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The gut microbiota has been proposed as a promising determinant for human health. Centenarians as a model for extreme aging may help us understand the correlation of gut microbiota with healthy aging and longevity. Here we confirmed that centenarians had microbiota elements usually associated with benefits to health. Our finding of a high capacity of glycolysis and related SCFA production represented a healthy microbiome and environment that is regarded as beneficial for host gut epithelium. The low abundance of genes encoding components of pathways involved in carbohydrate degradation was also found in the gut microbiota of Sardinian centenarians and is often associated with poor gut health. Overall, our study here represents an expansion of previous research investigating the age-related changes in gut microbiota. Furthermore, our study provides a new prospective for potential targets for gut microbiota intervention directed at limiting gut inflammation and pathology and enhancing a healthy gut barrier. Sardinia, Italy, has a high prevalence of residents who live more than 100 years. The reasons for longevity in this isolated region are currently unknown. Gut microbiota may hold a clue. To explore the role gut microbiota may play in healthy aging and longevity, we used metagenomic sequencing to determine the compositional and functional differences in gut microbiota associated with populations of different ages in Sardinia. Our data revealed that the gut microbiota of both young and elderly Sardinians shared similar taxonomic and functional profiles. A different pattern was found in centenarians. Within the centenarian group, the gut microbiota was correlated with the functional independence measurement of the host. Centenarians had a higher diversity of core microbiota species and microbial genes than those in the young and elderly. We found that the gut microbiota in Sardinian centenarians displayed a rearranged taxonomic pattern compared with those of the young and elderly, featured by depletion of Faecalibacterium prausnitzii and Eubacterium rectale and enriched for Methanobrevibacter smithii and Bifidobacterium adolescentis . Moreover, functional analysis revealed that the microbiota in centenarians had high capacity for central metabolism, especially glycolysis and fermentation to short-chain fatty acids (SCFAs), although the gut microbiota in centenarians was low in genes encoding enzymes involved in degradation of carbohydrates, including fibers and galactose. IMPORTANCE The gut microbiota has been proposed as a promising determinant for human health. Centenarians as a model for extreme aging may help us understand the correlation of gut microbiota with healthy aging and longevity. Here we confirmed that centenarians had microbiota elements usually associated with benefits to health. Our finding of a high capacity of glycolysis and related SCFA production represented a healthy microbiome and environment that is regarded as beneficial for host gut epithelium. The low abundance of genes encoding components of pathways involved in carbohydrate degradation was also found in the gut microbiota of Sardinian centenarians and is often associated with poor gut health. Overall, our study here represents an expansion of previous research investigating the age-related changes in gut microbiota. Furthermore, our study provides a new prospective for potential targets for gut microbiota intervention directed at limiting gut inflammation and pathology and enhancing a healthy gut barrier.

On 31 December 2019 the Wuhan Health Commission reported a cluster of atypical pneumonia cases that was linked to a wet market in the city of Wuhan, China. The first patients began experiencing symptoms of illness in mid-December 2019. Clinical isolates were found to contain a novel coronavirus with similarity to bat coronaviruses. As of 28 January 2020, there are in excess of 4,500 laboratory-confirmed cases, with > 100 known deaths. As with the SARS-CoV, infections in children appear to be rare. Travel-related cases have been confirmed in multiple countries and regions outside mainland China including Germany, France, Thailand, Japan, South Korea, Vietnam, Canada, and the United States, as well as Hong Kong and Taiwan. Domestically in China, the virus has also been noted in several cities and provinces with cases in all but one provinence. While zoonotic transmission appears to be the original source of infections, the most alarming development is that human-to-human transmission is now prevelant. Of particular concern is that many healthcare workers have been infected in the current epidemic. There are several critical clinical questions that need to be resolved, including how efficient is human-to-human transmission? What is the animal reservoir? Is there an intermediate animal reservoir? Do the vaccines generated to the SARS-CoV or MERS-CoV or their proteins offer protection against 2019-nCoV? We offer a research perspective on the next steps for the generation of vaccines. We also present data on the use of in silico docking in gaining insight into 2019-nCoV Spike-receptor binding to aid in therapeutic development. Diagnostic PCR protocols can be found at https://www.who.int/health-topics/coronavirus/laboratory-diagnostics-for-novel-coronavirus.

