Pathview Web: user friendly pathway visualization and data integration

Luo, Weijun; Pant, Gaurav; Bhavnasi, Yeshvant K.; Blanchard, Steven G.; Brouwer, Cory

doi:10.1093/nar/gkx372

Cited by 331 publications

(254 citation statements)

References 26 publications

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“…Box plots, violin plots, hierarchical clustering, 3D scatter plots, heatmaps, PCA, and t-SNE were visualized using R packages ggplot2, gridExtra, scatterplot3d, and pheatmap. Pathway maps were visualized using iPATH 3 (https://pathways.embl.de/)[60] and Pathview Web (https://pathview.uncc.edu/)[61]. Stacked column bars and functional enrichments were visualized on iMetaLab.ca.…”

Section: Methodsmentioning

confidence: 99%

RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

Ning

et al. 2019

Preprint

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13Background: Human-targeted drugs may exert off-target effects on the gut microbiota. 14 However, our understanding of such effects is limited due to a lack of rapid and scalable assay to 15 comprehensively assess microbiome responses to drugs. Drugs can drastically change the overall 16 microbiome abundance, microbial composition and functions of a gut microbiome. Although we 17 could comprehensively observe these microbiome responses using a series of tests, for the 18 purpose of a drug screening, it is important to decrease the number of analytical tools used. 19 Results: Here, we developed an approach to screen compounds against individual microbiomes 20 in vitro using metaproteomics adapted for both absolute bacterial abundances and functional 21 profiling of the microbiome. Our approach was evaluated by testing 43 compounds (including 22 four antibiotics) against five individual microbiomes. The method generated technically highly 23 reproducible readouts, including changes of overall microbiome abundance, microbiome 24 composition and functional pathways. Results show that besides the antibiotics, compounds 25 berberine and ibuprofen inhibited the accumulation of biomass during in vitro growth of the 26 microbiome. By comparing genus and species level-biomass contributions, selective 27 antibacterial-like activities were found with 36 of the 39 non-antibiotic compounds. Seven of our 28 compounds led to a global alteration of the metaproteome, with apparent compound-specific 29 patterns of functional responses. The taxonomic distributions of responded proteins varied 30 among drugs, i.e. different drugs affect functions of different members of the microbiome. We 31 also showed that bacterial function can shift in response to drugs without a change in the 32 abundance of the bacteria.33Conclusions: Current drug-microbiome interaction studies largely focus on relative microbiome 34 composition and microbial drug metabolism. In contrast, our workflow enables multiple insights 35 into microbiome absolute abundance and functional responses to drugs using metaproteomics as 36 the one-stop screening tool. The workflow is robust, reproducible and quantitative, and is 37 scalable for personalized high-throughput drug screening applications. 38

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Section: Methodsmentioning

confidence: 99%

RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

Ning

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…Box plots, violin plots, hierarchical clustering, 3D scatter plots, heatmaps, PCA, and t-SNE were visualized using R packages ggplot2, gridExtra, scatterplot3d, and pheatmap. Pathway maps were visualized using iPATH 3 (https:// pathways.embl.de/) [64] and Pathview Web (https://pathview.uncc.edu/) [65]. Stacked column bars and functional enrichments were visualized on iMetaLab.ca.…”

