Microbiome at the Frontier of Personalized Medicine

Revisit gut microbiota and its impact on human health and disease

Trillions of microbes have evolved with and continue to live on human beings. With the rapid advances in tools and technology in recent years, new knowledge and insight in cross-talk between the microbes and their hosts have gained. It is the aim of this work to critically review and summarize recent literature reports on the role of microbiota and mechanisms involved in the progress and development of major human diseases, which include obesity, hypertension, cardiovascular disease, diabetes, cancer, Inflammatory Bowel Disease (IBD), gout, depression and arthritis, as well as infant health and longevity.

Urinary tract infection due to anaerobic bacteria in a two-month-old infant

The significance of anaerobic bacteria as a pathogen in urinary tract infection (UTI) in children is unclear. A two-month-old infant presenting with poor feeding received a diagnosis of polymicrobial anaerobic UTI by next-generation sequencing and was found to have obstructive uropathy. Anaerobic bacteria may be a cause of UTI in children with urinary tract obstruction.

Clinical Indications and Compassionate Use of Phage Therapy: Personal Experience and Literature Review with a Focus on Osteoarticular Infections

The history of phage therapy started with its first clinical application in 1919 and continues its development to this day. Phages continue to lack any market approval in Western medicine as a recognized drug, but are increasingly used as an experimental therapy for the compassionate treatment of patients experiencing antibiotic failure. The few formal experimental phage clinical trials that have been completed to date have produced inconclusive results on the efficacy of phage therapy, which contradicts the many successful treatment outcomes observed in historical accounts and recent individual case reports. It would therefore be wise to identify why such a discordance exists between trials and compassionate use in order to better develop future phage treatment and clinical applications. The multitude of observations reported over the years in the literature constitutes an invaluable experience, and we add to this by presenting a number of cases of patients treated compassionately with phages throughout the past decade with a focus on osteoarticular infections. Additionally, an abundance of scientific literature into phage-related areas is transforming our knowledge base, creating a greater understanding that should be applied for future clinical applications. Due to the increasing number of treatment failures anticipatedfrom the perspective of a possible post-antibiotic era, we believe that the introduction of bacteriophages into the therapeutic arsenal seems a scientifically sound and eminently practicable consideration today as a substitute or adjuvant to antibiotic therapy.

A Phylogeny-Regularized Sparse Regression Model for Predictive Modeling of Microbial Community Data

Fueled by technological advancement, there has been a surge of human microbiome studies surveying the microbial communities associated with the human body and their links with health and disease. As a complement to the human genome, the human microbiome holds great potential for precision medicine. Efficient predictive models based on microbiome data could be potentially used in various clinical applications such as disease diagnosis, patient stratification and drug response prediction. One important characteristic of the microbial community data is the phylogenetic tree that relates all the microbial taxa based on their evolutionary history. The phylogenetic tree is an informative prior for more efficient prediction since the microbial community changes are usually not randomly distributed on the tree but tend to occur in clades at varying phylogenetic depths (clustered signal). Although community-wide changes are possible for some conditions, it is also likely that the community changes are only associated with a small subset of "marker" taxa (sparse signal). Unfortunately, predictive models of microbial community data taking into account both the sparsity and the tree structure remain under-developed. In this paper, we propose a predictive framework to exploit sparse and clustered microbiome signals using a phylogeny-regularized sparse regression model. Our approach is motivated by evolutionary theory, where a natural correlation structure among microbial taxa exists according to the phylogenetic relationship. A novel phylogeny-based smoothness penalty is proposed to smooth the coefficients of the microbial taxa with respect to the phylogenetic tree. Using simulated and real datasets, we show that our method achieves better prediction performance than competing sparse regression methods for sparse and clustered microbiome signals.