BackgroundAcute myeloid leukemia (AML) is a heterogeneous blood disease with poor treatment effect and high recurrence rate. With the deepening of non-coding RNA research, more and more miRNAs have been found to participate in various physiological processes of tumors. In this study, we tried to find the miRNA related to the prognosis of AML.MethodsCollect gene expression data and clinical information of AML patients in the Cancer Genome Atlas database for statistical analysis. The expression level of miR-195 of each patient was standardized by logCPM and then produced as a box plot according to subtype classification. TargetScan was used to predict the target genes of miR-195, and these genes were subjected to GO pathway enrichment analysis by Metascape. Differential miRNAs were screened through the DESeq2 package in the R language. Survival rates were estimated using the Kaplan–Meier method and the log-rank test. The multivariate Cox proportional hazard models of EFS and OS were established.ResultsWe found that the expression of miR-195 was the lowest in cytogenetically normal (CN-) AML, and high expression of miR-195 only promoted the prognosis of chemotherapy-only CN-AML patients (EFS: P = 0.016; OS: P = 0.035). Multivariate analysis showed that miR-195high was a favorable and independent factor for CN-AML (both P < 0.05). Further analysis showed that miR-195 may affect signal transduction through ANHAK2 in AML.ConclusionWe found that high expression of miR-195 can increase prognosis time of chemotherapy-only CN-AML patients, providing a new possibility for treatment.

Background The high degree of heterogeneity brought great challenges to the diagnosis and treatment of acute myeloid leukemia (AML). Although several different AML prognostic scoring models have been proposed to assess the prognosis of patients, the accuracy still needs to be improved. As important components of the tumor microenvironment, immune cells played important roles in the physiological functions of tumors and had certain research value. Therefore, whether the tumor immune microenvironment (TIME) can be used to assess the prognosis of AML aroused our great interest. Methods The patients’ gene expression profile from 7 GEO databases was normalized after removing the batch effect. TIME cell components were explored through Xcell tools and then hierarchically clustered to establish TIME classification. Subsequently, a prognostic model was established by Lasso-Cox. Multiple GEO databases and the Cancer Genome Atlas dataset were employed to validate the prognostic performance of the model. Receiver operating characteristic (ROC) and the concordance index (C-index) were utilized to assess the prognostic efficacy. Results After analyzing the composition of TIME cells in AML, we found infiltration of ten types of cells with prognostic significance. Then using hierarchical clustering methods, we established a TIME classification system, which clustered all patients into three groups with distinct prognostic characteristics. Using the differential genes between the first and third groups in the TIME classification, we constructed a 121-gene prognostic model. The model successfully divided 1229 patients into the low and high groups which had obvious differences in prognosis. The high group with shorter overall survival had more patients older than 60 years and more poor-risk patients (both P < 0.001). Besides, the model can perform well in multiple datasets and could further stratify the cytogenetically normal AML patients and intermediate-risk AML population. Compared with the European Leukemia Net Risk Stratification System and other AML prognostic models, our model had the highest C-index and the largest AUC of the ROC curve, which demonstrated that our model had the best prognostic efficacy. Conclusion A prognostic model for AML based on the TIME classification was constructed in our study, which may provide a new strategy for precision treatment in AML.

