Focus: Microbiome: Human Microbiota and Ophthalmic Disease

The human ocular surface, consisting of the cornea and conjunctiva, is colonized by an expansive, diverse microbial community. Molecular-based methods, such as 16S rRNA sequencing, has allowed for more comprehensive and precise identification of the species composition of the ocular surface microbiota compared to traditional culture-based methods. Evidence suggests that the normal microbiota plays a protective immunological role in preventing the proliferation of pathogenic species and thus, alterations in the homeostatic microbiome may be linked to ophthalmic pathologies. Further investigation of the ocular surface microbiome, as well as the microbiome of other areas of the body such as the oral mucosa and gut, and their role in the pathophysiology of diseases is a significant, emerging field of research, and may someday enable the development of novel probiotic approaches for the treatment and prevention of ophthalmic diseases.     

Contrasting Strategies: Human Eukaryotic Versus Bacterial Microbiome Research

Most discussions of human microbiome research have focused on bacterial investigations and findings. Our target is to understand how human eukaryotic microbiome research is developing, its potential distinctiveness, and how problems can be addressed. We start with an overview of the entire eukaryotic microbiome literature (578 papers), show tendencies in the human‐based microbiome literature, and then compare the eukaryotic field to more developed human bacterial microbiome research. We are particularly concerned with problems of interpretation that are already apparent in human bacterial microbiome research (e.g. disease causality, probiotic interventions, evolutionary claims). We show where each field converges and diverges, and what this might mean for progress in human eukaryotic microbiome research. Our analysis then makes constructive suggestions for the future of the field.     

Microbiome predators in changing soils

Microbiome predators shape the soil microbiome and thereby soil functions. However, this knowledge has been obtained from small-scale observations in fundamental rather than applied settings and has focused on a few species under ambient conditions. Therefore, there are several unaddressed questions on soil microbiome predators: (1) What is the role of microbiome predators in soil functioning? (2) How does global change affect microbiome predators and their functions? (3) How can microbiome predators be applied in agriculture? We show that there is sufficient evidence for the vital role of microbiome predators in soils and stress that global changes impact their functions, something that urgently needs to be addressed to better understand soil functioning as a whole. We are convinced that there is a potential for the application of microbiome predators in agricultural settings, as they may help to sustainably increase plant growth. Therefore, we plea for more applied research on microbiome predators.     

Experimental and analytical tools for studying the human microbiome

The human microbiome substantially affects many aspects of human physiology, including metabolism, drug interactions and numerous diseases. This realization, coupled with ever-improving nucleotide sequencing technology, has precipitated the collection of diverse data sets that profile the microbiome. In the past 2 years, studies have begun to include sufficient numbers of subjects to provide the power to associate these microbiome features with clinical states using advanced algorithms, increasing the use of microbiome studies both individually and collectively. Here we discuss tools and strategies for microbiome studies, from primer selection to bioinformatics analysis.     

Microbiome engineering: Current applications and its future

Microbiomes exist in all ecosystems and are composed of diverse microbial communities. Perturbation to microbiomes brings about undesirable phenotypes in the hosts, resulting in diseases and disorders, and disturbs the balance of the associated ecosystems. Engineering of microbiomes can be used to modify structures of the microbiota and restore ecological balance. Consequently, microbiome engineering has been employed for improving human health and agricultural productivity. The importance and current applications of microbiome engineering, particularly in humans, animals, plants and soil is reviewed. Furthermore, we explore the challenges in engineering microbiome and the future of this field, thus providing perspectives and outlook of microbiome engineering.     

Metaproteomic and Metabolomic Approaches for Characterizing the Gut Microbiome

The gut microbiome has been shown to play a significant role in human healthy and diseased states. The dynamic signaling that occurs between the host and microbiome is critical for the maintenance of host homeostasis. Analyzing the human microbiome with metaproteomics, metabolomics, and integrative multi‐omics analyses can provide significant information on markers for healthy and diseased states, allowing for the eventual creation of microbiome‐targeted treatments for diseases associated with dysbiosis. Metaproteomics enables functional activity information to be gained from the microbiome samples, while metabolomics provides insight into the overall metabolic states affecting/representing the host–microbiome interactions. Combining these functional ‐omic platforms together with microbiome composition profiling allows for a holistic overview on the functional and metabolic state of the microbiome and its influence on human health. Here the benefits of metaproteomics, metabolomics, and the integrative multi‐omic approaches to investigating the gut microbiome in the context of human health and diseases are reviewed.     

