High-resolution ISR amplicon sequencing reveals personalized oral microbiome

Infection and the microbiome in bronchiectasis

Bronchiectasis is marked by bronchial dilatation, recurrent infections and significant morbidity, underpinned by a complex interplay between microbial dysbiosis and immune dysregulation. The identification of distinct endophenotypes have refined our understanding of its pathogenesis, including its heterogeneous disease mechanisms that influence treatment and prognosis responses. Next-generation sequencing (NGS) has revolutionised the way we view airway microbiology, allowing insights into the "unculturable". Understanding the bronchiectasis microbiome through targeted amplicon sequencing and/or shotgun metagenomics has provided key information on the interplay of the microbiome and host immunity, a central feature of disease progression. The rapid increase in translational and clinical studies in bronchiectasis now provides scope for the application of precision medicine and a better understanding of the efficacy of interventions aimed at restoring microbial balance and/or modulating immune responses. Holistic integration of these insights is driving an evolving paradigm shift in our understanding of bronchiectasis, which includes the critical role of the microbiome and its unique interplay with clinical, inflammatory, immunological and metabolic factors. Here, we review the current state of infection and the microbiome in bronchiectasis and provide views on the future directions in this field.

Comparative analysis of gut microbiota in children with obstructive sleep apnea: assessing the efficacy of 16S rRNA gene sequencing in metabolic function prediction based on weight status

Background

Analyzing bacterial microbiomes consistently using next-generation sequencing (NGS) is challenging due to the diversity of synthetic platforms for 16S rRNA genes and their analytical pipelines. This study compares the efficacy of full-length (V1-V9 hypervariable regions) and partial-length (V3-V4 hypervariable regions) sequencing of synthetic 16S rRNA genes from human gut microbiomes, with a focus on childhood obesity.

Methods

In this observational and comparative study, we explored the differences between these two sequencing methods in taxonomic categorization and weight status prediction among twelve children with obstructive sleep apnea.

Results

The full-length NGS method by Pacbio® identified 118 genera and 248 species in the V1-V9 regions, all with a 0% unclassified rate. In contrast, the partial-length NGS method by Illumina® detected 142 genera (with a 39% unclassified rate) and 6 species (with a 99% unclassified rate) in the V3-V4 regions. These approaches showed marked differences in gut microbiome composition and functional predictions. The full-length method distinguished between obese and non-obese children using the Firmicutes/Bacteroidetes ratio, a known obesity marker (p = 0.046), whereas the partial-length method was less conclusive (p = 0.075). Additionally, out of 73 metabolic pathways identified through full-length sequencing, 35 (48%) were associated with level 1 metabolism, compared to 28 of 61 pathways (46%) identified through the partial-length method. The full-length NGS also highlighted complex associations between body mass index z-score, three bacterial species (Bacteroides ovatus, Bifidobacterium pseudocatenulatum, and Streptococcus parasanguinis ATCC 15912), and 17 metabolic pathways. Both sequencing techniques revealed relationships between gut microbiota composition and OSA-related parameters, with full-length sequencing offering more comprehensive insights into associated metabolic pathways than the V3-V4 technique.

Conclusion

These findings highlight disparities in NGS-based assessments, emphasizing the value of full-length NGS with amplicon sequence variant analysis for clinical gut microbiome research. They underscore the importance of considering methodological differences in future meta-analyses.

Oral-gut microbial transmission promotes diabetic coronary heart disease

BACKGROUND

Diabetes is a predominant driver of coronary artery disease worldwide. This study aims to unravel the distinct characteristics of oral and gut microbiota in diabetic coronary heart disease (DCHD). Simultaneously, we aim to establish a causal link between the diabetes-driven oral-gut microbiota axis and increased susceptibility to diabetic myocardial ischemia-reperfusion injury (MIRI).

METHODS

We comprehensively investigated the microbial landscape in the oral and gut microbiota in DCHD using a discovery cohort (n = 183) and a validation chohort (n = 68). Systematically obtained oral (tongue-coating) and fecal specimens were subjected to metagenomic sequencing and qPCR analysis, respectively, to holistically characterize the microbial consortia. Next, we induced diabetic MIRI by administering streptozotocin to C57BL/6 mice and subsequently investigated the potential mechanisms of the oral-gut microbiota axis through antibiotic pre-treatment followed by gavage with specific bacterial strains (Fusobacterium nucleatum or fecal microbiota from DCHD patients) to C57BL/6 mice.

RESULTS

Specific microbial signatures such as oral Fusobacterium nucleatum and gut Lactobacillus, Eubacterium, and Roseburia faecis, were identified as potential microbial biomarkers in DCHD. We further validated that oral Fusobacterium nucleatum and gut Lactobacillus are increased in DCHD patients, with a positive correlation between the two. Experimental evidence revealed that in hyperglycemic mice, augmented Fusobacterium nucleatum levels in the oral cavity were accompanied by an imbalance in the oral-gut axis, characterized by an increased coexistence of Fusobacterium nucleatum and Lactobacillus, along with elevated cardiac miRNA-21 and a greater extent of myocardial damage indicated by TTC, HE, TUNEL staining, all of which contributed to exacerbated MIRI.

CONCLUSION

Our findings not only uncover dysregulation of the oral-gut microbiota axis in diabetes patients but also highlight the pivotal intermediary role of the increased abundance of oral F. nucleatum and gut Lactobacillus in exacerbating MIRI. Targeting the oral-gut microbiota axis emerges as a potent strategy for preventing and treating DCHD. Oral-gut microbial transmission constitutes an intermediate mechanism by which diabetes influences myocardial injury, offering new insights into preventing acute events in diabetic patients with coronary heart disease.