Site-specific microbial communities are recognized as important factors in host health and disease. To better understand how the human microbiota potentially affects and is affected by its host during the aging process, the fundamental issue to address is the distribution of microbiota related to age. Here, we show an integrated view of the spatial distribution of microbes in a specific Mediterranean population (Sardinians) across a wide age range. Our study indicates that age plays a critical role in shaping the human microbiota in a habitat-dependent manner. The dynamic age-related microbiota changes we observed across multiple body sites may provide possibilities for modulating microbe communities to maintain or improve health during aging. Human body microbes interact with the host, forming microbial communities that are in continual flux during the aging process. Previous studies have mostly focused on surveying a single body habitat to determine the age-related variation in the bacterial and fungal communities. A more comprehensive understanding of the variation in the human microbiota and mycobiota across multiple body habitats related to aging is still unclear. To obtain an integrated view of the spatial distribution of microbes in a specific Mediterranean population across a wide age range, we surveyed the bacterial and fungal communities in the skin, oral cavity, and gut in the young, elderly, and centenarians in Sardinia using 16S rRNA gene and internal transcribed spacer 1 (ITS1) sequencing. We found that the distribution and correlation of bacterial and fungal communities in Sardinians were largely determined by body site. In each age group, the bacterial and fungal communities found in the skin were significantly different in structure. In the oral cavity, age had a marginal impact on the structures of the bacterial and fungal communities. Furthermore, the gut bacterial communities in centenarians clustered separately from those of the young and elderly, while the fungal communities in the gut habitat could not be separated by host age. IMPORTANCE Site-specific microbial communities are recognized as important factors in host health and disease. To better understand how the human microbiota potentially affects and is affected by its host during the aging process, the fundamental issue to address is the distribution of microbiota related to age. Here, we show an integrated view of the spatial distribution of microbes in a specific Mediterranean population (Sardinians) across a wide age range. Our study indicates that age plays a critical role in shaping the human microbiota in a habitat-dependent manner. The dynamic age-related microbiota changes we observed across multiple body sites may provide possibilities for modulating microbe communities to maintain or improve health during aging.

Acute myeloid leukemia (AML) is a heterogeneous blood cancer. Effective immunotherapies for AML are hindered by a lack of understanding of the tumor microenvironment (TME). Here, we retrieved published single‐cell RNA sequencing data for 128,688 cells derived from 29 bone marrow aspirates, including 21 AML patients and eight healthy donors. We established a global tumor ecosystem including nine main cell types. Myeloid, T, and NK cells were further re‐clustered and annotated. Developmental trajectory analysis indicated that exhausted CD8 + T cells might develop via tissue residual memory T cells (TRM) in the AML TME. Significantly higher expression levels of exhaustion molecules in AML TRM cells suggested that these cells were influenced by the TME and entered an exhausted state. Meanwhile, the upregulation of checkpoint molecules and downregulation of granzyme were also observed in AML NK cells, suggesting an exhaustion state. In conclusion, our comprehensive profiling of T/NK subpopulations provides deeper insights into the AML immunosuppressive ecosystem, which is critical for immunotherapies.

Multiple myeloma (MM) is a malignancy of terminally differentiated plasma cells and does not have sufficient prognostic indicators. Interferon gamma inducible protein 16 (IFI16) plays a crucial role in B-cell differentiation. Several studies have shown that IFI16 predicted prognosis in many cancers. However, the relationship between MM prognosis and IFI16 expression has not been studied. In our study, we analyzed the prognostic role of IFI16 expression and explored the possible mechanism in MM progression by using 4498 myeloma patients and 52 healthy donors from 13 independent gene expression omnibus (GEO) datasets. The IFI16 expression increased with myeloma progression, ISS stage, 1q21 amplification, and relapse (all P < 0.01). MM patients with higher IFI16 expression had shorter survival in six datasets (all P < 0.05). Furthermore, multivariate analysis indicated that enhanced IFI16 expression was an independent poor prognostic factor for EFS and OS (P = 0.007, 0.009, respectively). And PPI, GO, KEGG, and GSEA also confirmed that IFI16 promoted MM progression by participating in tumor-related pathways. In conclusion, our study confirmed that IFI16 was a poor prognostic biomarker in MM.

