Human Microbiota in Esophageal Adenocarcinoma: Pathogenesis, Diagnosis, Prognosis and Therapeutic Implications

Esophageal adenocarcinoma (EAC) is one of the main subtypes of esophageal cancer. The incidence rate of EAC increased progressively while the 5-year relative survival rates were poor in the past two decades. The mechanism of EAC has been studied extensively in relation to genetic factors, but less so with respect to human microbiota. Currently, researches about the relationship between EAC and the human microbiota is a newly emerging field of study. Herein, we present the current state of knowledge linking human microbiota to esophageal adenocarcinoma and its precursor lesion—gastroesophageal reflux disease and Barrett’s esophagus. There are specific human bacterial alternations in the process of esophageal carcinogenesis. And bacterial dysbiosis plays an important role in the process of esophageal carcinogenesis via inflammation, microbial metabolism and genotoxicity. Based on the human microbiota alternation in the EAC cascade, it provides potential microbiome-based clinical application. This review is focused on novel targets in prevention, diagnosis, prognosis, and therapy for esophageal adenocarcinoma.

Bifidobacterium animalis subsp. lactis BB-12 Has Effect Against Obesity by Regulating Gut Microbiota in Two Phases in Human Microbiota-Associated Rats

Bifidobacterium animalis subsp. lactis BB-12 (BB-12) is an extensively studied probiotics species, which has been reported to improve the human gut microbiota. This study aimed to confirm the effects of BB-12 on high-fat diet (HFD)-induced gut microbiota disorders. The probiotic BB-12 was consumed by human microbiota-associated rats and changes in gut microbiota were compared using next generation sequencing of the fecal samples collected from the normal chow group, the HFD group, and the BB-12-supplemented group. The enterotypes switched from Prevotella dominant to Akkermansia dominant as a result of switching diet from normal chow to HFD. BB-12 conferred protection on the gut microbiota composition of the rats by increasing the abundance of Prevotella and decreasing the abundance of Clostridium, Blautia, and Bacteroides in 0–3 weeks. In addition, Prevotella-dominant enterotype was maintained, which provides improve obesity effects. A decrease in body weight and the Firmicutes/Bacteroidetes ratio were also observed at week 3. While in 4–8 weeks, the enrichment of short-chain fatty acids-producing bacteria such as Eubacterium and Parabacteroides and probiotics such as Bifidobacterium was observed. The results revealed that BB-12 against obesity by regulating gut microbiota in two phases. After a short-term intervention, BB-12 supplementation suppressed the transition from the healthy to obesity state by protecting Prevotella-dominant enterotype, whereas after a long-term intervention, BB-12 ameliorates obesity by enriching beneficial bacteria in the gut.

Antimicrobial Resistance of Acetobacter and Komagataeibacter Species Originating from Vinegars

Consumers’ preference towards healthy and novel foods dictates the production of organic unfiltered bottled vinegar that still contains acetic acid bacteria. After ingesting vinegar, the bacteria come into close contact with the human microbiota, creating the possibility of horizontal gene transfer, including genetic determinants for antibiotic resistance. Due to the global spread of antimicrobial resistance (AMR), we analyzed the AMR of Acetobacter and Komagataeibacter species originating mainly from vinegars. Six antibiotics from different structural groups and mechanisms of action were selected for testing. The AMR was assessed with the disk diffusion method using various growth media. Although the number of resistant strains differed among the growth media, 97.4%, 74.4%, 56.4%, and 33.3% of strains were resistant to trimethoprim, erythromycin, ciprofloxacin, and chloramphenicol, respectively, on all three media. Moreover, 17.9% and 53.8% of all strains were resistant to four and three antibiotics of different antimicrobial classes, respectively. We then looked for antimicrobial resistance genes in the genome sequences of the reference strains. The most common genetic determinant potentially involved in AMR encodes an efflux pump. Since these genes pass through the gastrointestinal tract and may be transferred to human microbiota, further experiments are needed to analyze the probability of this scenario in more detail.

