The Airway Microbiome at Birth.

Alterations of pulmonary microbiome have been recognized in multiple respiratory disorders. It is critically important to ascertain if an airway microbiome exists at birth and if so, whether it is associated with subsequent lung disease. We found an established diverse and similar airway microbiome at birth in both preterm and term infants, which was more diverse and different from that of older preterm infants with established chronic lung disease (bronchopulmonary dysplasia). Consistent temporal dysbiotic changes in the airway microbiome were seen from birth to the development of bronchopulmonary dysplasia in extremely preterm infants. Genus Lactobacillus was decreased at birth in infants with chorioamnionitis and in preterm infants who subsequently went on to develop lung disease. Our results, taken together with previous literature indicating a placental and amniotic fluid microbiome, suggest fetal acquisition of an airway microbiome. We speculate that the early airway microbiome may prime the developing pulmonary immune system, and dysbiosis in its development may set the stage for subsequent lung disease

The Young Age And Plant-Based Diet Hypothesis For Low Sars-Cov-2 Infection And Covid-19 Pandemic In Sub-Saharan Africa

Since the outbreak of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the coronavirus disease-19 (COVID-19), in December 2019, the infection has spread around the globe. Some of the risk factors include social distancing, mask wearing, hand washing with soap, obesity, diabetes, hypertension, asthma, cardiovascular disease, and dysbiosis. Evidence has shown the incidence of total infection and death rates to be lower in sub-Saharan Africa when compared with North Africa, Europe and North America and many other parts of the world. The higher the metabolic syndrome rate, the higher the risk of SARS-CoV-2 infection. Africa has a lower rate of metabolic syndrome risk than many other continents. This paradox has puzzled several in the biomedical and scientific communities. Published results of research have demonstrated the exciting correlation that the combination of young age of the population coupled with their native plant-based diet has lowered their risk factors. The plant-based diet include whole grains (millet, sorghum), legumes (black-eye peas, dry beans, soybean), vegetables, potato, sweet potato, yams, squash, banana, pumpkin seeds, and moringa leaves, and lower consumption of meat. The plant-based diet results in a different gut microbiota than of most of the rest of the world. This has a significant impact on the survival rate of other populations. The plant-based diet results in lower rates of obesity, diabetes and dysbiosis, which could contribute to lower and less severe infections. However, these hypotheses need to be supported by more clinical and biostatistics data

Impact of Novel Sorghum Bran Diets on DSS-Induced Colitis.

We have demonstrated that polyphenol-rich sorghum bran diets alter fecal microbiota; however, little is known regarding their effect on colon inflammation. Our aim was to characterize the effect of sorghum bran diets on intestinal homeostasis during dextran sodium sulfate (DSS)-induced colitis. Male Sprague-Dawley rats (N = 20/diet) were provided diets containing 6% fiber from cellulose, or Black (3-deoxyanthocyanins), Sumac (condensed tannins) or Hi Tannin Black (both) sorghum bran. Colitis was induced (N = 10/diet) with three separate 48-h exposures to 3% DSS, and feces were collected. On Day 82, animals were euthanized and the colon resected. Only discrete mucosal lesions, with no diarrhea or bloody stools, were observed in DSS rats. Only bran diets upregulated proliferation and Tff3, Tgfβ and short chain fatty acids (SCFA) transporter expression after a DSS challenge. DSS did not significantly affect fecal SCFA concentrations. Bran diets alone upregulated repair mechanisms and SCFA transporter expression, which suggests these polyphenol-rich sorghum brans may suppress some consequences of colitis

Genome sequence of adherent-invasive Escherichia coli and comparative genomic analysis with other E. coli pathotypes

<p>Abstract</p> <p>Background</p> <p>Adherent and invasive <it>Escherichia coli </it>(AIEC) are commonly found in ileal lesions of Crohn's Disease (CD) patients, where they adhere to intestinal epithelial cells and invade into and survive in epithelial cells and macrophages, thereby gaining access to a typically restricted host niche. Colonization leads to strong inflammatory responses in the gut suggesting that AIEC could play a role in CD immunopathology. Despite extensive investigation, the genetic determinants accounting for the AIEC phenotype remain poorly defined. To address this, we present the complete genome sequence of an AIEC, revealing the genetic blueprint for this disease-associated <it>E. coli </it>pathotype.</p> <p>Results</p> <p>We sequenced the complete genome of <it>E. coli </it>NRG857c (O83:H1), a clinical isolate of AIEC from the ileum of a Crohn's Disease patient. Our sequence data confirmed a phylogenetic linkage between AIEC and extraintestinal pathogenic <it>E. coli </it>causing urinary tract infections and neonatal meningitis. The comparison of the NRG857c AIEC genome with other pathogenic and commensal <it>E. coli </it>allowed for the identification of unique genetic features of the AIEC pathotype, including 41 genomic islands, and unique genes that are found only in strains exhibiting the adherent and invasive phenotype.</p> <p>Conclusions</p> <p>Up to now, the virulence-like features associated with AIEC are detectable only phenotypically. AIEC genome sequence data will facilitate the identification of genetic determinants implicated in invasion and intracellular growth, as well as enable functional genomic studies of AIEC gene expression during health and disease.</p

