Randomized feature selection based semi-supervised latent Dirichlet allocation for microbiome analysis.

Health and disease are fundamentally influenced by microbial communities and their genes (the microbiome). An in-depth analysis of microbiome structure that enables the classification of individuals based on their health can be crucial in enhancing diagnostics and treatment strategies to improve the overall well-being of an individual. In this paper, we present a novel semi-supervised methodology known as Randomized Feature Selection based Latent Dirichlet Allocation (RFSLDA) to study the impact of the gut microbiome on a subject's health status. Since the data in our study consists of fuzzy health labels, which are self-reported, traditional supervised learning approaches may not be suitable. As a first step, based on the similarity between documents in text analysis and gut-microbiome data, we employ Latent Dirichlet Allocation (LDA), a topic modeling approach which uses microbiome counts as features to group subjects into relatively homogeneous clusters, without invoking any knowledge of observed health status (labels) of subjects. We then leverage information from the observed health status of subjects to associate these clusters with the most similar health status making it a semi-supervised approach. Finally, a feature selection technique is incorporated into the model to improve the overall classification performance. The proposed method provides a semi-supervised topic modelling approach that can help handle the high dimensionality of the microbiome data in association studies. Our experiments reveal that our semi-supervised classification algorithm is effective and efficient in terms of high classification accuracy compared to popular supervised learning approaches like SVM and multinomial logistic model. The RFSLDA framework is attractive because it (i) enhances clustering accuracy by identifying key bacteria types as indicators of health status, (ii) identifies key bacteria types within each group based on estimates of the proportion of bacteria types within the groups, and (iii) computes a measure of within-group similarity to identify highly similar subjects in terms of their health status.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand the dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune, and clinical markers of microbiomes from four body sites in 86 participants over 6 years. We found that microbiome stability and individuality are body-site specific and heavily influenced by the host. The stool and oral microbiome are more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. We identify individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlate across body sites, suggesting systemic dynamics influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals show altered microbial stability and associations among microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease.

Anti-cytomegalovirus antibody levels stratify human immune profiles across the lifespan.

Human cytomegalovirus (hCMV) is a ubiquitous latent persistent herpesvirus infecting 60-90% of the population worldwide. hCMV carriage in immunocompetent people is asymptomatic; thus, hCMV can be considered a component of normative aging. However, hCMV powerfully modulates many features of the immune, and likely other, systems and organs. Questions remain as to how hCMV carriage affects the human host. We used anti-CMV antibody titers as a stratifying criterion to examine the impact of "intensity" of hCMV infection as a potential biomarker of aging, inflammation, and immune homeostasis in a cohort of 247 participants stratified into younger (21-40 years) and older (> 65 years of age) groups. We showed that anti-CMV antibody titers increased with age and directly correlated to increased levels of soluble tumor necrosis factor (sTNFR) I in younger but not older participants. CD8 + cell numbers were reduced in the older group due to the loss in CD8 + T naïve (Tn) cells. In CMV carriers and, in particular, in anti-CMV Ab-high participants, this loss was mitigated or reversed by an increase in the numbers of CD8 + T effector memory (Tem) and T effector memory reexpressing CD45RA (Temra) cells. Analysis of CD38, HLA-DR, and CD57 expression revealed subset (CD4 or CD8)-specific changes that correlated with anti-CMV Ab levels. In addition, anti-CMV Ab levels predicted anti-CMV CD8 T cell responsiveness to different CMV open reading frames (ORFs) selectively in older participants, which correlated to the transcriptional order of expression of specific CMV ORFs. Implications of these results for the potential predictive value of anti-CMV Ab titers during aging are discussed.

Improved DNA Extraction and Amplification Strategy for 16S rRNA Gene Amplicon-Based Microbiome Studies.

