@article{rajczewski_blakeley-ruiz_meyer_vintila_mcilvin_bossche_searle_griffin_saito_kleiner_et al._2024, title={Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome}, url={http://dx.doi.org/10.1101/2024.09.18.613707}, DOI={10.1101/2024.09.18.613707}, abstractNote={Abstract Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.}, author={Rajczewski, Andrew and Blakeley-Ruiz, J. Alfredo and Meyer, Annaliese and Vintila, Simina and McIlvin, Matthew and Bossche, Tim Van Den and Searle, Brian C. and Griffin, Timothy and Saito, Mak and Kleiner, Manuel and et al.}, year={2024}, month={Sep} }
 @article{awan_bartlett_blakeley-ruiz_richie_theriot_kleiner_2024, title={Dietary protein from different sources escapes host digestion and is differentially modified by the microbiota}, url={http://dx.doi.org/10.1101/2024.06.26.600830}, DOI={10.1101/2024.06.26.600830}, abstractNote={Protein is an essential macronutrient and variations in its source and quantity have been shown to impact long-term health outcomes. Differential health impacts of dietary proteins from various sources are likely driven by differences in their digestibility by the host and subsequent availability to the intestinal microbiota. However, our current understanding regarding the fate of dietary proteins from different sources in the gut, specifically how component proteins within these sources interact with the host and the gut microbiota, is limited. To determine which dietary proteins are efficiently digested by the host and which proteins escape host digestion and are used by the gut microbiota, we used high-resolution mass spectrometry to quantify the proteins that make up different dietary protein sources before and after digestion in germ-free and conventionally raised mice. Contrary to expectation, we detected proteins from all sources in fecal samples of both germ-free and conventional mice suggesting that even protein sources with a high digestive efficiency make it in part to the colon where they can serve as a substrate for the microbiota. Additionally, we found clear patterns where specific component proteins of the dietary protein sources were used as a preferred substrate by the microbiota or were not as accessible to the microbiota. We found that specific proteins with functions that could impact host health and physiology were differentially enriched in germ-free or conventionally raised mice. These findings reveal large differences in the fate of dietary protein from various sources in the gut that could explain some of their differential health impacts.}, author={Awan, Ayesha and Bartlett, Alexandria and Blakeley-Ruiz, J. Alfredo and Richie, Tanner and Theriot, Casey and Kleiner, Manuel}, year={2024}, month={Jun} }
 @article{blakeley-ruiz_bartlett_mcmillan_awan_walsh_meyerhoffer_vintila_maier_richie_theriot_et al._2024, title={Dietary protein source strongly alters gut microbiota composition and function}, url={http://dx.doi.org/10.1101/2024.04.04.588169}, DOI={10.1101/2024.04.04.588169}, abstractNote={The source of protein in a persons diet affects their total life expectancy. However, the mechanisms by which dietary protein sources differentially impact human health and life expectancy are poorly understood. Dietary choices have major impacts on the composition and function of the intestinal microbiota that ultimately mediate host health. This raises the possibility that health outcomes based on dietary protein sources might be driven by interactions between dietary protein and the gut microbiota. In this study, we determine the effects of seven different sources of dietary protein on the gut microbiota in mice. We apply an integrated metagenomics-metaproteomics approach to simultaneously investigate the effects of these dietary protein sources on the gut microbiotas composition and function. The protein abundances measured by metaproteomics can provide microbial species abundances, and evidence for the phenotype of microbiota members on the molecular level because measured proteins allow us to infer the metabolic and physiological processes used by a microbial community. We showed that dietary protein source significantly altered the species composition and overall function of the gut microbiota. Different dietary protein sources led to changes in the abundance of microbial amino acid degrading proteins and proteins involved in the degradation of glycosylations on dietary protein. In particular, brown rice and egg white protein increased the abundance of amino acid degrading enzymes and egg white protein increased the abundance of bacteria and proteins usually associated with the degradation of the intestinal mucus barrier. These results show that dietary protein source can change the gut microbiotas metabolism, which could have major implications in the context of gut microbiota mediated diseases.}, author={Blakeley-Ruiz, J. Alfredo and Bartlett, Alexandria and McMillan, Arthur and Awan, Ayesha and Walsh, Molly Vanhoy and Meyerhoffer, Alissa and Vintila, Simina and Maier, Jessie and Richie, Tanner and Theriot, Casey and et al.}, year={2024}, month={Apr} }
