Metagenomics of the Human Body



Metagenomics of the Human Body introduces readers to the major findings from the human genome project and at the same time presents the crossover to the human metagenome/microbiome, which we are only starting to understand through the advent of newly emerging technologies and other developments. The book brings a new perspective by combining the information gained from the human genome with that derived from parallel metagenomic studies, and new results from investigating the effects of these microbes on the host immune system. As the field of metagenomics continues to evolve, Metagenomics of the Human Body brings together leaders in the field and their unique perspectives on this topic. The authors focus on the human genome and recent developments in the fields of microbial ecology and metagenomics of the microbial species that are associated with the human body. They also discuss the enormous implications for health and disease. Metagenomics of the Human Body is ideal for scientists, clinicians, community activists, undergraduate and graduate level students, as well as ethical and legal groups associated with or interested in the issues surrounding the human genome. About the Editor Dr. Karen E. Nelson is the Director of the Rockville Campus of the J. Craig Venter Institute (JCVI) where she has been for the past 14 years. She was formerly the Director of Human Microbiology and Metagenomics in the Department of Human Genomic Medicine at the JCVI. She has authored or co-authored over 100 publications, and is currently Editor-in-Chief of the Springer journal Microbial Ecology. She is also a standing member of the NRC Committee on Biodefense, a member of the American Society for Microbiology (ASM) Communications Committee and a Fellow of the ASM. © Springer Science+Business Media, LLC 2011. All rights reserved.

Chapters (16)

Disease may stems from the environment, genetics, and the human microbiome. In this chapter, we discuss what is currently known about the genetic and microbial contribution to human disease. Because this is a large area, we provide a high-level review of a few diseases to reveal underlying themes of the contribution of genetics and metagenomics to human disease. As changing a microbiome is a far easier task than changing one’s genome, manipulating it may prove an effective way to both treat and prevent disease where causal disease relationships can be established. Elucidating the interplay of the contributions of the genome and microbiome will be necessary to help us better understand disease.
The microbial ecosystems found along the body surfaces of mammals have provided a variety of complementary metabolic functions to their hosts. It is likely that the mammalian host and its microbiota form a coalition of cells, or a so-called “super-organism,” which mutually strives for survival. Unfortunately, the exact interactions between host and microbiota are for the most part unexplored. Our current understanding of host–microbe interactions mostly comes from studies on the gastrointestinal tract microbiota, which is the most densely populated microbial ecosystem of the mammalian host. Although mammalian host genes are greatly outnumbered by the total gene pool of their microbiota, there are several indications that host genotype is an important factor affecting the diversity and function of the microbiota. Communication between host cells and microbes is likely to be dependent on host-immune system-related genes and can therefore be influenced by polymorphisms in these genes. However, there are probably more genes which are important for host–microbe interactions that are not directly related to the immune system. Future studies should focus on the hierarchy in importance of host genotypes with relation to host–microbe interactions. Complicating the studies on host–microbe interactions are environmental factors, which can sometimes drastically influence both the host and its microbiota. Especially dietary influences should be taken into account while analyzing the interaction between the microbial communities of the gut and the host.
In the past, medical microbiology has largely relied on simplifying assumptions of one-to-one relationships: between a single pathogen and a single disease or between a single gene and virulence-related phenotype. Now, thanks to technical and conceptual advances, we are moving towards a new paradigm, in which pathogen–host interactions are best evaluated against the backdrop of the complex community of germs, genes and genomes known as the human microbiome, which acts as a reservoir of colonisation, virulence and resistance determinants. This new outlook blurs the boundaries between pathogen and commensal, emphasises the immunological crosstalk between microbiota and host and recognises the complex interplay between the human microbiome, colonisation resistance, diet, antibiotics and inflammation. On this view, pathogenesis is more like guerrilla warfare or terrorism than a clash between standing armies – the success of the pathogen, like that of the partisan, depending critically on what is happening in the local community.
In this chapter we discuss changing approaches to viral discovery and human health, summarize the current understanding of the human-associated viral community, and review contemporary methods in viral metagenomics. The virome is the community of viruses that populate an organism or ecosystem at any given time. This includes the “core” set of commensal viruses that do not give rise to clinical symptoms or viremia, combined with any acute or persistent infections that may be present. Recent technological advances enable us to sequence viral genomes without culturing or cloning. These methods permit not only the discovery of a wider range of viral pathogens, but also a broader assessment of the human virome in the absence of clinically recognized disease. A new focus in contemporary virology is the natural viral community of the human body. This will provide a background for recognition of emerging and previously unrecognized viruses. It should be possible to detect viral infection before the emergence of symptoms, which will have significant implications for health-care delivery.
