention via tirelizumab enabled disease control, and immune checkpoint inhibitors (ICIs) of PD-1 may be considered as the first-line option in patients with SUPS. Taken together, scRNA-seq analyses provided a powerful basis for this SUPS treatment, improved our understanding of complex human diseases, and may afforded an alternative approach for personalized medicine in the future.</p