The Intestinal Microbiota May Be a Potential Theranostic Tool for Personalized Medicine

he human intestine is colonized by a huge number of microorganisms from the moment of birth. This set of microorganisms found throughout the human body, is called the microbiota; the microbiome indicates the totality of genes that the microbiota can express, i.e., its genetic heritage. Thus, microbiota participates in and influences the proper functioning of the organism. The microbiota is unique for each person; it differs in the types of microorganisms it contains, the number of each microorganism, and the ratio between them, but mainly it changes over time and under the influence of many factors. Therefore, the correct functioning of the human body depends not only on the expression of its genes but also on the expression of the genes of the microorganisms it coexists with. This fact makes clear the enormous interest of community science in studying the relationship of the human microbiota with human health and the incidence of disease. The microbiota is like a unique personalized “mold” for each person; it differs quantitatively and qualitatively for the microorganisms it contains together with the relationship between them, and it changes over time and under the influence of many factors. We are attempting to modulate the microbial components in the human intestinal microbiota over time to provide positive feedback on the health of the host, from intestinal diseases to cancer. These interventions to modulate the intestinal microbiota as well as to identify the relative microbiome (genetic analysis) can range from dietary (with adjuvant prebiotics or probiotics) to fecal transplantation. This article researches the recent advances in these strategies by exploring their advantages and limitations. Furthermore, we aim to understand the relationship between intestinal dysbiosis and pathologies, through the research of resident microbiota, that would allow the personalization of the therapeutic antibiotic strategy

Role of MicroRNA in Inflammatory Bowel Disease: Clinical Evidence and the Development of Preclinical Animal Models.

The dysregulation of microRNA (miRNA) is implicated in cancer, inflammation, cardiovascular disorders, drug resistance, and aging. While most researchers study miRNA\u27s role as a biomarker, for example, to distinguish between various sub-forms or stages of a given disease of interest, research is also ongoing to utilize these small nucleic acids as therapeutics. An example of a common pleiotropic disease that could benefit from miRNA-based therapeutics is inflammatory bowel disease (IBD), which is characterized by chronic inflammation of the small and large intestines. Due to complex interactions between multiple factors in the etiology of IBD, development of therapies that effectively maintain remission for this disease is a significant challenge. In this review, we discuss the role of dysregulated miRNA expression in the context of clinical ulcerative colitis (UC) and Crohn\u27s disease (CD)-the two main forms of IBD-and the various preclinical mouse models of IBD utilized to validate the therapeutic potential of targeting these miRNA. Additionally, we highlight advances in the development of genetically engineered animal models that recapitulate clinical miRNA expression and provide powerful preclinical models to assess the diagnostic and therapeutic promise of miRNA in IBD

Prenatal exposure to environmental insults and enhanced risk of developing Schizophrenia and Autism Spectrum Disorder : focus on biological pathways and epigenetic mechanisms

When considering neurodevelopmental disorders (NDDs), Schizophrenia (SZ) and Autism Spectrum Disorder (ASD) are considered to be among the most severe in term of prevalence, morbidity and impact on the society. Similar features and overlapping symptoms have been observed at multiple levels, suggesting common pathophysiological bases. Indeed, recent genome-wide association studies (GWAS) and epidemiological data report shared vulnerability genes and environmental triggers across the two disorders. In this review, we will discuss the possible biological mechanisms, including glutamatergic and GABAergic neurotransmissions, inflammatory signals and oxidative stress related systems, which are targeted by adverse environmental exposures and that have been associated with the development of SZ and ASD. We will also discuss the emerging role of the gut microbiome as possible interplay between environment, immune system and brain development. Finally, we will describe the involvement of epigenetic mechanisms in the maintenance of long-lasting effects of adverse environments early in life. This will allow us to better understand the pathophysiology of these NDDs, and also to identify novel targets for future treatment strategies