Defining Porphyromonas gingivalis strains associated with periodontal disease

Porphyromonas gingivalis, a Gram-negative anaerobic bacterium commonly found in human subgingival plaque, is a major etiologic agent for periodontitis and has been associated with multiple systemic pathologies. Many P. gingivalis strains have been identified and different strains possess different virulence factors. Current oral microbiome approaches (16S or shotgun) have been unable to differentiate P. gingivalis strains. This study presents a new approach that aims to improve the accuracy of strain identification, using a detection method based on sequencing of the intergenic spacer region (ISR) which is variable between P. gingivalis strains. Our approach uses two-step PCR to amplify only the P. gingivalis ISR region. Samples are then sequenced with an Illumina sequencer and mapped to specific strains. Our approach was validated by examining subgingival plaque from 153 participants with and without periodontal disease. We identified the avirulent strain ATCC33277/381 as the most abundant strain across all sample types. The W83/W50 strain was significantly enriched in periodontitis, with 13% of participants harboring that strain. Overall, this approach can have significant implications not only for the diagnosis and treatment of periodontal disease but also for other diseases where P. gingivalis or its toxins have been implicated, such as Alzheimer's disease.

Explore variation of salivary bacteria across time and geolocations

Saliva is an informative body fluid that can be found at various crime scenes, and the salivary bacterial community has been revealed it is a potential auxiliary target for forensic identification. However, the variation of salivary bacterial community composition across time and geolocation needs to be explored. The study was designed to be carried out during the winter vacation that was across about 50 days and eight geographic locations. The high throughput sequencing was performed with the V3-V4 region of the16S rRNA gene to explore salivary bacterial community composition. An overall slight fluctuation of the salivary bacteria was observed, which primarily occurred in the relative abundance of the salivary bacterial taxa. The results of principal coordinate analysis and hierarchical clustering showed samples were clustered by the individuals. All individuals could be correctly identified with the random forest model. In summation, although the relative abundance of salivary bacteria varied across the changes of time and geolocation, the individualized characteristic of salivary bacteria remained steady, which is beneficial for the salivary bacterial application in personal identification.

Application of next-generation sequencing to identify different pathogens

Early and precise detection and identification of various pathogens are essential for epidemiological monitoring, disease management, and reducing the prevalence of clinical infectious diseases. Traditional pathogen detection techniques, which include mass spectrometry, biochemical tests, molecular testing, and culture-based methods, are limited in application and are time-consuming. Next generation sequencing (NGS) has emerged as an essential technology for identifying pathogens. NGS is a cutting-edge sequencing method with high throughput that can create massive volumes of sequences with a broad application prospects in the field of pathogen identification and diagnosis. In this review, we introduce NGS technology in detail, summarizes the application of NGS in that identification of different pathogens, including bacteria, fungi, and viruses, and analyze the challenges and outlook for using NGS to identify clinical pathogens. Thus, this work provides a theoretical basis for NGS studies and provides evidence to support the application of NGS in distinguishing various clinical pathogens.

Impact of HIV on the Oral Microbiome of Children Living in Sub-Saharan Africa, Determined by Using an rpoC Gene Fragment Metataxonomic Approach

Children living with HIV have a higher prevalence of oral diseases, including caries, but the mechanisms underlying this higher prevalence are not well understood. Here, we test the hypothesis that HIV infection is associated with a more cariogenic oral microbiome, characterized by an increase in bacteria involved in the pathogenesis of caries. We present data generated from supragingival plaques collected from 484 children representing three exposure groups: (i) children living with HIV (HI), (ii) children who were perinatally exposed but uninfected (HEU), and (iii) unexposed and therefore uninfected children (HUU). We found that the microbiome of HI children is distinct from those of HEU and HUU children and that this distinction is more pronounced in diseased teeth than healthy teeth, suggesting that the impact of HIV is more severe as caries progresses. Moreover, we report both an increase in bacterial diversity and a decrease in community similarity in our older HI cohort compared to our younger HI cohort, which may in part be a prolonged effect of HIV and/or its treatment. Finally, while Streptococcus mutans is often a dominant species in late-stage caries, it tended to be found at lower frequency in our HI cohort than in other groups. Our results highlight the taxonomic diversity of the supragingival plaque microbiome and suggest that broad and increasingly individualistic ecological shifts are responsible for the pathogenesis of caries in children living with HIV, coupled with a diverse and possibly severe impact on known cariogenic taxa that potentially exacerbates caries. IMPORTANCE Since its recognition as a global epidemic in the early 1980s, approximately 84.2 million people have been diagnosed with HIV and 40.1 million people have died from AIDS-related illnesses. The development and increased global availability of antiretroviral treatment (ART) regimens have dramatically reduced the mortality rate of HIV and AIDS, yet approximately 1.5 million new infections were reported in 2021, 51% of which are in sub-Saharan Africa. People living with HIV have a higher prevalence of caries and other chronic oral diseases, the mechanisms of which are not well understood. Here, we used a novel genetic approach to characterize the supragingival plaque microbiome of children living with HIV and compared it to the microbiomes of uninfected and perinatally exposed children to better understand the role of oral bacteria in the etiology of tooth decay in the context of HIV exposure and infection.