Next-generation sequencing technology has driven the rapid advancement of human microbiome studies by enabling community-level sequence profiling of microbiomes. Although all microbiome sequencing methods depend on recovering the DNA from a sample as a first critical step, lysis methods can be a major determinant of microbiome profile bias. Gentle enzyme-based DNA preparation methods preserve DNA quality but can bias the results by failing to open difficult-to-lyse bacteria. Mechanical methods like bead beating can also bias DNA recovery because the mechanical energy required to break tougher cell walls may shear the DNA of the more easily lysed microbes, and shearing can vary depending on the time and intensity of beating, influencing reproducibility. We introduce a non-mechanical, non-enzymatic, novel rapid microbial DNA extraction procedure suitable for 16S rRNA gene-based microbiome profiling applications that eliminates bead beating. The simultaneous application of alkaline, heat, and detergent ('Rapid' protocol) to milligram quantity samples provided consistent representation across the population of difficult and easily lysed bacteria equal to or better than existing protocols, producing sufficient high-quality DNA for full-length 16S rRNA gene PCR. The novel 'Rapid' method was evaluated using mock bacterial communities containing both difficult and easily lysed bacteria. Human fecal sample testing compared the novel Rapid method with a standard Human Microbiome Project (HMP) protocol for samples from lung cancer patients and controls. DNA recovered from both methods was analyzed using 16S rRNA gene sequencing of the V1V3 and V4 regions on the Illumina platform and the V1V9 region on the PacBio platform. Our findings indicate that the 'Rapid' protocol consistently yielded higher levels of Firmicutes species, which reflected the profile of the bacterial community structure more accurately, which was confirmed by mock community evaluation. The novel 'Rapid' DNA lysis protocol reduces population bias common to bead beating and enzymatic lysis methods, presenting opportunities for improved microbial community profiling, combined with the reduction in sample input to 10 milligrams or less, and it enables rapid transfer and simultaneous lysis of 96 samples in a standard plate format. This results in a 20-fold reduction in sample handling time and an overall 2-fold time advantage when compared to widely used commercial methods. We conclude that the novel 'Rapid' DNA extraction protocol offers a reliable alternative for preparing fecal specimens for 16S rRNA gene amplicon sequencing.

A serum-induced gene signature in hepatocytes is associated with pediatric nonalcoholic fatty liver disease.

OBJECTIVE: Pediatric nonalcoholic fatty liver disease (NAFLD) is a growing problem, but its underlying mechanisms are poorly understood. We used transcriptomic reporter cell assays to investigate differences in transcriptional signatures induced in hepatocyte reporter cells by the sera of children with and without NAFLD. METHODS: We studied serum samples from 45 children with NAFLD and 28 children without NAFLD. The sera were used to induce gene expression in cultured HepaRG cells and RNA-sequencing was used to determine gene expression. Computational techniques were used to compare gene expression patterns. RESULTS: Sera from children with NAFLD induced the expression of 195 genes that were significantly differentially expressed in hepatocytes compared to controls with obesity. NAFLD was associated with increased expression of genes promoting inflammation, collagen synthesis, and extracellular matrix remodeling. Additionally, there was lower expression of genes involved in endobiotic and xenobiotic metabolism, and downregulation of peroxisome function, oxidative phosphorylation, and xenobiotic, bile acid, and fatty acid metabolism. A 13-gene signature, including upregulation of TREM1 and MMP1 and downregulation of CYP2C9, was consistently associated with all diagnostic categories of pediatric NAFLD. CONCLUSION: The extracellular milieu of sera from children with NAFLD induced specific gene profiles distinguishable by a hepatocyte reporter system. Circulating factors may contribute to inflammation and extracellular matrix remodeling and impair xenobiotic and endobiotic metabolism in pediatric NAFLD.

Longitudinal profiling of the microbiome at four body sites reveals core stability and individualized dynamics during health and disease.