炎症性腸疾患モデルにおける腸管粘液バリア機能を制御する免疫系受容体の病態生理学的役割に関する研究

富山大学・富医薬博甲第352号・Ai Hertati・2020/12/16構成論文1Hertati A, Hayashi S, Ogawa Y, Yamamoto T and Kadowaki M (2020) Interleukin-4 Receptor α Subunit Deficiency Alleviates Murine Intestinal Inflammation In Vivo Through the Enhancement of Intestinal Mucosal Barrier Function. Front. Pharmacol. 11:573470. doi: 10.3389/fphar.2020.573470.初出は雑誌Frontiers in Pharmacologyで公表済み構成論文2Hertati A, Hayashi S, Ogata H, MMiyata K, Kato R, Yamamoto T, Kadowaki M. Morphological elucidation of short-chain fatty acid receptor GPR41-positive enteric sensory neurons in the colon of mice with dextran sulfate sodium-induced colitis. Heliyon. 6(12), e05647, 2020. doi:10.1016/j.heliyon.2020.e05647.富山大

Genomic insights into Mycobacterium tuberculosis and its interaction with the microbiota

Tuberculosis (TB) is the leading cause of death from a bacterial infection in humans. Despite its impact throughout history on humans across the globe, it remains challenging to diagnose and treat. This work used molecular biology and next generation sequencing to explore these issues. First, in a study to identify potential biomarkers of TB infection, the interaction between Mycobacterium tuberculosis (the causative agent of TB), the mouse immune system, and the murine gut microbiota was examined. The murine gut microbiota was observed to respond specifically to M. tuberculosis infection in several host genotypes, and these changes were most likely mediated by the adaptive immune system. Together, these data confirm that the response of the gut microbiota can be further explored for TB diagnostics. A second study was aimed at understanding the genetic mechanisms of resistance to a novel anti-mycobacterial compound. Resistance was mediated through loss of function of Rv2887, a previously unannotated gene that was found to be a multiple antibiotic resistance repressor (MarR) transcriptional regulator. Analysis of the function of Rv2887 led to the identification of a gene regulation mechanism that could be a potential new drug target. Finally, in a third study the genetic basis of geographic restriction of M. africanum, a mycobacterial species that causes similar disease to human TB but is usually only found in West Africa, was elucidated. Despite conventional dogma, analysis of M. africanum using new bioinformatics tools revealed that it is not a separate species from M. tuberculosis. Furthermore, M. africanum is unimpaired in transmission or virulence compared to M. tuberculosis, thus suggesting that the geographic restriction may be due to host factors. Taken together, this work explores the host-pathogen interactions and genetics of mycobacteria and provides novel insights into how these bacteria cause TB

Supervised learning methods for association detection, biomarker discovery, and pattern recognition in compositional omics data

Rapid advances and reduced cost in high throughput sequencing (HTS) technologies have enabled widespread profiling of microbial metagenomes and microbiomes in humans to better understand associations between microbial communities and disease. Data generated using these technologies are vast, high-dimensional, and nuanced, including limitations in instrument sequencing capacities and measurements that are inherently relative rather than absolute. Unlike absolute measurements, these relative counts — referred to as compositional data — require special methods for analysis and interpretation. Unfortunately, compositional data methodology are esoteric and generally not well adapted to high throughput sequencing data. Because of this, HTS data are often analyzed with traditional statistical methods that do not properly account for the underlying compositional sample space. This practice may result in spurious associations being reported which may limit study-to-study generalizations and reproducibility. In this thesis, building on existing literature in compositional data analysis and feature selection methodology, we develop a novel statistical association test and a powerful machine learning framework using robust pairwise logratios. Additionally, for each method, we developed freely available (GitHub) R packages (SelEnergyPermR \& DiCoVarML) with functions to perform the core analysis of each method. In the first chapter we provide a basic overview of compositional data and its connection to HTS data. In the second chapter, we present the SelEnergyPerm method for detecting sparse associations in high dimensional metagenomic data. In the third chapter, building on the concept of differential compositional variation proposed in SelEnergyPerm, we present the DiCoVarML framework for supervised classification and biomarker discovery. In the final chapter, we apply the SelEnergyPerm method to test for an association between toxicant exposures and the composition of microbial communities in the nasal passage. Using a parsimonious logratio signature detected by SelEnergyPerm, we then perform integrative analysis, where we explore the connection between nasal microbiome dsybiosis and immune mediator expression in nasal lavage fluid.Doctor of Philosoph