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  1. Book ; Online: Systems Biology and the Challenge of Deciphering the Metabolic Mechanisms Underlying Cancer

    Diener, Christian / Resendis-Antonio, Osbaldo

    2017  

    Abstract: Since the discovery of the Warburg effect in the 1920s cancer has been tightly associated with the genetic and metabolic state of the cell. One of the hallmarks of cancer is the alteration of the cellular metabolism in order to promote proliferation and ... ...

    Abstract Since the discovery of the Warburg effect in the 1920s cancer has been tightly associated with the genetic and metabolic state of the cell. One of the hallmarks of cancer is the alteration of the cellular metabolism in order to promote proliferation and undermine cellular defense mechanisms such as apoptosis or detection by the immune system. However, the strategies by which this is achieved in different cancers and sometimes even in different patients of the same cancer is very heterogeneous, which hinders the design of general treatment options.Recently, there has been an ongoing effort to study this phenomenon on a genomic scale in order to understand the causality underlying the disease. Hence, current "omics" technologies have contributed to identify and monitor different biological pieces at different biological levels, such as genes, proteins or metabolites. These technological capacities have provided us with vast amounts of clinical data where a single patient may often give rise to various tissue samples, each of them being characterized in detail by genomescale data on the sequence, expression, proteome and metabolome level. Data with such detail poses the imminent problem of extracting meaningful interpretations and translating them into specific treatment options. To this purpose, Systems Biology provides a set of promising computational tools in order to decipher the mechanisms driving a healthy cell's metabolism into a cancerous one. However, this enterprise requires bridging the gap between large data resources, mathematical analysis and modeling specifically designed to work with the available data. This is by no means trivial and requires high levels of communication and adaptation between the experimental and theoretical side of research
    Keywords Science (General) ; Physiology ; Biology (General)
    Size 1 electronic resource (142 p.)
    Publisher Frontiers Media SA
    Document type Book ; Online
    Note English ; Open Access
    HBZ-ID HT020099567
    ISBN 9782889453337 ; 2889453332
    Database ZB MED Catalogue: Medicine, Health, Nutrition, Environment, Agriculture

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  2. Article: Metagenomic estimation of dietary intake from human stool.

    Diener, Christian / Gibbons, Sean M

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Dietary intake is tightly coupled to gut microbiota composition, human metabolism, and to the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually quantified using dietary questionnaires, which tend to focus on broad ...

    Abstract Dietary intake is tightly coupled to gut microbiota composition, human metabolism, and to the incidence of virtually all major chronic diseases. Dietary and nutrient intake are usually quantified using dietary questionnaires, which tend to focus on broad food categories, suffer from self-reporting biases, and require strong compliance from study participants. Here, we present MEDI (Metagenomic Estimation of Dietary Intake): a method for quantifying dietary intake using food-derived DNA in stool metagenomes. We show that food items can be accurately detected in metagenomic shotgun sequencing data, even when present at low abundances (>10 reads). Furthermore, we show how dietary intake, in terms of DNA abundance from specific organisms, can be converted into a detailed metabolic representation of nutrient intake. MEDI could identify the onset of solid food consumption in infants and it accurately predicted food questionnaire responses in an adult population. Additionally, we were able to identify specific dietary features associated with metabolic syndrome in a large clinical cohort, providing a proof-of-concept for detailed quantification of individual-specific dietary patterns without the need for questionnaires.
    Language English
    Publishing date 2024-02-06
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.02.02.578701
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: More is Different: Metabolic Modeling of Diverse Microbial Communities.

    Diener, Christian / Gibbons, Sean M

    mSystems

    2023  Volume 8, Issue 2, Page(s) e0127022

    Abstract: Microbial consortia drive essential processes, ranging from nitrogen fixation in soils to providing metabolic breakdown products to animal hosts. However, it is challenging to translate the composition of microbial consortia into their emergent ... ...

    Abstract Microbial consortia drive essential processes, ranging from nitrogen fixation in soils to providing metabolic breakdown products to animal hosts. However, it is challenging to translate the composition of microbial consortia into their emergent functional capacities. Community-scale metabolic models hold the potential to simulate the outputs of complex microbial communities in a given environmental context, but there is currently no consensus for what the fitness function of an entire community should look like in the presence of ecological interactions and whether community-wide growth operates close to a maximum. Transitioning from single-taxon genome-scale metabolic models to multitaxon models implies a growth cone without a well-specified growth rate solution for individual taxa. Here, we argue that dynamic approaches naturally overcome these limitations, but they come at the cost of being computationally expensive. Furthermore, we show how two nondynamic, steady-state approaches approximate dynamic trajectories and pick ecologically relevant solutions from the community growth cone with improved computational scalability.
    MeSH term(s) Models, Biological ; Microbial Consortia
    Language English
    Publishing date 2023-03-21
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ISSN 2379-5077
    ISSN (online) 2379-5077
    DOI 10.1128/msystems.01270-22
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: Coarse graining the human gut microbiome.

