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Follow your gut : the enormous impact of tiny microbes
\"In just the last few years, scientists have shown how the microscopic life within our bodies--particularly within our intestines--has an astonishing impact on our lives. Your health, mood, sleep patterns, eating preferences--even your likelihood of getting bitten by mosquitoes--can be traced in part to the tiny creatures that live on and inside of us. In [this book], pioneering scientist Rob Knight pairs with award-winning science journalist Brendan Buhler to explain ... why these new findings matter to everyone\"--Amazon.com.
Book
Role of the microbiome in human development
The host-microbiome supraorganism appears to have coevolved and the unperturbed microbial component of the dyad renders host health sustainable. This coevolution has likely shaped evolving phenotypes in all life forms on this predominantly microbial planet. The microbiota seems to exert effects on the next generation from gestation, via maternal microbiota and immune responses. The microbiota ecosystems develop, restricted to their epithelial niches by the host immune system, concomitantly with the host chronological development, providing early modulation of physiological host development and functions for nutrition, immunity and resistance to pathogens at all ages. Here, we review the role of the microbiome in human development, including evolutionary considerations, and the maternal/fetal relationships, contributions to nutrition and growth. We also discuss what constitutes a healthy microbiota, how antimicrobial modern practices are impacting the human microbiota, the associations between microbiota perturbations, host responses and diseases rocketing in urban societies and potential for future restoration.
Journal Article
Dirt is good : the advantage of germs for your child's developing immune system
\"From two of the world's top scientists and one of the world's top science writers (all parents), Dirt Is Good is a Q&A-based guide to everything you need to know about kids & germs. \"Is it OK for my child to eat dirt?\" That's just one of the many questions authors Jack Gilbert and Rob Knight are bombarded with every week from parents all over the world. They've heard everything from \"My two-year-old gets constant ear infections. Should I give her antibiotics? Or probiotics?\" to \"I heard that my son's asthma was caused by a lack of microbial exposure. Is this true, and if so what can I do about it now?\" Google these questions, and you'll be overwhelmed with answers. The internet is rife with speculation and misinformation about the risks and benefits of what most parents think of as simply germs, but which scientists now call the microbiome : the combined activity of all the tiny organisms inside our bodies and the surrounding environment that have an enormous impact on our health and well-being. Who better to turn to for answers than Drs. Gilbert and Knight, two of the top scientists leading the investigation into the microbiome--an investigation that is producing fascinating discoveries and bringing answers to parents who want to do the best for their young children. Dirt Is Good is a comprehensive, authoritative, accessible guide you've been searching for\"-- Provided by publisher.
Book
Microbiota succession throughout life from the cradle to the grave
Associations between age and the human microbiota are robust and reproducible. The microbial composition at several body sites can predict human chronological age relatively accurately. Although it is largely unknown why specific microorganisms are more abundant at certain ages, human microbiota research has elucidated a series of microbial community transformations that occur between birth and death. In this Review, we explore microbial succession in the healthy human microbiota from the cradle to the grave. We discuss the stages from primary succession at birth, to disruptions by disease or antibiotic use, to microbial expansion at death. We address how these successions differ by body site and by domain (bacteria, fungi or viruses). We also review experimental tools that microbiota researchers use to conduct this work. Finally, we discuss future directions for studying the microbiota’s relationship with age, including designing consistent, well-powered, longitudinal studies, performing robust statistical analyses and improving characterization of non-bacterial microorganisms.The human microbiota can undergo dramatic changes during different phases of life (for example, during colonization after birth, after disturbances or in old age). In this Review, Knight and colleagues discuss the microbiota successions that occur from the cradle to the grave.
Journal Article
Microbial endocrinology: the interplay between the microbiota and the endocrine system
The new field of microbiome research studies the microbes within multicellular hosts and the many effects of these microbes on the host's health and well-being. We now know that microbes influence metabolism, immunity and even behavior. Essential questions, which are just starting to be answered, are what are the mechanisms by which these bacteria affect specific host characteristics. One important but understudied mechanism appears to involve hormones. Although the precise pathways of microbiota-hormonal signaling have not yet been deciphered, specific changes in hormone levels correlate with the presence of the gut microbiota. The microbiota produces and secretes hormones, responds to host hormones and regulates expression levels of host hormones. Here, we summarize the links between the endocrine system and the gut microbiota. We categorize these interactions by the different functions of the hormones, including those affecting behavior, sexual attraction, appetite and metabolism, gender and immunity. Future research in this area will reveal additional connections, and elucidate the pathways and consequences of bacterial interactions with the host endocrine system.
This review summarizes the links between the host endocrine system and microbiota functions, reporting both effects of the host hormones on bacteria and effects of the microbiota on host hormones influencing behavior, appetite and metabolism, gender and immunity.
