@phdthesis{Costea2016,
  author    = {Costea, Paul Igor},
  title     = {Stratification and variation of the human gut microbiota},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-139649},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2016},
  abstract  = {The microbial communities that live inside the human gastrointestinal tract -the human gut microbiome- are important for host health and wellbeing. Characterizing this new "organ", made up of as many cells as the human body itself, has recently become possible through technological advances. Metagenomics, the high-throughput sequencing of DNA directly from microbial communities, enables us to take genomic snapshots of thousands of microbes living together in this complex ecosystem, without the need for isolating and growing them. Quantifying the composition of the human gut microbiome allows us to investigate its properties and connect it to host physiology and disease. The wealth of such connections was unexpected and is probably still underestimated. Due to the fact that most of our dietary as well as medicinal intake affects the microbiome and that the microbiome itself interacts with our immune system through a multitude of pathways, many mechanisms have been proposed to explain the observed correlations, though most have yet to be understood in depth. An obvious prerequisite to characterizing the microbiome and its interactions with the host is the accurate quantification of its composition, i.e. determining which microbes are present and in what numbers they occur. Historically, standard practices have existed for sample handling, DNA extraction and data analysis for many years. However, these were generally developed for single microbe cultures and it is not always feasible to implement them in large scale metagenomic studies. Partly because of this and partly because of the excitement that new technology brings about, the first metagenomic studies each took the liberty to define their own approach and protocols. From early meta-analysis of these studies it became clear that the differences in sample handling, as well as differences in computational approaches, made comparisons across studies very difficult. This restricts our ability to cross-validate findings of individual studies and to pool samples from larger cohorts. To address the pressing need for standardization, we undertook an extensive comparison of 21 different DNA extraction methods as well as a series of other sample manipulations that affect quantification. We developed a number of criteria for determining the measurement quality in the absence of a mock community and used these to propose best practices for sampling, DNA extraction and library preparation. If these were to be accepted as standards in the field, it would greatly improve comparability across studies, which would dramatically increase the power of our inferences and our ability to draw general conclusions about the microbiome. Most metagenomics studies involve comparisons between microbial communities, for example between fecal samples from cases and controls. A multitude of approaches have been proposed to calculate community dissimilarities (beta diversity) and they are often combined with various preprocessing techniques. Direct metagenomics quantification usually counts sequencing reads mapped to specific taxonomic units, which can be species, genera, etc. Due to technology-inherent differences in sampling depth, normalizing counts is necessary, for instance by dividing each count by the sum of all counts in a sample (i.e. total sum scaling), or by subsampling. To derive a single value for community (dis-)similarity, multiple distance measures have been proposed. Although it is theoretically difficult to benchmark these approaches, we developed a biologically motivated framework in which distance measures can be evaluated. This highlights the importance of data transformations and their impact on the measured distances. Building on our experience with accurate abundance estimation and data preprocessing techniques, we can now try and understand some of the basic properties of microbial communities. In 2011, it was proposed that the space of genus level variation of the human gut microbial community is structured into three basic types, termed enterotypes. These were described in a multi-country cohort, so as to be independent of geography, age and other host properties. Operationally defined through a clustering approach, they are "densely populated areas in a multidimensional space of community composition"(source) and were proposed as a general stratifier for the human population. Later studies that applied this concept to other datasets raised concerns about the optimum number of clusters and robustness of the clustering approach. This heralded a long standing debate about the existence of structure and the best ways to determine and capture it. Here, we reconsider the concept of enterotypes, in the context of the vastly increased amounts of available data. We propose a refined framework in which the different types should be thought of as weak attractors in compositional space and we try to implement an approach to determining which attractor a sample is closest to. To this end, we train a classifier on a reference dataset to assign membership to new samples. This way, enterotypes assignment is no longer dataset dependent and effects due to biased sampling are minimized. Using a model in which we assume the existence of three enterotypes characterized by the same driver genera, as originally postulated, we show the relevance of this stratification and propose it to be used in a clinical setting as a potential marker for disease development. Moreover, we believe that these attractors underline different rules of community assembly and we recommend they be accounted for when analyzing gut microbiome samples. While enterotypes describe structure in the community at genus level, metagenomic sequencing can in principle achieve single-nucleotide resolution, allowing us to identify single nucleotide polymorphisms (SNPs) and other genomic variants in the gut microbiome. Analysis methodology for this level of resolution has only recently been developed and little exploration has been done to date. Assessing SNPs in a large, multinational cohort, we discovered that the landscape of genomic variation seems highly structured even beyond species resolution, indicating that clearly distinguishable subspecies are prevalent among gut microbes. In several cases, these subspecies exhibit geo-stratification, with some subspecies only found in the Chinese population. Generally however, they present only minor dispersion limitations and are seen across most of our study populations. Within one individual, one subspecies is commonly found to dominate and only rarely are several subspecies observed to co-occur in the same ecosystem. Analysis of longitudinal data indicates that the dominant subspecies remains stable over periods of more than three years. When interrogating their functional properties we find many differences, with specific ones appearing relevant to the host. For example, we identify a subspecies of E. rectale that is lacking the flagellum operon and find its presence to be significantly associated with lower body mass index and lower insulin resistance of their hosts; it also correlates with higher microbial community diversity. These associations could not be seen at the species level (where multiple subspecies are convoluted), which illustrates the importance of this increased resolution for a more comprehensive understanding of microbial interactions within the microbiome and with the host. Taken together, our results provide a rigorous basis for performing comparative metagenomics of the human gut, encompassing recommendations for both experimental sample processing and computational analysis. We furthermore refine the concept of community stratification into enterotypes, develop a reference-based approach for enterotype assignment and provide compelling evidence for their relevance. Lastly, by harnessing the full resolution of metagenomics, we discover a highly structured genomic variation landscape below the microbial species level and identify common subspecies of the human gut microbiome. By developing these high-precision metagenomics analysis tools, we thus hope to contribute to a greatly improved understanding of the properties and dynamics of the human gut microbiome.},
