Topical emollient therapy with sunflower seed oil alters the skin microbiota of young children with severe acute malnutrition in Bangladesh: A randomised, controlled study.

BACKGROUND: Topical emollient therapy with sunflower seed oil (SSO) reduces risk of sepsis and mortality in very preterm infants in low- or middle-income countries (LMICs). Proposed mechanisms include modulation of skin and possibly gut barrier function. The skin and gut microbiota play important roles in regulating barrier function, but the effects of emollient therapy on these microbiotas are poorly understood. METHODS: We characterised microbiota structure and diversity with 16S rRNA gene amplicon sequence data and ecological statistics in 20 children with severe acute malnutrition (SAM) aged 2-24 months, at four skin sites and in stool, during a randomised, controlled trial of emollient therapy with SSO in Bangladesh. Microbes associated with therapy were identified with tree-based sparse discriminant analysis. RESULTS: The skin microbiota of Bangladeshi children with SAM was highly diverse and displayed significant variation in structure as a function of physical distance between sites. Microbiota structure differed between the study groups (P = 0.005), was more diverse in emollient-treated subjects-including on the forehead which did not receive direct treatment-and changed with each day (P = 0.005) at all skin sites. Overall, Prevotellaceae were the most differentially affected by emollient treatment; several genera within this family became more abundant in the emollient group than in the controls across several skin sites. Gut microbiota structure was associated with sample day (P = 0.045) and subject age (P = 0.045), but was not significantly affected by emollient treatment (P = 0.060). CONCLUSIONS: Emollient therapy altered the skin microbiota in a consistent and temporally coherent manner. We speculate that therapy with SSO enhances skin barrier function in part through alterations in the microbiota, and through systemic mechanisms. Strategies to strengthen skin and gut barrier function in populations at risk, such as children in LMICs like Bangladesh, might include deliberate manipulation of their skin microbiota. TRIAL REGISTRATION: ClinicalTrials.gov: NCT02616289

Profiling The Salivary Microbiome In The Qatari Population

Humans are living ecosystems composed of human cells and microbes. The microbiome is the collection of microbes and their genes. Recent breakthrough in the high throughput sequencing technologies made it possible for us to understand the composition of the human microbiome. Launched by the National Institutes of Health in USA, the human microbiome project indicated that our bodies harbor a wide array of microbes, specific to each body site with inter and intra-personal variabilities. Numerous studies have indicated that, the microbiome composition plays an important role in health and disease, thus highlighting the significance of microbiome research in human health. Saliva is a biofluid secreted from salivary glands composed of water, electrolytes, mucus, DNA, RNA, proteins, enzymes and microbes. Several studies assessed the role of the salivary microbiome in many conditions ranging from local diseases of the oral cavity such as dental carries and gingivitis to neurodevelopmental disease such as autism, indicating the potential of applying the knowledge generated from the salivary microbiome projects towards a better understanding of various pathological conditions. In this study, we aim to profile the salivary microbiome of the Qatari population and identify the oral microbial communities in individuals with diabetes or obesity. 100 saliva samples collected from Qatari participants, selected randomly, were retrieved from Qatar Biobank repository. Samples were collected by spitting in a tube. After microbial DNA extraction, 16S rRNA gene was sequenced using Illumina Miseq. Microbial profiles were then correlated with the individual phenotypic and clinical data to identify the microbial signatures associated with health and disease conditions, with special focus on diabetes and obesity due to the increasing prevalence rate of both conditions in Qatar

Profiling The Salivary Microbiome In The Qatari Population

Humans are living ecosystems composed of human cells and microbes. The microbiome is the collection of microbes and their genes. Recent breakthrough in the high throughput sequencing technologies made it possible for us to understand the composition of the human microbiome. Launched by the National Institutes of Health in USA, the human microbiome project indicated that our bodies harbor a wide array of microbes, specific to each body site with inter and intra-personal variabilities. Numerous studies have indicated that, the microbiome composition plays an important role in health and disease, thus highlighting the significance of microbiome research in human health. Saliva is a biofluid secreted from salivary glands composed of water, electrolytes, mucus, DNA, RNA, proteins, enzymes and microbes. Several studies assessed the role of the salivary microbiome in many conditions ranging from local diseases of the oral cavity such as dental carries and gingivitis to neurodevelopmental disease such as autism, indicating the potential of applying the knowledge generated from the salivary microbiome projects towards a better understanding of various pathological conditions. In this study, we aim to profile the salivary microbiome of the Qatari population and identify the oral microbial communities in individuals with diabetes or obesity. 100 saliva samples collected from Qatari participants, selected randomly, were retrieved from Qatar Biobank repository. Samples were collected by spitting in a tube. After microbial DNA extraction, 16S rRNA gene was sequenced using Illumina Miseq. Microbial profiles were then correlated with the individual phenotypic and clinical data to identify the microbial signatures associated with health and disease conditions, with special focus on diabetes and obesity due to the increasing prevalence rate of both conditions in Qatar