Evaluating Knowledge of Human Microbiota among University Students in Jordan, an Online Cross-Sectional Survey

Human microbiota have a significant impact on the health of individuals, and reciprocally, lifestyle choices of individuals have an important effect on the diversity and composition of microbiota. Studies assessing microbiota knowledge among the public are lacking, although it is hypothesized that this knowledge can motivate healthier behavior. Hence, this study aimed to measure microbiota knowledge among university students, and the effect of this knowledge on behavioral beliefs. A descriptive cross-sectional study was conducted among students from various fields of study enrolled at the University of Jordan, using an online questionnaire. The questionnaire consisted of 3 parts: demographics, general knowledge of microbiota, and behavioral beliefs related to microbiota. Four hundred and two responses were collected from verified university students. Participants were divided into two groups depending on whether they took a formal microbiology course (45 h) or not. Results from those two groups were compared using appropriate statistical methods. Results showed that most participants, even those who did not take a formal microbiology course, displayed good knowledge of what microbiota is and how they can be influenced by personal and environmental factors. Participants who took a microbiology course had significantly higher microbiota knowledge scores and were more aware of the effect of antibiotics on microbiota. Participants’ behavioral beliefs regarding their antibiotic use, but not their diet and lifestyle choices, were affected by their knowledge of microbiota. The study indicates that disseminating knowledge regarding microbiota and microbiology in general, can improve behaviors related to antibiotic use.

The Effect of COVID-19 Pandemic on the Infants’ Microbiota and the Probability of Development of Allergic and Autoimmune Diseases

The human microbiota plays a significant role in various mechanisms of the body. The formation of a healthy microbiota, especially in early childhood, has a significant effect on maintaining human health. Since the onset of coronavirus disease 2019 (COVID-19), the disease has caused many changes in human life. According to the available information, many of these factors affect the composition and diversity of the body’s microbiota, so this pandemic may alter and disrupt the microbiota and consequently increase the incidence of other diseases such as allergic and autoimmune disorders, especially in children and infants born in this era. In this review, the probable impact of the COVID-19 pandemic on body’s microbiota and its relationship with the emergence of future diseases is discussed.

Kernel principal components based cascade forest towards disease identification with human microbiota

Background Numerous pieces of clinical evidence have shown that many phenotypic traits of human disease are related to their gut microbiome, i.e., inflammation, obesity, HIV, and diabetes. Through supervised classification, it is feasible to determine the human disease states by revealing the intestinal microbiota compositional information. However, the abundance matrix of microbiome data is so sparse, an interpretable deep model is crucial to further represent and mine the data for expansion, such as the deep forest model. What’s more, overfitting can still exist in the original deep forest model when dealing with such “large p, small n” biology data. Feature reduction is considered to improve the ensemble forest model especially towards the disease identification in the human microbiota. Methods In this work, we propose the kernel principal components based cascade forest method, so-called KPCCF, to classify the disease states of patients by using taxonomic profiles of the microbiome at the family level. In detail, the kernel principal components analysis method is first used to reduce the original dimension of human microbiota datasets. Besides, the processed data is fed into the cascade forest to preliminarily discriminate against the disease state of the samples. Results The proposed KPCCF algorithm can represent the small-scale and high-dimension human microbiota datasets with the sparse feature matrix. Systematic comparison experiments demonstrate that our method consistently outperforms the state-of-the-art methods with the comparative study on 4 datasets. Conclusion Despite sharing some common characteristics, a one-size-fits-all solution does not exist in any space. The traditional depth model has limitations in the biological application of the unbalanced scale between small samples and high dimensions. KPCCF distinguishes from the standard deep forest model for its excellent performance in the microbiota field. Additionally, compared to other dimensionality reduction methods, the kernel principal components analysis method is more suitable for microbiota datasets.

Comparison of fecal and oral collection methods for studies of the human microbiota in two Iranian cohorts