微生物组学及其在厌氧消化中的研究进展

我国每年产生大量的有机废弃物,如果处置不当将会对生态、气候以及人类健康造成重大影响。厌氧消化是一种可靠的、绿色的、可持续的有机废弃物处理方式,但由于缺乏准确有效的监测手段,厌氧消化微观过程常常被视为“黑盒”。随着微生物组学的发展,学者们在菌群与运行参数关联性分析、代谢途径分析等方面有了更深入的认识。本文从“三阶段、四菌群”的厌氧消化过程出发,介绍了常用微生物组学的类型,包括:16S rRNA基因组、宏基因组、宏转录组和宏蛋白组;详细阐述了物种组成分析、α多样性分析、OTU相似性分析以及多元统计学分析等6种常用的微生物群落生物信息学分析方法;系统回顾了厌氧消化过程的微生物学研究进展,以期能为分析厌氧消化的微生物群落结构和功能、开发新的厌氧消化工艺和技术提供支持。     

The Human Intestinal Microbiome: A New Frontier of Human Biology

To analyze the vast number and variety of microorganisms inhabitingthe human intestine, emerging metagenomic technologies are extremelypowerful. The intestinal microbes are taxonomically complexand constitute an ecologically dynamic community (microbiota)that has long been believed to possess a strong impact on humanphysiology. Furthermore, they are heavily involved in the maturationand proliferation of human intestinal cells, helping to maintaintheir homeostasis and can be causative of various diseases,such as inflammatory bowel disease and obesity. A simplifiedanimal model system has provided the mechanistic basis for themolecular interactions that occur at the interface between suchmicrobes and host intestinal epithelia. Through metagenomicanalysis, it is now possible to comprehensively explore thegenetic nature of the intestinal microbiome, the mutually interactingsystem comprising the host cells and the residing microbialcommunity. The human microbiome project was recently launchedas an international collaborative research effort to furtherpromote this newly developing field and to pave the way to anew frontier of human biology, which will provide new strategiesfor the maintenance of human health.     

微生物组与动物疫病防控

微生物组研究的发展推动了人类不断探索人体微生物群与疾病之间的相关性。然而,微生物组学在动物疫病防控中的研究尚处于起步阶段。本文对动物疫病防控领域中微生物组研究所发挥的6个作用进行了阐述：揭示疾病与菌群的相关性,鉴定新发病原体,确立有益于维持机体健康生长的菌群,筛选疾病防控的新药物和新制剂,开发新疫苗或改进疫苗的使用效果,提出更简单有效的防控措施。     

Focus: Microbiome: Breathing Better Through Bugs: Asthma and the Microbiome

Asthma is a highly heterogeneous disease characterized by inflammation of the airways, which invokes symptoms such as wheeze, dyspnea, and chest tightness. Asthma is the product of multiple interconnected immunological processes and represents a constellation of related, but distinct, disease phenotypes. The prevalence of asthma has more than doubled since the 1980s, and efforts to understand this increase have inspired consideration of the microbiome as a key player in the pathophysiology and regulation of this disease. While recent years have seen an explosion of new research in this area, researchers are only beginning to untangle to mechanisms by which the microbiome may influence asthma. This review will focus on the relationship between the microbiome and the immune system and how this influences development of asthma. This review will also highlight evidence that may point the way toward new therapies and potential cures for this ancient respiratory foe.     

phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

Background

The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data.

Results

Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research.

Conclusions

The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.     