Independent Effects of HIV and Antiretroviral Therapy on the Oral Microbiome Identified by Multivariate Analyses

The oral microbiome is an important predictor of health and disease. We recently reported significant yet modest effects of HIV under highly active antiretroviral therapy (ART) on the oral microbiome (bacterial and fungal) in a large cohort of HIV-positive (HIV+) and matched HIV-negative (HIV-) individuals. As it was unclear whether ART added to or masked further effects of HIV on the oral microbiome, the present study aimed to analyze the effects of HIV and ART independently, which also included HIV- subjects on preexposure prophylaxis (PrEP) therapy. Cross-sectional analyses of the effect of HIV devoid of ART (HIV+ ART- versus matched HIV- subjects) showed a significant effect on both the bacteriome and mycobiome (P < 0.024) after controlling for other clinical variables (permutational multivariate analysis of variance [PERMANOVA] of Bray-Curtis dissimilarity). Cross-sectional analyses evaluating the effects of ART (HIV+ ART+ versus HIV+ ART- subjects) revealed a significant effect on the mycobiome (P < 0.007) but not the bacteriome. In parallel longitudinal analyses, ART (before versus after the initiation of ART) had a significant effect on the bacteriome, but not the mycobiome, of HIV+ and HIV- PrEP subjects (P < 0.005 and P < 0.016, respectively). These analyses also revealed significant differences in the oral microbiome and several clinical variables between HIV- PrEP subjects (pre-PrEP) and the HIV-matched HIV- group (P < 0.001). At the species level, a small number of differences in both bacterial and fungal taxa were identified within the effects of HIV and/or ART. We conclude that the effects of HIV and ART on the oral microbiome are similar to those of the clinical variables but collectively are modest overall. IMPORTANCE The oral microbiome can be an important predictor of health and disease. For persons living with HIV (PLWH), HIV and highly active antiretroviral therapy (ART) may have a significant influence on their oral microbiome. We previously reported a significant effect of HIV with ART on both the bacteriome and mycobiome. It was unclear whether ART added to or masked further effects of HIV on the oral microbiome. Hence, it was important to evaluate the effects of HIV and ART independently. For this, multivariate cross-sectional and longitudinal oral microbiome analyses (bacteriome and mycobiome) were conducted within the cohort, including HIV+ ART+ subjects and HIV+ and HIV- (preexposure prophylaxis [PrEP]) subjects before and after the initiation of ART. While we report independent significant effects of HIV and ART on the oral microbiome, we conclude that their influence is similar to that of the clinical variables but collectively modest overall.

Industrial and Ruminant Trans-Fatty Acids-Enriched Diets Differentially Modulate the Microbiome and Fecal Metabolites in C57BL/6 Mice

Industrially originated trans-fatty acids (I-tFAs), such as elaidic acid (EA), and ruminant trans-fatty acids (R-tFAs), such as trans-palmitoleic acid (TPA), may have opposite effects on metabolic health. The objective was to compare the effects of consuming 2–3% I-tFA or R-tFA on the gut microbiome and fecal metabolite profile in mice after 7 and 28 days. Forty C57BL/6 mice were assigned to one of the four prepared formulations: lecithin nanovesicles, lecithin nanovesicles with EA or TPA, or water. Fecal samples and animals’ weights were collected on days 0, 7, and 28. Fecal samples were used to determine gut microbiome profiles by 16S rRNA sequencing and metabolite concentrations by GC/MS. At 28 days, TPA intake decreased the abundance of Staphylococcus sp55 but increased Staphylococcus sp119. EA intake also increased the abundance of Staphylococcus sp119 but decreased Ruminococcaceae UCG-014, Lachnospiraceae, and Clostridium sensu stricto 1 at 28 days. Fecal short-chain fatty acids were increased after TPA while decreased after EA after 7 and 28 days. This study shows that TPA and EA modify the abundance of specific microbial taxa and fecal metabolite profiles in distinct ways.

Determining the most accurate 16S rRNA hypervariable region for taxonomic identification from respiratory samples

16S rRNA gene profiling, which contains nine hypervariable regions (V1-V9), is the gold standard for identifying taxonomic units by high-throughput sequencing. Microbiome studies combine two or more region sequences (usually V3-V4) to increase the resolving power for identifying bacterial taxa. We compare the resolving powers of V1-V2, V3-V4, V5-V7, and V7-V9 to improve microbiome analyses in sputum samples from patients with chronic respiratory diseases. DNA were isolated from 33 human sputum samples, and libraries were created using a QIASeq screening panel intended for Illumina platforms (16S/ITS; Qiagen Hilden, Germany). The analysis included a mock community as a microbial standard control (ZymoBIOMICS). We used the Deblur algorithm to identify bacterial amplicon sequence variants (ASVs) at the genus level. Alpha diversity was significantly higher for V1-V2, V3-V4, and V5-V7 compared with V7-V9, and significant compositional dissimilarities in the V1-V2 and V7-V9 analyses versus the V3-V4 and V5-V7 analyses. A cladogram confirmed these compositional differences, with the latter two being very similar in composition. The combined hypervariable regions showed significant differences when discriminating between the relative abundances of bacterial genera. The area under the curve revealed that V1-V2 had the highest resolving power for accurately identifying respiratory bacterial taxa from sputum samples. Our study confirms that 16S rRNA hypervariable regions provide significant differences for taxonomic identification in sputum. Comparing the taxa of microbial community standard control with the taxa samples, V1-V2 combination exhibits the most sensitivity and specificity. Thus, while third generation full-length 16S rRNA sequencing platforms become more available, the V1-V2 hypervariable regions can be used for taxonomic identification in sputum.

Decoding the microbial universe with metagenomics: a brief insight

A major part of any biological system on earth involves microorganisms, of which the majority are yet to be cultured. The conventional methods of culturing microbes have given fruitful outcomes yet have limitations. The curiosity for better understanding has led to the development of culture-independent molecular methods that help push aside the roadblocks of earlier methods. Metagenomics unifies the scientific community in search of a better understanding of the functioning of the ecosystem and its component organisms. This approach has opened a new paradigm in advanced research. It has brought to light the vast diversity and novelty among microbial communities and their genomes. This review focuses on the development of this field over time, the techniques and analysis of data generated through sequencing platforms, and its prominent interpretation and representation.