Background To initiate fecal and oral collections in prospective cohort studies for microbial analyses, it is essential to understand how field conditions and geographic differences may impact microbial communities. This study aimed to investigate the impact of fecal and oral sample collection methods and room temperature storage on collection samples for studies of the human microbiota. Results We collected fecal and oral samples from participants in two Iranian cohorts located in rural Yazd (n = 46) and urban Gonbad (n = 38) and investigated room temperature stability over 4 days of fecal (RNAlater and fecal occult blood test [FOBT] cards) and comparability of fecal and oral (OMNIgene ORAL kits and Scope mouthwash) collection methods. We calculated interclass correlation coefficients (ICCs) based on 3 alpha and 4 beta diversity metrics and the relative abundance of 3 phyla. After 4 days at room temperature, fecal stability ICCs and ICCs for Scope mouthwash were generally high for all microbial metrics. Similarly, the fecal comparability ICCs for RNAlater and FOBT cards were high, ranging from 0.63 (95% CI: 0.46, 0.75) for the relative abundance of Firmicutes to 0.93 (95% CI: 0.89, 0.96) for unweighted Unifrac. Comparability ICCs for OMNIgene ORAL and Scope mouthwash were lower than fecal ICCs, ranging from 0.55 (95% CI: 0.36, 0.70) for the Shannon index to 0.79 (95% CI: 0.69, 0.86) for Bray-Curtis. Overall, RNAlater, FOBT cards and Scope mouthwash were stable up to 4 days at room temperature. Samples collected using FOBT cards were generally comparable to RNAlater while the OMNIgene ORAL were less similar to Scope mouthwash. Conclusions As microbiome measures for feces samples collected using RNAlater, FOBT cards and oral samples collected using Scope mouthwash were stable over four days at room temperature, these would be most appropriate for microbial analyses in these populations. However, one collection method should be consistently since each method may induce some differences.

Current Knowledge About the Implication of Bacterial Microbiota in Human Health and Disease

Recent advances in molecular genetics and the invention of new technologies led to a development in our knowledge about human microbiota, specifically bacterial one. The microbiota plays a fundamental role in the immunologic, hormonal and metabolic homeostasis of the host. After the initiation of the Human Microbiome Project, it became clear that the human microbiota consists of the 10-100 trillion symbiotic microbial cells harbored by each person, primarily bacteria in the gut, but also in other spots as the skin, mouth, nose, and vagina. Despite of the differences in studying bacterial species, decreased bacterial diversity and persistence has been connected with several diverse human diseases primarily diabetes, IBD (inflammatory bowel disease) and others; attempts were made even to explain psychiatric pathology. Several species emerged as dominant and were clearly linked to certain disorders or accepted as biomarkers of others. The current review aims to discuss key issues of our current knowledge about bacteria in human, the difficulties and methods of its analysis, its contribution to human health and responsibility for human diseases.

Recovery of strain-resolved genomes from human microbiome through an integration framework of single-cell genomics and metagenomics

Background Obtaining high-quality (HQ) reference genomes from microbial communities is crucial for understanding the phylogeny and function of uncultured microbes in complex microbial ecosystems. Despite improvements in bioinformatic approaches to generate curated metagenome-assembled genomes (MAGs), existing metagenome binners obtain population consensus genomes but they are nowhere comparable to genomes sequenced from isolates in terms of strain level resolution. Here, we present a framework for the integration of single-cell genomics and metagenomics, referred to as single-cell (sc) metagenomics, to reconstruct strain-resolved genomes from microbial communities at once. Results Our sc-metagenomics integration framework, termed SMAGLinker, uses single-cell amplified genomes (SAGs) generated using microfluidic technology as binning guides and integrates them with metagenome-assembled genomes (MAGs) to recover improved draft genomes. We compared sc-metagenomics with the metagenomics-alone approach using conventional metagenome binners. The sc-metagenomics approach showed precise contig binning and higher recovery rates (>97%) of rRNA and plasmids than conventional metagenomics in genome reconstruction from the cell mock community. In human microbiota samples, sc-metagenomics recovered the largest number of genomes with a total of 103 gut microbial genomes (21 HQ, with 65 showing >90% completeness) and 45 skin microbial genomes (10 HQ, with 40 showing >90% completeness), respectively. Conventional metagenomics recovered one Staphylococcus hominis genome, whereas sc-metagenomics recovered two S. hominis genomes from identical skin microbiota sample. Single-cell sequencing revealed that these S. hominis genomes were derived from two distinct strains harboring specifically different plasmids. We found that all conventional S. hominis MAGs had a substantial lack or excess of genome sequences and contamination from other Staphylococcus species (S. epidermidis). Conclusions SMAGLinker enabled us to obtain strain-resolved genomes in the mock community and human microbiota samples by assigning metagenomic sequences correctly and covering both highly conserved genes such as rRNA genes and unique extrachromosomal elements, including plasmids. SMAGLinker will provide HQ genomes that are difficult to obtain using metagenomics alone and will facilitate the understanding of microbial ecosystems by elucidating detailed metabolic pathways and horizontal gene transfer networks. SMAGLinker is available at https://github.com/kojiari/smaglinker.