Metagenomics is a rapidly changing field of microbial biology that provides insights into the diversity and functional capacity of the microbial communities. In order to improve the phylogenetic and physiological interpretation of metagenomic data, it is essential to produce sequence data for individual reference strains. The NIH-supported Human Microbiome Project (HMP) plans to sequence the genomes of 900 reference strains representing isolates from all major body sites. This Chapter describes the approaches used by the strain selection groups of the HMP and International Human Microbiome Consortium (IHMC) to achieve this goal as well as some current and future challenges and opportunities facing those interested in metagenomics of the human body. Although advances in DNA sequencing technology have helped make the selection and sequencing of reference strains less dependent on cultivation and large quantities of DNA, using the data in pursuit of strain isolation and purification should not be neglected. The international collaborations that have developed via the leadership of North American and European research groups have also created an excellent opportunity to undertake a pangenomic analysis of human microbiomes, which may substantially increase the value of comparative analysis of metagenomic datasets, leading to a better understanding of host–microbiome relationships in health and disease.
Humans live in association with abundant, complex, and dynamic microbial populations (the microbiome) that colonize many body sites, including the vaginal tract. Interactions between the host and the vaginal microbiota greatly affect women’s health, where they often serve a protective role in maintaining vaginal health. Disruption of the microbial composition can lead to increased susceptibility to various urogenital diseases, including bacterial vaginosis (BV), vulvovaginal candidiasis (VVC), pelvic inflammatory disease (PID), and sexually transmitted diseases (STDs) such as infection with Chlamydia, Trichomonas, and human immunodeficiency virus (HIV). The composition of the vaginal microbiota also has a notable impact on pregnancy and neonatal outcome, including complications such as preterm labor and delivery. Understanding the composition and dynamics of the vaginal ecosystem as well as the involvement of metabolic and immunologic components is an area of increasing interest and research.
The human lower respiratory tract is considered sterile in normal healthy individuals (Flanagan et al., 2007; Speert, 2006) despite the fact that every day we breathe in multiple microorganisms present in the air and aspirate thousands of organisms from the mouth and nasopharynx. This apparent sterility is maintained by numerous interrelated components of the lung physical structures such as the mucociliary elevator and components of the innate and adaptive immune systems (discussed below) (reviewed in (Diamond et al., 2000; Gerritsen, 2000)). However, it is possible that the observed sterility might be a result of the laboratory practices applied to study the flora of the lungs. Historically, researchers faced with a set of diseases characterized by a changing and largely cryptic lung microbiome have lacked tools to study lung ecology as a whole and have concentrated on familiar, cultivatable candidate pathogens.
The human skin, as the largest organ of the human body, protects the underlying tissues and plays an important role as a front-line defense system against external environmental changes and invading pathogens. It is colonized by a unique and complex microbial ecosystem, including bacteria, fungi, and bacteriophages, some of which could become pathogenic under certain circumstances. The skin microbiota is complex. Several hundred different microbial species reside on the skin. Its composition and distribution are uniquely different from the flora of other organs.
The human oral cavity is estimated to contain more than 750 bacterial species (Jenkinson and Lamont, 2005; Paster et al., 2006). Although this figure is controversial, the fact remains that up to half of the species in the oral microbiota cannot yet be cultivated in the laboratory. Therefore, metagenomics is a powerful way of accessing these unculturable bacteria in order to understand the role of the oral microbiota in health and disease and to mine for useful products such as enzymes, energy sources and antimicrobial agents. The Human Oral Microbiome Database (HOMD provides comprehensive information on what is known about the composition of the oral microbiota using information derived from cultivation and metagenomic data based on 16S rRNA gene sequencing.
In the book Metagenomics of the Human Body (ISBN: 978-1-4419-7088-6), the book editor and the publisher are retracting the chapter entitled “The Human and His Microbiome Risk Factors for Infections”. Unfortunately, long paragraphs of the original articles and reviews, including those by the author herself, were used in the chapter without appropriate acknowledgment. Many original articles cited in the chapter were copied verbatim and not referenced. After carefully examining the chapter, it was decide that it indeed constituted an issue of plagiarism.
