Key genes and integrated modules in hematopoietic differentiation of human embryonic stem cells: a comprehensive bioinformatic analysis

The transcriptomic landscape of canonical activation of NLRP3 inflammasome from bone marrow-derived macrophages

The NLRP3 inflammasome has gained significant attention due to its participation in diverse cellular processes. Nevertheless, the detailed framework of the canonical NLRP3 inflammasome assembly still remains unrevealed. This study aims to elucidate the transcriptomic landscape of the various stages involved in the canonical activation of the NLRP3 inflammasome in BMDMs by integrating RNA-seq, bioinformatics, and molecular dynamics analyses. The model for the canonical activation of the NLRP3 inflammasome was confirmed through morphological observations, functional assessments (ELISA and LDH), and protein detection (western blot). Subsequently, cells were subjected to RNA sequencing following three groups: control, priming (LPS 500 ng/ml, 4 h), and activation (LPS 500 ng/ml, 4 h; ATP 5 mM, 1 h). A total of 9116 differentially expressed genes (DEGs) were identified, which exerted regulatory effects on various pathways, including cell metabolism, ion fluxes, post-translational modifications, and organelles. Subsequently, six hub genes (Sirt3, Stat3, Syk, Trpm2, Tspo, and Txnip) were identified via integrating literature review and database screening. Finally, the three-dimensional structures of these six hub proteins were obtained using the MD-optimized RoseTTAFold and Gromacs simulations (at least 200 ns). In summary, our research offers novel insights into the transcriptomic-level understanding of the assembly of the canonical NLRP3 inflammasome.

Role of PLC/IP3 /IP3 R axis in excess molybdenum exposure induced apoptosis in duck renal tubular epithelial cells

Excess molybdenum (Mo) is harmful to animals, but its nephrotoxicity has not been comprehensively explained. To appraise the influences of excess Mo on Ca homeostasis and apoptosis via PLC/IP3 /IP3 R axis, primary duck renal tubular epithelial cells were exposed to 480 μM and 960 μM Mo, and joint of 960 μM Mo and 10 μM 2-APB or 0.125 μM U-73122 for 12 h (U-73122 pretreated for 1 h), respectively. The data revealed that the increment of [Ca2+ ]c induced by Mo mainly originated from intracellular Ca storage. Mo exposure reduced [Ca2+ ]ER , elevated [Ca2+ ]mit , [Ca2+ ]c , and the expression of Ca homeostasis-related factors (Calpain, CaN, CRT, GRP94, GRP78 and CaMKII). 2-APB could effectively reverse subcellular Ca2+ redistribution by inhibiting IP3 R, which confirmed that [Ca2+ ]c overload induced by Mo originated from ER. Additionally, PLC inhibitor U-73122 remarkably mitigated the change, and dramatically reduced the number of apoptotic cells, the expression of Bak-1, Bax, cleaved-Caspase-3/Caspase-3, and notably increased the expression of Bcl-xL, Bcl-2, and Bcl-2/Bax ratio. Overall, the results confirmed that the Ca2+ liberation of ER via PLC/IP3 /IP3 R axis was the main cause of [Ca2+ ]c overload, and then stimulated apoptosis in duck renal tubular epithelial cells.

Expression and prognostic analysis of BGN in head and neck squamous cell carcinoma

OBJECTIVE

BGN belongs to class of small leucine rich proteoglycans, which is high expression in plenty of human cancers. However, the detailed role of BGN remains unclear in Head and neck squamous cell carcinoma (HNSC).

MATERIALS AND METHODS

In this study, we assessed the transcriptional expression, protein expression, prognosis, co-expressed genes, functional enrichment, and hub genes in HNSC patients based on the data published in the following databases: ONCOMINE, GEPIA, GEO, LinkedOmics, and HPA databases. Data from the TCGA database was used to analyze the correlations between BGN expression and different clinicopathological features, as well as prognostic analysis.

RESULTS

We found that the expression of BGN is higher in patients with HNSC than in control tissues. Pathologically, high BGN expression was significantly correlated with T3 and T4 stage. Besides, high expression of BGN is a poor prognostic factor for overall surviva, not disease free survival. The co-expression genes associated with BGN expression exhibited enriched in various function and pathway, such as extracellular matrix, mitochondrion, PI3K-Akt signaling pathway. A total of 10 hub genes were identified from the co-expressed genes, within which five genes, including FSTL1, LAMB1, SDC2, VCAN, and IGFBP7, were significantly increased in patient's with HNSC. BGN exhibited weak correlations with tumor-infiltrating CD4+ T, macrophages cell, and dendritic cells. Futhermore, many markers of infiltrating immune cells, such as Treg, showed different BGN-related immune infiltration patterns. BGN expression showed strong correlations with diverse immune marker sets in COAD and STAD.