Journal Article
Evolving approaches to profiling the microbiome in skin disease
Despite its harsh and dry environment, human skin is home to diverse microbes, including bacteria, fungi, viruses, and microscopic mites. These microbes form communities that may exist at the skin surface, deeper skin layers, and within microhabitats such as the hair follicle and sweat glands, allowing complex interactions with the host immune system. Imbalances in the skin microbiome, known as dysbiosis, have been linked to various inflammatory skin disorders, including atopic dermatitis, acne, and psoriasis. The roles of abundant commensal bacteria belonging to Staphylococcus and Cutibacterium taxa and the fungi Malassezia , where particular species or strains can benefit the host or cause disease, are increasingly appreciated in skin disorders. Furthermore, recent research suggests that the interactions between microorganisms and the host’s immune system on the skin can have distant and systemic effects on the body, such as on the gut and brain, known as the “skin-gut” or “skin-brain” axes. Studies on the microbiome in skin disease have typically relied on 16S rRNA gene sequencing methods, which cannot provide accurate information about species or strains of microorganisms on the skin. However, advancing technologies, including metagenomics and other functional ‘omic’ approaches, have great potential to provide more comprehensive and detailed information about the skin microbiome in health and disease. Additionally, inter-species and multi-kingdom interactions can cause cascading shifts towards dysbiosis and are crucial but yet-to-be-explored aspects of many skin disorders. Better understanding these complex dynamics will require meta-omic studies complemented with experiments and clinical trials to confirm function. Evolving how we profile the skin microbiome alongside technological advances is essential to exploring such relationships. This review presents the current and emerging methods and their findings for profiling skin microbes to advance our understanding of the microbiome in skin disease.
Journal Article
The Earth Microbiome project: successes and aspirations
The Earth Microbiome Project (EMP) was launched in August 2010, with the ambitious aim of constructing a global catalogue of the uncultured microbial diversity of this planet. The primary vision of the Earth Microbiome Project, to process the microbial diversity and functional potential from approximately 200,000 environmental samples, marks it as an undertaking so massive that it was at first considered to be pure folly (as late as 2012, Jonathan Eisen was quoted in Nature as saying Knight and Gilbert literally talk about sampling the entire planet. It is ludicrous and not feasible - yet they are doing it [1]).
Journal Article
Establishing microbial composition measurement standards with reference frames
Differential abundance analysis is controversial throughout microbiome research. Gold standard approaches require laborious measurements of total microbial load, or absolute number of microorganisms, to accurately determine taxonomic shifts. Therefore, most studies rely on relative abundance data. Here, we demonstrate common pitfalls in comparing relative abundance across samples and identify two solutions that reveal microbial changes without the need to estimate total microbial load. We define the notion of “reference frames”, which provide deep intuition about the compositional nature of microbiome data. In an oral time series experiment, reference frames alleviate false positives and produce consistent results on both raw and cell-count normalized data. Furthermore, reference frames identify consistent, differentially abundant microbes previously undetected in two independent published datasets from subjects with atopic dermatitis. These methods allow reassessment of published relative abundance data to reveal reproducible microbial changes from standard sequencing output without the need for new assays.
Most microbiome studies make conclusions based on changes in relative abundance of taxa, inferred from sequencing data. Here, the authors highlight common pitfalls in comparing relative abundance across samples, and identify solutions that reveal microbial changes without the need to estimate total microbial load.
Journal Article
Global patterns in bacterial diversity
Microbes are difficult to culture. Consequently, the primary source of information about a fundamental evolutionary topic, life's diversity, is the environmental distribution of gene sequences. We report the most comprehensive analysis of the environmental distribution of bacteria to date, based on 21,752 16S rRNA sequences compiled from 111 studies of diverse physical environments. We clustered the samples based on similarities in the phylogenetic lineages that they contain and found that, surprisingly, the major environmental determinant of microbial community composition is salinity rather than extremes of temperature, pH, or other physical and chemical factors represented in our samples. We find that sediments are more phylogenetically diverse than any other environment type. Surprisingly, soil, which has high species-level diversity, has below-average phylogenetic diversity. This work provides a framework for understanding the impact of environmental factors on bacterial evolution and for the direction of future sequencing efforts to discover new lineages.
Journal Article
Structure-based protein function prediction using graph convolutional networks
The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, we introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures. It outperforms current leading methods and sequence-based Convolutional Neural Networks and scales to the size of current sequence repositories. Augmenting the training set of experimental structures with homology models allows us to significantly expand the number of predictable functions. DeepFRI has significant de-noising capability, with only a minor drop in performance when experimental structures are replaced by protein models. Class activation mapping allows function predictions at an unprecedented resolution, allowing site-specific annotations at the residue-level in an automated manner. We show the utility and high performance of our method by annotating structures from the PDB and SWISS-MODEL, making several new confident function predictions. DeepFRI is available as a webserver at
https://beta.deepfri.flatironinstitute.org/
.
The rapid increase in the number of proteins in sequence databases and the diversity of their functions challenge computational approaches for automated function prediction. Here, the authors introduce DeepFRI, a Graph Convolutional Network for predicting protein functions by leveraging sequence features extracted from a protein language model and protein structures.
Journal Article