Genome-Centric Dynamics Shape the Diversity of Oral Bacterial Populations

Two major viewpoints have been put forward for how microbial populations change, differing in whether adaptation is driven principally by gene-centric or genome-centric processes. Longitudinal sampling at microbially relevant timescales, i.e., days to weeks, is critical for distinguishing these mechanisms. Because of its significance for both microbial ecology and human health and its accessibility and high level of curation, we used the oral microbiota to study bacterial intrapopulation genome dynamics. Metagenomes were generated by shotgun sequencing of total community DNA from the healthy tongues of 17 volunteers at four to seven time points obtained over intervals of days to weeks. We obtained 390 high-quality metagenome-assembled genomes (MAGs) defining population genomes from 55 genera. The vast majority of genes in each MAG were tightly linked over the 2-week sampling window, indicating that the majority of the population's genomes were temporally stable at the MAG level. MAG-defined populations were composed of up to 5 strains, as determined by single-nucleotide-variant frequencies. Although most were stable over time, individual strains carrying over 100 distinct genes that rose from low abundance to dominance in a population over a period of days were detected. These results indicate a genome-wide as opposed to a gene-level process of population change. We infer that genome-wide selection of ecotypes is the dominant mode of adaptation in the oral populations over short timescales. IMPORTANCE The oral microbiome represents a microbial community of critical relevance to human health. Recent studies have documented the diversity and dynamics of different bacteria to reveal a rich, stable ecosystem characterized by strain-level dynamics. However, bacterial populations and their genomes are neither monolithic nor static; their genomes are constantly evolving to lose, gain, or alter their functional potential. To better understand how microbial genomes change in complex communities, we used culture-independent approaches to reconstruct the genomes (MAGs) for bacterial populations that approximated different species, in 17 healthy donors' mouths over a 2-week window. Our results underscored the importance of strain-level dynamics, which agrees with and expands on the conclusions of previous research. Altogether, these observations reveal patterns of genomic dynamics among strains of oral bacteria occurring over a matter of days.

Microbe-Immune-Stress Interactions Impact Behaviour during Postnatal Development

Decades of research have established the role of microbiota-brain communication in behaviour and brain function. Studies have shown that microbiota composition and diversity are influenced by a variety of factors including host genetics, diet, and other environmental exposures, with implications for the immunological and neurobiological development of the host organism. To further understand early-life interactions between environment, genetic factors, the microbiome and the central nervous system, we investigated the impact of postnatal stress in C57Bl/6 wild type and T-cell deficient mice on microbe-brain interactions and behaviour. Mice were exposed to immune challenge with lipopolysaccharide (LPS) at postnatal day (P) 3 and maternal separation at P9 (16 h overnight). Behavioural assessment of growth and development as well as behaviour (righting reflex, ultrasonic vocalizations in response to brief maternal separation, open field, sociability, and grooming) was conducted. Microbiota diversity and composition of fecal samples collected at P24 revealed reduced alpha diversity in T-cell-deficient mice as well as genotype- and stress-related taxa. Notably, integrated analyses of microbiota and behaviour in the context of immunocompromise revealed key behavioural related taxa that may be important to brain development. These findings are important to determining the influence of genetic and environmental factors on gut microbiota and advances our understanding microbiome-brain signaling pathways on neurodevelopment and behaviour.

The oral microbiota and cardiometabolic health: A comprehensive review and emerging insights

There is mounting evidence demonstrating that oral dysbiosis causes periodontal disease and promotes the development of cardiovascular disease. The advancement of omics techniques has driven the optimization of oral microbiota species analysis and has provided a deeper understanding of oral pathogenic bacteria. A bi-directional relationship exists between the oral microbiota and the host, and oral-gut microbiota transfer is known to alter the composition of the gut microbiota and may cause local metabolic disorders. Furthermore, cardiovascular health can also be highly affected by oral microbiota functions and metabolites, including short-chain fatty acids (SCFAs), nitric oxide (NO), hydrogen sulfide (H2S), and some lipid metabolites. Studies have found that trimethylamine oxide (TMAO) may have adverse effects on cardiovascular health, whereas SCFAs, NO, and H2S have cardioprotective effects. SCFAs and H2S exert varying oral and cardiovascular effects, however reports on this specific topic remain controversial. Previous evidences are accustomed to summarizing the functions of oral microbiota in the context of periodontitis. The direct relationship between oral microbiota and cardiovascular diseases is insufficient. By systematically summarizing the methods associated with oral microbiota transplantation (OMT), this review facilitates an investigation into the causal links between oral microbiota and cardiovascular disease. The concomitant development of omics, bioinformatics, bacterial culture techniques, and microbiota transplantation techniques is required to gain a deeper understanding of the relationship between oral microbiota and cardiovascular disease occurrence.