Human gastrointestinal tract harbors an ecosystem composed of the gastrointestinal mucosa and the commensal microbiota. The gastrointestinal microbiota plays an intricate and sometimes pivotal role for our health and well-being. Infectogenomics that studies the interaction between host genetic factors and the composition of the microbiota should yield further insights into the nature of the occurrence of infections in the gastrointestinal tract when the gastrointestinal ecosystem changed from eubiosis to dysbiosis.
The prevailing theory of autoimmune disease, that the body creates autoantibodies that attack “self,” was developed during an era when culture-based methods vastly underestimated the number of microbes capable of persisting in and on Homo sapiens. Thanks to the advent of culture-independent tools, the human body is now known to harbor billions of microbes whose collective genomes work in concert with the human genome. Thus, the human genome can no longer be studied in isolation. Some of these microbes persist by slowing the activity of the vitamin D receptor nuclear receptor, affecting the expression of endogenous antimicrobials and other key components of the innate immune system. It seems that bacteria that cause autoimmune disease accumulate over a lifetime, with individuals picking up pathogens with greater ease over time, as the immune response becomes increasingly compromised. Any one autoimmune disease is likely due to many different microbes within the metagenomic microbiota. This helps explain the high levels of comorbidity observed among patients with autoimmune conditions. What are commonly believed to be autoantibodies may instead be created in response to this metagenomic microbiota when the adaptive immune system is forced to deal with disintegration of infected cells. Similarly, haplotypes associated with autoimmune conditions vary widely among individuals and populations. They are more suggestive of a regional infectious model rather than a model in which an illness is caused by inherited variation of HLA haplotypes
Liver fibrosis is characterized by an excessive deposition of extracellular matrix proteins that occurs in chronic liver disease of any origin. Cirrhosis occurs with the development of regenerating nodules of hepatocytes. Patients with decompensated liver cirrhosis have a poor prognosis, and liver transplantation is often necessary. There are no effective antifibrotic treatments for patients with chronic liver diseases. Intestinal dysbiosis and bacterial translocation are common in patients with liver disease, and there is strong evidence that the translocation of bacteria and their products across the epithelial barrier contributes to the progression of liver fibrosis. Supporting evidence comes from animal studies demonstrating that intestinal decontamination is associated with decreased liver fibrogenesis. Despite this strong association, the exact molecular mechanism of how intestinal bacterial overgrowth and translocation contribute to liver disease progression remains unknown. In this chapter we describe microbial changes in response to liver injury and chronic liver disease and the consequences of intestinal dysbiosis on host biology. We will initially focus on fatty liver disease associated with obesity and liver injury induced by alcohol. We then highlight how therapeutic interventions may modify the gastrointestinal microflora and prevent or reduce disease progression.
The gut microbiota has evolved intimate symbiotic relationships with the human host and is considered as an internal “microbial organ.” It has also been shown to exhibit an immensely diverse, complex composition and significant involvement in human health and disease by use of various high-throughput “omics” techniques. However, the molecular basis of these host–microbe interactions and the role of individual bacterial species remain unclear. In this Chapter, we discuss strategies and techniques for understanding the host–microbiome symbiosis, the modulation of human metabolic phenotype especially through the gut–liver axis, and potential therapies for the gut microbiota.
MetaHIT ( has as a first objective the creation of a catalog of the microbial genes from our intestinal tract, thus laying foundations for characterization of the gut microbial communities. Next, it aims to explore associations between microbial genes and human phenotypes. For that, it develops, on the one hand, molecular tools for profiling of the intestinal microbial genes that are harbored by any individual, and on the other, a bio-informatics resource to organize and interpret heterogeneous information, including sequencing data and clinical metadata. Moreover, MetaHIT develops approaches to detect and analyze functional interactions of microbes and the human host, focusing on the role of target genes in the microbial cell and the effect of gene products on the human host. MetaHIT targets two pathologies, obesity and inflammatory bowel diseases (Crohn’s disease and ulcerative colitis). The studies involve (i) cross-sectional comparisons of healthy and sick individuals; (ii) longitudinal follow-up of patients in clinical remission; (iii) nutritional intervention related to the stability of gut microbial community; and (iv) comparison of patients responding or not to a drug treatment.