CONCLUSIONS

Our results demonstrated that BGN is high expression in HNSC and is a poor prognostic factor for clinical outcome in patients with HNSC. It could serve as a potential prognostic biomarker for patients survival in HNSC.

Transcriptomic Changes in Mouse Bone Marrow-Derived Macrophages Exposed to Neuropeptide FF

Neuropeptide FF (NPFF) is a neuropeptide that regulates various biological activities. Currently, the regulation of NPFF on the immune system is an emerging field. However, the influence of NPFF on the transcriptome of primary macrophages has not been fully elucidated. In this study, the effect of NPFF on the transcriptome of mouse bone marrow-derived macrophages (BMDMs) was explored by RNA sequencing, bioinformatics, and molecular simulation. BMDMs were treated with 1 nM NPFF for 18 h, followed by RNA sequencing. Differentially expressed genes (DEGs) were obtained, followed by GO, KEGG, and PPI analysis. A total of eight qPCR-validated DEGs were selected as hub genes. Subsequently, the three-dimensional (3-D) structures of the eight hub proteins were constructed by Modeller and Rosetta. Next, the molecular dynamics (MD)-optimized 3-D structure of hub protein was acquired with Gromacs. Finally, the binding modes between NPFF and hub proteins were studied by Rosetta. A total of 2655 DEGs were obtained (up-regulated 1442 vs. down-regulated 1213), and enrichment analysis showed that NPFF extensively regulates multiple functional pathways mediated by BMDMs. Moreover, the 3-D structure of the hub protein was obtained after MD-optimization. Finally, the docking modes of NPFF-hub proteins were predicted. Besides, NPFFR2 was expressed on the cell membrane of BMDMs, and NPFF 1 nM significantly activated NPFFR2 protein expression. In summary, instead of significantly inhibiting the expression of the immune-related gene transcriptome of RAW 264.7 cells, NPFF simultaneously up-regulated and down-regulated the gene expression profile of a large number of BMDMs, hinting that NPFF may profoundly affect a variety of cellular processes dominated by BMDMs. Our work provides transcriptomics clues for exploring the influence of NPFF on the physiological functions of BMDMs.

Prolactin-Releasing Peptide Differentially Regulates Gene Transcriptomic Profiles in Mouse Bone Marrow-Derived Macrophages

Prolactin-releasing Peptide (PrRP) is a neuropeptide whose receptor is GPR10. Recently, the regulatory role of PrRP in the neuroendocrine field has attracted increasing attention. However, the influence of PrRP on macrophages, the critical housekeeper in the neuroendocrine field, has not yet been fully elucidated. Here, we investigated the effect of PrRP on the transcriptome of mouse bone marrow-derived macrophages (BMDMs) with RNA sequencing, bioinformatics, and molecular simulation. BMDMs were exposed to PrRP (18 h) and were subjected to RNA sequencing. Differentially expressed genes (DEGs) were acquired, followed by GO, KEGG, and PPI analysis. Eight qPCR-validated DEGs were chosen as hub genes. Next, the three-dimensional structures of the proteins encoded by these hub genes were modeled by Rosetta and Modeller, followed by molecular dynamics simulation by the Gromacs program. Finally, the binding modes between PrRP and hub proteins were investigated with the Rosetta program. PrRP showed no noticeable effect on the morphology of macrophages. A total of 410 DEGs were acquired, and PrRP regulated multiple BMDM-mediated functional pathways. Besides, the possible docking modes between PrRP and hub proteins were investigated. Moreover, GPR10 was expressed on the cell membrane of BMDMs, which increased after PrRP exposure. Collectively, PrRP significantly changed the transcriptome profile of BMDMs, implying that PrRP may be involved in various physiological activities mastered by macrophages.