Optimization and Evaluation of the 30S-S11 rRNA Gene for Taxonomic Profiling of Oral Streptococci

Dental caries is a multifactorial disease driven by interactions between the highly complex microbial biofilm community and host factors like diet, oral hygiene habits, and age. The oral streptococci are one of the most dominant members of the plaque biofilm and are implicated in disease but also in maintaining oral health. Current methods used for studying the supragingival plaque community commonly sequence portions of the16S rRNA gene, which often cannot taxonomically resolve members of the streptococcal community past the genus level due to their sequence similarity. The goal of this study was to design and evaluate a more reliable and cost-effective method to identify oral streptococci at the species level by applying a new locus, the 30S-S11 rRNA gene, for high-throughput amplicon sequencing. The study results demonstrate that the newly developed single-copy 30S-S11 gene locus resolved multiple amplicon sequence variants (ASVs) within numerous species, providing much improved taxonomic resolution over 16S rRNA V4. Moreover, the results reveal that different ASVs within a species were found to change in abundance at different stages of caries progression. These findings suggest that strains of a single species may perform distinct roles along a biochemical spectrum associated with health and disease. The improved identification of oral streptococcal species will provide a better understanding of the different ecological roles of oral streptococci and inform the design of novel oral probiotic formulations for prevention and treatment of dental caries. IMPORTANCE The microbiota associated with the initiation and progression of dental caries has yet to be fully characterized. Although much insight has been gained from 16S rRNA hypervariable region DNA sequencing, this approach has several limitations, including poor taxonomic resolution at the species level. This is particularly relevant for oral streptococci, which are abundant members of oral biofilm communities and major players in health and caries disease. Here, we develop a new method for taxonomic profiling of oral streptococci based on the 30S-S11 rRNA gene, which provides much improved resolution over 16S rRNA V4 (resolving 10 as opposed to 2 species). Importantly, 30S-S11 can resolve multiple amplicon sequence variants (ASVs) within species, providing an unprecedented insight into the ecological progression of caries. For example, our findings reveal multiple incidences of different ASVs within a species with contrasting associations with health or disease, a finding that has high relevance toward the informed design of prebiotic and probiotic therapy.

Oral Microbiome Transmission and Infant Feeding Habits

Transmission of oral microbiota from mother to infant is a highly relevant and, so far, understudied topic due to lack of mainstream high-throughput methods for the assessment of bacterial diversity at a strain level. In their recent article in mBio, S. Kageyama, M. Furuta, T. Takeshita, J. Ma, et al. (mBio 13:e03452-21, 2021, https://doi.org/10.1128/mbio.03452-21) evaluated oral microbial transmission from mothers to their infants by using full-length analysis of the 16S rRNA gene and demonstrated the applicability of this method for assessment of transmission of oral bacteria at the single-nucleotide-difference level. By analyzing different metadata of the mother-infant pairs, they discovered that the presence of maternal oral bacteria was higher in formula-fed infants compared to infants who were breastfed or received mixed feeding. This interesting finding suggests that breastfeeding may prevent early maturation of infant's oral microbiome. The physiological role of this phenomenon still needs to be elucidated.

Role of the microbiome in oral cancer occurrence, progression and therapy

The oral cavity, like other digestive or mucosal sites, contains a site-specific microbiome that plays a significant role in maintaining health and homeostasis. Strictly speaking, the gastrointestinal tract starts from the oral cavity, with special attention paid to the specific flora of the oral cavity. In healthy people, the microbiome of the oral microenvironment is governed by beneficial bacteria, that benefit the host by symbiosis. When a microecological imbalance occurs, changes in immune and metabolic signals affect the characteristics of cancer, as well as chronic inflammation, disruption of the epithelial barrier, changes in cell proliferation and cell apoptosis, genomic instability, angiogenesis, and epithelial barrier destruction and metabolic regulation. These pathophysiological changes could result in oral cancer. Rising evidence suggests that oral dysbacteriosis and particular microbes may play a positive role in the evolution, development, progression, and metastasis of oral cancer, for instance, oral squamous cell carcinoma (OSCC) through direct or indirect action.

Standardized studies of the oral microbiome: From technology-driven to hypothesis-driven

The microbiome is in a symbiotic relationship with the host. Among the microbial consortia in the human body, that in the oral cavity is complex. Instead of repeatedly confirming biomarkers of oral and systemic diseases, recent studies have focused on a unified clinical diagnostic standard in microbiology that reduces the heterogeneity caused by individual discrepancies. Research has also been conducted on other topics of greater clinical importance, including bacterial pathogenesis, and the effects of drugs and treatments. In this review, we divide existing research into technology-driven and hypothesis-driven, according to whether there is a clear research hypothesis. This classification allows the demonstration of shifts in the direction of oral microbiology research. Based on the shifts, we suggested that establishing clear hypotheses may be the solution to major research challenges.

Comparative Evaluation of the Salivary and Buccal Mucosal Microbiota by 16S rRNA Sequencing for Forensic Investigations

The human microbiome has emerged as a new potential biomarker for forensic investigations with the development of high-throughput sequencing and bioinformatic analysis during the last decade. The oral cavity has many different microbial habitats, with each habit colonized by specific and individualized microbiota. As saliva and buccal mucosa are common biological evidence in forensic science, understanding the differences of microbial communities between the two is important for forensic original identification. Moreover, the oral microbiota is individualized, whereas there are few studies on the application of forensic personal identification that need to be supplemented. In this study, Streptococcus was the most abundant genus, with an average relative abundance of 49.61% in the buccal mucosa, while in the saliva, Streptococcus, Veillonella, and Neisseria had similar proportions (20%, 15%, 16%) and were the dominant genera. The α and β diversity displayed a significant distinctness between the saliva and buccal mucosal groups. The community assembly mechanism stated that the deterministic process played a more significant effect in shaping the salivary bacterial community assembly than buccal mucosa, which explained the microbial differences. Of the test samples, 93.3% can be correctly classified with the random forest model based on the microbial differences. Targeting the low-abundance bacteria at the species level, 52% of experimental participants could be discriminated by using the observed unique bacterial species. In conclusion, the salivary bacterial community composition differed from that of the buccal mucosa and showed high richness and diversity. With the random forest model, the microbiota of saliva and buccal mucosa can be classified, which can be used in identifying the source of oral biological trace. Furthermore, each individual has a unique bacterial community pattern, and the presence or absence of unique bacteria and differences in the composition of the core oral microbiota are the key points for forensic personal discrimination that supplement the study of oral microbial application to forensic personal discrimination. Whether for original identification or personal discrimination, the oral microbiome has great potential for application.