The human microbiome refers to all of the species that inhabit the human body, residing both on and in it. Over the past several years, there has been a significantly increased interest directed to the understanding of the microorganisms that reside on and in the human body. These studies of the human microbiome promise to reveal all these species and increase our understanding of the normal inhabitants, those that trigger disease and those that vary in response to disease conditions. It is anticipated that these directed research efforts, coupled with new technological advances, will ultimately allow one to gain a greater understanding of the relationships of these species with their human hosts. The various chapters in this book present a range of aspects of human microbiome research, explain the scientific and technological rationale, and highlight the significant potential that the results from these studies hold. In this chapter, we begin to address the potential and long-term implications of the knowledge gained from human microbiome research (which currently is centered in the developed world) for the developing world, which has often lagged behind in the benefits of these new technologies and their implications to new research areas.
... With the advent of massive sequencing methods there was an important increase in the number of reports on the characterization of bacterial communities using the 16S rRNA gene as marker. Since only partial sequences are obtained from different variable regions, however, the discrepancies in the results promoted comparative studies between some variable regions and the full-length gene (Nelson 2011, Sun et al. 2013. ...
... The percentage of unculturable organisms varies depending on the environment from which they come and how intensely they have been studied. For example, in the human microbiome, the percentage of unculturable organisms is approximately 70-80% (Nelson 2011), whereas in marine biomes it is higher than 97% (Rappé and Giovannoni 2003). Studies of marine microbial communities would benefit from the application of genomic techniques that prevent the isolation and growth of microbes while generating useful information for their taxonomic identification and classification. ...
... Sin embargo, las secuencias son parciales y corresponden a distintas regiones variables. Las discrepancias en los hallazgos fomentó estudios comparativos entre algunas regiones variables y el gen completo (Nelson 2011, Sun et al. 2013. ...
New sequencing technologies and analytical capabilities have stimulated the study of microbial communities from specific environments, enabling researchers to understand the complexity of those systems. The 16S rRNA gene has proved very useful in describing the diversity and characterization of marine microbial communities, particularly of uncultivated organisms. The development of new sequencing techniques has contributed to the exponential increase in the number of reported 16S rRNA sequences as barcodes for microorganisms, forcing a review of concepts and methods for the taxonomic classification of these organisms. Manipulation and analysis of large amounts of genetic information have prompted the development of specific databases, specialized algorithms, and computational tools to compare thousands of such sequences and make a taxonomic assignment. Complete 16S rRNA sequences are thus needed for accurate and reproducible taxonomy assignment in the study of marine bacterial communities. © 2015 Universidad Autonoma de Baja California. All rights reserved.
... Ludzki organizm zasiedlany jest przez zróżnicowane drobnoustroje należące do trzech głównych domen: bakterii, archea i eukariota, które stanowią mikrobiom człowieka i są one konieczne do prawidłowego funkcjonowania makroorganizmu, w tym utrzymania jego statusu odpornościowego [4,21]. Wśród nich są nie tylko drobnoustroje komensalne i symbiotyczne występujące na skórze, w jamie ustnej, przewodzie pokarmowym, oraz w układzie oddechowym i moczowo--płciowym, ale i te, które wywołują stany patologiczne, w tym choroby zakaźne [71]. Termin ,,mikrobiom" po raz pierwszy został użyty przez laureata nagrody Nobla Joshua Lederberg'a, który sugerował aby używać go do określenia zbiorowego genomu wszystkich drobnoustrojów komensalnych, symbiotycznych i chorobotwórczych bytujących w ludzkim organizmie [44]. ...
... Ludzka skóra jest największym narządem ciała człowieka i odgrywa ważną rolę w układzie odpornościowym, stanowiąc pierwszą linię obrony przed zmianami środowiska zewnętrznego, jak i przed atakiem drobnoustrojów, w tym patogennych. Powierzchnia skóry, którą określa się na 1,8 m 2 , kolonizowana jest przez różne drobnoustroje, które reprezentują bak-terie, archea, wirusy, w tym bakteriofagi oraz grzyby [35,71]. Ten ekosystem jest zróżnicowany topograficznie, ze względu na różnice anatomiczne jego regionów. ...