Cellular processes involved in RAW 264.7 macrophages exposed to NPFF: A transcriptional study

Neuropeptide FF (NPFF) is a neuropeptide that modulates various physiological processes. The regulatory role of NPFF in the immune and inflammatory response is currently being revealed. However, the effect of NPFF at the transcriptome level in macrophages has not been fully elucidated. Here, the impact of NPFF on gene expression at the transcriptome level of RAW 264.7 cells was investigated by RNA-seq. RAW 264.7 macrophages were treated with NPFF (1 nM) for 18 h, followed by RNA-seq examination. Differentially expressed genes (DEGs) were acquired, followed by GO, KEGG, and PPI analysis. A total of eight qPCR-verified DEGs were obtained. Next, three-dimensional models of the eight hub proteins were constructed by using homology modeling with Modeller (9v23). Finally, molecular dynamics simulation (300 ns) was performed with GROMACS 2018.2 to investigate the structural characteristics of these hub proteins. NPFF had no detectable effect on the morphology of RAW264.7 cells. A total of 211 DEGs were acquired, and an enrichment study demonstrated that the immune response-related pathway was significantly inhibited by NPFF. Moreover, the molecular dynamics optimized-protein models of the hub proteins were obtained. Collectively, NPFF inhibited the expression of immune-related genes in RAW 264.7 cells at the transcriptome level, which suggested a negative relationship between NPFF and this set of immune-related genes in RAW 264.7 macrophages. Therefore, our data may provide direct evidence of the role of NPFF in peripheral or central inflammatory diseases.

Optimized combination methods for exploring and verifying disease-resistant transcription factors in melon

A large amount of omics data and number of bioinformatics tools has been produced. However, the methods for further exploring omics data are simple, in particular, to mine key regulatory genes, which are a priority concern in biological systems, and most of the specific functions are still unknown. First, raw data of two genotypes of melon (susceptible and resistant) were obtained by transcriptome analysis. Second, 391 transcription factors (TFs) were identified from the plant transcription factor database and cucurbit genomics database. Then, functional enrichment analysis indicated that these genes were mainly annotated in the process of transcription regulation. Third, 243 and 230 module-specific TFs were screened by weighted gene coexpression network analysis and short time series expression miner, respectively. Several TF genes, such as WRKYs and bHLHs, were regarded as key regulatory genes according to the values of significantly different modules. The coexpression network showed that these TF genes were significant correlated with resistance (R) genes, such as DRP2, RGA3, DRP1 and NB-ARC. Fourth, cis-acting element analysis illustrated that these R genes may bind to WRKY and bHLH. Finally, the expression of WRKY genes was verified by quantitative reverse transcription PCR (RT-qPCR). Phylogenetic analysis was carried out to further confirm that these TFs may play a critical role in Curcurbitaceae disease resistance. This study provides a new optimized combination strategy to explore the functions of TFs in a wide spectrum of biological processes. This strategy may also effectively predict potential relationships in the interactions of essential genes.

Transcriptome Analysis Reveals High Similarities between Adult Human Cardiac Stem Cells and Neural Crest-Derived Stem Cells

For the identification of a stem cell population, the comparison of transcriptome data enables the simultaneous analysis of tens of thousands of molecular markers and thus enables the precise distinction of even closely related populations. Here, we utilized global gene expression profiling to compare two adult human stem cell populations, namely neural crest-derived inferior turbinate stem cells (ITSCs) of the nasal cavity and human cardiac stem cells (hCSCs) from the heart auricle. We detected high similarities between the transcriptomes of both stem cell populations, particularly including a range of neural crest-associated genes. However, global gene expression likewise reflected differences between the stem cell populations with regard to their niches of origin. In a broader analysis, we further identified clear similarities between ITSCs, hCSCs and other adherent stem cell populations compared to non-adherent hematopoietic progenitor cells. In summary, our observations reveal high similarities between adult human cardiac stem cells and neural crest-derived stem cells from the nasal cavity, which include a shared relation to the neural crest. The analyses provided here may help to understand underlying molecular regulators determining differences between adult human stem cell populations.

Differentiation of human induced pluripotent stem cells into erythroid cells

During the last years, several strategies have been made to obtain mature erythrocytes or red blood cells (RBC) from the bone marrow or umbilical cord blood (UCB). However, UCB-derived hematopoietic stem cells (HSC) are a limited source and in vitro large-scale expansion of RBC from HSC remains problematic. One promising alternative can be human pluripotent stem cells (PSCs) that provide an unlimited source of cells. Human PSCs, including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), are self-renewing progenitors that can be differentiated to lineages of ectoderm, mesoderm, and endoderm. Several previous studies have revealed that human ESCs can differentiate into functional oxygen-carrying erythrocytes; however, the ex vivo expansion of human ESC-derived RBC is subjected to ethical concerns. Human iPSCs can be a suitable therapeutic choice for the in vitro/ex vivo manufacture of RBCs. Reprogramming of human somatic cells through the ectopic expression of the transcription factors (OCT4, SOX2, KLF4, c-MYC, LIN28, and NANOG) has provided a new avenue for disease modeling and regenerative medicine. Various techniques have been developed to generate enucleated RBCs from human iPSCs. The in vitro production of human iPSC-derived RBCs can be an alternative treatment option for patients with blood disorders. In this review, we focused on the generation of human iPSC-derived erythrocytes to present an overview of the current status and applications of this field.

