Derived myeloid lineage induced pluripotent stem as a platform to study human C-C chemokine receptor type 5Δ32 homozygotes.

The C-C chemokine receptor type 5 (CCR5) expressed on immune cells supports inflammatory responses by directing cells to the inflammation site. CCR5 is also a major coreceptor for macrophage tropic human immunodeficiency viruses (R5-HIV-1) and its variants can confer protection from HIV infection, making it an ideal candidate to target for therapy. We developed a stepwise protocol that differentiates induced pluripotent stem cells (iPSCs) from individuals homozygous for the CCR5Δ32 variant and healthy volunteers into myeloid lineage induced monocytes (iMono) and macrophages (iMac). By characterizing iMono and iMac against their primary counterparts, we demonstrated that CCR5Δ32 homozygous cells are endowed with similar pluripotent potential for self-renewal and differentiation as iPSC lines generated from non-variant individuals while also showing resistance to HIV infection. In conclusion, these cells are a platform to investigate CCR5 pathophysiology in HIV-positive and negative individuals and to help develop novel therapies.

Assessing Biomaterial-Induced Stem Cell Lineage Fate by Machine Learning-Based Artificial Intelligence.

Current functional assessment of biomaterial-induced stem cell lineage fate in vitro mainly relies on biomarker-dependent methods with limited accuracy and efficiency. Here a "Mesenchymal stem cell Differentiation Prediction (MeD-P)" framework for biomaterial-induced cell lineage fate prediction is reported. MeD-P contains a cell-type-specific gene expression profile as a reference by integrating public RNA-seq data related to tri-lineage differentiation (osteogenesis, chondrogenesis, and adipogenesis) of human mesenchymal stem cells (hMSCs) and a predictive model for classifying hMSCs differentiation lineages using the k-nearest neighbors (kNN) strategy. It is shown that MeD-P exhibits an overall accuracy of 90.63% on testing datasets, which is significantly higher than the model constructed based on canonical marker genes (80.21%). Moreover, evaluations of multiple biomaterials show that MeD-P provides accurate prediction of lineage fate on different types of biomaterials as early as the first week of hMSCs culture. In summary, it is demonstrated that MeD-P is an efficient and accurate strategy for stem cell lineage fate prediction and preliminary biomaterial functional evaluation.

STAT3 modulates reprogramming efficiency of human somatic cells; insights from autosomal dominant Hyper IgE syndrome caused by STAT3 mutations.

Human induced pluripotent stem cell (iPSC) technology has opened exciting opportunities for stem-cell-based therapy. However, its wide adoption is precluded by several challenges including low reprogramming efficiency and potential for malignant transformation. Better understanding of the molecular mechanisms of the changes that cells undergo during reprograming is needed to improve iPSCs generation efficiency and to increase confidence for their clinical use safety. Here, we find that dominant negative mutations in STAT3 in patients with autosomal-dominant hyper IgE (Job's) syndrome (AD-HIES) result in greatly reduced reprograming efficiency of primary skin fibroblasts derived from skin biopsies. Analysis of normal skin fibroblasts revealed upregulation and phosphorylation of endogenous signal transducer and activator of transcription 3 (STAT3) and its binding to the NANOG promoter following transduction with OKSM factors. This coincided with upregulation of NANOG and appearance of cells expressing pluripotency markers. Upregulation of NANOG and number of pluripotent cells were greatly reduced throughout the reprograming process of AD-HIES fibroblasts that was restored by over-expression of functional STAT3. NANOGP8, the human-specific NANOG retrogene that is often expressed in human cancers, was also induced during reprogramming, to very low but detectable levels, in a STAT3-dependent manner. Our study revealed the critical role of endogenous STAT3 in facilitating reprogramming of human somatic cells.

Impaired angiogenesis and extracellular matrix metabolism in autosomal-dominant hyper-IgE syndrome.

There are more than 7000 described rare diseases, most lacking specific treatment. Autosomal-dominant hyper-IgE syndrome (AD-HIES, also known as Job's syndrome) is caused by mutations in STAT3. These patients present with immunodeficiency accompanied by severe nonimmunological features, including skeletal, connective tissue, and vascular abnormalities, poor postinfection lung healing, and subsequent pulmonary failure. No specific therapies are available for these abnormalities. Here, we investigated underlying mechanisms in order to identify therapeutic targets. Histological analysis of skin wounds demonstrated delayed granulation tissue formation and vascularization during skin-wound healing in AD-HIES patients. Global gene expression analysis in AD-HIES patient skin fibroblasts identified deficiencies in a STAT3-controlled transcriptional network regulating extracellular matrix (ECM) remodeling and angiogenesis, with hypoxia-inducible factor 1α (HIF-1α) being a major contributor. Consistent with this, histological analysis of skin wounds and coronary arteries from AD-HIES patients showed decreased HIF-1α expression and revealed abnormal organization of the ECM and altered formation of the coronary vasa vasorum. Disease modeling using cell culture and mouse models of angiogenesis and wound healing confirmed these predicted deficiencies and demonstrated therapeutic benefit of HIF-1α-stabilizing drugs. The study provides mechanistic insights into AD-HIES pathophysiology and suggests potential treatment options for this rare disease.

An Atlas of Network Topologies Reveals Design Principles for Caenorhabditis elegans Vulval Precursor Cell Fate Patterning.

The vulval precursor cell (VPC) fate patterning in Caenorhabditis elegans is a classic model experimental system for cell fate determination and patterning in development. Despite its apparent simplicity (six neighboring cells arranged in one dimension) and many experimental and computational efforts, the patterning strategy and mechanism remain controversial due to incomplete knowledge of the complex biology. Here, we carry out a comprehensive computational analysis and obtain a reservoir of all possible network topologies that are capable of VPC fate patterning under the simulation of various biological environments and regulatory rules. We identify three patterning strategies: sequential induction, morphogen gradient and lateral antagonism, depending on the features of the signal secreted from the anchor cell. The strategy of lateral antagonism, which has not been reported in previous studies of VPC patterning, employs a mutual inhibition of the 2° cell fate in neighboring cells. Robust topologies are built upon minimal topologies with basic patterning strategies and have more flexible and redundant implementations of modular functions. By simulated mutation, we find that all three strategies can reproduce experimental error patterns of mutants. We show that the topology derived by mapping currently known biochemical pathways to our model matches one of our identified functional topologies. Furthermore, our robustness analysis predicts a possible missing link related to the lateral antagonism strategy. Overall, we provide a theoretical atlas of all possible functional networks in varying environments, which may guide novel discoveries of the biological interactions in vulval development of Caenorhabditis elegans and related species.