Filters








661 Hits in 4.8 sec

Predicted Relative Metabolomic Turnover (PRMT): determining metabolic turnover from a coastal marine metagenomic dataset

Peter E Larsen, Frank R Collart, Dawn Field, Folker Meyer, Kevin P Keegan, Christopher S Henry, John McGrath, John Quinn, Jack A Gilbert
2011 Microbial Informatics and Experimentation  
Our analysis of metagenomic data from a timeseries study in the Western English Channel demonstrated considerable correlations between predicted relative metabolic turnover and seasonal changes in abundance  ...  Results: We propose a methodology, Predicted Relative Metabolic Turnover (PRMT) that defines and enables exploration of metabolite-space inferred from the metagenome.  ...  Sequence data was produced with a grant from the Natural Environmental Research Council (NERC -NE/F00138X/1).  ... 
doi:10.1186/2042-5783-1-4 pmid:22587810 pmcid:PMC3348665 fatcat:bntcgqkqprg5rkgnlztnyl5yiq

Towards predicting the environmental metabolome from metagenomics with a mechanistic model

Daniel R. Garza, Marcel C. van Verk, Martijn A. Huynen, Bas E. Dutilh
2018 Nature Microbiology  
Here, we bridge this gap by predicting the environmental metabolome directly from the metagenome.  ...  For this purpose, we adjusted an existing algorithm, named Predicted Relative Metabolic Turnover (PRMT) score 10,25 , that predicts the metabolic turnover in one sample relative to another and applied  ...  Berkers (Utrecht University) for insights regarding the annotation of untargeted metabolome datasets and the CMBI Comics Group for fruitful discussions.  ... 
doi:10.1038/s41564-018-0124-8 pmid:29531366 fatcat:hw5ixnyzn5fkdbyeookf354dei

Systems-based approaches to unravel multi-species microbial community functioning

Florence Abram
2015 Computational and Structural Biotechnology Journal  
Some of the most transformative discoveries promising to enable the resolution of this century's grand societal challenges will most likely arise from environmental science and particularly environmental  ...  Understanding how microbes interact in situ, and how microbial communities respond to environmental changes remains an enormous challenge for science.  ...  Predictive modelling approaches, such as PRMT (Predictive Relative Metabolic Turnover; 33) have been recently designed to explore multi-species community functioning in the context of metagenomics.  ... 
doi:10.1016/j.csbj.2014.11.009 pmid:25750697 pmcid:PMC4348430 fatcat:6gkn2idw75gcngr5q2h7xsmr64

Computational Approaches for Integrative Analysis of the Metabolome and Microbiome

Jasmine Chong, Jianguo Xia
2017 Metabolites  
In this review, we provide an overview of different computational approaches that have been used in recent years for integrative analysis of metabolome and microbiome data, ranging from statistical correlation  ...  In this context, metabolomics is increasingly applied to complement sequencing-based approaches (marker genes or shotgun metagenomics) to enable resolution of microbiome-conferred functionalities associated  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/metabo7040062 pmid:29156542 pmcid:PMC5746742 fatcat:j25rzjkxxbgzzkx6dl3t3bqoui

Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

Cecilia Noecker, Alexander Eng, Sujatha Srinivasan, Casey M. Theriot, Vincent B. Young, Janet K. Jansson, David N. Fredricks, Elhanan Borenstein, Laura M. Sanchez
2016 mSystems  
Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism  ...  whether these predictions agree with measured metabolomic profiles.  ...  We adapted the predicted relative metabolomic turnover (PRMT) method developed by Larsen et al.  ... 
doi:10.1128/msystems.00013-15 pmid:27239563 pmcid:PMC4883586 fatcat:asifyutdyvhqzd7pdk6b3p56iy

