Comparative Gut Microbiome in Trachypithecus leucocephalus and Other Primates in Guangxi, China, Based on Metagenome Sequencing.

The Trachypithecus leucocephalus (white-headed langur) is a highly endangered, karst-endemic primate species, inhabiting the karst limestone forest in Guangxi, Southwest China. How white-headed langurs adapted to karst limestone and special dietary remains unclear. It is the first time to study the correlation between the gut microbiome of primates and special dietary, and environment in Guangxi. In the study, 150 fecal samples are collected from nine primates in Guangxi, China. Metagenomic sequencing is used to analyze and compare the gut microbiome composition and diversity between white-headed langurs and other primates. Our results indicate that white-headed langurs has a higher diversity of microbiome than other primates, and the key microbiome are phylum Firmicutes, class Clostridia, family Lachnospiraceae, and genera Clostridiates and Ruminococcus, which are related to the digestion and degradation of cellulose. Ten genera are significantly more abundant in white-headed langurs and François' langur than in other primates, most of which are high-temperature microbiome. Functional analysis reveals that energy synthesis-related pathways and sugar metabolism-related pathways are less abundant in white-headed langurs and François' langur than in other primates. This phenomenon could be an adaptation mechanism of leaf-eating primates to low-energy diet. The gut microbiome of white-headed langurs is related to diet and karst limestone environment. This study could serve as a reference to design conservation breeding, manage conservation units, and determine conservation priorities.

Screening and Identification of Human Endogenous Retrovirus-K mRNAs for Breast Cancer Through Integrative Analysis of Multiple Datasets.

Objective: Human endogenous retroviruses (HERVs) make up 8% of the human genome. HERVs are biologically active elements related to multiple diseases. HERV-K, a subfamily of HERVs, has been associated with certain types of cancer and suggested as an immunologic target in some tumors. The expression levels of HERV-K in breast cancer (BCa) have been studied as biomarkers and immunologic therapeutic targets. However, HERV-K has multiple copies in the human genome, and few studies determined the transcriptional profile of HERV-K copies across the human genome for BCa. Methods: Ninety-one HERV-K indexes with entire proviral sequences were used as the reference database. Nine raw sequencing datasets with 243 BCa and 137 control samples were mapped to this database by Salmon software. The differential proviral expression across several groups was analyzed by DESeq2 software. Results: First, the clustering of each dataset demonstrated that these 91 HERV-K proviruses could well cluster the BCa and control samples when the normal controls were normal cells or healthy donor tissues. Second, several common HERV-K proviruses that are closely related with BCa risk were significantly differentially expressed (p adj < 0.05 and absolute log2FC > 1.5) in the tissues and cell lines. Additionally, almost all the HERV-K proviruses had higher expression in BCa tissue than in healthy donor tissue. Notably, we first found the expression of 17p13.1 provirus that located with TP53 should regulate TP53 expression in ER+ and HER2+ BCa. Conclusion: The expression profiling of these 91 HERV-K proviruses can be used as biomarkers to distinguish individuals with BCa and healthy controls. Some proviruses, especially 17p13.1, were strongly associated with BCa risk. The results suggest that HERV-K expression profiles may be appropriate biomarkers and targets for BCa.

Emerging Severe Acute Respiratory Syndrome Coronavirus 2 Mutation Hotspots Associated With Clinical Outcomes and Transmission.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the cause of the ongoing coronavirus disease 2019 (COVID-19) pandemic. Understanding the influence of mutations in the SARS-CoV-2 gene on clinical outcomes is critical for treatment and prevention. Here, we analyzed all high-coverage complete SARS-CoV-2 sequences from GISAID database from January 1, 2020, to January 1, 2021, to mine the mutation hotspots associated with clinical outcome and developed a model to predict the clinical outcome in different epidemic strains. Exploring the cause of mutation based on RNA-dependent RNA polymerase (RdRp) and RNA-editing enzyme, mutation was more likely to occur in severe and mild cases than in asymptomatic cases, especially A > G, C > T, and G > A mutations. The mutations associated with asymptomatic outcome were mainly in open reading frame 1ab (ORF1ab) and N genes; especially R6997P and V30L mutations occurred together and were correlated with asymptomatic outcome with high prevalence. D614G, Q57H, and S194L mutations were correlated with mild and severe outcome with high prevalence. Interestingly, the single-nucleotide variant (SNV) frequency was higher with high percentage of nt14408 mutation in RdRp in severe cases. The expression of ADAR and APOBEC was associated with clinical outcome. The model has shown that the asymptomatic percentage has increased over time, while there is high symptomatic percentage in Alpha, Beta, and Gamma. These findings suggest that mutation in the SARS-CoV-2 genome may have a direct association with clinical outcomes and pandemic. Our result and model are helpful to predict the prevalence of epidemic strains and to further study the mechanism of mutation causing severe disease.