Section: Data Visualizationsmentioning

confidence: 99%

RapidAIM: a culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

et al. 2020

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Background: Human-targeted drugs may exert off-target effects or can be repurposed to modulate the gut microbiota. However, our understanding of such effects is limited due to a lack of rapid and scalable assay to comprehensively assess microbiome responses to drugs. Drugs and other compounds can drastically change the overall abundance, taxonomic composition, and functions of a gut microbiome.Results: Here, we developed an approach to screen compounds against individual microbiomes in vitro, using metaproteomics to both measure absolute bacterial abundances and to functionally profile the microbiome. Our approach was evaluated by testing 43 compounds (including 4 antibiotics) against 5 individual microbiomes. The method generated technically highly reproducible readouts, including changes of overall microbiome abundance, microbiome composition, and functional pathways. Results show that besides the antibiotics, the compounds berberine and ibuprofen inhibited the accumulation of biomass during in vitro growth of the microbiota. By comparing genus and species level-biomass contributions, selective antibacterial-like activities were found with 35 of the 39 non-antibiotic compounds. Seven of the compounds led to a global alteration of the metaproteome, with apparent compound-specific patterns of functional responses. The taxonomic distributions of altered proteins varied among drugs, i.e., different drugs affect functions of different members of the microbiome. We also showed that bacterial function can shift in response to drugs without a change in the abundance of the bacteria.Conclusions: Current drug-microbiome interaction studies largely focus on relative microbiome composition and microbial drug metabolism. In contrast, our workflow enables multiple insights into microbiome absolute abundance and functional responses to drugs. The workflow is robust, reproducible, and quantitative and is scalable for personalized high-throughput drug screening applications.

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“…This last analysis was further filtered by setting a cutoff of $5 genes per pathway, z scores $2, and P # 0.05. To better visualize the pathway enrichment, Pathview Web was used (22). Validation of gene expression: quantitative RT-PCR (qRT-PCR) assays were performed with an Eppendorff Mastercycler using iScript one-step RT-PCR kit probes (Bio-Rad, Hercules, CA, USA).…”

Section: Hepatic Gene Expressionmentioning

confidence: 99%

Ileal interposition surgery targets the hepatic TGF‐β pathway, influencing gluconeogenesis and mitochondrial bioenergetics in the UCD‐T2DM rat model of diabetes

Hung,

Napoli,

Ross-Inta

et al. 2019

FASEB j.

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Ileal interposition (IT) is a surgical procedure that increases the delivery of incompletely digested nutrients and biliary and pancreatic secretions to the distal intestinal mucosa. Here, we investigated the metabolic impact of this intervention in 2‐mo‐old prediabetic University of California, Davis type 2 diabetes mellitus rats by assessing liver gene expression at 1.5 mo post‐IT surgery. Pathway analysis indicated decreased signaling via TGF‐β/Smad (a family of proteins named mothers against decapentaplegic homologs), peroxisome proliferator‐activated receptor (PPAR), and PI3K‐Akt‐AMPK–mechanistic target of rapamycin, likely targeting hepatic stellate cells because differentiation and activation of these cells is associated with decreased signaling via PPAR and TGF‐β/Smad. IT surgery up‐regulated the expression of genes involved in regulation of cholesterol and terpenoid syntheses and down‐regulated those involved in glycerophospholipid metabolism [including cardiolipin (CL)], lipogenesis, and gluconeogenesis. Consistent with the down‐regulation of the hepatic CL pathway, IT surgery produced a metabolic switch in liver, kidney cortex, and fat depots toward decreased mitochondrial fatty acid β‐oxidation, the process required to fuel high energy–demanding pathways (e.g., gluconeogenesis and glyceroneogenesis), whereas opposite effects were observed in skeletal and cardiac muscles. This study demonstrates for the first time the presence of metabolic pathways that complement the effects of IT surgery to maximize its benefits and potentially identify similarly effective, durable, and less invasive therapeutic options for metabolic disease, including inhibitors of TGF‐β signaling.—Hung, C., Napoli, E., Ross‐Inta, C., Graham, J., Flores‐Torres, A. L., Stanhope, K. L., Froment, P., Havel, P. J., Giulivi, C. Ileal interposition surgery targets the hepatic TGF‐β pathway, influencing gluconeogenesis and mitochondrial bioenergetics in the UCD‐T2DM rat model of diabetes. FASEB J. 33, 11270–11283 (2019). http://www.fasebj.org

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Pathview Web: user friendly pathway visualization and data integration

Cited by 331 publications

References 26 publications

RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

RapidAIM: a culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs

Ileal interposition surgery targets the hepatic TGF‐β pathway, influencing gluconeogenesis and mitochondrial bioenergetics in the UCD‐T2DM rat model of diabetes

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