Metabolome of human gut microbiome is predictive of host dysbiosis

Peter E. Larsen, Yang Dai
2015 GigaScience  
Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed  ...  The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human  ...  This contribution originates in part from the "Environment Sensing and Response" Scientific Focus Area (SFA) program at Argonne National Laboratory.  ... 
doi:10.1186/s13742-015-0084-3 pmid:26380076 pmcid:PMC4570295 fatcat:gl6x3giv5rhhtfqj3krsffzv7i

Predictive metabolomic profiling of microbial communities using amplicon or metagenomic sequences

Himel Mallick, Eric A. Franzosa, Lauren J. Mclver, Soumya Banerjee, Alexandra Sirota-Madi, Aleksandar D. Kostic, Clary B. Clish, Hera Vlamakis, Ramnik J. Xavier, Curtis Huttenhower
2019 Nature Communications  
Here, we describe a computational approach to predict potentially unobserved metabolites in new microbial communities, given a model trained on paired metabolomes and metagenomes from the environment of  ...  Our results thus demonstrate that this 'predictive metabolomic' approach can aid in experimental design and provide useful insights into the thousands of community profiles for which only metagenomes are  ...  Acknowledgements We thank Tiffany Poon for project management and Heather Kang for editorial assistance and feedback on the manuscript. This work was funded in part by the US National Science  ... 
doi:10.1038/s41467-019-10927-1 pmid:31316056 pmcid:PMC6637180 fatcat:zv2cv234erejjbhyv26poz4wbm

A Comparative Evaluation of Tools to Predict Metabolite Profiles From Microbiome Sequencing Data

Xiaochen Yin, Tomer Altman, Erica Rutherford, Kiana A. West, Yonggan Wu, Jinlyung Choi, Paul L. Beck, Gilaad G. Kaplan, Karim Dabbagh, Todd Z. DeSantis, Shoko Iwai
2020 Frontiers in Microbiology  
With the pre-trained model on over 900 microbiome-metabolome paired samples, the ML approach yielded the most accurate predictions (i.e., highest F1 scores) of metabolite occurrences in the human gut and  ...  Our findings demonstrate the possibility of predicting metabolites from microbiome sequencing data, while highlighting certain limitations in detecting differential metabolites, and provide a framework  ...  A method called predicted relative metabolomic turnover (PRMT) was used to predict metabolites from a coastal marine metagenomics dataset, and the predicted metabolites correlated strongly with environmental  ... 
doi:10.3389/fmicb.2020.595910 pmid:33343536 pmcid:PMC7746778 fatcat:iw7kxszyefad5enuhb2wpp27mm

"Omics" Technologies for the Study of Soil Carbon Stabilization: A Review

David P. Overy, Madison A. Bell, Jemaneh Habtewold, Bobbi L. Helgason, Edward G. Gregorich
2021 Frontiers in Environmental Science  
metabolomics).  ...  Linking the data derived from these various platforms will enhance our knowledge of structure and function of the microbial communities involved in soil carbon cycling and stabilization.  ...  In comparison to metagenomics studies, there are relatively few metatranscriptomics studies in the literature that investigate soil carbon cycling in agricultural soils.  ... 
doi:10.3389/fenvs.2021.617952 doaj:45a9f0daa96c449294da492bd03ec46d fatcat:tn6zl3xlknfx3bamxd3cvunxvu

Synthesizing Systems Biology Knowledge from Omics Using Genome-Scale Models

Sanjeev Dahal, James T. Yurkovich, Hao Xu, Bernhard O. Palsson, Laurence Yang
2020 Proteomics  
The ability to interpret omics in the context of biological systems has yielded important findings for human health, environmental biotechnology, bioenergy, and metabolic engineering.  ...  In principle, the combination of multiple omic data types can provide an integrated view of the entire biological system. This integration requires appropriate models in a systems biology approach.  ...  .), the Institute for Systems  ... 
doi:10.1002/pmic.201900282 pmid:32579720 fatcat:h3euvl3j5vggjmbh5buaspz4uy

Space-type radiation induces multimodal responses in the mouse gut microbiome and metabolome

