Multi‐omics approach to elucidate the gut microbiota activity: Metaproteomics and metagenomics connection

Guirro, Maria; Costa, Andréa Moscardini da; Gual‐Grau, Andreu; Mayneris‐Perxachs, Jordi; Torrell, Helena; Herrero, Pol; Canela, Núria; Arola, Lluı́s

doi:10.1002/elps.201700476

Cited by 30 publications

(29 citation statements)

References 43 publications

(43 reference statements)

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“…In particular, MS analysis is a time-consuming process. To this end, a fast-pass screening process should consider using techniques such as tandem mass tags (TMT) [52,53] to multiplex multiple microbiome samples in one MS analysis. Furthermore, our workflow only measures the direct effects of compounds on the microbiome.…”

Section: Discussionmentioning

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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Section: Discussionmentioning

confidence: 99%

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

et al. 2020

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“…In particular, MS analysis is a time-consuming process. To this end, a fast-pass screening process such as tandem mass tags (TMT)[49, 50] could be used to multiplex multiple microbiome samples in one MS analysis. Furthermore, our workflow only measures the direct effects of compounds on the microbiome.…”

Section: Discussionmentioning

confidence: 99%

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

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et al. 2019

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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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“…In previous studies, [ 21,24 ] the feeding of a cafeteria diet to Sprague Dawley rats induced an obesogenic pattern with significant increases in body weight and fat mass, elevated systolic blood pressure, hypertriglyceridemia, hyperglycemia, and high levels of low‐density lipoprotein cholesterol (LDL‐c), which are criteria required for MS diagnosis. Consequently, when applying the harmonized human definition of MS to Sprague Dawley rats consuming a cafeteria diet, the rats exhibited a reflex of fat mass, elevated triglyceride (TG) levels (drug treatment for elevated TG is an alternate indicator), reduced high‐density lipoprotein cholesterol (HDL‐c) levels (drug treatment for reduced HDL‐c is an alternate indicator), elevated blood pressure (systolic or diastolic (antihypertensive drug treatment in a person with a history of hypertension is an alternate indicator), and/or elevated fasting plasma glucose levels (drug treatment of elevated glucose is an alternate indicator).…”

Section: Resultsmentioning

confidence: 99%

“…The rationale for choosing this dose was based on the beneficial effects of hesperidin reported in previous works focused on MS factors in rat models. [ 14,22 ] Accordingly, the human equivalent dose of 100 mg kg −1 hesperidin was 1350 mg per day for a 60 kg human, [ 21,23 ] a dose achievable with hesperidin‐rich orange juice.…”

Section: Methodsmentioning

confidence: 99%

Proteomic Analysis of Heart and Kidney Tissues in Healthy and Metabolic Syndrome Rats after Hesperidin Supplementation

Pla‐Pagà

Guirro

Gual‐Grau

et al. 2020

Molecular Nutrition Food Res

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Scope: Proteomics has provided new strategies to elucidate the mechanistic action of hesperidin, a flavonoid present in citrus fruits. Thus, the aim of the present study is to determine the effects of hesperidin supplementation (HS) on the proteomic profiles of heart and kidney tissue samples from healthy and metabolic syndrome (MS) rats. Methods and results: 24 Sprague Dawley rats are randomized into four groups: healthy rats fed with a standard diet without HS, healthy rats administered with HS (100 mg kg −1 day −1 ), MS rats without HS, and MS rats administered with HS (100 mg kg −1 day −1 ) for eight weeks. Heart and kidney samples are obtained, and proteomic analysis is performed by mass spectrometry. Multivariate, univariate, and ingenuity pathways analyses are performed. Comparative and semiquantitative proteomic analyses of heart and kidney tissues reveal differential protein expression between MS rats with and without HS. The top diseases and functions implicated are related to the cardiovascular system, free radical scavenging, lipid metabolism, glucose metabolism, and renal and urological diseases. Conclusion: This study is the first to demonstrate the protective capacity of hesperidin to change to the proteomic profiles in relation to different cardiovascular risk biomarkers in the heart and kidney tissues of MS rats.

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Multi‐omics approach to elucidate the gut microbiota activity: Metaproteomics and metagenomics connection

Cited by 30 publications

References 43 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

Proteomic Analysis of Heart and Kidney Tissues in Healthy and Metabolic Syndrome Rats after Hesperidin Supplementation

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