To understand dynamic interplay between the human microbiome and host during health and disease, we analyzed the microbial composition, temporal dynamics, and associations with host multi-omics, immune and clinical markers of microbiomes from four body sites in 86 participants over six years. We found that microbiome stability and individuality are body-site-specific and heavily influenced by the host. The stool and oral microbiome were more stable than the skin and nasal microbiomes, possibly due to their interaction with the host and environment. Also, we identified individual-specific and commonly shared bacterial taxa, with individualized taxa showing greater stability. Interestingly, microbiome dynamics correlated across body sites, suggesting systemic coordination influenced by host-microbial-environment interactions. Notably, insulin-resistant individuals showed altered microbial stability and associations between microbiome, molecular markers, and clinical features, suggesting their disrupted interaction in metabolic disease. Our study offers comprehensive views of multi-site microbial dynamics and their relationship with host health and disease. Study Highlights: The stability of the human microbiome varies among individuals and body sites.Highly individualized microbial genera are more stable over time.At each of the four body sites, systematic interactions between the environment, the host and bacteria can be detected.Individuals with insulin resistance have lower microbiome stability, a more diversified skin microbiome, and significantly altered host-microbiome interactions.

The preterm human milk microbiota fluctuates by postpartum week and is characterized by gestational age and maternal BMI.

IMPORTANCE: Despite a growing recognition that the type of nutrition received by preterm infants influences their intestinal microbiome and health outcomes, the microbiota of mother's own milk (MOM), pasteurized donor human milk (PDHM), and infant formula remain poorly characterized. In our study, we found that the structure of microbial communities, bacterial diversity, and relative abundances of specific genera were significantly different between MOM, PDHM, and formula. Additionally, our results suggest that the microbiota of MOM changes as a function of time and maternal factors. Lastly, we identified three lactotypes within MOM that have distinct microbial compositions and described the maternal factors associated with them. These findings set the stage for future research aimed at advancing our knowledge of the microbiota of preterm infant nutrition and the specific influence it may have on health outcomes.

Targeted metabolomics reveals plasma biomarkers and metabolic alterations of the aging process in healthy young and older adults.

With the exponential growth in the older population in the coming years, many studies have aimed to further investigate potential biomarkers associated with the aging process and its incumbent morbidities. Age is the largest risk factor for chronic disease, likely due to younger individuals possessing more competent adaptive metabolic networks that result in overall health and homeostasis. With aging, physiological alterations occur throughout the metabolic system that contribute to functional decline. In this cross-sectional analysis, a targeted metabolomic approach was applied to investigate the plasma metabolome of young (21-40y; n = 75) and older adults (65y + ; n = 76). A corrected general linear model (GLM) was generated, with covariates of gender, BMI, and chronic condition score (CCS), to compare the metabolome of the two populations. Among the 109 targeted metabolites, those associated with impaired fatty acid metabolism in the older population were found to be most significant: palmitic acid (p < 0.001), 3-hexenedioic acid (p < 0.001), stearic acid (p = 0.005), and decanoylcarnitine (p = 0.036). Derivatives of amino acid metabolism, 1-methlyhistidine (p = 0.035) and methylhistamine (p = 0.027), were found to be increased in the younger population and several novel metabolites were identified, such as cadaverine (p = 0.034) and 4-ethylbenzoic acid (p = 0.029). Principal component analysis was conducted and highlighted a shift in the metabolome for both groups. Receiver operating characteristic analyses of partial least squares-discriminant analysis models showed the candidate markers to be more powerful indicators of age than chronic disease. Pathway and enrichment analyses uncovered several pathways and enzymes predicted to underlie the aging process, and an integrated hypothesis describing functional characteristics of the aging process was synthesized. Compared to older participants, the young group displayed greater abundance of metabolites related to lipid and nucleotide synthesis; older participants displayed decreased fatty acid oxidation and reduced tryptophan metabolism, relative to the young group. As a result, we offer a better understanding of the aging metabolome and potentially reveal new biomarkers and predicted mechanisms for future study.

The Fungal Microbiome of the Upper Airway Is Associated With Future Loss of Asthma Control and Exacerbation Among Children With Asthma.