In vitro model systems for exploring oral biofilms: From single-species populations to complex multi-species communities

Numerous in vitro biofilm model systems are available to study oral biofilms. Over the past several decades, increased understanding of oral biology and advances in technology have facilitated more accurate simulation of intraoral conditions and have allowed for the increased generalizability of in vitro oral biofilm studies. The integration of contemporary systems with confocal microscopy and 16S rRNA community profiling has enhanced the capabilities of in vitro biofilm model systems to quantify biofilm architecture and analyse microbial community composition. In this review, we describe several model systems relevant to modern in vitro oral biofilm studies: the constant depth film fermenter, Sorbarod perfusion system, drip-flow reactor, modified Robbins device, flowcells and microfluidic systems. We highlight how combining these systems with confocal microscopy and community composition analysis tools aids exploration of oral biofilm development under different conditions and in response to antimicrobial/anti-biofilm agents. The review closes with a discussion of future directions for the field of in vitro oral biofilm imaging and analysis.

Single-gene long-read sequencing illuminates Escherichia coli strain dynamics in the human intestinal microbiome

Gut microbiome is of major interest due to its close relationship to health and disease. Bacteria usually vary in gene content, leading to functional variations within species, so resolution higher than species-level methods is needed for ecological and clinical relevance. We design a protocol to identify strains in selected species with high discrimination and in high numbers by amplicon sequencing of the flagellin gene. We apply the protocol to fecal samples from a human diet trial, targeting Escherichia coli. Across the 119 samples from 16 individuals, there are 1,532 amplicon sequence variants (ASVs), but only 32 ASVs are dominant in one or more fecal samples, despite frequent dominant strain turnover. Major strains in an intestine are found to be commonly accompanied by a large number of satellite cells, and many are identified as potential extraintestinal pathogens. The protocol could be used to track epidemics or investigate the intra- or inter-host diversity of pathogens.

Taxonomic and Functional Dysregulation in Salivary Microbiomes During Oral Carcinogenesis

Exploring microbial community compositions in humans with healthy versus diseased states is crucial to understand the microbe-host interplay associated with the disease progression. Although the relationship between oral cancer and microbiome was previously established, it remained controversial, and yet the ecological characteristics and their responses to oral carcinogenesis have not been well studied. Here, using the bacterial 16S rRNA gene amplicon sequencing along with the in silico function analysis by PICRUSt2 (Phylogenetic Investigation of Communities by Reconstruction of Unobserved States 2), we systematically characterized the compositions and the ecological drivers of saliva microbiome in the cohorts of orally healthy, non-recurrent oral verrucous hyperplasia (a pre-cancer lesion), and oral verrucous hyperplasia–associated oral cancer at taxonomic and function levels, and compared them with the re-analysis of publicly available datasets. Diversity analyses showed that microbiome dysbiosis in saliva was significantly linked to oral health status. As oral health deteriorated, the number of core species declined, and metabolic pathways predicted by PICRUSt2 were dysregulated. Partitioned beta-diversity revealed an extremely high species turnover but low function turnover. Functional beta-diversity in saliva microbiome shifted from turnover to nestedness during oral carcinogenesis, which was not observed at taxonomic levels. Correspondingly, the quantitative analysis of stochasticity ratios showed that drivers of microbial composition and functional gene content of saliva microbiomes were primarily governed by the stochastic processes, yet the driver of functional gene content shifted toward deterministic processes as oral cancer developed. Re-analysis of publicly accessible datasets supported not only the distinctive family taxa of Veillonellaceae and Actinomycetaceae present in normal cohorts but also that Flavobacteriaceae and Peptostreptococcaceae as well as the dysregulated metabolic pathways of nucleotides, amino acids, fatty acids, and cell structure were related to oral cancer. Using predicted functional profiles to elucidate the correlations to the oral health status shows superior performance than using taxonomic data among different studies. These findings advance our understanding of the oral ecosystem in relation to oral carcinogenesis and provide a new direction to the development of microbiome-based tools to study the interplay of the oral microbiome, metabolites, and host health.

Strain-Level Profiling of Oral Microbiota with Targeted Sequencing

Targeted sequencing of one or more regions of the bacterial 16S rRNA gene fragment has emerged as a gold standard for investigating taxonomic diversity in complex microbial communities, such as those found in the oral cavity. While this approach is useful for identifying bacteria up to genus level, its ability to distinguish between many closely related oral species, or explore strain-level variations within each species, is very limited. Here we present an approach based on targeted sequencing the 16S-23S Intergenic Spacer Region (ISR) in the bacterial ribosomal operon for taxonomic characterization of microbial communities at a subspecies or strain level. This approach retains the advantages of 16S-based methods, such as easy library preparation, high throughput, short amplicon sizes, and low cost of sequencing, while providing subspecies-level resolution as a result of naturally higher genetic diversity present in the ISR compared to the 16S hypervariable regions. These advantages make it an excellent tool for high-resolution oral microbiota characterization.

Comparison of targeted metagenomics and IS-Pro methods for analysing the lung microbiome

Background

Targeted metagenomics and IS-Pro method are two of the many methods that have been used to study the microbiome. The two methods target different regions of the 16 S rRNA gene. The aim of this study was to compare targeted metagenomics and IS-Pro methods for the ability to discern the microbial composition of the lung microbiome of COPD patients.

