Histamine releasing factor and elongation factor 1 alpha secreted via malaria parasites extracellular vesicles promote immune evasion by inhibiting specific T cell responses

Protozoan pathogens secrete nanosized particles called extracellular vesicles (EVs) to facilitate their survival and chronic infection. Here, we show the inhibition by Plasmodium berghei NK65 blood stage‐derived EVs of the proliferative response of CD4⁺ T cells in response to antigen presentation. Importantly, these results were confirmed in vivo by the capacity of EVs to diminish the ovalbumin‐specific delayed type hypersensitivity response. We identified two proteins associated with EVs, the histamine releasing factor (HRF) and the elongation factor 1α (EF‐1α) that were found to have immunosuppressive activities. Interestingly, in contrast to WT parasites, EVs from genetically HRF‐ and EF‐1α‐deficient parasites failed to inhibit T cell responses in vitro and in vivo. At the level of T cells, we demonstrated that EVs from WT parasites dephosphorylate key molecules (PLCγ1, Akt, and ERK) of the T cell receptor signalling cascade. Remarkably, immunisation with EF‐1α alone or in combination with HRF conferred a long‐lasting antiparasite protection and immune memory. In conclusion, we identified a new mechanism by which P. berghei‐derived EVs exert their immunosuppressive functions by altering T cell responses. The identification of two highly conserved immune suppressive factors offers new conceptual strategies to overcome EV‐mediated immune suppression in malaria‐infected individuals.     

Diversity of the Fusarium pathogens associated with crown rot in the Huanghuai wheat-growing region of China

To investigate the distribution and diversity of the pathogens associated with Fusarium crown rot in the Huanghuai wheat-growing region (HHWGR) of China, we collected wheat samples with symptomatic stem bases from seven provinces in the HHWGR between 2013 and 2016. A total of 1196 isolates obtained from 222 locations were identified as 9 Fusarium species based on morphological and molecular identification. Of these pathogen species, F. pseudograminearum was the dominant species. Furthermore, F. sinensis was isolated from the disease specimens and tested for virulence to wheat. The result of the pathogenicity revealed that an intraspecific differentiation existed in F. pseudograminearum; sequence analysis of the EF-1α gene showed that 194 F. pseudograminearum isolates were differentiated into two distinct clades which closed to the strains from Australia and China respectively, but neither pathogenicity nor EF-1α sequence was related to the geographic origins of these isolates. However, universal rice primers-polymerase chain reaction showed a correlation with the geographical origins of the 194 isolates, which were divided into eight subclusters, the level of genetic diversity was higher within a geographical population than among the different populations. The results of these analyses can be directly used to facilitate disease monitoring and development of control strategies.     

Chloroplast clustering around the nucleus is a general response to pathogen perception in Nicotiana benthamiana

It is increasingly clear that chloroplasts play a central role in plant stress responses. Upon activation of immune responses, chloroplasts are the source of multiple defensive signals, including reactive oxygen species (ROS). Intriguingly, it has been described that chloroplasts establish physical contact with the nucleus, through clustering around it and extending stromules, following activation of effector-triggered immunity (ETI). However, how prevalent this phenomenon is in plant–pathogen interactions, how its induction occurs, and what the underlying biological significance is are important questions that remain unanswered. Here, we describe that the chloroplast perinuclear clustering seems to be a general plant response upon perception of an invasion threat. Indeed, activation of pattern-triggered immunity, ETI, transient expression of the Rep protein from geminiviruses, or infection with viruses or bacteria all are capable of triggering this response in Nicotiana benthamiana. Interestingly, this response seems non-cell-autonomous, and exogenous treatment with H₂O₂ is sufficient to elicit this relocalization of chloroplasts, which appears to require accumulation of ROS. Taken together, our results indicate that chloroplasts cluster around the nucleus during plant–pathogen interactions, suggesting a fundamental role of this positioning in plant defence, and identify ROS as sufficient and possibly required for the onset of this response.     

Perivascular adipose tissue‐derived stromal cells contribute to vascular remodeling during aging

Aging is an independent risk factor for vascular diseases. Perivascular adipose tissue (PVAT), an active component of the vasculature, contributes to vascular dysfunction during aging. Identification of underlying cell types and their changes during aging may provide meaningful insights regarding the clinical relevance of aging‐related vascular diseases. Here, we take advantage of single‐cell RNA sequence to characterize the resident stromal cells in the PVAT (PVASCs) and identified different clusters between young and aged PVASCs. Bioinformatics analysis revealed decreased endothelial and brown adipogenic differentiation capacities of PVASCs during aging, which contributed to neointimal hyperplasia after perivascular delivery to ligated carotid arteries. Mechanistically, in vitro and in vivo studies both suggested that aging‐induced loss of peroxisome proliferator‐activated receptor‐γ coactivator‐1 α (PGC1α) was a key regulator of decreased brown adipogenic differentiation in senescent PVASCs. We further demonstrated the existence of human PVASCs (hPVASCs) and overexpression of PGC1α improved hPVASC delivery‐induced vascular remodeling. Our finding emphasizes that differentiation capacities of PVASCs alter during aging and loss of PGC1α in aged PVASCs contributes to vascular remodeling via decreased brown adipogenic differentiation.     

