Rapamycin improves Graves' orbitopathy by suppressing CD4+ cytotoxic T lymphocytes.

CD4+ cytotoxic T lymphocytes (CTLs) were recently implicated in immune-mediated inflammation and fibrosis progression of Graves' orbitopathy (GO). However, little is known about therapeutic targeting of CD4+ CTLs. Herein, we studied the effect of rapamycin, an approved mTOR complex 1 (mTORC1) inhibitor, in a GO mouse model, in vitro, and in patients with refractory GO. In the adenovirus-induced model, rapamycin significantly decreased the incidence of GO. This was accompanied by the reduction of both CD4+ CTLs and the reduction of orbital inflammation, adipogenesis, and fibrosis. CD4+ CTLs from patients with active GO showed upregulation of the mTOR pathway, while rapamycin decreased their proportions and cytotoxic function. Low-dose rapamycin treatment substantially improved diplopia and the clinical activity score in steroid-refractory patients with GO. Single-cell RNA-Seq revealed that eye motility improvement was closely related to suppression of inflammation and chemotaxis in CD4+ CTLs. In conclusion, rapamycin is a promising treatment for CD4+ CTL-mediated inflammation and fibrosis in GO.

Frequent exacerbators of chronic obstructive pulmonary disease have distinguishable sputum microbiome signatures during clinical stability.

Introduction: Frequent exacerbation phenotype of chronic obstructive pulmonary disease (COPD) represents a more concerning disease subgroup requiring better prevention and intervention, of which airway microbiome provides new perspective for further exploration. Methods: To investigate whether frequent exacerbators of COPD have distinguishable sputum microbiome during clinical stability, COPD patients at high disease grades with or without frequent exacerbation were recruited for sputum microbiome analysis. Sputum samples were collected during clinical stability and underwent 16S rRNA sequencing, which was then subjected for amplicon sequence variants (ASVs)-based microbiome analysis. Results: Our results revealed that compared with healthy controls and infrequent exacerbators, frequent COPD exacerbators have distinguishably dysbiotic sputum microbiome, as featured by fewer ASVs features, lower alpha diversity, distinct beta diversity patterns. Further taxonomic compositional analysis illustrated the structural distinctions between frequent COPD exacerbators and infrequent exacerbators at differential taxa levels and highlighted Stenotrephomonas due to its prominent elevation in frequent COPD exacerbators, providing a promising candidate for further exploration of microbiome biomarker. Moreover, we also demonstrated that frequent exacerbation phenotype is distinguishable from infrequent exacerbation phenotype with respect of functional implications. Conclusion: Our study demonstrated the first positive correlation between the frequent exacerbation phenotype of COPD and the sputum microbiome during clinical stability in a single-center Chinese COPD cohort and provide potential diagnostic and therapeutic targets for further investigation.

Cerebrospinal Fluid from Healthy Pregnant Women Does Not Harbor a Detectable Microbial Community.

Cerebrospinal fluid (CSF) circulating in the human central nervous system has long been considered aseptic in healthy individuals, because normally, the blood-brain barrier can protect against microbial invasions. However, this dogma has been called into question by several reports that microbes were identified in human brains, raising the question of whether there is a microbial community in the CSF of healthy individuals without neurological diseases. Here, we collected CSF samples and other samples, including one-to-one matched oral and skin swab samples (positive controls), from 23 pregnant women aged between 23 and 40 years. Normal saline samples (negative controls), sterile swabs, and extraction buffer samples (contamination controls) were also collected. Twelve of the CSF specimens were also used to evaluate the physiological activities of detected microbes. Metagenomic and metatranscriptomic sequencing was performed in these 116 specimens. A total of 620 nonredundant microbes were detected, which were dominated by bacteria (74.6%) and viruses (24.2%), while in CSF samples, metagenomic sequencing found only 26 nonredundant microbes, including one eukaryote, four bacteria, and 21 viruses (mostly bacteriophages). The beta diversity of microbes compared between CSF metagenomic samples and other types of samples (except negative controls) was significantly different from that of the CSF self-comparison. In addition, there was no active or viable microbe in the matched metagenomic and metatranscriptomic sequencing of CSF specimens after subtracting those also found in normal saline, DNA extraction buffer, and skin swab specimens. In conclusion, our results showed no strong evidence of a colonized microbial community present in the CSF of healthy individuals. IMPORTANCE The microbiome is prevalent throughout human bodies, with profound health implications. However, it remains unclear whether it is present and active in human CSF, which has been long considered aseptic due to the blood-brain barrier. Here, we applied unbiased metagenomic and metatranscriptomic sequencing to detect the presence of a microbiome in CSF collected from 23 pregnant women with matched controls. Analysis of 116 specimens found no strong evidence to support the presence of a colonized microbiome in CSF. Our findings will strengthen our understanding of the internal environment of the CSF in healthy people, which has strong implications for human health, especially for neurological infections and disorders, and will help further disease diagnostics, prevention, and therapeutics in clinical settings.

MEpurity: estimating tumor purity using DNA methylation data.

MOTIVATION: Tumor purity is a fundamental property of each cancer sample and affects downstream investigations. Current tumor purity estimation methods either require matched normal sample or report moderately high tumor purity even on normal samples. It is critical to develop a novel computational approach to estimate tumor purity with sufficient precision based on tumor-only sample. RESULTS: In this study, we developed MEpurity, a beta mixture model-based algorithm, to estimate the tumor purity based on tumor-only Illumina Infinium 450k methylation microarray data. We applied MEpurity to both The Cancer Genome Atlas (TCGA) cancer data and cancer cell line data, demonstrating that MEpurity reports low tumor purity on normal samples and comparable results on tumor samples with other state-of-art methods. AVAILABILITY AND IMPLEMENTATION: MEpurity is a C++ program which is available at https://github.com/xjtu-omics/MEpurity. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

PVTree: A Sequential Pattern Mining Method for Alignment Independent Phylogeny Reconstruction.

Phylogenetic tree is essential to understand evolution and it is usually constructed through multiple sequence alignment, which suffers from heavy computational burdens and requires sophisticated parameter tuning. Recently, alignment free methods based on k-mer profiles or common substrings provide alternative ways to construct phylogenetic trees. However, most of these methods ignore the global similarities between sequences or some specific valuable features, e.g., frequent patterns overall datasets. To make further improvement, we propose an alignment free algorithm based on sequential pattern mining, where each sequence is converted into a binary representation of sequential patterns among sequences. The phylogenetic tree is further constructed via clustering distance matrix which is calculated from pattern vectors. To increase accuracy for highly divergent sequences, we consider pattern weight and filtering redundancy sub-patterns. Both simulated and real data demonstrates our method outperform other alignment free methods, especially for large sequence set with low similarity.