  subject      = {Mensch},
  language  = {en}
}
@phdthesis{Frey2011,
  author    = {Frey, Monika},
  title     = {Effects and mechanisms of a putative human pheromone},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-72292},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {There is evidence that pheromones are communicative signals in animals. However, the existence and function of human pheromones are still under discussion. During the last years several substances have been labeled as putative human pheromones and especially 4,16-androstadien-3-one (androstadienone), found in male and female sweat, became subject of intense investigation. In contrast to common odors androstadienone presumably modulates human physiological and psychological reactions. Data suggest that androstadienone might influence the processing of visual cues, specifically faces or affective stimuli, via projections from the fusiform gyrus and the amygdala. Moreover, attentional processes may be modulated, which is supported by explicit and implicit behavioral data. This thesis includes three experimental studies examining effects of androstadienone exposure on behavioral and cortical reactions to visual and emotional stimuli. The main hypotheses were that androstadienone might influence human behavior to and perception of visual cues. The first study sought to clarify androstadienone effects on attention-related reactions as well as on behavioral tendencies. Motoric approach-avoidance reactions in response to happy and angry facial expressions were investigated in 30 women and 32 men. Participants either inhaled androstadienone or a control solution, without knowing the real content, while performing the following task: they had to push away or to pull towards them a joystick as fast as possible in reaction to either an angry or a happy cartoon face, which was presented on a computer screen. Results showed that androstadienone modulated the participant´s task performance by accelerating the reaction speed compared to the control compound. Faster reactions were observed particularly when reacting to angry faces but not when reacting to happy faces. This might be explained by the finding that human body odors, the source of androstadienone, were found to activate the human fear system, i.e. modulating fear-related attentional processes. Therefore, the quicker reaction towards angry faces with exposure to androstadienone could be due to an enhanced allocation of attentional resources towards fear-related cues like angry faces. Results also showed that androstadienone enhanced men´s approach tendency towards faces independent of emotional expressions. This observation might be explained by androstadienone´s former shown ability to improve attractiveness ratings of other persons. In this regard, the endogenous odor might enhance evaluations of faces in men and, thus, might improve their willingness to approach social stimuli. In contrast to men, women already showed in the control condition higher approach tendency towards faces. Therefore, androstadienone might rather maintain than enhance the approach score in women. In the second study event-related brain potentials (ERPs) triggered by social and non-social visual stimuli were investigated by means of electroencephalography. In a double-blind between-subjects design 51 women participated. Twenty-eight women inhaled androstadienone, whereas 23 women inhaled a control solution. Four different picture categories, i.e. real faces, pictures with couples, pictures with social and non-social scenes, each including three different valence categories, i.e. positive, negative and neutral, should clarify the stimulus type or context androstadienone is acting on. The androstadienone compared to the control odor did not influence brain responses significantly. Explorative analyses, however, suggested that androstadienone influences the processing of faces. While in the control group angry faces elicited larger P300 amplitudes than happy faces, the androstadienone group showed similar P300 amplitudes concerning all emotional expressions. This observation tentatively indicates that the endogenous odor might indeed affect the neuronal responses to emotional facial stimuli, especially late components reflecting evaluative processes. However, this observation has to be verified and further investigated, in particular whether androstadienone caused reduced responses to angry faces or enhanced responses to happy faces. The third study investigated androstadienone effects on face processing especially in men. ERPs elicited by happy, angry and neutral cartoon faces, which were presented on a computer screen, were measured while 16 men, not knowing the applicated odor, inhaled either androstadienone or a control solution. Exposure to androstadienone significantly increased later neuronal responses, the P300 amplitude. This belated component of the ERP reflects attention allocation and evaluative processes towards important stimuli. Therefore, androstadienone might facilitate central nervous face processing by enhancing attention towards these stimuli. In sum, the current results corroborate the notion of androstadienone as an active social chemosignal. In minute amounts and not detectable as an odor it influenced cortical and motoric reactions. Therefore, it might be concluded that androstadienone indeed affects cognitive functions like attentional processes and in turn affects our behavior. The current results further support the notion that androstadienone acts like a human modulator pheromone, namely modulating ongoing behavior or a psychological reaction to a particular context, changing stimulus sensitivity, salience and sensory-motor integration. However, these conclusions remain tentative until further replication takes place, best in ecologically valid environments. Furthermore, one has to keep in mind that the current studies could not replicate several previous findings and could not verify some hypotheses assuming communicative effects of androstadienone. Thus, the main assumption of this thesis that androstadienone is an active chemosignal is still challenged. Also, whether the term "pheromone" is indeed suitable to label androstadienone remains open.},
  subject      = {Pheromon},
  language  = {en}
}