Long non-coding RNA CCAT1 promotes cervical cancer cell proliferation and invasion by regulating the miR-181a-5p/MMP14 axis

Cervical cancer is a serious threat to women’s health and is the third most common malignancy in women worldwide. Recent studies indicate that the long non-coding RNA CCAT1 plays a role in the malignant behavior of many tumors. However, the role of CCAT1 in cervical cancer is still unknown. Our aim is to evaluate the expression and investigate the regulatory role and potential mechanism of CCAT1 in cervical cancer. CCAT1 expression was measured by qRT-PCR. In addition, CCK-8 assays, colony formation assays, qRT-PCR assays, Transwell assays and xenograft experiments were performed to determine the role of CCAT1 in the proliferation and invasion in cervical cancer cells. The expression of CCAT1 in the cervical cancer tissues was higher than in the adjacent normal tissues. Overexpressing CCAT1 promoted cervical cancer cell proliferation, colony formation, and invasion in vitro. Elevated CCAT1 suppressed miR-181a expression, which was accompanied by an increased expression of MMP14 and HB-EGF. In contrast, knocking down CCAT1 resulted in increased expression of miR-181a, along with decreased expression of MMP14 and HB-EGF. Thus, CCAT1 is a key oncogenic lncRNA associated with cervical cancer and plays a role in promoting cervical cancer cell proliferation and invasion by regulating the miR-181a-5p/MMP14 axis.     

Integrative analysis identifies potential DNA methylation biomarkers for pan-cancer diagnosis and prognosis

DNA methylation status is closely associated with diverse diseases, and is generally more stable than gene expression, thus abnormal DNA methylation could be important biomarkers for tumor diagnosis, treatment and prognosis. However, the signatures regarding DNA methylation changes for pan-cancer diagnosis and prognosis are less explored. Here we systematically analyzed the genome-wide DNA methylation patterns in diverse TCGA cancers with machine learning. We identified seven CpG sites that could effectively discriminate tumor samples from adjacent normal tissue samples for 12 main cancers of TCGA (1216 samples, AUC > 0.99). Those seven potential diagnostic biomarkers were further validated in the other 9 different TCGA cancers and 4 independent datasets (AUC > 0.92). Three out of the seven CpG sites were correlated with cell division, DNA replication and cell cycle. We also identified 12 CpG sites that can effectively distinguish 26 different cancers (7605 samples), and the result was repeatable in independent datasets as well as two disparate tumors with metastases (micro-average AUC > 0.89). Furthermore, a series of potential signatures that could significantly predict the prognosis of tumor patients for 7 different cancer were identified via survival analysis (p-value < 1e-4). Collectively, DNA methylation patterns vary greatly between tumor and adjacent normal tissues, as well as among different types of cancers. Our identified signatures may aid the decision of clinical diagnosis and prognosis for pan-cancer and the potential cancer-specific biomarkers could be used to predict the primary site of metastatic breast and prostate cancers.     

MCLPMDA: A novel method for miRNA‐disease association prediction based on matrix completion and label propagation

MiRNAs are a class of small non‐coding RNAs that are involved in the development and progression of various complex diseases. Great efforts have been made to discover potential associations between miRNAs and diseases recently. As experimental methods are in general expensive and time‐consuming, a large number of computational models have been developed to effectively predict reliable disease‐related miRNAs. However, the inherent noise and incompleteness in the existing biological datasets have inevitably limited the prediction accuracy of current computational models. To solve this issue, in this paper, we propose a novel method for miRNA‐disease association prediction based on matrix completion and label propagation. Specifically, our method first reconstructs a new miRNA/disease similarity matrix by matrix completion algorithm based on known experimentally verified miRNA‐disease associations and then utilizes the label propagation algorithm to reliably predict disease‐related miRNAs. As a result, MCLPMDA achieved comparable performance under different evaluation metrics and was capable of discovering greater number of true miRNA‐disease associations. Moreover, case study conducted on Breast Neoplasms further confirmed the prediction reliability of the proposed method. Taken together, the experimental results clearly demonstrated that MCLPMDA can serve as an effective and reliable tool for miRNA‐disease association prediction.     

3D Printing of Tunable Energy Storage Devices with Both High Areal and Volumetric Energy Densities

Developing advanced supercapacitors with both high areal and volumetric energy densities remains challenging. In this work, self‐supported, compact carbon composite electrodes are designed with tunable thickness using 3D printing technology for high‐energy‐density supercapacitors. The 3D carbon composite electrodes are composed of the closely stacked and aligned active carbon/carbon nanotube/reduced graphene oxide (AC/CNT/rGO) composite filaments. The AC microparticles are uniformly embedded in the wrinkled CNT/rGO conductive networks without using polymer binders, which contributes to the formation of abundant open and hierarchical pores. The 3D‐printed ultrathick AC/CNT/rGO composite electrode (ten layers) features high areal and volumetric mass loadings of 56.9 mg cm^?2 and 256.3 mg cm^?3, respectively. The symmetric cell assembled with the 3D‐printed thin GO separator and ultrathick AC/CNT/rGO electrodes can possess both high areal and volumetric capacitances of 4.56 F cm^?2 and 10.28 F cm^?3, respectively. Correspondingly, the assembled ultrathick and compact symmetric cell achieves high areal and volumetric energy densities of 0.63 mWh cm^?2 and 1.43 mWh cm^?3, respectively. The all‐component extrusion‐based 3D printing offers a promising strategy for the fabrication of multiscale and multidimensional structures of various high‐energy‐density electrochemical energy storage devices.