... Mikroflora skóry warunkowana jest także wiekiem gospodarza i płcią [71]. Wykazano, że skóra płodu w macicy jest jałowa, po czym jej pierwsza kolonizacja bakteriami następuje podczas naturalnego porodu lub w czasie cesarskiego cięcia [71]. ...
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The human microbiome is represented by bacteria, archea, viruses, including bacteriophages, and fungi. These microorganisms colonize the human body and are necessary for the maintenance of homeostasis, including human immune status. Even though human microbiome is vital for the functioning of the human organism, it is still poorly understood, especially when it comes to archea, but also viruses and fungi. The aim of this study is to present the current state of knowlegde about the microorganisms inhabiting essential biotypes of the human body, i.e. the skin, the mouth and the digestive tract, as well as the respiratory and urogenital tract.
... В ведение. Cогласно современным представлениям, около квадриллиона вирусов находится внутри и на поверхности тела человека [1]. Желудочно-кишечный тракт (ЖКТ) человека содержит около 10 14 микробных клеток [2,3], предположительно, общий вес бактерий в организме человека составляет около 2 кг [4]. ...
Background. In recent years, much attention has been paid to the importance and role of the gut microbiota in human health maintaining and its composition violations in various diseases. Aim. The aim of the study was to analyze the up-to-date literature on the intestinal microbiota, its composition, role and functions in maintaining human health, as well as on the factors affecting the composition of the intestinal microbiota. Material and methods. An analytical review of published studies on the intestinal microbiota was conducted. Results and discussion. The development of new metagenomic methods for studying the microbiota has led to a fundamental breakthrough in the advancement of ideas about its role, composition and functions in the human body. Despite significant differences in the composition of the gut microbiota in healthy people, the microbiota of a healthy person remains relatively stable throughout life; its composition is influenced by a number of factors: mode of delivery, age, geographic area of residence, genetic characteristics of the person, consumption of related drugs, diet, and others. Treatment with antibiotics may also lead to pronounced changes in the composition of the intestinal microbiota. Other adverse events of antibiotic therapy may include the development of antibiotic-resistant strains of bacteria; resistance may be due to the presence of genes encoding resistance factors to antibacterial drugs. Conclusion. Thus, the gut microbiota plays a tremendous role in maintaining human health and the development of a number of diseases.
... Таким образом, поддержание кишечного гомеостаза толстого кишечника человека реализуется через феномен микробного распознавания «свой-чу жой», проявляющегося в способности бифидофлоры проводить первичный отбор микросимбионтов за счет оппозитного (усиление/подавление) влияния на базовые физиологические критерии ассоциантов и дифференцированного воздействия на про-или противовоспалительный потенциал лимфоцитов. Ранее выявленная способность сигналов от бифидобактерий через TLR-2 перекрывать и вытеснять сигналы от других микросимбионтов на дендритные клетки [8,12,13], являющиеся важным клеточным звеном врожденного и адаптивного иммунитета, в совокупности с полученными результатами могут свидетельствовать о ключевой роли бифидофлоры в процессах иммуномоду ляции и поддержания кишечного гомеостаза человека. ...
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Aim. To study the production of cytokins on the model of peripheral blood lymphocytes under the activity of Bifidobacterium bifidum 791 strain induced by Lactobacillus fermentum 90T-C4, Escherichia coli 157 and Staphylococcus aureus 209 metabolites. Materials and methods. Reference strains of «self» and «поп-self» types of bacteria were used in the investigation. «Self/non-self» microbial recognition method (Bukharin O.V., Perunova N.B., 2011). Mononuclear leukocytes were isolated from the blood of healthy donors by gradient centrifugation in ficoll-verographin density gradient (Pharmacia, Sweden). Production of pro-(IFN-y, TNF-a, IL-6, IL-17) and anti-inflammatory (IL-10) cytokins was investigated in mononuclear culture by ELISA method. The results are statistically processed. Results. Similarities in the direction of lymphocyte reaction and «self» and «поп-self» microbial differentiation of bifidobacteria were found. It was determined that in reaction to «поп-self» reference cultures the lymphocytes increased pro-inflammatory potential and increased anti-inflammatory potential in reaction to «self» bacteria. Preliminary co-incubation of bifidobacteria with L.fermentum metabolites 90T-C4 increased anti-inflammatory effect of B. bifldum 791, whereas lymphocyte reaction to E. coli and staphylococcus induced bifidobacteria was changed to pro-inflammatory. Conclusion. Combined unidirectional influence of microbiota and its metabolic activity on cytokine level might enhance defence effect of intestinal immune response. The capacity of bifidoflora to carry out primary selection of microsymbionts on account of intermicrobial «recognition» and differentiated exposure to lymphocyte pro- and anti-inflammatory potential evidences the key role of bifidoflora in the human intestine homeostasis maintenance.