    Diener, Christian / Gibbons, Sean M

    Cell host & microbe

    2023  Volume 31, Issue 7, Page(s) 1076–1078

    Abstract: The composition of the human gut microbiome is heterogeneous across people. However, if you squint, co-abundant microbial genera emerge, accounting for much of this ecological variability. In this issue of Cell Host & Microbe, Frioux et al. provide a ... ...

    Abstract The composition of the human gut microbiome is heterogeneous across people. However, if you squint, co-abundant microbial genera emerge, accounting for much of this ecological variability. In this issue of Cell Host & Microbe, Frioux et al. provide a workflow for identifying these bacterial guilds, or "enterosignatures."
    MeSH term(s) Humans ; Gastrointestinal Microbiome ; Microbiota ; Bacteria/genetics ; RNA, Ribosomal, 16S/genetics ; RNA, Bacterial
    Chemical Substances RNA, Ribosomal, 16S ; RNA, Bacterial
    Language English
    Publishing date 2023-11-21
    Publishing country United States
    Document type Journal Article
    ZDB-ID 2278004-X
    ISSN 1934-6069 ; 1931-3128
    ISSN (online) 1934-6069
    ISSN 1931-3128
    DOI 10.1016/j.chom.2023.06.001
    Database MEDical Literature Analysis and Retrieval System OnLINE

    Full text online

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    In stock of ZB MED Cologne/Königswinter

    Zs.A 6578: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  5. Article: Personalized

    Carr, Alex / Baliga, Nitin S / Diener, Christian / Gibbons, Sean M

    bioRxiv : the preprint server for biology

    2024  

    Abstract: Clostridioides ... ...

    Abstract Clostridioides difficile
    Language English
    Publishing date 2024-01-04
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.04.28.538771
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Elucidating human gut microbiota interactions that robustly inhibit diverse

    Sulaiman, Jordy Evan / Thompson, Jaron / Qian, Yili / Vivas, Eugenio I / Diener, Christian / Gibbons, Sean M / Safdar, Nasia / Venturelli, Ophelia S

    bioRxiv : the preprint server for biology

    2024  

    Abstract: The human gut ... ...

    Abstract The human gut pathogen
    Language English
    Publishing date 2024-04-17
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2024.04.13.589383
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article ; Online: Meta-analysis of the human upper respiratory tract microbiome reveals robust taxonomic associations with health and disease.

    Quinn-Bohmann, Nick / Freixas-Coutin, Jose A / Seo, Jin / Simmons, Ruth / Diener, Christian / Gibbons, Sean M

    BMC biology

    2024  Volume 22, Issue 1, Page(s) 93

    Abstract: Background: The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification ... ...

    Abstract Background: The human upper respiratory tract (URT) microbiome, like the gut microbiome, varies across individuals and between health and disease states. However, study-to-study heterogeneity in reported case-control results has made the identification of consistent and generalizable URT-disease associations difficult.
    Results: In order to address this issue, we assembled 26 independent 16S rRNA gene amplicon sequencing data sets from case-control URT studies, with approximately 2-3 studies per respiratory condition and ten distinct conditions covering common chronic and acute respiratory diseases. We leveraged the healthy control data across studies to investigate URT associations with age, sex, and geographic location, in order to isolate these associations from health and disease states.
    Conclusions: We found several robust genus-level associations, across multiple independent studies, with either health or disease status. We identified disease associations specific to a particular respiratory condition and associations general to all conditions. Ultimately, we reveal robust associations between the URT microbiome, health, and disease, which hold across multiple studies and can help guide follow-up work on potential URT microbiome diagnostics and therapeutics.
    MeSH term(s) Humans ; Microbiota/genetics ; RNA, Ribosomal, 16S/genetics ; Respiratory System/microbiology ; Respiratory Tract Diseases/microbiology ; Case-Control Studies ; Male ; Bacteria/genetics ; Bacteria/classification ; Bacteria/isolation & purification ; Female
    Chemical Substances RNA, Ribosomal, 16S
    Language English
    Publishing date 2024-04-23
    Publishing country England
    Document type Journal Article ; Meta-Analysis ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 2133020-7
    ISSN 1741-7007 ; 1741-7007
    ISSN (online) 1741-7007
    ISSN 1741-7007
    DOI 10.1186/s12915-024-01887-0
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Island biogeography theory and the gut: why taller people tend to harbor more diverse gut microbiomes.