Methods

Spontaneously expectorated sputum specimens were collected from COPD patients. Bacterial DNA was extracted and used for targeted metagenomics and IS-Pro method. The analysis was performed using QIIME2 (targeted metagenomics) and IS-Pro software (IS-Pro method). Additionally, a laboratory cost per isolate and time analysis was performed for each method.

Results

Statistically significant differences were observed in alpha diversity when targeted metagenomics and IS-Pro methods’ data were compared using the Shannon diversity measure (p-value = 0.0006) but not with the Simpson diversity measure (p-value = 0.84). Distinct clusters with no overlap between the two technologies were observed for beta diversity. Targeted metagenomics had a lower relative abundance of phyla, such as the Proteobacteria, and higher relative abundance of phyla, such as Firmicutes when compared to the IS-Pro method. Haemophilus, Prevotella and Streptococcus were most prevalent genera across both methods. Targeted metagenomics classified 23 % (144/631) of OTUs to a species level, whereas IS-Pro method classified 86 % (55/64) of OTUs to a species level. However, unclassified OTUs accounted for a higher relative abundance when using the IS-Pro method (35 %) compared to targeted metagenomics (5 %). The two methods performed comparably in terms of cost and time; however, the IS-Pro method was more user-friendly.

Conclusions

It is essential to understand the value of different methods for characterisation of the microbiome. Targeted metagenomics and IS-Pro methods showed differences in ability in identifying and characterising OTUs, diversity and microbial composition of the lung microbiome. The IS-Pro method might miss relevant species and could inflate the abundance of Proteobacteria. However, the IS-Pro kit identified most of the important lung pathogens, such as Burkholderia and Pseudomonas and may work in a more diagnostics-orientated setting. Both methods were comparable in terms of cost and time; however, the IS-Pro method was easier to use.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12866-021-02288-x.

The Relationship Between the Gut Microbiome and Neurodegenerative Diseases

Many recent studies have shown that the gut microbiome plays important roles in human physiology and pathology. Also, microbiome-based therapies have been used to improve health status and treat diseases. In addition, aging and neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, have become topics of intense interest in biomedical research. Several researchers have explored the links between these topics to study the potential pathogenic or therapeutic effects of intestinal microbiota in disease. But the exact relationship between neurodegenerative diseases and gut microbiota remains unclear. As technology advances, new techniques for studying the microbiome will be developed and refined, and the relationship between diseases and gut microbiota will be revealed. This article summarizes the known interactions between the gut microbiome and neurodegenerative diseases, highlighting assay techniques for the gut microbiome, and we also discuss the potential therapeutic role of microbiome-based therapies in diseases.

Defining the resilience of the human salivary microbiota by a 520-day longitudinal study in a confined environment: the Mars500 mission

BACKGROUND

The human microbiota plays several roles in health and disease but is often difficult to determine which part is in intimate relationships with the host vs. the occasional presence. During the Mars500 mission, six crewmembers lived completely isolated from the outer world for 520 days following standardized diet regimes. The mission constitutes the first spaceflight simulation to Mars and was a unique experiment to determine, in a longitudinal study design, the composition and importance of the resident vs. a more variable microbiota-the fraction of the human microbiota that changes in time and according to environmental conditions-in humans.

METHODS

Here, we report the characterization of the salivary microbiota from 88 samples taken during and after Mars500 mission for a total of 720 days. Amplicon sequencing of the V3-V4 regions of 16S rRNA gene was performed, and results were analyzed monitoring the diversity of the microbiota while evaluating the effect of the three main variables present in the experimental system: time, diet, and individuality of each subject.

RESULTS

Results showed statistically significant effects for either time, diet, and individuality of each subject. The main contribution came from the individuality of each subject, emphasizing salivary microbiota-personalized features, and an individual-based resilience of the microbiota.

CONCLUSIONS

The uniqueness of Mars500 mission, allowed to dampen the effect of environmental variables on salivary microbiota, highlighting its pronounced personalization even after sharing the same physical space for more than a year. Video abstract.

Acquisition of oral microbiota is driven by environment, not host genetics

BACKGROUND

The oral microbiota is acquired very early, but the factors shaping its acquisition are not well understood. Previous studies comparing monozygotic (MZ) and dizygotic (DZ) twins have suggested that host genetics plays a role. However, all twins share an equal portion of their parent's genome, so this model is not informative for studying parent-to-child transmission. We used a novel study design that allowed us to directly examine the genetics of transmission by comparing the oral microbiota of biological versus adoptive mother-child dyads.

RESULTS

No difference was observed in how closely oral bacterial community profiles matched for adoptive versus biological mother-child pairs, indicating little if any effect of host genetics on the fidelity of transmission. Both adopted and biologic children more closely resembled their own mother as compared to unrelated women, supporting the role of contact and environment. Mother-child strain similarity increased with the age of the child, ruling out early effects of host genetic influence that are lost over time. No effect on the fidelity of mother-child strain sharing from vaginal birth or breast feeding was seen. Analysis of extended families showed that fathers and mothers were equally similar to their children, and that cohabitating couples showed even greater strain similarity than mother-child pairs. These findings support the role of contact and shared environment, and age, but not genetics, as determinants of microbial transmission, and were consistent at both species and strain level resolutions, and across multiple oral habitats. In addition, analysis of individual species all showed similar results.

CONCLUSIONS

The host is clearly active in shaping the composition of the oral microbiome, since only a few of the many bacterial species in the larger environment are capable of colonizing the human oral cavity. Our findings suggest that these host mechanisms are universally shared among humans, since no effect of genetic relatedness on fidelity of microbial transmission could be detected. Instead our findings point towards contact and shared environment being the driving factors of microbial transmission, with a unique combination of these factors ultimately shaping the highly personalized human oral microbiome. Video abstract.