... Even between genetically closely 56 related hosts, environmental variation can create a significant deviation in gut microbiota. For 57 instance, when reared in distinct environments, pairs of human twins (Zoetendal & Akkermans 58 2009;Nelson 2011;Kostic et al. 2013), mice siblings (Gootenberg & Turnbaugh 2011) ...
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Host-associated gut microbial communities can have large impacts on host ecology and evolution, and are typically shaped by host taxonomy and diet. Different host species often harbor distinct microbial communities, potentially because (1) host dietary specialization determines microbial colonization, (2) host-specific selection acts on diet-acquired microbiota, and (3) a combination of both processes. While the first possibility involves passive community structuring, the other two may arise from a functional association and should produce stable microbial communities. However, these alternatives have rarely been tested in wild host populations. We used 16S rRNA amplicon sequencing to characterize the gut bacterial communities of six dragonfly species collected across multiple seasons and locations. We found that variation in bacterial community composition was predominantly explained by sampling season and location, and secondarily by host species. To distinguish the role of host dietary specialization and host-imposed selection, we used insect-specific primers to identify prey in the gut contents of three focal dragonfly species. We found that these dragonflies, considered to be generalist predators, consumed distinct prey, with seasonal diet variation. Together, the patterns of host dietary specialization and spatial and temporal variation suggest a strong role of passive processes in shaping the gut bacterial community. Indeed, the abundance and distribution of ~76% of the bacterial community members were consistent with neutral community assembly. Our results contradict the pervasive expectation that host-imposed selection shapes gut microbial communities, and highlight the importance of joint analyses of variation in host diet and gut microbial communities of natural host populations.
... Even more applications of these methods are used in agriculture (93), food science and pharmaceuticals (32), and forensics (49, 79,82,182). Many large-scale metagenomic projects are now generating comprehensive microbial sequence collections for different environments (e.g., human-associated [116,167], soil [54,171], and ocean environments [17,142]). Since microbial communities change as they interact with other organisms and as the environment changes, time-series analyses have also become common (21,24,77,115,172). ...
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Metagenomic approaches are now commonly used in microbial ecology to study microbial communities in more detail, including many strains that cannot be cultivated in the laboratory. Bioinformatic analyses make it possible to mine huge metagenomic datasets and discover general patterns that govern microbial ecosystems. However, the findings of typical metagenomic and bioinformatic analyses still do not completely describe the ecology and evolution of microbes in their environments. Most analyses still depend on straightforward sequence similarity searches against reference databases. We herein review the current state of metagenomics and bioinformatics in microbial ecology and discuss future directions for the field. New techniques will allow us to go beyond routine analyses and broaden our knowledge of microbial ecosystems. We need to enrich reference databases, promote platforms that enable meta- or comprehensive analyses of diverse metagenomic datasets, devise methods that utilize long-read sequence information, and develop more powerful bioinformatic methods to analyze data from diverse perspectives.
... Previously, the human microbiota are often taken as commensals; yet they can be engaged in mutual interactions with their hosts, directly or indirectly. The microbiome has been described as an ecosystem in which equilibrium of various members is required to keep a person healthy [12]. The colonization resistance phenomenon of healthy gut microbiota is a well-known example to help host defense against the pathogen infection through two major mechanisms: (1) there would be the direct competition between commensal bacteria and pathogens since they require similar ecological niches, including consumption of nutrients, release of bacteriocins or proteinaceous toxins and altering host environmental conditions (such as pH value) [13,14]; (2) the commensal microbiota could also inhibit the growth of the pathogens indirectly by activating the defense responses in the host that can be enhanced by the commensal microbiota through promoting mucosal barrier function, such as eliciting the production of antimicrobial peptides and IgA [15][16][17]. ...