Background Human endogenous retroviruses (HERVs), suspected to be transposition-defective, may reshape the transcriptional network of the human genome by regulatory elements distributed in their long terminal repeats (LTRs). HERV-K (HML-2), the most preserved group with the least number of accumulated of mutations, has been associated with aberrant gene expression in tumorigenesis and autoimmune diseases. Because of the high sequence similarity between different HERV-Ks, current methods have limitations in providing genome-wide mapping specific for individual HERV-K (HML-2) members, a major barrier in delineating HERV-K (HML-2) function. Results In an attempt to obtain detailed distribution information of HERV-K (HML-2), we utilized a PCR-based target enrichment sequencing protocol for HERV-K (HML-2) (PTESHK) loci, which not only maps the presence of reference loci, but also identifies non-reference loci, enabling determination of the genome-wide distribution of HERV-K (HML-2) loci. Here we report on the genomic data obtained from three individuals. We identified a total of 978 loci using this method, including 30 new reference loci and 5 non-reference loci. Among the 3 individuals in our study, 14 polymorphic HERV-K (HML-2) loci were identified, and solo-LTR330 and N6p21.32 were identified as polymorphic for the first time. Conclusions Interestingly, PTESHK provides an approach for the identification of the genome-wide distribution of HERV-K (HML-2) and can be used for the identification of polymorphic loci. Since polymorphic HERV-K (HML-2) integrations are suspected to be related to various diseases, PTESHK can supplement other emerging techniques in accessing polymorphic HERV-K (HML-2) elements in cancer and autoimmune diseases.

The prognosis role of CCT3 in MM and the possible pathways it involved were studied in our research. By analyzing ten independent datasets (including 48 healthy donors, 2220 MM, 73 MGUS, and 6 PCL), CCT3 was found to express higher in MM than healthy donors, and the expression level was gradually increased from MGUS, SMM, MM to PCL (all P < 0.01). By analyzing three independent datasets (GSE24080, GSE2658, and GSE4204), we found that CCT3 was a significant indicator of poor prognosis (all P < 0.01). KEGG and GSEA analysis showed that CCT3 expression was associated with JAK-STAT3 pathway, Hippo signaling pathway, and WNT signaling pathway. In addition, different expressed genes analysis revealed MYC, which was one of the downstream genes regulated by JAK-STAT3 pathway, was upregulated in MM. This confirms that JAK-STAT3 signaling pathway may promote the progress of disease which was regulated by CCT3 expression. Our study revealed that CCT3 may play a supporting role at the diagnosis of myeloid, and high expression of CCT3 suggested poor prognosis in MM. CCT3 expression may promote the progression of MM mainly by regulating MYC through JAK-STAT3 signaling pathway.

Elevated extrachromosomal circular DNA (eccDNA) has been reported to accelerate tumor pathogenesis. Although the eccDNA profiles of other tumors have been established, the landscape of the eccDNA of acute myeloid leukemia (AML) has not been revealed. Our study first depicted the eccDNA profile of normal hematopoiesis and AML evolution by exploiting the ATAC-seq and RNA-seq data from nine healthy donors and 12 AML patients, which contained a total of 137 cell samples and 96 RNA-seq samples (including 16 blood cell types of the normal hematopoietic and AML hierarchies). We found the number of eccDNAs generally increased with the evolution of normal hematopoiesis and AML. The ecDNAs and ring chromosomes were found to reappear both in normal hematopoiesis and AML cells. Furthermore, we compared the eccDNAs of AML with normal cells. There were almost 300 AML-specific genes, including the known oncogenes NRAS , MCL1 , EVI1 , GATA2 , WT1 , and PAK1 . And the ecDNA (chr11: 58668376-58826008) occurred in five out of 17 AML evolution-related cells, which was associated with the high expression of the GLYATL1 gene and the high expressed GLYATL1 was a poor prognostic factor. In conclusion, the eccDNA profiles of normal hematopoiesis and AML evolution were depicted and the recurrent eccDNAs we revealed might be utilized in the treatment of AML as biomarkers.