Microbiota restoration reduces antibiotic-resistant bacteria gut colonization in patients with recurrent Clostridioides difficile infection from the open-label PUNCH CD study

BACKGROUND

Once antibiotic-resistant bacteria become established within the gut microbiota, they can cause infections in the host and be transmitted to other people and the environment. Currently, there are no effective modalities for decreasing or preventing colonization by antibiotic-resistant bacteria. Intestinal microbiota restoration can prevent Clostridioides difficile infection (CDI) recurrences. Another potential application of microbiota restoration is suppression of non-C. difficile multidrug-resistant bacteria and overall decrease in the abundance of antibiotic resistance genes (the resistome) within the gut microbiota. This study characterizes the effects of RBX2660, a microbiota-based investigational therapeutic, on the composition and abundance of the gut microbiota and resistome, as well as multidrug-resistant organism carriage, after delivery to patients suffering from recurrent CDI.

METHODS

An open-label, multi-center clinical trial in 11 centers in the USA for the safety and efficacy of RBX2660 on recurrent CDI was conducted. Fecal specimens from 29 of these subjects with recurrent CDI who received either one (N = 16) or two doses of RBX2660 (N = 13) were analyzed secondarily. Stool samples were collected prior to and at intervals up to 6 months post-therapy and analyzed in three ways: (1) 16S rRNA gene sequencing for microbiota taxonomic composition, (2) whole metagenome shotgun sequencing for functional pathways and antibiotic resistome content, and (3) selective and differential bacterial culturing followed by isolate genome sequencing to longitudinally track multidrug-resistant organisms.

RESULTS

Successful prevention of CDI recurrence with RBX2660 correlated with taxonomic convergence of patient microbiota to the donor microbiota as measured by weighted UniFrac distance. RBX2660 dramatically reduced the abundance of antibiotic-resistant Enterobacteriaceae in the 2 months after administration. Fecal antibiotic resistance gene carriage decreased in direct relationship to the degree to which donor microbiota engrafted.

CONCLUSIONS

Microbiota-based therapeutics reduce resistance gene abundance and resistant organisms in the recipient gut microbiome. This approach could potentially reduce the risk of infections caused by resistant organisms within the patient and the transfer of resistance genes or pathogens to others.

TRIAL REGISTRATION

ClinicalTrials.gov, NCT01925417 ; registered on August 19, 2013.

Significant effect of HIV/HAART on oral microbiota using multivariate analysis

Persons infected with HIV are particularly vulnerable to a variety of oral microbial diseases. Although various study designs and detection approaches have been used to compare the oral microbiota of HIV-negative and HIV-positive persons, both with and without highly active antiretroviral therapy (HAART), methods have varied, and results have not been consistent or conclusive. The purpose of the present study was to compare the oral bacterial community composition in HIV-positive persons under HAART to an HIV-negative group using 16S rRNA gene sequence analysis. Extensive clinical data was collected, and efforts were made to balance the groups on clinical variables to minimize confounding. Multivariate analysis was used to assess the independent contribution of HIV status. Eighty-nine HIV-negative participants and 252 HIV-positive participants under HAART were sampled. The independent effect of HIV under HAART on the oral microbiome was statistically significant, but smaller than the effect of gingivitis, periodontal disease, smoking, caries, and other clinical variables. In conclusion, a multivariate comparison of a large sample of persons with HIV under HAART to an HIV-negative control group showed a complex set of clinical features that influenced oral bacterial community composition, including the presence of HIV under HAART.

High taxonomic diversity of Micromonospora strains isolated from Medicago sativa nodules in Western Spain and Australia

The genus Micromonospora has been found in nodules of several legumes and some new species of this genus were isolated from these plant organs. In this study we analysed the taxonomic diversity of Micromonospora strains isolated from alfalfa nodules in Spain and Australia on the basis of three phylogenetic markers, the rrs and gyrB genes and 16S-23S intergenic spacer (ITS). The genome analysis of selected strains representative of different clusters or lineages found after rrs, gyrB and ITS analyses confirmed the results obtained with these phylogenetic markers. They showed that the analysed strains belong to at least 18 Micromonospora species including previously described ones, such as Micromonospora noduli, Micromonospora ureilytica, Micromonospora taraxaci, Micromonospora zamorensis, Micromonospora aurantiaca and Micromonospora tulbaghiae. Most of these strains belong to undescribed species of Micromonospora showing the high taxonomic diversity of strains from this genus inhabiting alfalfa nodules. Although Micromonospora strains are not able to induce the formation of these nodules, and it seems that they do not contribute to fix atmospheric nitrogen, they could play a role related with the mechanisms of plant growth promotion and pathogen protection presented by Micromonospora strains isolated from legume nodules.

On the Role of Bioinformatics and Data Science in Industrial Microbiome Applications

Advances in sequencing and computational biology have drastically increased our capability to explore the taxonomic and functional compositions of microbial communities that play crucial roles in industrial processes. Correspondingly, commercial interest has risen for applications where microbial communities make important contributions. These include food production, probiotics, cosmetics, and enzyme discovery. Other commercial applications include software that takes the user's gut microbiome data as one of its inputs and outputs evidence-based, automated, and personalized diet recommendations for balanced blood sugar levels. These applications pose several bioinformatic and data science challenges that range from requiring strain-level resolution in community profiles to the integration of large datasets for predictive machine learning purposes. In this perspective, we provide our insights on such challenges by touching upon several industrial areas, and briefly discuss advances and future directions of bioinformatics and data science in microbiome research.