    Sarmiento, Katherine Ramos / Carr, Alex / Diener, Christian / Locey, Kenneth J / Gibbons, Sean M

    bioRxiv : the preprint server for biology

    2023  

    Abstract: Prior work has shown a positive scaling relationship between vertebrate body size and gut microbiome alpha-diversity. This observation mirrors commonly observed species area relationships (SAR) in many other ecosystems. Here, we show a similar scaling ... ...

    Abstract Prior work has shown a positive scaling relationship between vertebrate body size and gut microbiome alpha-diversity. This observation mirrors commonly observed species area relationships (SAR) in many other ecosystems. Here, we show a similar scaling relationship between human height and gut microbiome alpha-diversity across two large, independent cohorts, controlling for a wide range of relevant covariates, such as body mass index, age, sex, and bowel movement frequency. Island Biogeography Theory (IBT), which predicts that larger islands tend to harbor greater species diversity through neutral demographic processes, provides a simple mechanism for these positive SARs. Using an individual-based model of IBT adapted to the gut, we demonstrate that increasing the length of a flow-through ecosystem is associated with increased species diversity. We delve into the possible clinical implications of these SARs in the American Gut Cohort. Consistent with prior observations that lower alpha-diversity is a risk factor for
    Language English
    Publishing date 2023-08-12
    Publishing country United States
    Document type Preprint
    DOI 10.1101/2023.08.08.552554
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: Growth phase estimation for abundant bacterial populations sampled longitudinally from human stool metagenomes.

    Lim, Joe J / Diener, Christian / Wilson, James / Valenzuela, Jacob J / Baliga, Nitin S / Gibbons, Sean M

    Nature communications

    2023  Volume 14, Issue 1, Page(s) 5682

    Abstract: Longitudinal sampling of the stool has yielded important insights into the ecological dynamics of the human gut microbiome. However, human stool samples are available approximately once per day, while commensal population doubling times are likely on the ...

    Abstract Longitudinal sampling of the stool has yielded important insights into the ecological dynamics of the human gut microbiome. However, human stool samples are available approximately once per day, while commensal population doubling times are likely on the order of minutes-to-hours. Despite this mismatch in timescales, much of the prior work on human gut microbiome time series modeling has assumed that day-to-day fluctuations in taxon abundances are related to population growth or death rates, which is likely not the case. Here, we propose an alternative model of the human gut as a stationary system, where population dynamics occur internally and the bacterial population sizes measured in a bolus of stool represent a steady-state endpoint of these dynamics. We formalize this idea as stochastic logistic growth. We show how this model provides a path toward estimating the growth phases of gut bacterial populations in situ. We validate our model predictions using an in vitro Escherichia coli growth experiment. Finally, we show how this method can be applied to densely-sampled human stool metagenomic time series data. We discuss how these growth phase estimates may be used to better inform metabolic modeling in flow-through ecosystems, like animal guts or industrial bioreactors.
    MeSH term(s) Animals ; Humans ; Metagenome ; Ecosystem ; Feces ; Body Fluids ; Population Density ; Escherichia coli/genetics
    Language English
    Publishing date 2023-09-14
    Publishing country England
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, Non-P.H.S.
    ZDB-ID 2553671-0
    ISSN 2041-1723 ; 2041-1723
    ISSN (online) 2041-1723
    ISSN 2041-1723
    DOI 10.1038/s41467-023-41424-1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article: MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota.

    Diener, Christian / Gibbons, Sean M / Resendis-Antonio, Osbaldo

    mSystems

    2020  Volume 5, Issue 1

    Abstract: Compositional changes in the gut microbiota have been associated with a variety of medical conditions such as obesity, Crohn's disease, and diabetes. However, connecting microbial community composition to ecosystem function remains a challenge. Here, we ... ...

    Abstract Compositional changes in the gut microbiota have been associated with a variety of medical conditions such as obesity, Crohn's disease, and diabetes. However, connecting microbial community composition to ecosystem function remains a challenge. Here, we introduce MICOM, a customizable metabolic model of the human gut microbiome. By using a heuristic optimization approach based on L2 regularization, we were able to obtain a unique set of realistic growth rates that corresponded well with observed replication rates. We integrated adjustable dietary and taxon abundance constraints to generate personalized metabolic models for individual metagenomic samples. We applied MICOM to a balanced cohort of metagenomes from 186 people, including a metabolically healthy population and individuals with type 1 and type 2 diabetes. Model results showed that individual bacterial genera maintained conserved niche structures across humans, while the community-level production of short-chain fatty acids (SCFAs) was heterogeneous and highly individual specific. Model output revealed complex cross-feeding interactions that would be difficult to measure
    Language English
    Publishing date 2020-01-21
    Publishing country United States
    Document type Journal Article
    ISSN 2379-5077
    ISSN 2379-5077
    DOI 10.1128/mSystems.00606-19
    Database MEDical Literature Analysis and Retrieval System OnLINE

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