BACKGROUND: Accumulating evidence suggests that the upper airway bacterial microbiota is implicated in asthma inception, severity, and exacerbation. Unlike bacterial microbiota, the role of the upper airway fungal microbiome (mycobiome) in asthma control is poorly understood. RESEARCH QUESTION: What are the upper airway fungal colonization patterns among children with asthma and their relationship with subsequent loss of asthma control and exacerbation of asthma? STUDY DESIGN AND METHODS: The study was coupled with the Step Up Yellow Zone Inhaled Corticosteroids to Prevent Exacerbations (ClinicalTrials.gov Identifier: NCT02066129) clinical trial. The upper airway mycobiome was investigated using Internal transcribed spacer 1 (ITS1) sequencing of nasal blow samples collected from children with asthma when asthma was well controlled (baseline, n = 194) and during early signs of loss of asthma control (yellow zone [YZ], n = 107). RESULTS: At baseline, 499 fungal genera were detected in the upper airway samples, with two commensal fungal species, Malassezia globosa and Malassezia restricta, being most dominant. The relative abundance of Malassezia species varies by age, BMI, and race. Higher relative abundance of M globosa at baseline was associated with lower risk of future YZ episodes (P = .038) and longer time to development of first YZ episode (P = .022). Higher relative abundance of M globosa at YZ episode was associated with lower risk of progression from YZ episode to severe asthma exacerbation (P = .04). The upper airway mycobiome underwent significant changes from baseline to YZ episode, and increased fungal diversity was correlated highly with increased bacterial diversity (ρ = 0.41). INTERPRETATION: The upper airway commensal mycobiome is associated with future asthma control. This work highlights the importance of the mycobiota in asthma control and may contribute to the development of fungi-based markers to predict asthma exacerbation.

The microbial community dynamics of cocaine sensitization in two behaviorally divergent strains of collaborative cross mice.

The gut-brain axis is increasingly recognized as an important pathway involved in cocaine use disorder. Microbial products of the murine gut have been shown to affect striatal gene expression, and depletion of the microbiome by antibiotic treatment alters cocaine-induced behavioral sensitization in C57BL/6J male mice. Some reports suggest that cocaine-induced behavioral sensitization is correlated with drug self-administration behavior in mice. Here, we profile the composition of the naïve microbiome and its response to cocaine sensitization in two collaborative cross (CC) strains. These strains display extremely divergent behavioral responses to cocaine sensitization. A high-responding strain, CC004/TauUncJ (CC04), has a gut microbiome that contains a greater amount of Lactobacillus than the cocaine-nonresponsive strain CC041/TauUncJ (CC41). The gut microbiome of CC41 is characterized by an abundance of Eisenbergella, Robinsonella and Ruminococcus. In response to cocaine, CC04 has an increased Barnsiella population, while the gut microbiome of CC41 displays no significant changes. PICRUSt functional analysis of the functional potential of the gut microbiome in CC04 shows a significant number of potential gut-brain modules altered after exposure to cocaine, specifically those encoding for tryptophan synthesis, glutamine metabolism, and menaquinone synthesis (vitamin K2). Depletion of the microbiome by antibiotic treatment revealed an altered cocaine-sensitization response following antibiotics in female CC04 mice. Depleting the microbiome by antibiotic treatment in males revealed increased infusions for CC04 during a cocaine intravenous self-administration dose-response curve. Together these data suggest that genetic differences in cocaine-related behaviors may involve the microbiome.

Microbial glutamate metabolism predicts intravenous cocaine self-administration in diversity outbred mice.