Hub Proteins Involved in RAW 264.7 Macrophages Exposed to Direct Current Electric Field

At present, studies on macrophage proteins mainly focus on biological stimuli, with less attention paid to the responses of macrophage proteins to physical stimuli, such as electric fields. Here, we exploited the electric field-sensitive hub proteins of macrophages. RAW 264.7 macrophages were treated with a direct current electric field (dcEF) (200 mV/mm) for four hours, followed by RNA-Seq analysis. Differentially expressed genes (DEGs) were obtained, followed by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) and protein–protein interaction (PPI) analysis. Eight qPCR-verified DEGs were selected. Subsequently, three-dimensional protein models of DEGs were modeled by Modeller and Rosetta, followed by molecular dynamics simulation for 200 ns with GROMACS. Finally, dcEFs (10, 50, and 500 mV/mm) were used to simulate the molecular dynamics of DEG proteins for 200 ns, followed by trajectory analysis. The dcEF has no obvious effect on RAW 264.7 morphology. A total of 689 DEGs were obtained, and enrichment analysis showed that the steroid biosynthesis pathway was most affected by the dcEF. Moreover, the three-dimensional protein structures of hub proteins were constructed, and trajectory analysis suggested that the dcEF caused an increase in the atomic motion of the protein in a dcEF-intensity-dependent manner. Overall, we provide new clues and a basis for investigating the hub proteins of macrophages in response to electric field stimulation.

Ribosome and Translational Control in Stem Cells

Embryonic stem cells (ESCs) and adult stem cells (ASCs) possess the remarkable capacity to self-renew while remaining poised to differentiate into multiple progenies in the context of a rapidly developing embryo or in steady-state tissues, respectively. This ability is controlled by complex genetic programs, which are dynamically orchestrated at different steps of gene expression, including chromatin remodeling, mRNA transcription, processing, and stability. In addition to maintaining stem cell homeostasis, these molecular processes need to be rapidly rewired to coordinate complex physiological modifications required to redirect cell fate in response to environmental clues, such as differentiation signals or tissue injuries. Although chromatin remodeling and mRNA expression have been extensively studied in stem cells, accumulating evidence suggests that stem cell transcriptomes and proteomes are poorly correlated and that stem cell properties require finely tuned protein synthesis. In addition, many studies have shown that the biogenesis of the translation machinery, the ribosome, is decisive for sustaining ESC and ASC properties. Therefore, these observations emphasize the importance of translational control in stem cell homeostasis and fate decisions. In this review, we will provide the most recent literature describing how ribosome biogenesis and translational control regulate stem cell functions and are crucial for accommodating proteome remodeling in response to changes in stem cell fate.

Cellular Processes Involved in Jurkat Cells Exposed to Nanosecond Pulsed Electric Field

Recently, nanosecond pulsed electric field (nsPEF) has been considered as a new tool for tumor therapy, but its molecular mechanism of function remains to be fully elucidated. Here, we explored the cellular processes of Jurkat cells exposed to nanosecond pulsed electric field. Differentially expressed genes (DEGs) were acquired from the GEO2R, followed by analysis with a series of bioinformatics tools. Subsequently, 3D protein models of hub genes were modeled by Modeller 9.21 and Rosetta 3.9. Then, a 100 ns molecular dynamics simulation for each hub protein was performed with GROMACS 2018.2. Finally, three kinds of nsPEF voltages (0.01, 0.05, and 0.5 mV/mm) were used to simulate the molecular dynamics of hub proteins for 100 ns. A total of 1769 DEGs and eight hub genes were obtained. Molecular dynamic analysis, including root mean square deviation (RMSD), root mean square fluctuation (RMSF), and the Rg, demonstrated that the 3D structure of hub proteins was built, and the structural characteristics of hub proteins under different nsPEFs were acquired. In conclusion, we explored the effect of nsPEF on Jurkat cell signaling pathway from the perspective of molecular informatics, which will be helpful in understanding the complex effects of nsPEF on acute T-cell leukemia Jurkat cells.