Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn's Disease

Mills, Robert H.; Vázquez-Baeza, Yoshiki; Zhu, Quanyin; Jiang, Lingjing; Gaffney, James; Humphrey, Greg; Smarr, Larry; Knight, Rob; Gonzalez, David J.

doi:10.1128/msystems.00337-18

Cited by 51 publications

(60 citation statements)

References 83 publications

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“…Future efforts could be aimed at incorporating co-culture of host cells/tissue and gut bacteria [51–53] into a high-throughput drug screening process for achieving more comprehensive insights on host-drug-microbiome interaction. Metaproteomics is a tool that is orthogonal to other omics technologies [17], hence for the need of deeper investigations, RapidAIM could also be coupled with techniques such as metagenomics or metabolomics for a multiple dimension view of the microbiome interaction with drugs.…”

Section: Discussionmentioning

confidence: 99%

“…Moreover, there is little insight on which microbial traits actually contribute to the functional activities of the microbiome, as functions predicted from 16S rDNA or metagenomics analyses are not necessarily expressed. Studies have shown that gene copy numbers are not representative of protein levels [17]. In addition, RNA expression have limited correlation to the actual protein abundance [18].…”

Section: Introductionmentioning

confidence: 99%

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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: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

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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“…In the current study, we observed over 5,600 proteins that that could hold new biological insights into the impact of dietary fiber versus fermented foods. While this identification depth is greater than some of the first reported metaproteomic searches on stool, newer studies have reported substantially more host and microbial protein identifications (53,000 total proteins, various biological matrices) 9,17,21 . We attribute the decreased number of identifications in our current study to several factors.…”

Section: Discussionmentioning

confidence: 84%

“…Thus, we suspect many low-abundant, sample-specific host and microbial proteins were not identified. To combat this, future iterations of SHT-Pro could incorporate peptide fractionation and longer mass spectrometry runs per sample, which has been shown to significantly increase identification of low-abundant host and microbial proteins 9 . In this context, striking a balance between throughput and proteomic depth is crucial, as the biological and health-related significance of low-abundance proteins remains promising but unclear.…”

Section: Discussionmentioning

confidence: 99%

“…One major hindrance to broader implementation has been low sample processing throughput. Indeed, while we and others previously demonstrated the power and utility of stool proteomics, those studies relied on data generated at rates as low as 10-30 samples per week 6–9 . Additionally, workflows developed for processing for cell culture and tissue lysates are not optimized to eliminate contaminating molecules that are abundant in stool.…”

Section: Introductionmentioning

confidence: 99%

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High-Throughput Stool Metaproteomics: Method and Application to Human Specimens

González

Wastyk

Topf

et al. 2020

Preprint

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16Stool-based proteomics is capable of significantly augmenting our understanding of 17 host-gut microbe interactions. However, in comparison to competing technologies such 18 as metagenomics and 16S rRNA sequencing, it is under-utilized due to its low 19 throughput and the negative impact sample contaminants can have on highly sensitive 20 mass spectrometry equipment. Here, we present a new stool proteomic processing 21 pipeline that addresses these shortcomings in a highly reproducible and quantitative 22 manner. Using this method, 290 samples from a dietary intervention study were 23 processed in approximately 1.5 weeks, largely done by a single researcher. These data 24 indicated a subtle but distinct monotonic increase in the number of significantly altered 25 proteins between study participants on fiber-or fermented food-enriched diets. Lastly, 26we were able to classify study participants based on their diet-altered proteomic profiles, 27 and demonstrated that classification accuracies of up to 89% could be achieved by 28 increasing the number of subjects considered. Taken together, this study represents the 29 first high throughout proteomic method for processing stool samples in a technically 30 reproducible manner, and has the potential to elevate stool-based proteomics as an 31 essential tool for profiling host-gut microbiome interactions in a clinical setting. 32 Importance 33Widely available technologies based on DNA sequencing have been used to describe 34 the kinds of microbes that might correlate with health and disease. However, 35 mechanistic insight might be best achieved through careful study of the dynamic 36 proteins at the interface between the foods we eat, our microbes, and ourselves. Mass-37 spectrometry-based proteomics has the potential to revolutionize our understanding of 38 this complex system but its application to clinical studies has been hampered by low-39 throughput and laborious experimentation pipelines. In response, we developed SHT-40Pro, the first high-throughput pipeline designed to rapidly handle large stool sample 41 sets. With it, a single researcher can process over one hundred stool samples per week 42for mass spectrometry analysis, roughly 10 times faster than previous methods. Since 43 SHT-Pro is fairly simple to implement using commercially available reagents, it should 44 be easily adaptable to large-scale clinical studies. 45 human health and disease, and has been associated with disorders ranging from 48 inflammatory bowel disease to autism 1,2 . Stool is a biologically rich biomaterial, 49 containing host, microbe, and dietary proteins, among a rich array of biomolecules. The 50 broad proteinaceous representation of relevant biological entities and interactions, in 51 conjunction with non-invasive sample collection, makes stool ideal for studying the 52 complex ecosystem at the host-gut microbe interface 3 . Microbiome composition can be 53 readily determined using 16S rRNA gene sequencing from stool DNA, and due to its 54 high-throughput nature, is well-suite...

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