The gut microbiome is thought to play a critical role in the onset and development of psychiatric disorders, including depression and substance use disorder (SUD). To test the hypothesis that the microbiome affects addiction predisposing behaviors and cocaine intravenous self-administration (IVSA) and to identify specific microbes involved in the relationship, we performed 16S rRNA gene sequencing on feces from 228 diversity outbred mice. Twelve open field measures, two light-dark assay measures, one hole board and novelty place preference measure significantly differed between mice that acquired cocaine IVSA (ACQ) and those that failed to acquire IVSA (FACQ). We found that ACQ mice are more active and exploratory and display decreased fear than FACQ mice. The microbial abundances that differentiated ACQ from FACQ mice were an increased abundance of Barnesiella, Ruminococcus, and Robinsoniella and decreased Clostridium IV in ACQ mice. There was a sex-specific correlation between ACQ and microbial abundance, a reduced Lactobacillus abundance in ACQ male mice, and a decreased Blautia abundance in female ACQ mice. The abundance of Robinsoniella was correlated, and Clostridium IV inversely correlated with the number of doses of cocaine self-administered during acquisition. Functional analysis of the microbiome composition of a subset of mice suggested that gut-brain modules encoding glutamate metabolism genes are associated with the propensity to self-administer cocaine. These findings establish associations between the microbiome composition and glutamate metabolic potential and the ability to acquire cocaine IVSA thus indicating the potential translational impact of targeting the gut microbiome or microbial metabolites for treatment of SUD. This article is part of the Special Issue on "Microbiome & the Brain: Mechanisms & Maladies".

Blackcurrants Reduce the Risk of Postmenopausal Osteoporosis: A Pilot Double-Blind, Randomized, Placebo-Controlled Clinical Trial.

Beneficial effects of blackcurrant supplementation on bone metabolism in mice has recently been demonstrated, but no studies are available in humans. The current study aimed to examine the dose-dependent effects of blackcurrant in preventing bone loss and the underlying mechanisms of action in adult women. Forty peri- and early postmenopausal women were randomly assigned into one of three treatment groups for 6 months: (1) a placebo (control group, n = 13); (2) 392 mg/day of blackcurrant powder (low blackcurrant, BC, group, n = 16); and (3) 784 mg/day of blackcurrant powder (high BC group, n = 11). The significance of differences in outcome variables was tested by repeated-measures ANOVA with treatment and time as between- and within-subject factors, respectively. Overall, blackcurrant supplementation decreased the loss of whole-body bone mineral density (BMD) compared to the control group (p < 0.05), though the improvement of whole-body BMD remained significant only in the high BC group (p < 0.05). Blackcurrant supplementation also led to a significant increase in serum amino-terminal propeptide of type 1 procollagen (P1NP), a marker of bone formation (p < 0.05). These findings suggest that daily consumption of 784 mg of blackcurrant powder for six months mitigates the risk of postmenopausal bone loss, potentially through enhancing bone formation. Further studies of larger samples with various skeletal conditions are warranted to confirm these findings.

Bifidobacterial carbohydrate/nucleoside metabolism enhances oxidative phosphorylation in white adipose tissue to protect against diet-induced obesity.

BACKGROUND: Comparisons of the gut microbiome of lean and obese humans have revealed that obesity is associated with the gut microbiome plus changes in numerous environmental factors, including high-fat diet (HFD). Here, we report that two species of Bifidobacterium are crucial to controlling metabolic parameters in the Korean population. RESULTS: Based on gut microbial analysis from 99 Korean individuals, we observed the abundance of Bifidobacterium longum and Bifidobacterium bifidum was markedly reduced in individuals with increased visceral adipose tissue (VAT), body mass index (BMI), blood triglyceride (TG), and fatty liver. Bacterial transcriptomic analysis revealed that carbohydrate/nucleoside metabolic processes of Bifidobacterium longum and Bifidobacterium bifidum were associated with protecting against diet-induced obesity. Oral treatment of specific commercial Bifidobacterium longum and Bifidobacterium bifidum enhanced bile acid signaling contributing to potentiate oxidative phosphorylation (OXPHOS) in adipose tissues, leading to reduction of body weight gain and improvement in hepatic steatosis and glucose homeostasis. Bifidobacterium longum or Bifidobacterium bifidum manipulated intestinal sterol biosynthetic processes to protect against diet-induced obesity in germ-free mice. CONCLUSIONS: Our findings support the notion that treatment of carbohydrate/nucleoside metabolic processes-enriched Bifidobacterium longum and Bifidobacterium bifidum would be a novel therapeutic strategy for reprograming the host metabolic homeostasis to protect against metabolic syndromes, including diet-induced obesity. Video Abstract.

