Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort).
Sofia K. ForslundRima ChakarounMaria Zimmermann‐KogadeevaLajos MarkóJudith Aron‐WisnewskyTrine NielsenTill Birkner
0
Citation
0
Reference
10
Related Paper
Abstract:
*******************************************************************MetaDrugs workflow
******************************************************************* Data analysis pipeline for investigating drug-host-microbiome relationships in cardiometabolic disease (MetaCardis cohort). For questions and requests, please contact:
Sofia K. Forslund (sofia.forslund@mdc-berlin.de)
and Till Birkner (till.birkner@mdc-berlin.de) *******************************************************************
Contents:
-------------------------------------------------------------------
Data files:
metadata.tar.gz - archived cohort metadata files
input_features.tar.gz - archived preprocessed serum and urine metabolome and gut microbiome features
output_complete.tar.gz - archived example analysis output files for each of the input feature file
output_rerun.tar.gz - archived empty directory for generating test output files as described in this document
-------------------------------------------------------------------
Text files:
archived in feature_names.tar.gz:
atcs_names - full names for atcs drug compounds
contrast_names - full names for disease comparison groups
file_names - brief description of the files in input_features folder
gmm_names - full names of GMM modules
kegg_names - full names of KEGG modules
ko_names - full names of KO modules
metadata_names - full names of metadata features
mOTU_names - species names for metagenomics data
taxon_names - taxon names for metagenomics data
-------------------------------------------------------------------
Scripts:
-------------------------------------------------------------------
runFrame.r - main wrapper script envoking the analysis pipeline
-------------------------------------------------------------------
runFrame_rel_comb.r - script calculating drug combination effects
runFrame_rel.r - script calculating dosage effects
testCombPresenceSeparate.r - testing of significant drug combination effects beyond single drug effects
testDosagePresenceSeparate.pl - testing of significant drug dosage effects beyond single drug effects
testDosagePresenceSeparateNegative.pl - testing of unique drug dosage effects beyond single drug effects
-------------------------------------------------------------------
prettifyResults_uncollapsed.pl - wrapper scripts to create and format a single analysis output file
makeTables.r - wrapper script to make excel tables with analysis results
-------------------------------------------------------------------
Example output file:
-------------------------------------------------------------------
output_all_formatted_noc_uncollapsed_complete.tsv - contains all disease-drug-host-microbiome feature analysis results in one place.
*******************************************************************
Topics:
We are in the midst of a revolution of knowledge regarding the human microbiome. The revolution comes from the explosion of knowledge on the role of our microbiomes in systemic disease, overall well-being, behavior, and many other health states that we previously would have never thought of microbiomes driving these complex states. Of all the complex microbiomes across the body, substantial evidence has shown that the gut microbiome appears to be the pivotal microbiome in the body. While there was always some sense of interactions between the microbiomes of the body, only recently has evidence built a fascinating picture of two- and three-way interactions between our microbiomes and organ systems. Now we are obtaining exciting data showing how one microbiome—the gut microbiome—has a definitive effect on the composition and metabolic activity of the skin microbiome. We are in a new era of discovery on how important our microbiomes are to our health and vitality. As we move into a new decade, more interactions and levels of regulation are sure to be discovered.
Gut microbiome
Vitality
Cite
Citations (1)
Living ‘things’ coexist with microorganisms, known as the microbiota/microbiome that provides essential physiological functions to its host. Despite this reliance, the microbiome is malleable and can be altered by several factors including birth‐mode, age, antibiotics, nutrition, and disease. In this minireview, we consider how other microbiomes and microbial communities impact the host microbiome and the host through the concept of microbiome collisions (initial exposures) and interactions. Interactions include changes in host microbiome composition and functionality and/or host responses. Understanding the impact of other microbiomes and microbial communities on the microbiome and host are important considering the decline in human microbiota diversity in the developed world – paralleled by the surge of non‐communicable, inflammatory‐based diseases. Thus, surrounding ourselves with rich and diverse beneficial microbiomes and microbial communities to collide and interact with should help to diminish the loss in microbial diversity and protect from certain diseases. In the same vein, our microbiomes not only influence our health but potentially the health of those close to us. We also consider strategies for enhanced host microbiome collisions and interactions through the surrounding environment that ensure increased microbiome diversity and functionality contributing to enhanced symbiotic return to the host in terms of health benefit.
Cite
Citations (6)
The process of microbiome development arguably begins before birth. Vertical transmission of bacteria from the mother to the infant is a keystone event in microbiome development. Subsequent to birth, the developing microbiome is vulnerable to influence from a wide range of factors. Additionally, the microbiome can influence the health and development of the host infant. This intricate interaction of the gastrointestinal microbiome and the host has been described as both symbiotic and dysbiotic. Defining these terms, a symbiotic microbiome is where the microbiome and host provide mutual benefit to each other. A pathogenic microbiome, or more precisely a gastrointestinal microbiome associated with disease, is increasing described as dysbiotic. This review seeks to investigate the factors that contribute to evolving a disease-causing or ‘dysbiotic’ microbiome. This review covers the development of the gastrointestinal microbiome in infants, the interaction of the microbiome with the host, and its contribution to host immunity and investigates specific features of the gastrointestinal microbiome that are associated with disease.