Microbiota dysbiosis and barrier dysfunction in inflammatory bowel disease and colorectal cancers: exploring a common ground hypothesis

Inflammatory bowel disease (IBD) is a multifactorial disease which arises as a result of the interaction of genetic, environmental, barrier and microbial factors leading to chronic inflammation in the intestine. Patients with IBD had a higher risk of developing colorectal carcinoma (CRC), of which the subset was classified as colitis-associated cancers. Genetic polymorphism of innate immune receptors had long been considered a major risk factor for IBD, and the mutations were also recently observed in CRC. Altered microbial composition (termed microbiota dybiosis) and dysfunctional gut barrier manifested by epithelial hyperpermeability and high amount of mucosa-associated bacteria were observed in IBD and CRC patients. The findings suggested that aberrant immune responses to penetrating commensal microbes may play key roles in fueling disease progression. Accumulative evidence demonstrated that mucosa-associated bacteria harbored colitogenic and protumoral properties in experimental models, supporting an active role of bacteria as pathobionts (commensal-derived opportunistic pathogens). Nevertheless, the host factors involved in bacterial dysbiosis and conversion mechanisms from lumen-dwelling commensals to mucosal pathobionts remain unclear. Based on the observation of gut leakiness in patients and the evidence of epithelial hyperpermeability prior to the onset of mucosal histopathology in colitic animals, it was postulated that the epithelial barrier dysfunction associated with mucosal enrichment of specific bacterial strains may predispose the shift to disease-associated microbiota. The speculation of leaky gut as an initiating factor for microbiota dysbiosis that eventually led to pathological consequences was proposed as the "common ground hypothesis", which will be highlighted in this review. Overall, the understanding of the core interplay between gut microbiota and epithelial barriers at early subclinical phases will shed light to novel therapeutic strategies to manage chronic inflammatory disorders and colitis-associated cancers.

The Probiotic Effectiveness in Preventing Experimental Colitis Is Correlated With Host Gut Microbiota

Current evidence to support extensive use of probiotics in inflammatory bowel disease is limited and factors that contribute to the inconsistent effectiveness of clinical probiotic therapy are not completely known. Here, we used Bifidobacterium longum JDM 301 as a model probiotic to study potential factors that may influence the effect of probiotics in experimental colitis. We found that the effect of B. longum JDM 301 in tempering experimental colitis varied across individual mice even with the same genetic background. The probiotic efficacy was highly correlated with the host gut microbial community features. Consumption of a diet rich in fat could exacerbate mucosal injury-induced colitis but could not change the host responsiveness to B. longum JDM 301 treatment, suggesting of potential mechanistic differences between regulating colitis pathogenesis, and modulating probiotic efficacies by the gut microbiota. Together, our results suggest that personalized microbiome features may modify the probiotic therapeutic effect and support the idea of personalized probiotic medicine in inflammatory bowel disease.

Turning omics data into therapeutic insights

Omics technologies have made it easier and cheaper to evaluate thousands of biological molecules at once. These advances have led to novel therapies approved for use in the clinic, elucidated the mechanisms behind disease-associated mutations, led to increased accuracy in disease subtyping and personalized medicine, and revealed novel uses and treatment regimes for existing drugs through drug repurposing and pharmacology studies. In this review, we summarize some of these milestones and discuss the potential of integrative analyses that combine multiple data types for further advances.

Metabolome analysis for investigating host-gut microbiota interactions

Dysbiosis of the gut microbiome is associated with host health conditions. Many diseases have shown to have correlations with imbalanced microbiota, including obesity, inflammatory bowel disease, cancer, and even neurodegeneration disorders. Metabolomics studies targeting small molecule metabolites that impact the host metabolome and their biochemical functions have shown promise for studying host-gut microbiota interactions. Metabolome analysis determines the metabolites being discussed for their biological implications in host-gut microbiota interactions. To facilitate understanding the critical aspects of metabolome analysis, this article reviewed (1) the sample types used in host-gut microbiome studies; (2) mass spectrometry (MS)-based analytical methods and (3) useful tools for MS-based data processing/analysis. In addition to the most frequently used sample type, feces, we also discussed others biosamples, such as urine, plasma/serum, saliva, cerebrospinal fluid, exhaled breaths, and tissues, to better understand gut metabolite systemic effects on the whole organism. Gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), three powerful tools that can be utilized to study host-gut microbiota interactions, are included with examples of their applications. After obtaining big data from MS-based instruments, noise removal, peak detection, missing value imputation, and data analysis are all important steps for acquiring valid results in host-gut microbiome research. The information provided in this review will help new researchers aiming to join this field by providing a global view of the analytical aspects involved in gut microbiota-related metabolomics studies.