Multidomain analyses of a longitudinal human microbiome intestinal cleanout perturbation experiment

Our work focuses on the stability, resilience, and response to perturbation of the bacterial communities in the human gut. Informative flash flood-like disturbances that eliminate most gastrointestinal biomass can be induced using a clinically-relevant iso-osmotic agent. We designed and executed such a disturbance in human volunteers using a dense longitudinal sampling scheme extending before and after induced diarrhea. This experiment has enabled a careful multidomain analysis of a controlled perturbation of the human gut microbiota with a new level of resolution. These new longitudinal multidomain data were analyzed using recently developed statistical methods that demonstrate improvements over current practices. By imposing sparsity constraints we have enhanced the interpretability of the analyses and by employing a new adaptive generalized principal components analysis, incorporated modulated phylogenetic information and enhanced interpretation through scoring of the portions of the tree most influenced by the perturbation. Our analyses leverage the taxa-sample duality in the data to show how the gut microbiota recovers following this perturbation. Through a holistic approach that integrates phylogenetic, metagenomic and abundance information, we elucidate patterns of taxonomic and functional change that characterize the community recovery process across individuals. We provide complete code and illustrations of new sparse statistical methods for high-dimensional, longitudinal multidomain data that provide greater interpretability than existing methods

Characterization of Urinary Microbiome and Their Association with Health and Disease

There has been a growing interest in human microbiome studies in the past decade, with the development of high-throughput sequencing techniques. These microorganisms interact and respond to the host as an entity, and are involved in various homeostatic functions including nutrition digestion, immune response, metabolism and endocrine regulation. The urinary microbiome, however, remains relatively under-investigated. One of the technical challenges of urinary microbiome studies is the samples usually contain a large number of host cells and low microbial biomass. These samples with the high host, low microbial abundance (“high-low” samples) are associated with increased risk of compromised quality of 16s rRNA gene sequencing results. An analysis with mock samples showed that mechanisms of host materials interfering with microbiome analysis includes reducing microbial DNA extract yield by competitively binding to the filter of DNA extraction column, inhibiting PCR amplification of 16S rRNA gene regions as non-target DNA, and consuming sequencing depth by unspecific amplification from PCR. To counter these issues, a refined processing protocol and a quality checking tool were developed for handling “high-low” samples. With these methods, a combination of sequencing-based methods and enhanced culture-based methods showed evidence of bacteria in renal tissue samples. On the other hand, the optimal urine sample collection and storage methods for microbiome study have not been reported. An optimisation experiment showed that urine samples with a volume higher than 20 mL and stored in centrifuged pellets generated the best sequencing results. The urinary microbiome of healthy subjects and urinary stone patients were characterised using 16s rRNA gene sequencing and enhanced quantitative urine culture (EQUC) techniques. Although no clear distinction was observed of urinary microbiome profiles between healthy subjects and urinary stone patients, male and female individuals do have their unique urinary microbiome profiles. The urinary microbiome profile of an individual remained stable throughout three months. Investigation of urine samples of metabolic stone patients before and after lithotripsy showed fluctuations in their urinary microbiome profiles, with newly-emerged microbes in sequencing results correlated with microbes cultured from stone samples. These results suggested bacteria liberated from metabolic stones during lithotripsy

