A complete guide to human microbiomes: Body niches, transmission, development, dysbiosis, and restoration

Microbiota insights into pet ownership and human health

The relationship between pet and owner has already been studied in several studies. Reviewing and summarizing studies on human and pet microbiota and their effects due to keeping pets is the purpose of the current study. Microbiota of the gut, oral cavity, and skin are unique to each individual, and this is also true of their pets (cats and dogs). Microbiota homeostasis is essential for the health of pets and their owners. Dysbiosis or imbalances in the microbiota can increase the risk of disorder progressions such as IBD or Clostridium difficile infections, among others. The microbial communities of humans change as a result of various factors, such as keeping pets. Pet owners frequently contact domestic dogs and cats, which affects their microbiota. As a result of keeping pets, the microbiota of different areas of the human body has changed, which has been associated with a decrease in pathogenic bacteria and an increase in beneficial bacteria.

Ecological and evolutionary mechanisms driving within-patient emergence of antimicrobial resistance

The ecological and evolutionary mechanisms of antimicrobial resistance (AMR) emergence within patients and how these vary across bacterial infections are poorly understood. Increasingly widespread use of pathogen genome sequencing in the clinic enables a deeper understanding of these processes. In this Review, we explore the clinical evidence to support four major mechanisms of within-patient AMR emergence in bacteria: spontaneous resistance mutations; in situ horizontal gene transfer of resistance genes; selection of pre-existing resistance; and immigration of resistant lineages. Within-patient AMR emergence occurs across a wide range of host niches and bacterial species, but the importance of each mechanism varies between bacterial species and infection sites within the body. We identify potential drivers of such differences and discuss how ecological and evolutionary analysis could be embedded within clinical trials of antimicrobials, which are powerful but underused tools for understanding why these mechanisms vary between pathogens, infections and individuals. Ultimately, improving understanding of how host niche, bacterial species and antibiotic mode of action combine to govern the ecological and evolutionary mechanism of AMR emergence in patients will enable more predictive and personalized diagnosis and antimicrobial therapies.

The Role of Estrogen and Estrogen Receptors in Head and Neck Tumors

Head and neck squamous cell carcinoma (HNSCC) is the most common histological form of head and neck tumors (HNTs), which originate from the epithelium of the lips and oral cavity, pharynx, larynx, salivary glands, nasal cavity, and sinuses. The main risk factors include consumption of tobacco in all forms and alcohol, as well as infections with high-risk human papillomaviruses or the Epstein-Barr virus. Regardless of the etiological agent, the risk of developing different types of HNTs is from two to more than six times higher in males than in females. The reason for such disparities probably lies in a combination of both biological and psychosocial factors. Therefore, it is hypothesized that exposure to female sex hormones, primarily estrogen, provides women with protection against the formation and metastasis of HNTs. In this review, we synthesized available knowledge on the role of estrogen and estrogen receptors (ERs) in the development and progression of HNTs, with special emphasis on membrane ERs, which are much less studied. We can summarize that in addition to epidemiologic studies unequivocally pointing to the protective effect of estrogen in women, an increased expression of both nuclear ERs, ERα, and ERβ, and membrane ERs, ERα36, GPER1, and NaV1.2, was present in different types of HNSCC, for which anti-estrogens could be used as an effective therapeutic approach.

Non-significant influence between aerobic and anaerobic sample transport materials on gut (fecal) microbiota in healthy and fat-metabolic disorder Thai adults

Background

The appropriate sample handling for human fecal microbiota studies is essential to prevent changes in bacterial composition and quantities that could lead to misinterpretation of the data.

Methods

This study firstly identified the potential effect of aerobic and anaerobic fecal sample collection and transport materials on microbiota and quantitative microbiota in healthy and fat-metabolic disorder Thai adults aged 23-43 years. We employed metagenomics followed by 16S rRNA gene sequencing and 16S rRNA gene qPCR, to analyze taxonomic composition, alpha diversity, beta diversity, bacterial quantification, Pearson's correlation with clinical factors for fat-metabolic disorder, and the microbial community and species potential metabolic functions.