 @article{bartlett_blakeley-ruiz_richie_theriot_kleiner_2023, title={Large Quantities of Bacterial DNA and Protein in Common Dietary Protein Source Used in Microbiome Studies}, url={http://dx.doi.org/10.1101/2023.12.07.570621}, DOI={10.1101/2023.12.07.570621}, abstractNote={AbstractDiet has been shown to greatly impact the intestinal microbiota. To understand the role of individual dietary components, defined diets with purified components are frequently used in diet-microbiota studies. Many of the frequently used defined diets use purified casein as the protein source. Previous work indicated that this casein contains microbial DNA potentially impacting results of microbiome studies. Other diet-based microbially derived molecules that may impact microbiome measurements, such as proteins detected by metaproteomics, have not been determined for casein. Additionally, other protein sources used in microbiome studies have not been characterized for their microbial content. We used metagenomics and metaproteomics to identify and quantify microbial DNA and protein in a casein-based defined diet to better understand potential impacts on metagenomic and metaproteomic microbiome studies. We further tested six additional defined diets with purified protein sources with an integrated metagenomic-metaproteomic approach and show that contaminating microbial protein is unique to casein within the tested set as microbial protein was not identified in diets with other protein sources. We also illustrate the contribution of diet-derived microbial protein in diet-microbiota studies by metaproteomic analysis of stool samples from germ-free mice (GF) and mice with a conventional microbiota (CV) following consumption of diets with casein and non-casein protein. This study highlights a potentially confounding factor in diet-microbiota studies that must be considered through evaluation of the diet itself within a given study.ImportanceMany diets used in diet-microbiota studies use casein as the source of dietary protein. We found large quantities of microbial DNA and protein in casein-based diets. This microbial DNA and protein are resilient to digestion as it is present in fecal samples of mice consuming casein-based diets. This contribution of diet-derived microbial DNA and protein to microbiota measurements may influence results and conclusions and must therefore be considered in diet-microbiota studies. We tested additional dietary protein sources and did not detect microbial DNA or protein. Our findings highlight the necessity of evaluating diet samples in diet-microbiota studies to ensure that potential microbial content of the diet can be accounted for in microbiome measurements.}, author={Bartlett, Alexandria and Blakeley-Ruiz, Alfredo and Richie, Tanner and Theriot, Casey and Kleiner, Manuel}, year={2023}, month={Dec} }
 @article{blakeley-ruiz_kleiner_2022, title={Considerations for constructing a protein sequence database for metaproteomics}, volume={20}, ISSN={["2001-0370"]}, url={http://dx.doi.org/10.1016/j.csbj.2022.01.018}, DOI={10.1016/j.csbj.2022.01.018}, abstractNote={Mass spectrometry-based metaproteomics has emerged as a prominent technique for interrogating the functions of specific organisms in microbial communities, in addition to total community function. Identifying proteins by mass spectrometry requires matching mass spectra of fragmented peptide ions to a database of protein sequences corresponding to the proteins in the sample. This sequence database determines which protein sequences can be identified from the measurement, and as such the taxonomic and functional information that can be inferred from a metaproteomics measurement. Thus, the construction of the protein sequence database directly impacts the outcome of any metaproteomics study. Several factors, such as source of sequence information and database curation, need to be considered during database construction to maximize accurate protein identifications traceable to the species of origin. In this review, we provide an overview of existing strategies for database construction and the relevant studies that have sought to test and validate these strategies. Based on this review of the literature and our experience we provide a decision tree and best practices for choosing and implementing database construction strategies.}, journal={COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL}, publisher={Elsevier BV}, author={Blakeley-Ruiz, J. Alfredo and Kleiner, Manuel}, year={2022}, pages={937–952} }
 @article{blakeley-ruiz_mcclintock_shrestha_poudel_yang_giannone_choo_podar_baghdoyan_lydic_et al._2022, title={Morphine and high-fat diet differentially alter the gut microbiota composition and metabolic function in lean versus obese mice}, volume={2}, url={http://dx.doi.org/10.1038/s43705-022-00131-6}, DOI={10.1038/s43705-022-00131-6}, abstractNote={Abstract
               There are known associations between opioids, obesity, and the gut microbiome, but the molecular connection/mediation of these relationships is not understood. To better clarify the interplay of physiological, genetic, and microbial factors, this study investigated the microbiome and host inflammatory responses to chronic opioid administration in genetically obese, diet-induced obese, and lean mice. Samples of feces, urine, colon tissue, and plasma were analyzed using targeted LC-MS/MS quantification of metabolites, immunoassays of inflammatory cytokine levels, genome-resolved metagenomics, and metaproteomics. Genetic obesity, diet-induced obesity, and morphine treatment in lean mice each showed increases in distinct inflammatory cytokines. Metagenomic assembly and binning uncovered over 400 novel gut bacterial genomes and species. Morphine administration impacted the microbiome’s composition and function, with the strongest effect observed in lean mice. This microbiome effect was less pronounced than either diet or genetically driven obesity. Based on inferred microbial physiology from the metaproteome datasets, a high-fat diet transitioned constituent microbes away from harvesting diet-derived nutrients and towards nutrients present in the host mucosal layer. Considered together, these results identified novel host-dependent phenotypes, differentiated the effects of genetic obesity versus diet induced obesity on gut microbiome composition and function, and showed that chronic morphine administration altered the gut microbiome.