Medicine in Microecology最新文献

Gut microbiota plays an important role in maintaining a healthy intestine. Escherichia coli (E.coli) is a commensal bacteria colonizes the mucous membranes of the gut, intestine, and urinary tract. However, these strains incorporate genetic elements to become pathotype and affected in hundreds of millions of people worldwide. Seven pathotypes have been categorized such as Entero-Hemorrhagic E.coli (EHEC), Entero-Aggregative E.coli (EAEC), Entero-Pathogenic E.coli (EPEC), Entero-Toxigenic E.coli (ETEC), Diffusely Adherent E.coli (DAEC), Entero-Invasive E.coli (EIEC) and Adherent-Invasive E.coli (AIEC), and each pathotype possess distinct virulence mechanism and virulence factors to disrupt the host intestinal epithelial cells that cause diarrhea and other intestinal inflammation. This review highlights the various fimbrial and afimbrial adherence mechanisms of E.coli pathovars, and how it competes with commensal bacteria in achieving pathogenicity in the host. Such adherence mechanisms are mediated by virulence proteins that have a significant impact on the outcome of intestinal inflammation.

The ongoing global pandemic of COVID-19 disease, which is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mainly infect lung epithelial cells, and spread mainly through respiratory droplets. However, recent studies showed potential intestinal infection of SARS-CoV-2, implicated the possibility that the intestinal infection of SARS-CoV-2 may correlate with the dysbiosis of gut microbiota, as well as the severity of COVID-19 symptoms. Here, we investigated the alteration of the gut microbiota in COVID-19 patients, as well as analyzed the correlation between the altered microbes and the levels of intestinal inflammatory cytokine IL-18, which was reported to be elevated in the serum of in COVID-19 patients. Comparing with healthy controls or seasonal flu patients, the gut microbiota showed significantly reduced diversity, with increased opportunistic pathogens in COVID-19 patients. Also, IL-18 level was higher in the fecal samples of COVID-19 patients than in those of either healthy controls or seasonal flu patients. Moreover, the IL-18 levels were even higher in the fecal supernatants obtained from COVID-19 patients that tested positive for SARS-CoV-2 RNA than those that tested negative in fecal samples. These results indicate that changes in gut microbiota composition might contribute to SARS-CoV-2-induced production of inflammatory cytokines in the intestine and potentially also to the onset of a cytokine storm.

Accumulated evidence has shown that commensal microorganisms play key roles in human physiology and diseases. Dysbiosis of the human-associated microbial communities, often referred to as the human microbiome, has been associated with many diseases. Applying supervised classification analysis to the human microbiome data can help us identify subsets of microorganisms that are highly discriminative and hence build prediction models that can accurately classify unlabeled samples. Here, we systematically compare two state-of-the-art ensemble classifiers: Random Forests (RF), eXtreme Gradient Boosting decision trees (XGBoost) and two traditional methods: The elastic net (ENET) and Support Vector Machine (SVM) in the classification analysis of 29 benchmark human microbiome datasets. We find that XGBoost outperforms all other methods only in a few benchmark datasets. Overall, the XGBoost, RF and ENET display comparable performance in the remaining benchmark datasets. The training time of XGBoost is much longer than others, partially due to the much larger number of hyperparameters in XGBoost. We also find that the most important features selected by the four classifiers partially overlap. Yet, the difference between their classification performance is almost independent of this overlap.

Psoriasis is a chronic inflammatory skin disease associated with epidermal keratinocyte hyperplasia and epidermal immune cell over-activation. Compositions of both local skin and gut microbiome are linked to modulation of inflammation and disease severity in psoriasis. Owing to the situation that different bacteria may elicit differential immune or inflammatory responses from epidermal immune cells and keratinocytes, and to-date no single pathogen was highlighted to be responsible for psoriasis, disruption of homeostasis (dysbiosis) in the original microbial ecosystems may create a disease-promoting environment, and as a whole may be a primary causal factor. Several studies have provided evidence that the dominant IL-23/IL-17 pathogenesis pathway is regulated by metabolites produced by gut and skin microbiota. This review summarizes the approaches commonly used for functional characterization of the microbiome compositions associated with development of clinical phenotypes of psoriasis. The underlying mechanisms by which microbiota modulate immune cells and keratinocytes are also proposed.

Objective

The pandemic 2019 Coronavirus disease (COVID-19) is the greatest concern globally. Here we analyzed the epidemiological features of China, South Korea, Italy and Spain to find out the relationship of major public health events and epidemiological curves.

Study design

In this study we described and analyzed the epidemiological characteristics of COVID-19 in and outside China. We used GAM to generate the epidemiological curves and simulated infection curves with reported incubation period.

Results

The epidemiological curves derived from the GAM suggested that the infection curve can reflect the public health measurements sensitively. Under the massive actions token in China, the infection curve flattened at 23rd of January. While surprisingly, even before Wuhan lockdown and first level response of public emergency in Guangdong and Shanghai, those infection curve came to the reflection point both at 21st of January, which indicated the mask wearing by the public before 21st Jan were the key measure to cut off the transmission. In the countries outside China, infection curves also changed in response to measures, but its rate of decline was much smaller than the curve of China's.