Focus: Microbiome: Treating Obesity and Metabolic Syndrome with Fecal Microbiota Transplantation

The worldwide prevalence of metabolic syndrome, which includes obesity and its associated diseases, is rising rapidly. The human gut microbiome is recognized as an independent environmental modulator of host metabolic health and disease. Research in animal models has demonstrated that the gut microbiome has the functional capacity to induce or relieve metabolic syndrome. One way to modify the human gut microbiome is by transplanting fecal matter, which contains an abundance of live microorganisms, from a healthy individual to a diseased one in the hopes of alleviating illness. Here we review recent evidence suggesting efficacy of fecal microbiota transplant (FMT) in animal models and humans for the treatment of obesity and its associated metabolic disorders.     

国家自然科学基金资助微生物组研究的现状与效果分析*

国家自然科学基金项目对科学研究具有扶持、引导作用,其资助和成果情况可在一定程度上反映出我国前沿科技领域的研究重点和发展趋势。选取2010—2021年国家自然科学基金资助微生物组基础研究情况为分析对象,对资助年度、资助金额、资助类别、资助单位、项目成果等内容进行统计分析,反映国家自然科学基金资助微生物组基础研究的现状、特点以及资助效果,为微生物组相关领域的研究和管理人员提供参考和支撑。     

Microbiome Structure and Function: A New Framework for Interpreting Data

A distinction between different notions of “structure” and “function” is suggested for interpreting the overwhelming amount of data on microbiome structure and function. Sequence data, biochemical agents, interaction networks, taxonomic communities, and their dynamics can be linked to potential or actual biochemical activities, causal roles, and selected effects, respectively. This conceptual clarification has important methodological consequences for how to interpret existing data and approach open questions in contemporary microbiome research practice. In particular, the field will have to start thinking about notions of function more directly. Also see the video abstract here https://youtu.be/j5pq5uGld1k .     

Conditional Regression Based on a Multivariate Zero-Inflated Logistic-Normal Model for Microbiome Relative Abundance Data

The human microbiome plays critical roles in human health and has been linked to many diseases. While advanced sequencing technologies can characterize the composition of the microbiome in unprecedented detail, it remains challenging to disentangle the complex interplay between human microbiome and disease risk factors due to the complicated nature of microbiome data. Excessive numbers of zero values, high dimensionality, the hierarchical phylogenetic tree and compositional structure are compounded and consequently make existing methods inadequate to appropriately address these issues. We propose a multivariate two-part zero-inflated logistic-normal model to analyze the association of disease risk factors with individual microbial taxa and overall microbial community composition. This approach can naturally handle excessive numbers of zeros and the compositional data structure with the discrete part and the logistic-normal part of the model. For parameter estimation, an estimating equations approach is employed that enables us to address the complex inter-taxa correlation structure induced by the hierarchical phylogenetic tree structure and the compositional data structure. This model is able to incorporate standard regularization approaches to deal with high dimensionality. Simulation shows that our model outperforms existing methods. Our approach is also compared to others using the analysis of real microbiome data.     

The amphibian microbiome: natural range of variation,pathogenic dysbiosis,and role in conservation

Recent research in humans, livestock, and wildlife using high-throughput next-generation sequencing (NGS) has identified that resident microbiota play an essential role in disease resistance, host health, and adaptation to biotic and abiotic stressors. Since amphibians are currently facing population declines and extinctions attributable to anthropogenic pressures and emerging diseases, an understanding of the effects of microbiome dysbiosis and mitigation is a prerequisite for amphibian conservation and disease management. Interest is now growing with regard to understanding the influence of unfavorable environmental conditions on the amphibian microbiome and the effects of dysbiosis on the susceptibility to pathogenic infections. Here, we summarize information on the amphibian microbiome, specifically concerning intrinsic and extrinsic factors that shape the skin and gut microbiome. We explore diverse types of unfavorable environmental perturbations and the ways in which they can impact the microbiota of an individual so that we can better comprehend the consequences of stressors and dysbiosis on pathogen emergence and health. We discuss the role of the microbiome in amphibian conservation and identify gaps of knowledge that need to be filled if we are to achieve a meta-organism conservation approach. NGS studies should be complemented with other high-throughput “-omic” approaches to target microbiome functionality. Understanding the microbiome might be the missing piece in the overall strategy that will help maintain the health of amphibians in a world with highly affected environments and that will prevent/mitigate emerging infectious diseases.     