}, number={1}, journal={ISME Communications}, publisher={Springer Science and Business Media LLC}, author={Blakeley-Ruiz, J. Alfredo and McClintock, Carlee S. and Shrestha, Him K. and Poudel, Suresh and Yang, Zamin K. and Giannone, Richard J. and Choo, James J. and Podar, Mircea and Baghdoyan, Helen A. and Lydic, Ralph and et al.}, year={2022}, month={Aug} }
 @phdthesis{blakeley-ruiz_2020, title={Extracting detailed metabolic information and connections from mammalian gut microbiomes via metaproteomics}, url={https://trace.tennessee.edu/utk_graddiss/6194}, journal={University of Tennessee}, school={University of Tennessee}, author={Blakeley-Ruiz, Jose A.}, year={2020}, month={Dec} }
 @article{combining integrated systems-biology approaches with intervention-based experimental design provides a higher-resolution path forward for microbiome research_2019, url={http://dx.doi.org/10.1017/s0140525x18002911}, DOI={10.1017/s0140525x18002911}, abstractNote={Abstract
	  The Hooks et al. review of microbiota-gut-brain (MGB) literature provides a constructive criticism of the general approaches encompassing MGB research. This commentary extends their review by: (a) highlighting capabilities of advanced systems-biology “-omics” techniques for microbiome research and (b) recommending that combining these high-resolution techniques with intervention-based experimental design may be the path forward for future MGB research.}, journal={Behavioral and Brain Sciences}, year={2019} }
 @article{metaproteomics reveals persistent and phylum-redundant metabolic functional stability in adult human gut microbiomes of crohn’s remission patients despite temporal variations in microbial taxa, genomes, and proteomes_2019, url={http://dx.doi.org/10.1186/s40168-019-0631-8}, DOI={10.1186/s40168-019-0631-8}, abstractNote={The gut microbiome plays a fundamental role in the human host's overall health by contributing key biological functions such as expanded metabolism and pathogen defense/immune control. In a healthy individual, the gut microbiome co-exists within the human host in a symbiotic, non-inflammatory relationship that enables mutual benefits, such as microbial degradation of indigestible food products into small molecules that the host can utilize, and enhanced pathogen defense. In abnormal conditions, such as Crohn's disease, this favorable metabolic relationship breaks down and a variety of undesirable activities result, including chronic inflammation and other health-related issues. It has been difficult, however, to elucidate the overall functional characteristics of this relationship because the microbiota can vary substantially in composition for healthy humans and possibly even more in individuals with gut disease conditions such as Crohn's disease. Overall, this suggests that microbial membership composition may not be the best way to characterize a phenotype. Alternatively, it seems to be more informative to examine and characterize the functional composition of a gut microbiome. Towards that end, this study examines 25 metaproteomes measured in several Crohn's disease patients' post-resection surgery across the course of 1 year, in order to examine persistence of microbial taxa, genes, proteins, and metabolic functional distributions across time in individuals whose microbiome might be more variable due to the gut disease condition.The measured metaproteomes were highly personalized, with all the temporally-related metaproteomes clustering most closely by individual. In general, the metaproteomes were remarkably distinct between individuals and to a lesser extent within individuals. This prompted a need to characterize the metaproteome at a higher functional level, which was achieved by annotating identified protein groups with KEGG orthologous groups to infer metabolic modules. At this level, similar and redundant metabolic functions across multiple phyla were observed across time and between individuals. Tracking through these various metabolic modules revealed a clear path from carbohydrate, lipid, and amino acid degradation to central metabolism and finally the production of fermentation products.The human gut metaproteome can vary quite substantially across time and individuals. However, despite substantial intra-individual variation in the metaproteomes, there is a clear persistence of conserved metabolic functions across time and individuals. Additionally, the persistence of these core functions is redundant across multiple phyla but is not always observable in the same sample. Finally, the gut microbiome's metabolism is not driven by a set of discrete linear pathways but a web of interconnected reactions facilitated by a network of enzymes that connect multiple molecules across multiple pathways.}, journal={Microbiome}, year={2019}, month={Dec} }