Gut microbiome
Dysbiosis
Intestinal Microbiome
Cite
Citations (0)
Abstract Plant-associated microorganisms have significant impacts on plant biology, ecology, and evolution. Although several studies have examined the factors driving variations in plant microbiomes, the mechanisms underlying the assembly of the plant microbiome are still poorly understood. In this study, we used gnotobiotic plants to test (i) whether seedlings create a selective environment and drive the assembly of root and leaf microbiomes through deterministic or stochastic processes, and (ii) whether seedlings structure the microbiome that is transferred through seeds using deterministic processes and whether this pattern changes when seedlings are exposed to the environmental microbiome. Our results show that the microbiome of gnotobiotic plants (i.e., inherited through seeds) is not under the selective influence of the host plant but changes quickly when plants are exposed to soil microbiomes. Within one week, plants were able to select microorganisms from the inocula, assemble the root microbiome, and assemble the shoot microbiome. This study supports the hypothesis that plants at early developmental stages might exert strong selective activity on their microbiomes and contribute to clarifying the mechanisms of plant microbiome assembly.
Cite
Citations (0)
Cite
Citations (1)
We introduce two concepts to quantify the novelty of a microbiome. The first, the microbiome novelty score (MNS), allows identification of microbiomes that are especially different from what is already sequenced. The second, the microbiome attention score (MAS), allows identification of microbiomes that have many close neighbors, implying that considerable scientific attention is devoted to their study. By computing a microbiome focus index based on the MNS and MAS, we objectively track and compare the novelty and attention scores of individual microbiome samples and projects over time and predict future trends in the field; i.e., we work toward yielding fundamentally new microbiomes rather than filling in the details. Therefore, MNS, MAS, and MFI can serve as “alt-metrics” for evaluating a microbiome project or prospective developments in the microbiome field, both of which are done in the context of existing microbiome big data.
Human Microbiome Project
Amplicon sequencing
Identification
Cite
Citations (34)
A search-based strategy is useful for large-scale mining of microbiome data sets, such as a bird’s-eye view of the microbiome data space and disease diagnosis via microbiome big data. Here, we introduce Microbiome Search Engine 2 (MSE 2), a microbiome database platform for searching query microbiomes against the existing microbiome data sets on the basis of their similarity in taxonomic structure or functional profile.
Cite
Citations (19)
Dysbiosis of the microbiome has been associated with type II diabetes mellitus, obesity, inflammatory bowel disorders, and colorectal cancer, and recently, the Human Microbiome Project Consortium has helped to define a healthy microbiome. Now research has begun to investigate how the microbiome is established, and in this article, we will discuss the maternal influences on the establishment of the microbiome. The inoculation of an individual's microbiome is highly dependent on the maternal microbiome, and changes occur in the maternal microbiome during pregnancy that may help to shape the neonatal microbiome. Further, we consider how mode of delivery may shape the developing microbiome of a neonate, and we end by discussing how the microbiome may impact preterm birth and the possibility of bacterial colonization of the placenta. Although the current literature demonstrates that the transformation of the maternal microbiome during pregnancy effects the establishment of the neonatal microbiome, further research is needed to explore how the microbiome shapes our metabolism and developing immune system.
Dysbiosis
Human Microbiome Project
Cite
Citations (68)
Intense recent interest in understanding how the human gut microbiome influences health has kindled a concomitant interest in linking dietary choices to microbiome variation. Diet is known to be a driver of microbiome variation, and yet the precise mechanisms by which certain dietary components modulate the microbiome, and by which the microbiome produces byproducts and secondary metabolites from dietary components, are not well understood. Interestingly, despite the strong influence of diet on the gut microbiome, the majority of microbiome studies published to date contain little or no analysis of dietary intake. Although an increasing number of microbiome studies are now collecting some form of dietary data or even performing diet interventions, there are no clear standards in the microbiome field for how to collect diet data or how to design a diet-microbiome study. In this paper, we review the current practices in diet-microbiome analysis and study design and make several recommendations for best practices to provoke broader discussion in the field. Based on current literature, we recommend that microbiome studies include multiple consecutive microbiome samples per study timepoint or phase and multiple days of dietary history prior to each microbiome sample whenever feasible. We find evidence that direct effects of diet on the microbiome are likely to be observable within days, while the length of an intervention required for observing microbiome-mediated effects on the host phenotype or host biomarkers, depending on the outcome, may be much longer, on the order of weeks or months. Finally, recent studies demonstrating that diet-microbiome interactions are personalized suggest that diet-microbiome studies should either include longitudinal sampling within individuals to identify personalized responses, or should include an adequate number of participants spanning a range of microbiome types to identify generalized responses.
Gut microbiome
Human Microbiome Project
Cite
Citations (110)