A major limitation in anti-tuberculosis drug screening is the lack of reliable and scalable models for homogeneous human primary macrophage cells of non-cancer origin. Here we report a modified protocol for generating homogeneous populations of macrophage-like cells from human embryonic stem cells. The induced macrophages, referred to as iMACs, presented similar transcriptomic profiles and characteristic immunological features of classical macrophages and were permissive to viral and bacterial infection, in particular Mycobacterium tuberculosis (Mtb). More importantly, iMAC production was amenable to scale up. To evaluate iMAC efficiency in high-throughput anti-tuberculosis drug screening, we performed a phenotypic screening against intracellular Mtb, involving a library of 3,716 compounds that included FDA-approved drugs and other bioactive compounds. Our primary screen identified 120 hits, which were validated in a secondary screen by dose-intracellular and-extracellular Mtb assays. Our confirmatory studies identified a novel anti-Mtb compound, 10-DEBC, also showing activity against drug-resistant strains.

Human pluripotent stem cells (hPSCs) have promising therapeutic applications due to their infinite capacity for self-renewal and pluripotency. Genomic stability is imperative for the clinical use of hPSCs; however, copy number variation (CNV), especially recurrent CNV at 20q11.21, may contribute genomic instability of hPSCs. Furthermore, the effects of CNVs in hPSCs at the whole-transcriptome scale are poorly understood. This study aimed to examine the functional in vivo and in vitro effects of frequently detected CNVs at 20q11.21 during early-stage differentiation of hPSCs. Comprehensive transcriptome profiling of abnormal hPSCs revealed that the differential gene expression patterns had a negative effect on differentiation potential. Transcriptional heterogeneity identified by single-cell RNA sequencing (scRNA-seq) of embryoid bodies from two different isogenic lines of hPSCs revealed alterations in differentiated cell distributions compared with that of normal cells. RNA-seq analysis of 22 teratomas identified several differentially expressed lineage-specific markers in hPSCs with CNVs, consistent with the histological results of the altered ecto/meso/endodermal ratio due to CNVs. Our results suggest that CNV amplification contributes to cell proliferation, apoptosis, and cell fate specification. This work shows the functional consequences of recurrent genetic abnormalities and thereby provides evidence to support the development of cell-based applications.

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Large insertions and deletions (indels), including copy number variations (CNVs), are commonly seen in many diseases. Standard approaches for indel detection rely on well-established methods such as qPCR or short tandem repeat (STR) markers. Recently, a number of tools for CNV detection based on next-generation sequencing (NGS) data have also been developed; however, use of these methods is limited. Here, we used whole-exome sequencing (WES) in patients previously diagnosed with CMT1A or HNPP using STR markers to evaluate the ability of WES to improve the clinical diagnosis. Patients were evaluated utilizing three CNV detection tools including CONIFER, ExomeCNV and CEQer, and array comparative genomic hybridization (aCGH). We identified a breakpoint region at 17p11.2-p12 in patients with CMT1A and HNPP. CNV detection levels were similar in both 6 Gb (mean read depth = 80×) and 17 Gb (mean read depth = 190×) data. Taken together, these data suggest that 6 Gb WES data are sufficient to reveal the genetic causes of various diseases and can be used to estimate single mutations, indels, and CNVs simultaneously. Furthermore, our data strongly indicate that CNV detection by NGS is a rapid and cost-effective method for clinical diagnosis of genetically heterogeneous disorders such as CMT neuropathy. Conflict of interestThe authors report no conflict of interest. Structural variants including copy number variation (CNV) and insertions and deletions (indel) have been highlighted as the causes of genetic disorders. Recently, it has been reported that CNVs significantly contribute to various diseases such as neurodevelopmental disorders, intellectual disabilities and numerous cancers

Macrophages exhibit high plasticity to achieve their roles in maintaining tissue homeostasis, innate immunity, tissue repair and regeneration. Therefore, macrophages are being evaluated for cell-based therapeutics against inflammatory disorders and cancer. To overcome the limitation related to expansion of primary macrophages and cell numbers, human pluripotent stem cell (hPSC)-derived macrophages are considered as an alternative source of primary macrophages for clinical application. However, the quality of hPSC-derived macrophages with respect to the biological homogeneity remains still unclear. We previously reported a technique to produce hPSC-derived macrophages referred to as iMACs, which is amenable for scale-up. In this study, we have evaluated the biological homogeneity of the iMACs using a transcriptome dataset of 6,230 iMACs obtained by single-cell RNA sequencing. The dataset provides a valuable genomic profile for understanding the molecular characteristics of hPSC-derived macrophage cells and provide a measurement of transcriptomic homogeneity. Our study highlights the usefulness of single cell RNA-seq data in quality control of the cell-based therapy products.

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IntroductionDespite of massive endeavors to characterize inflammation in COVID-19 patients, the core network of inflammatory mediators responsible for severe pneumonia stillremain remains elusive. MethodsHere, we performed quantitative and kinetic analysis of 191 inflammatory factors in 955 plasma samples from 80 normal controls (sample n = 80) and 347 confirmed COVID-19 pneumonia patients (sample n = 875), including 8 deceased patients. ResultsDifferential expression analysis showed that 76% of plasmaproteins (145 factors) were upregulated in severe COVID-19 patients comparedwith moderate patients, confirming overt inflammatory responses in severe COVID-19 pneumonia patients. Global correlation analysis of the plasma factorsrevealed two core inflammatory modules, core I and II, comprising mainly myeloid cell and lymphoid cell compartments, respectively, with enhanced impact in a severity-dependent manner. We observed elevated IFNA1 and suppressed IL12p40, presenting a robust inverse correlation in severe patients, which was strongly associated with persistent hyperinflammation in 8.3% of moderate pneumonia patients and 59.4% of severe patients. DiscussionAberrant persistence of pulmonary and systemic inflammation might be associated with long COVID-19 sequelae. Our comprehensive analysis of inflammatory mediators in plasmarevealed the complexity of pneumonic inflammation in COVID-19 patients anddefined critical modules responsible for severe pneumonic progression.

Understanding and monitoring virus-mediated infections has gained importance since the global outbreak of the coronavirus disease 2019 (COVID-19) pandemic. Studies of high-throughput omics-based immune profiling of COVID-19 patients can help manage the current pandemic and future virus-mediated pandemics. Although COVID-19 is being studied since past 2 years, detailed mechanisms of the initial induction of dynamic immune responses or the molecular mechanisms that characterize disease progression remains unclear. This study involved comprehensively collected biospecimens and longitudinal multi-omics data of 300 COVID-19 patients and 120 healthy controls, including whole genome sequencing (WGS), single-cell RNA sequencing combined with T cell receptor (TCR) and B cell receptor (BCR) sequencing (scRNA(+scTCR/BCR)-seq), bulk BCR and TCR sequencing (bulk TCR/BCR-seq), and cytokine profiling. Clinical data were also collected from hospitalized COVID-19 patients, and HLA typing, laboratory characteristics, and COVID-19 viral genome sequencing were performed during the initial diagnosis. The entire set of biospecimens and multi-omics data generated in this project can be accessed by researchers from the National Biobank of Korea with prior approval. This distribution of largescale multi-omics data of COVID-19 patients can facilitate the understanding of biological crosstalk involved in COVID-19 infection and contribute to the development of potential methodo-logies for its diagnosis and treatment. [BMB Reports 2022; 55(9): 465-471]