Gut microbiome insights into the pathophysiology of inflammatory bowel disease

The global prevalence of inflammatory bowel disease (IBD) has been steadily rising since the turn of the century. IBD is a chronic gastrointestinal disease with no cure, and it therefore has a significant lifelong burden for people with the disease. The causal mechanisms of IBD are not fully understood, and genetic factors do not entirely explain its development. One factor, the gut microbiome (i.e., the microorganisms that inhabit the gut together with their genes and metabolic products), has been implicated in IBD, and studying it offers an opportunity to further our understanding of how the disease develops and persists. Individuals with IBD have gut microbiomes that look different from healthy individuals, a phenomenon often described as ‘dysbiosis’. It has been difficult to define specifically what dysbiosis means for people with the disease as there is wide variation between study designs, while also having methodological limitations and oversights. Despite this, therapies for IBD are being developed around altering the gut microbiome. An encouraging treatment option is faecal microbiota transplantation (FMT), wherein a gut microbiome sample (stool) from a healthy donor is transferred to a recipient with IBD. The efficacy of FMT is currently comparable to other therapeutics for IBD, and continued research of the gut microbiome may lead to improvements in FMT. This thesis takes an interdisciplinary approach to studying the gut microbiome in IBD to offer insights into the pathophysiology of the disease. Most gut microbiome studies of IBD have centred around bacteria, and this thesis provides an alternative perspective by highlighting the necessity of including nonbacterial gut microbes—namely fungi, protozoa, and viruses—in IBD research. This point is then demonstrated with the use of computational and statistical methods to show that intestinal fungi and protozoa have an altered distribution in IBD. Through these methods, it is also shown how nonbacterial microbes can be used to improve what is known of FMT. In addition to the inclusion of nonbacterial microbes, longitudinal studies are necessary to improve the efficacy of FMT by revealing the microbial changes that lead to remission. These studies are more accessible when flexible sampling types are used to enable participants to collect their own samples. The comparability of an alternative sample type (dry stool swabs) collected by participants is evaluated in this thesis against its reference sample type (whole stool) in a longitudinal study of FMT for IBD. Lastly, this thesis provides a guide to designing longitudinal microbiome studies in clinical and public health research that is built on critical statistical considerations. Overall, this thesis synthesises insights from microbiome research with clinical and biostatistical expertise to bridge the gap between basic and translational science. The knowledge presented in this thesis paves the way for advancements and alternative approaches to gut microbiome research that will ultimately improve outcomes for individuals with the disease.Thesis (Ph.D.) -- University of Adelaide, School of Biological Sciences, 202

Fibre degradation by pig microbiota

Rapeseed meal (RSM), a by-product from rapeseed oil production, is not only a suitable protein source for swine feed but also a potential energy source. RSM contains a high amount of cell wall polysaccharides, even higher when compared to soybean meal commonly used in the feed industry. A drawback of RSM is that the complex cell wall polysaccharides cannot be utilized by endogenous enzymes from monogastric animals, and also can only be partly fermented by the microbial community in the gastrointestinal tract (GIT). Therefore, enzymatic and chemical treatment on RSM were performed to improve the recalcitrant fibre degradability of RSM in the thesis

Microbial Community Structure and Function: Implications for Current and Future Respiratory Therapies

Thesis advisor: Babak MomeniDiseases of the upper respiratory tract encompass a plethora of complex multifaceted etiologies ranging from acute viral and bacterial infections to chronic diseases of the lung and nasal cavity. Due to this inherent complexity, typical treatments often fail in the face of recalcitrant infections and/or severe forms of chronic disease, including asthma. Thus, in order to provide improved standard of care, the mechanisms at play in hard-to-treat etiologies must be better understood. More recently, research has demonstrated a significant association between microbiota and many URT diseases. Previous work has also identified species capable of directly inhibiting standard treatments used to control asthma exacerbations. Despite an exhaustive collection of data characterizing microbiota composition in states of both health and disease, our knowledge of what microbiota profiles are observed in what specific disease etiologies is severely lacking. Yet, gaining these insights is crucial for the translation of such data into application. In this thesis I sought to: 1) identify gut microbiota profiles associated with severe and treatment resistant forms of childhood asthma, and 2) formulate a predictive model to facilitate the restructuring of microbiota for desired therapeutic outcomes. To identify gut microbiota and metabolites enriched in severe and treatment resistant childhood asthma, I looked to an ongoing longitudinal human study on vitamin D and childhood asthma. In this study, I find several fecal bacterial taxa and metabolites associated with more severe (i.e., higher wheeze proportion) and treatment resistant asthma in children at age 3 years. Specifically, several Veillonella species were enriched in children with higher wheeze proportion and in children that responded poorly to inhaled corticosteroid treatment (ICS) (i.e., non-responders). Haemophilus parainfluenzae, a species previously identified as enriched in the airway of adults with ICS-resistant asthma, was also uniquely enriched in children considered ICS non-responders in this study. Several metabolic pathways were also distinctly enriched: histidine metabolism was enriched in children with higher wheeze proportion while sphingolipid metabolism was enriched in ICS non-responders. Both metabolic pathways have been previously identified in association with asthma, further corroborating their role in this disease. Yet, this study is the first to identify these taxa and metabolites in children with preexisting and treatment resistant asthma. In the pursuit of improved treatment outcomes for recalcitrant URT diseases, recent efforts have turned towards microbiota-based therapies. While such treatments have proven successful in the treatment of gastrointestinal infections, these methods have not yet been extended to other conditions. Considering this, I ask whether a predictive model describing microbial interactions can facilitate the restructuring of microbiota for desired therapeutic outcomes. For this, I use a community of nasal microbiota to determine when a simply Lotka-Volterra-like (LV) model is a suitable representation for microbial interactions. I then utilize our LV-like model to examine whether environmental fluctuations have a major influence on community assembly and composition. For this, I looked specifically at pH fluctuations. In this study, I found that LV-like models are most suitable for describing community dynamics in complex low nutrient conditions. I also identified simple in vitro experiments that can reliably predict the suitability of a LV-like model for describing outcomes of a two-species community. When our LV-like model was applied to an in silico community of nasal species to determine the impact of environmental fluctuations, I find that nasal communities are generally robust against pH fluctuations and that, in this condition, facilitative interactions are a stabilizing force, and thus, selected for in in silico enrichment experiments. Overall, this thesis further corroborates the association of microbiota with URT diseases and treatment outcomes while also providing unique insight into their association with specific etiologies in childhood asthma. This thesis also provides a framework for developing models able to facilitate the development of future microbiota-based therapies while also determining how, and when, environmental factors impact community assembly and composition.Thesis (PhD) — Boston College, 2021.Submitted to: Boston College. Graduate School of Arts and Sciences.Discipline: Biology