Conclusion

The present analysis comparing the epidemiological curves in China, South Korea, Italy and Spain supports the importance of mask wearing by the public. Analysis of the infection curve helped to clarify the impact of important public health events, evaluate the efficiencies of prevention measures, and showed wearing masks in public resulted in significantly reduced daily infected cases.

The human body harbours around 100 trillion microbial cells within a network of complex ecosytems. There is now a well-established correlation between microbes and health in conditions associated with chronic inflammation, and much research has focused on the microbe-to-human axis of communication. At a molecular level, the particular microbial activities and functions that dictate a “healthy” microbiota remain enigmatic. However, evidence from human and animal studies suggests that the host exercises control over the composition of microbial populations through the tightly regulated production and release of hormones, metabolites, nucleic acids, and immune effectors like cytokines. Many of these molecules are taken up by, or bind directly to, microbial cells, and it has been proposed that extracellular vesicles may help to carry these molecules directly to bacteria for enhanced uptake. Understanding how host control of the microbiota may become dysregulated in disease states will lead to novel ways of treating diseases and symptoms. Here we review the evidence for host regulation of the resident and pathogenic microbiota, with a focus on molecular mechanisms of communication in health and disease, and pinpoint how this knowledge may benefit future therapeutics.

Metagenomics is a rapidly growing field aimed at identifying and characterizing the microbial genomes within diverse environmental samples. The key research area in metagenomics is the identification of non-host sequences within a host genomic background, which may represent potential microorganisms associated with the host. The aim of this study was to develop an efficient, portable and reproducible metagenomics pipeline for identifying and characterizing microbial reads from high throughput RNA sequencing (RNA-seq) data. The nf-rnaSeqMetagen pipeline presented in this study was developed using Nextflow as a workflow management system to orchestrate applications used in the pipeline and to handle input/output data between processes. All applications were containerized using Singularity to facilitate parallelization, portability and reproducibility. The pipeline takes RNA-seq reads as input and filters out reads belonging to the host organism. The remaining exogenous reads are then characterized using the kraken2 database constructed from bacterial, archaeal, and viral genomes. RNA-seq data from skin samples of patients with the systemic sclerosis (SSc) disease were used to test the pipeline and to identify possible pathogens, so as to better understand the onset and progression of the disease. A number of bacterial species belonging to Arthrobacter, Bacillus, Brachybacterium, Dietzia and Pseudarthrobacter were found to be of clinical relevance and highly common in the SSc patients. nf-rnaSeqMetagen was also extended to work with other metagenomics studies using RNA-seq data and adapted to work on different computational platforms. The nf-rnaSeqMetagen pipeline is freely available on GitHub (https://github.com/phelelani/nf-rnaSeqMetagen).

Human gut virome play critical roles in maintaining gut microbial composition and functionality, as well as host physiology and immunology. Yet, there are insufficient amount of studies on this topic mainly due to methodological limitations, including enrichment of viruses (phages and host viruses) as well as short read-length from current sequencing technology. Here we developed a full working protocol for analyzing human gut virome using physical enrichment, reverse transcription and random amplification, and eventually the state-of-art single-molecule real-time sequencing (SMRT) platform of Oxford Nanopore Technology (ONT). We demonstrate that sequencing viral DNA directly, or viral cDNA/DNA after amplification using ONT achieves much longer reads and provides more information regarding virome diversity, many of the virome sequences do not have match in current databases. Moreover, direct DNA sequencing of virome provides first insights into the epigenetic modifications on phages, where signals of methylations can be directly detected. Our study demonstrates that progressing sequencing technology and bioinformatic improvements will bring more knowledge into virome composition, diversity and potentially their important functions.

The mammalian intestine harbors a collection of microbes ranging from viruses, archaea, protozoa, helminths, bacteria to fungi. This trans-kingdom community, the microbiota, has been demonstrated to modulate host immunity in health and disease. While bacterial components in this community have been extensively studied in the last two decades, the impact and composition of the fungal community in the gut, the mycobiome, have been recently unraveled. Multiple inflammatory diseases have been shown to link to change of gut mycobiome composition, predominantly the abundance of Candida species in the feces. While Candida species as a major colonizer in immunocompetent human beings are mostly supposed not harmful, they can cause life-threatening systemic infection under immunocompromised situation. Here we review the recent advances about the impact of Candida gut colonization on host immunity and development of inflammatory diseases in the absence of infections. We also discuss potential gaps in understanding the role of Candida species in inflammatory disease and the future perspective.

The theory of ominous octet proposed by Dr. Defronzo in 2008 has emphasized the underlying complicated pathogenesis mechanism in type 2 diabetes. Recently it was further identified that gut microbiota dysbiosis is also closely related to development of chronic inflammations related diseases including diabetes. Diabetes is characterized by "leaky gut" syndrome where bacterial cell wall components enter the blood circulation of animal host in a higher amount. These may cause metabolic endotoxemia and systemic low-grade inflammation, affecting vital organs related to the ominous octet. On the other hand, the bacterial metabolites also systemically affect glucose homeostasis and energy utilization. The effects of current clinically available oral antidiabetic drugs (OAD) are related to altering the compositions of gut microbiota, among which metformin are the most extensively explored. Gut microbiota therefore play an important role as a functional cross-bridge between host environment and the ominous octet, modulating diabetes. With continuing explorations, in the future gut microbiota may serve as a diagnostic biomarker in personalized medicine. Its modulation may also be used as a novel approach to treat type 2 diabetes.