Dietary Patterns Affect the Gut Microbiome-The Link to Risk of Cardiometabolic Diseases

Clusters of bacterial species within the gut microenvironment, or gut enterotype, have been correlated with cardiometabolic disease risk. The metabolic products and metabolites that bacteria produce, such as short-chain fatty acids, secondary bile acids, and trimethylamine, may also affect the microbial community and disease risk. Diet has a direct impact on the gut microenvironment by providing substrates to and promoting the colonization of resident bacteria. To date, few dietary patterns have been evaluated for their effect on the gut microbiome, but the Mediterranean diet and Vegetarian diets have shown favorable effects for both the gut microbiome and cardiometabolic disease risk. This review examines the gut microbiome as a mediator between these dietary patterns and cardiometabolic disease risk.

Human gut microbiome: hopes, threats and promises

The microbiome has received increasing attention over the last 15 years. Although gut microbes have been explored for several decades, investigations of the role of microorganisms that reside in the human gut has attracted much attention beyond classical infectious diseases. For example, numerous studies have reported changes in the gut microbiota during not only obesity, diabetes, and liver diseases but also cancer and even neurodegenerative diseases. The human gut microbiota is viewed as a potential source of novel therapeutics. Between 2013 and 2017, the number of publications focusing on the gut microbiota was, remarkably, 12 900, which represents four-fifths of the total number of publications over the last 40 years that investigated this topic. This review discusses recent evidence of the impact of the gut microbiota on metabolic disorders and focus on selected key mechanisms. This review also aims to provide a critical analysis of the current knowledge in this field, identify putative key issues or problems and discuss misinterpretations. The abundance of metagenomic data generated on comparing diseased and healthy subjects can lead to the erroneous claim that a bacterium is causally linked with the protection or the onset of a disease. In fact, environmental factors such as dietary habits, drug treatments, intestinal motility and stool frequency and consistency are all factors that influence the composition of the microbiota and should be considered. The cases of the bacteria Prevotella copri and Akkermansia muciniphila will be discussed as key examples.

Extraction of Small Molecules from Fecal Samples and Testingof Their Activity on Microbial Physiology

The human body is colonized by vast communities of microbes, collectively known as microbiota, or microbiome. Although microbes colonize every surface of our bodies that is exposed to the external environment, the biggest collection of microbes colonizing humans and other mammals can be found in the gastrointestinal tract. Given the fact that the human gut is colonized by several hundred microbial species, our group hypothesized that the chemical diversity of this environment should be significant, and that many of the molecules present in that environment would have important signaling roles. Therefore, we devised a protocol to extract these molecules from human feces and test their signaling properties. Potentially bioactive extracts can be tested through addition to culture medium and analyses of bacterial growth and gene expression, among other properties. The protocol described herein provides an easy and rapid method for the extraction and testing of metabolites from fecal samples using Salmonella enterica as a model organism. This protocol can also be adapted to the extraction of small molecules from other matrices, such as cultured mammalian cells, tissues, body fluids, and axenic microbial cultures, and the resulting extracts can be tested against various microbial species.

Food Design To Feed the Human Gut Microbiota

The gut microbiome has an enormous impact on the life of the host, and the diet plays a fundamental role in shaping microbiome composition and function. The way food is processed is a key factor determining the amount and type of material reaching the gut bacteria and influencing their growth and the production of microbiota metabolites. In this perspective, the current possibilities to address food design toward a better feeding of gut microbiota are highlighted, together with a summary of the most interesting microbial metabolites that can be made from dietary precursors.