Mise en place d'approches bioinformatiques innovantes pour l'intégration de données multi-omiques longitudinales

Les nouvelles technologies «omiques» à haut débit, incluant la génomique, l'épigénomique, la transcriptomique, la protéomique, la métabolomique ou encore la métagénomique, ont connues ces dernières années un développement considérable. Indépendamment, chaque technologie omique est une source d'information incontournable pour l'étude du génome humain, de l'épigénome, du transcriptome, du protéome, du métabolome, et également de son microbiote permettant ainsi d'identifier des biomarqueurs responsables de maladies, de déterminer des cibles thérapeutiques, d'établir des diagnostics préventifs et d'accroître les connaissances du vivant. La réduction des coûts et la facilité d'acquisition des données multi-omiques à permis de proposer de nouveaux plans expérimentaux de type série temporelle où le même échantillon biologique est séquencé, mesuré et quantifié à plusieurs temps de mesures. Grâce à l'étude combinée des technologies omiques et des séries temporelles, il est possible de capturer les changements d'expressions qui s'opèrent dans un système dynamique pour chaque molécule et avoir une vision globale des interactions multi-omiques, inaccessibles par une approche simple standard. Cependant le traitement de cette somme de connaissances multi-omiques fait face à de nouveaux défis : l'évolution constante des technologies, le volume des données produites, leur hétérogénéité, la variété des données omiques et l'interprétabilité des résultats d'intégration nécessitent de nouvelles méthodes d'analyses et des outils innovants, capables d'identifier les éléments utiles à travers cette multitude d'informations. Dans cette perspective, nous proposons plusieurs outils et méthodes pour faire face aux challenges liés à l'intégration et l'interprétation de ces données multi-omiques particulières. Enfin, l'intégration de données multi-omiques longitudinales offre des perspectives dans des domaines tels que la médecine de précision ou pour des applications environnementales et industrielles. La démocratisation des analyses multi-omiques et la mise en place de méthodes d'intégration et d'interprétation innovantes permettront assurément d'obtenir une meilleure compréhension des écosystèmes biologiques.New high-throughput «omics» technologies, including genomics, epigenomics, transcriptomics, proteomics, metabolomics and metagenomics, have expanded considerably in recent years. Independently, each omics technology is an essential source of knowledge for the study of the human genome, epigenome, transcriptome, proteome, metabolome, and also its microbiota, thus making it possible to identify biomarkers leading to diseases, to identify therapeutic targets, to establish preventive diagnoses and to increase knowledge of living organisms. Cost reduction and ease of multi-omics data acquisition resulted in new experimental designs based on time series in which the same biological sample is sequenced, measured and quantified at several measurement times. Thanks to the combined study of omics technologies and time series, it is possible to capture the changes in expression that take place in a dynamic system for each molecule and get a comprehensive view of the multi-omics interactions, which was inaccessible with a simple standard omics approach. However, dealing with this amount of multi-omics data faces new challenges: continuous technological evolution, large volumes of produced data, heterogeneity, variety of omics data and interpretation of integration results require new analysis methods and innovative tools, capable of identifying useful elements through this multitude of information. In this perspective, we propose several tools and methods to face the challenges related to the integration and interpretation of these particular multi-omics data. Finally, integration of longidinal multi-omics data offers prospects in fields such as precision medicine or for environmental and industrial applications. Democratisation of multi-omics analyses and the implementation of innovative integration and interpretation methods will definitely lead to a deeper understanding of eco-systems biology