Exploratory studies of oral and fecal microbiome in healthy human aging.

Growing evidence has linked an altered host fecal microbiome composition with health status, common chronic diseases, and institutionalization in vulnerable older adults. However, fewer studies have described microbiome changes in healthy older adults without major confounding diseases or conditions, and the impact of aging on the microbiome across different body sites remains unknown. Using 16S ribosomal RNA gene sequencing, we reconstructed the composition of oral and fecal microbiomes in young (23-32; mean = 25 years old) and older (69-94; mean = 77 years old) healthy community-dwelling research subjects. In both body sites, we identified changes in minor bacterial operational taxonomic units (OTUs) between young and older subjects. However, the composition of the predominant bacterial species of the healthy older group in both microbiomes was not significantly different from that of the young cohort, which suggests that dominant bacterial species are relatively stable with healthy aging. In addition, the relative abundance of potentially pathogenic genera, such as Rothia and Mycoplasma, was enriched in the oral microbiome of the healthy older group relative to the young cohort. We also identified several OTUs with a prevalence above 40% and some were more common in young and others in healthy older adults. Differences with aging varied for oral and fecal samples, which suggests that members of the microbiome may be differentially affected by aging in a tissue-specific fashion. This is the first study to investigate both oral and fecal microbiomes in the context of human aging, and provides new insights into interactions between aging and the microbiome within two different clinically relevant sites.

Murine Model for Measuring Effects of Humanized-Dosing of Antibiotics on the Gut Microbiome.

There is a current need for enhancing our insight in the effects of antimicrobial treatment on the composition of human microbiota. Also, the spontaneous restoration of the microbiota after antimicrobial treatment requires better understanding. This is best addressed in well-defined animal models. We here present a model in which immune-competent or neutropenic mice were administered piperacillin-tazobactam (TZP) according to human treatment schedules. Before, during and after the TZP treatment, fecal specimens were longitudinally collected at established intervals over several weeks. Gut microbial taxonomic distribution and abundance were assessed through culture and molecular means during all periods. Non-targeted metabolomics analyses of stool samples using Quadrupole Time of Flight mass spectrometry (QTOF MS) were also applied to determine if a metabolic fingerprint correlated with antibiotic use, immune status, and microbial abundance. TZP treatment led to a 5-10-fold decrease in bacterial fecal viability counts which were not fully restored during post-antibiotic follow up. Two distinct, relatively uniform and reproducible restoration scenarios of microbiota changes were seen in post TZP-treatment mice. Post-antibiotic flora could consist of predominantly Firmicutes or, alternatively, a more diverse mix of taxa. In general, the pre-treatment microbial communities were not fully restored within the screening periods applied. A new species, closely related to Eubacterium siraeum, Mageeibacillus indolicus, and Saccharofermentans acetigenes, became predominant post-treatment in a significant proportion of mice, identified by 16S rRNA gene sequencing. Principal component analysis of QTOF MS of mouse feces successfully distinguished treated from non-treated mice as well as immunocompetent from neutropenic mice. We observe dynamic but distinct and reproducible responses in the mouse gut microbiota during and after TZP treatment and propose the current murine model as a useful tool for defining the more general post-antibiotic effects in the gastro-intestinal ecosystem where humanized antibiotic dosing may ultimately facilitate extrapolation to humans.

Defining the microbiome of the head and neck: A contemporary review.