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Microbes have co-evolved with human beings for millions of years. They play a very important role in maintaining the health of the host. With the advancement in next generation sequencing technology, the microbiome profiling in the host can be obtained under different circumstances. This review focuses on the current knowledge of the alteration of complex microbial communities upon the infection of different pathogens, such as human immunodeficiency virus, hepatitis B virus, influenza virus, and Mycobacterium tuberculosis, at different body sites. It is believed that the increased understanding of the correlation between infectious disease and the alteration of the microbiome can contribute to better management of disease progression in the future. However, future studies may need to be more integrative so as to establish the exact causality of diseases by analyzing the correlation between microorganisms within the human host and the pathogenesis of infectious diseases.
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Background: With the reduction of gene sequencing cost and demand for emerging technologies such as precision medical treatment and deep learning in genome, it is an era of gene data outbreaks today. How to store, transmit and analyze these data has become a hotspot in the current research. Now the compression algorithm based on reference is widely used due to its high compression ratio. There exists a big problem that the data from different gene banks can't merge directly and share information efficiently, because these data are usually compressed with different references. The traditional workflow is decompression-and-recompression, which is too simple and time-consuming. We should improve it and speed it up. Results: In this paper, we focus on this problem and propose a set of transformation algorithms to cope with it. We will 1) analyze some different compression algorithms to find the similarities and the differences among all of them, 2) come up with a naïve method named TDM for data transformation between difference gene banks and finally 3) optimize former method TDM and propose the method named TPI and the method named TGI. A number of experiment result proved that the three algorithms we proposed are an order of magnitude faster than traditional decompression-and-recompression workflow. Conclusions: Firstly, the three algorithms we proposed all have good performance in terms of time. Secondly, they have their own different advantages faced with different dataset or situations. TDM and TPI are more suitable for small-scale gene data transformation, while TGI is more suitable for large-scale gene data transformation.
The current century has seen the discovery of a new trend in science, infectious symbiology, which studies ambiguous interactions between microbes and humans (from peaceful contacts to direct antagonism). What underlies these interrelations? What do such different outcomes depend on? These are important questions for Homo sapiens because, only after having deciphered the mechanisms of these outcomes (from health to disease), will we become able to control them. Here one naturally recalls I.P. Pavlov, who held that “explanation is not the goal of science. The goal of science is power.” However, to rule this world, humans need knowledge. Although the problems of infectious pathology remain the same, we should take a fresh look at them and use this knowledge to preserve our own health. The material proposed here is a new look at old problems and at the opening prospects.
Conference Paper
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Discrete linear classifier is a very sparse class of decision model that has proved useful to reduce overfitting in very high dimension learning problems. However, learning discrete linear classifier is known as a difficult problem. It requires finding a discrete linear model minimizing the classification error over a given sample. A ternary classifier is a classifier defined by a pair (w, r) where w is a vector in {-1, 0, +1}n and r is a nonnegative real capturing the threshold or offset. The goal of the learning algorithm is to find a vector of weights in {-1, 0, +1}n that minimizes the hinge loss of the linear model from the training data. This problem is NP-hard and one approach consists in exactly solving the relaxed continuous problem and to heuristically derive discrete solutions. A recent paper by the authors has introduced a randomized rounding algorithm [1] and we propose in this paper more sophisticated algorithms that improve the generalization error. These algorithms are presented and their performances are experimentally analyzed. Our results show that this kind of compact model can address the complex problem of learning predictors from bioinformatics data such as metagenomics ones where the size of samples is much smaller than the number of attributes. The new algorithms presented improve the state of the art algorithm to learn ternary classifier. The source of power of this improvement is done at the expense of time complexity.
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Material and methods: We recall the definition of epistasis and extend it for metagenomic biomarkers and then we describe the overview of our method metaBOOST and provide detailed information about each step of metaBOOST. Results: We describe the data sources for both simulation studies and real metagenomic datasets. Then, we describe the procedure of simulation studies and provide results for it. After that, we conduct real datasets studies and report the results. Conclusions and discussion: Finally, we conclude our method and discuss some possible improvements for the future.
Interest in the role of the microbiome in human health has burgeoned over the past decade with the advent of new technologies for interrogating complex microbial communities. The large-scale dynamics of the microbiome can be described by many of the tools and observations used in the study of population ecology. Deciphering the metagenome and its aggregate genetic information can also be used to understand the functional properties of the microbial community. Both the microbiome and metagenome probably have important functions in health and disease; their exploration is a frontier in human genetics.
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