Results

Our study successfully obtained microbiota results in percent and quantitative compositions. Each sample exhibited quality sequences with a >99% Good's coverage index, and a relatively plateau rarefaction curve. Alpha diversity indices showed no statistical difference in percent and quantitative microbiota OTU richness and evenness, between aerobic and anaerobic sample transport materials. Obligate and facultative anaerobic species were analyzed and no statistical difference was observed. Supportively, the beta diversity analysis by non-metric multidimensional scale (NMDS) constructed using various beta diversity coefficients showed resembling microbiota community structures between aerobic and anaerobic sample transport groups (P = 0.86). On the other hand, the beta diversity could distinguish microbiota community structures between healthy and fat-metabolic disorder groups (P = 0.02), along with Pearson's correlated clinical parameters (i.e., age, liver stiffness, GGT, BMI, and TC), the significantly associated bacterial species and their microbial metabolic functions. For example, genera such as Ruminococcus and Bifidobacterium in healthy human gut provide functions in metabolisms of cofactors and vitamins, biosynthesis of secondary metabolites against gut pathogens, energy metabolisms, digestive system, and carbohydrate metabolism. These microbial functional characteristics were also predicted as healthy individual biomarkers by LEfSe scores. In conclusion, this study demonstrated that aerobic sample collection and transport (<48 h) did not statistically affect the microbiota and quantitative microbiota analyses in alpha and beta diversity measurements. The study also showed that the short-term aerobic sample collection and transport still allowed fecal microbiota differentiation between healthy and fat-metabolic disorder subjects, similar to anaerobic sample collection and transport. The core microbiota were analyzed, and the findings were consistent. Moreover, the microbiota-related metabolic potentials and bacterial species biomarkers in healthy and fat-metabolic disorder were suggested with statistical bioinformatics (i.e., Bacteroides plebeius).

Effectiveness assessment of using water environmental microHI to predict the health status of wild fish

Aquatic wildlife health assessment is critically important for aquatic wildlife conservation. However, the health assessment of aquatic wildlife (especially aquatic wild animals) is difficult and often accompanied by invasive survey activities and delayed observability. As there is growing evidence that aquatic environmental microbiota could impact the health status of aquatic animals by influencing their symbiotic microbiota, we propose a non-invasive method to monitor the health status of wild aquatic animals using the environmental microbiota health index (microHI). However, it is unknown whether this method is effective for different ecotype groups of aquatic wild animals. To answer this question, we took a case study in the middle Yangtze River and studied the water environmental microbiota and fish gut microbiota at the fish community level, population level, and ecotype level. The results showed that the gut microHI of the healthy group was higher than that of the unhealthy group at the community and population levels, and the overall gut microHI was positively correlated with the water environmental microHI, whereas the baseline gut microHI was species-specific. Integrating these variations in four ecotype groups (filter-feeding, scraper-feeding, omnivorous, and carnivorous), only the gut microHI of the carnivorous group positively correlated with water environmental microHI. Alcaligenaceae, Enterobacteriaceae, and Achromobacter were the most abundant groups with health-negative-impacting phenotypes, had high positive correlations between gut sample group and environment sample group, and had significantly higher abundance in unhealthy groups than in healthy groups of carnivorous, filter-feeding, and scraper-feeding ecotypes. Therefore, using water environmental microHI to indicate the health status of wild fish is effective at the community level, is effective just for carnivorous fish at the ecotype level. In the middle Yangtze River, Alcaligenaceae, Enterobacteriaceae (family level), and Achromobacter (genus level) were the key water environmental microbial groups that potentially impacted wild fish health status. Of course, more data and research that test the current hypothesis and conclusion are encouraged.

An updated overview on the relationship between human gut microbiome dysbiosis and psychiatric and psychological disorders

There is a lot of evidence establishing that nervous system development is related to the composition and functions of the gut microbiome. In addition, the central nervous system (CNS) controls the imbalance of the intestinal microbiota, constituting a bidirectional communication system. At present, various gut-brain crosstalk routes have been described, including immune, endocrine and neural circuits via the vagal pathway. Several empirical data have associated gut microbiota alterations (dysbiosis) with neuropsychiatric diseases, such as Alzheimer's disease, autism and Parkinson's disease, and with other psychological disorders, like anxiety and depression. Fecal microbiota transplantation (FMT) therapy has shown that the gut microbiota can transfer behavioral features to recipient animals, which provides strong evidence to establish a causal-effect relationship. Interventions, based on prebiotics, probiotics or synbiotics, have demonstrated an important influence of microbiota on neurological disorders by the synthesis of neuroactive compounds that interact with the nervous system and by the regulation of inflammatory and endocrine processes. Further research is needed to demonstrate the influence of gut microbiota dysbiosis on psychiatric and psychological disorders, and how microbiota-based interventions may be used as potential therapeutic tools.