David Casero, Kirandeep Gill, Vijayalakshmi Sridharan, Igor Koturbash, Gregory Nelson, Martin Hauer-Jensen, Marjan Boerma, Jonathan Braun, Amrita K. Cheema
2017 Microbiome  
These were accompanied by changes in the abundance of multiple metabolites, which were related to the enzymatic activity of the predicted metagenome by means of metabolic network modeling.  ...  The observed radiation-induced changes in microbiota diversity and composition were analyzed at the functional level.  ...  The authors would also like to acknowledge the Metabolomics Shared Resource in Georgetown University (Washington DC, USA) partially supported by NIH/NCI/CCSG grant P30-CA051008.  ... 
doi:10.1186/s40168-017-0325-z pmid:28821301 pmcid:PMC5563039 fatcat:zfcmuxs27rgbpegy5jsj56zqpy

Omics for understanding microbial functional dynamics

Janet K. Jansson, Josh D. Neufeld, Mary Ann Moran, Jack A Gilbert
2011 Environmental Microbiology  
relative changes in the turnover of specific metabolites.  ...  Once we can use comparative metagenomics (i.e. across time/space or in response to a known manipulation) to explore the changing metabolic potential of a microbial community, it may be possible to predict  ... 
doi:10.1111/j.1462-2920.2011.02518.x pmid:21651688 fatcat:b4es4hnkhnestdgyvjeq7bdsdq

Systems Biology and Multi-Omics Integration: Viewpoints from the Metabolomics Research Community

Farhana R. Pinu, David J. Beale, Amy M. Paten, Konstantinos Kouremenos, Sanjay Swarup, Horst J. Schirra, David Wishart
2019 Metabolites  
The use of multiple omics techniques (i.e., genomics, transcriptomics, proteomics, and metabolomics) is becoming increasingly popular in all facets of life science.  ...  integration that was held at the recent 'Australian and New Zealand Metabolomics Conference' (ANZMET 2018) in Auckland, New Zealand (Sept. 2018).  ...  Acknowledgments: The authors would like to thank the organizing committee of ANZMET 2018. Conflicts of Interest: The authors declare no conflict of interest. Metabolites 2019, 9, 76  ... 
doi:10.3390/metabo9040076 pmid:31003499 pmcid:PMC6523452 fatcat:deiwu7rgpnb3tfr7glbewoyar4

Satellite remote sensing data can be used to model marine microbial metabolite turnover

Peter E Larsen, Nicole Scott, Anton F Post, Dawn Field, Rob Knight, Yuki Hamada, Jack A Gilbert
2014 The ISME Journal  
The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value o10 À 6 ) with their observed relative abundance in sequenced metagenomes.  ...  Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites.  ...  We also thank the anonymous reviewers from multiple journals who significantly helped us to revise and refine this work to improve the clarity and impact.  ... 
doi:10.1038/ismej.2014.107 pmid:25072414 pmcid:PMC4274419 fatcat:uoiq7pe2wrhy3gg5brocpz6rlq

The Newest "Omics"—Metagenomics and Metabolomics—Enter the Battle against the Neglected Tropical Diseases

Geoffrey A. Preidis, Peter J. Hotez, Aaron R. Jex
2015 PLoS Neglected Tropical Diseases  
The metagenomics and metabolomics eras have dawned on the neglected tropical diseases, bringing new promise for the development of diagnostics, therapeutics, and vaccines.  ...  Similarly, Fasciola hepatica infection in rats induced metabolic changes in areas as remote from the liver as brain tissue.  ...  In parallel, the field of metabolomics emerged as the systematic, nonbiased analysis of all low-molecular-weight small molecules, or metabolites, produced by a system in response to an environmental stimulus  ... 
doi:10.1371/journal.pntd.0003382 pmid:25675250 pmcid:PMC4326130 fatcat:hlygcfucajfn7nnrobvk44xmre
« Previous Showing results 1 — 15 out of 661 results