Rapidly expanding knowledge on the role of the gut microbiome in health and disease

The human gut is colonized by a wide diversity of micro-organisms, which are now known to play a key role in the human host by regulating metabolic functions and immune homeostasis. Many studies have indicated that the genomes of our gut microbiota, known as the gut microbiome or our “other genome” could play an important role in immune-related, complex diseases, and growing evidence supports a causal role for gut microbiota in regulating predisposition to diseases. A comprehensive analysis of the human gut microbiome is thus important to unravel the exact mechanisms by which the gut microbiota are involved in health and disease. Recent advances in next-generation sequencing technology, along with the development of metagenomics and bioinformatics tools, have provided opportunities to characterize the microbial communities. Furthermore, studies using germ-free animals have shed light on how the gut microbiota are involved in autoimmunity. In this review we describe the different approaches used to characterize the human microbiome, review current knowledge about the gut microbiome, and discuss the role of gut microbiota in immune homeostasis and autoimmunity. Finally, we indicate how this knowledge could be used to improve human health by manipulating the gut microbiota. This article is part of a Special Issue entitled: From Genome to Function.     

Using a multiple-delivery-mode training approach to develop local capacity and infrastructure for advanced bioinformatics in Africa

With more microbiome studies being conducted by African-based research groups, there is an increasing demand for knowledge and skills in the design and analysis of microbiome studies and data. However, high-quality bioinformatics courses are often impeded by differences in computational environments, complicated software stacks, numerous dependencies, and versions of bioinformatics tools along with a lack of local computational infrastructure and expertise. To address this, H3ABioNet developed a 16S rRNA Microbiome Intermediate Bioinformatics Training course, extending its remote classroom model. The course was developed alongside experienced microbiome researchers, bioinformaticians, and systems administrators, who identified key topics to address. Development of containerised workflows has previously been undertaken by H3ABioNet, and Singularity containers were used here to enable the deployment of a standard replicable software stack across different hosting sites. The pilot ran successfully in 2019 across 23 sites registered in 11 African countries, with more than 200 participants formally enrolled and 106 volunteer staff for onsite support. The pulling, running, and testing of the containers, software, and analyses on various clusters were performed prior to the start of the course by hosting classrooms. The containers allowed the replication of analyses and results across all participating classrooms running a cluster and remained available posttraining ensuring analyses could be repeated on real data. Participants thus received the opportunity to analyse their own data, while local staff were trained and supported by experienced experts, increasing local capacity for ongoing research support. This provides a model for delivering topic-specific bioinformatics courses across Africa and other remote/low-resourced regions which overcomes barriers such as inadequate infrastructures, geographical distance, and access to expertise and educational materials.     

Dysbiosis in the Gut Bacterial Microbiome of Patients with Uveitis,an Inflammatory Disease of the Eye

Uveitis (UVT), an inflammatory disease of the eye significantly contributes to vision impairment and blindness. Uveitis is associated with systemic infectious and autoimmune diseases, but in most cases, the aetiology remains unidentified. Dysbiosis in the gut microbiome has been implicated in autoimmune diseases, inflammatory diseases, cancers and mental disorders. In a mice model of autoimmune UVT, it was observed that manipulating the gut microbiome reduces the inflammation and disease severity. Further, alterations in the bacterial gut microbiome and their metabolites were reported in UVT patients from a Chinese cohort. Hence, it is worth comparing the bacterial gut microbiome of UVT patients with that of healthy controls (HC) to ascertain whether dysbiosis of the gut microbiome has implications in UVT. Our analyses showed reduced diversity of several anti-inflammatory organisms including Faecalibacterium, Bacteroides, Lachnospira, Ruminococcus and members of Lachnospiraceae and Ruminococcaceae families, and enrichment of Prevotella (proinflammatory) and Streptococcus (pathogenic) OTUs in UVT microbiomes compared to HC. In addition, decrease in probiotic and antibacterial organisms was observed in UVT compared to HC microbiomes. Heatmap and PCoA plots also indicated significant variations in the microbiomes of UVT versus HC. This is the first study demonstrating dysbiosis in the gut bacterial communities of UVT patients in an Indian cohort and suggests a role of the gut microbiome in the pathophysiology of UVT.