Gut-Brain Axis Deregulation and Its Possible Contribution to Neurodegenerative Disorders

The gut-brain axis is an essential communication pathway between the central nervous system (CNS) and the gastrointestinal tract. The human microbiota is composed of a diverse and abundant microbial community that compasses more than 100 trillion microorganisms that participate in relevant physiological functions such as host nutrient metabolism, structural integrity, maintenance of the gut mucosal barrier, and immunomodulation. Recent evidence in animal models has been instrumental in demonstrating the possible role of the microbiota in neurodevelopment, neuroinflammation, and behavior. Furthermore, clinical studies suggested that adverse changes in the microbiota can be considered a susceptibility factor for neurological disorders (NDs), such as Alzheimer's disease (AD), Parkinson's disease (PD), Huntington's disease (HD), and amyotrophic lateral sclerosis (ALS). In this review, we will discuss evidence describing the role of gut microbes in health and disease as a relevant risk factor in the pathogenesis of neurodegenerative disorders, including AD, PD, HD, and ALS.

Obesity-Associated Non-T2 Mechanisms in Obese Asthmatic Individuals

Obesity and asthma are two common health issues that have shown increased prevalence in recent years and have become a significant socioeconomic burden worldwide. Obesity increases asthma incidence and severity. Obese asthmatic individuals often experience increased exacerbation rates, enhanced airway remodeling, and reduced response to standard corticosteroid therapy. Recent studies indicate that obesity-associated non-T2 factors such as mechanical stress, hyperinsulinemia, systemic inflammation, adipose tissue mediators, metabolic dysregulation, microbiome dysbiosis, and high-fat-diet are responsible for increased asthma symptoms and reduced therapeutic response in obese asthmatic individuals. This manuscript reviews the recent findings highlighting the role of obesity-associated factors that contribute to airway hyper-reactivity, airway inflammation and remodeling, and immune cell dysfunction, consequently contributing to worsening asthma symptoms. Furthermore, the review also discusses the possible future therapies that might play a role in reducing asthma symptoms by diminishing the impact of obesity-associated non-T2 factors.

Critical review of 16S rRNA gene sequencing workflow in microbiome studies: From primer selection to advanced data analysis

The multi-batch reanalysis approach of jointly reevaluating gene/genome sequences from different works has gained particular relevance in the literature in recent years. The large amount of 16S ribosomal ribonucleic acid (rRNA) gene sequence data stored in public repositories and information in taxonomic databases of the same gene far exceeds that related to complete genomes. This review is intended to guide researchers new to studying microbiota, particularly the oral microbiota, using 16S rRNA gene sequencing and those who want to expand and update their knowledge to optimise their decision-making and improve their research results. First, we describe the advantages and disadvantages of using the 16S rRNA gene as a phylogenetic marker and the latest findings on the impact of primer pair selection on diversity and taxonomic assignment outcomes in oral microbiome studies. Strategies for primer selection based on these results are introduced. Second, we identified the key factors to consider in selecting the sequencing technology and platform. The process and particularities of the main steps for processing 16S rRNA gene-derived data are described in detail to enable researchers to choose the most appropriate bioinformatics pipeline and analysis methods based on the available evidence. We then produce an overview of the different types of advanced analyses, both the most widely used in the literature and the most recent approaches. Several indices, metrics and software for studying microbial communities are included, highlighting their advantages and disadvantages. Considering the principles of clinical metagenomics, we conclude that future research should focus on rigorous analytical approaches, such as developing predictive models to identify microbiome-based biomarkers to classify health and disease states. Finally, we address the batch effect concept and the microbiome-specific methods for accounting for or correcting them.