OBJECTIVE: The purpose of this paper is to define the microbiome of the head and neck by characterizing and distinguishing the commensal bacteria from pathogenic species. STUDY DESIGN: Literature review. METHODS: Pubmed and Google scholar databases were queried for relevant articles. Keywords such as "middle ear microbiome", "outer ear microbiome", "sinonasal microbiome", "tonsil microbiome", and "laryngeal microbiome" were utilized separately to identify articles pertaining to each topic of study. All applicable abstracts were chosen for initial review and relevant abstracts were then selected for review of the full texts. Articles that did not study the human microbiome, those not written primarily in English, those that were not readily available for full review, and case reports were excluded from the study. RESULTS: Limited studies that investigate the microbial environments of isolated anatomic subsites in the head and neck exist, however the comprehensive microbiome of the head and neck has yet to be completely defined. Based on this review, various studies of the ears, larynx, tonsils and sinus microbiomes exist and yield valuable information, however they are limited in scope and anatomic subsite. In this literature review, these studies are compiled in order to create a comprehensive text inclusive of the known microbial elements of the major anatomic subsites of the head and neck, namely the tonsils, larynx, sinus, outer ear and middle ear. CONCLUSIONS: The significance of the human microbiome in identifying and preventing disease has been established in various physiologic systems, however there is limited research on the microbiome of the head and neck. Understanding the microbiome of the head and neck can help differentiate disease-prone patients from normal patients and guide treatment regimens and antibiotic usage, to aid in resistance control and limit adverse effects of antibiotic overuse. Understanding the elements that lead to dysbiosis can help treat and even prevent common conditions as tonsillitis and rhinosinusitis. In this review, we provide a comprehensive review to serve as an initial background for future studies to define the head and neck microbiome distinguished by all relevant subsites.

Alterations in subgingival microbiota during full-fixed appliance orthodontic treatment-A prospective study.

BACKGROUND: Full-fixed appliance orthodontic treatment (commonly called braces) increases plaque accumulation and the risk of gingivitis and periodontitis. However, little consensus exists on changes to subgingival microbiota and specific periodontopathogens during treatment with braces. Prior studies have been hampered by selection biases due to dependence on culture conditions, candidate-based PCR and shallow sequencing methods. OBJECTIVE: The objective was to provide the first longitudinal, culture-free and deep-sequence profiling of subgingival bacteria in subjects during early stages of full-fixed orthodontic treatment. METHODS: We performed 16S rRNA next-generation sequencing (NGS) on 168 subgingival samples collected at 4 distinct mandibular tooth sites per subject before (0 weeks) and during (6 and 12 weeks) orthodontic intervention in 9 experimental and 5 control subjects not undergoing treatment. RESULTS: Overall, we noted that orthodontic intervention led to increased microbial richness, accompanied by an increased incidence of localized gingivitis/mild periodontitis in subjects requiring orthodontic treatment compared to controls, as well as significant baseline variations in subgingival microbiomes in all subjects. Moreover, we confirmed individual- and site-dependent microbiome variability (in particular, the lingual site harboured higher microbiome diversity than buccal sites) that orthodontic bands may lead to more prolonged shifts in microbial changes compared to brackets, and evidence of adaptive enrichment of consensus bacteria with orthodontic intervention (12 novel, consensus bacterial species were identified). CONCLUSION: Our study, along with evolving global profiling methods and data analyses, builds a strong foundation for further analyses of subgingival microbiomes during full-fixed orthodontic treatment.

Metagenomics and chemotherapy-induced nausea: A roadmap for future research.

Uncontrolled chemotherapy-induced nausea and vomiting can reduce patients' quality of life and may result in premature discontinuation of chemotherapy. Although nausea and vomiting are commonly grouped together, research has shown that antiemetics are clinically effective against chemotherapy-induced vomiting (CIV) but less so against chemotherapy-induced nausea (CIN). Nausea remains a problem for up to 68% of patients who are prescribed guideline-consistent antiemetics. Despite the high prevalence of CIN, relatively little is known regarding its etiology independent of CIV. This review summarizes a metagenomics approach to the study and treatment of CIN with the goal of encouraging future research. Metagenomics focuses on genetic risk factors and encompasses both human (ie, host) and gut microbial genetic variation. Little work to date has focused on metagenomics as a putative biological mechanism of CIN. Metagenomics has the potential to be a powerful tool in advancing scientific understanding of CIN by identifying new biological pathways and intervention targets. The investigation of metagenomics in the context of well-established demographic, clinical, and patient-reported risk factors may help to identify patients at risk and facilitate the prevention and management of CIN.