StrainIQ: A Novel n-Gram-Based Method for Taxonomic Profiling of Human Microbiota at the Strain Level

The emergence of next-generation sequencing (NGS) technology has greatly influenced microbiome research and led to the development of novel bioinformatics tools to deeply analyze metagenomics datasets. Identifying strain-level variations in microbial communities is important to understanding the onset and progression of diseases, host-pathogen interrelationships, and drug resistance, in addition to designing new therapeutic regimens. In this study, we developed a novel tool called StrainIQ (strain identification and quantification) based on a new n-gram-based (series of n number of adjacent nucleotides in the DNA sequence) algorithm for predicting and quantifying strain-level taxa from whole-genome metagenomic sequencing data. We thoroughly evaluated our method using simulated and mock metagenomic datasets and compared its performance with existing methods. On average, it showed 85.8% sensitivity and 78.2% specificity on simulated datasets. It also showed higher specificity and sensitivity using n-gram models built from reduced reference genomes and on models with lower coverage sequencing data. It outperforms alternative approaches in genus- and strain-level prediction and strain abundance estimation. Overall, the results show that StrainIQ achieves high accuracy by implementing customized model-building and is an efficient tool for site-specific microbial community profiling.

The Gut-Peritoneum Axis in Peritoneal Dialysis and Peritoneal Fibrosis

Peritoneal fibrosis is an important cause of peritoneal dialysis (PD) discontinuation worldwide and is associated with high morbidity and mortality rate. Although the era of metagenomics has provided new insights into the interactions between the gut microbiota and fibrosis in various organs and tissues, its role in peritoneal fibrosis has rarely been discussed. This review provides a scientific rationale and points out the potential role of gut microbiota in peritoneal fibrosis. In addition, the interaction between the gut, circulatory, and peritoneal microbiota is highlighted, with an emphasis on the relationship to PD outcomes. More research is needed to elucidate the mechanisms underlying the role of gut microbiota in peritoneal fibrosis and potentially unveil new target options for the management of PD technique failure.

HIV, opioid use, and alterations to the gut microbiome: elucidating independent and synergistic effects

Background

The microbiome is essential to immune development, defense against pathogens, and modulation of inflammation. Microbial dysbiosis has been reported in various diseases including human immunodeficiency virus (HIV) and opioid use disorder (OUD). Notably, people living with HIV (PLWH) have been reported to both have higher rates of OUD and use opioids at higher rates than the general public. Thus, studying gut microbial alterations in people living with HIV and with OUD could elucidate mechanisms pertaining to how these conditions both shape and are shaped by the microbiome. However, to date few studies have investigated how HIV and OUD in combination impact the microbiome.

Aim of review

Here, we review previous studies outlining interactions between HIV, opioid use, and microbial dysbiosis and describe attempts to treat this dysbiosis with fecal microbial transplantation, probiotics, and dietary changes.

Key scientific concepts of review

While the limited number of studies prevent overgeneralizations; accumulating data suggest that HIV and opioid use together induce distinct alterations in the gut microbiome. Among the three existing preclinical studies of HIV and opioid use, two studies reported a decrease in Lachnospiraceae and Ruminococcaceae, and one study reported a decrease in Muribaculaceae in the combined HIV and opioid group relative to HIV-alone, opioid-alone, or control groups. These bacteria are known to modulate immune function, decrease colonic inflammation, and maintain gut epithelial barrier integrity in healthy individuals. Accordingly, modulation of the gut microbiome to restore gut homeostasis may be attempted to improve both conditions. While mixed results exist regarding treating dysbiosis with microbial restoration in PLWH or in those with opioid dependency, larger well-defined studies that can improve microbial engraftment in hosts hold much promise and should still be explored.

Getting closer to modeling the gut-brain axis using induced pluripotent stem cells

The gut microbiome (GM), the gut barrier, and the blood-brain barrier (BBB) are key elements of the gut-brain axis (GBA). The advances in organ-on-a-chip and induced pluripotent stem cell (iPSCs) technology might enable more physiological gut-brain-axis-on-a-chip models. The ability to mimic complex physiological functions of the GBA is needed in basic mechanistic research as well as disease research of psychiatric, neurodevelopmental, functional, and neurodegenerative diseases, such as Alzheimer’s disease and Parkinson’s disease. These brain disorders have been associated with GM dysbiosis, which may affect the brain via the GBA. Although animal models have paved the way for the breakthroughs and progression in the understanding of the GBA, the fundamental questions of exactly when, how, and why still remain unanswered. The research of the complex GBA have relied on equally complex animal models, but today’s ethical knowledge and responsibilities demand interdisciplinary development of non-animal models to study such systems. In this review we briefly describe the gut barrier and BBB, provide an overview of current cell models, and discuss the use of iPSCs in these GBA elements. We highlight the perspectives of producing GBA chips using iPSCs and the challenges that remain in the field.