All Publications


  • Metabolic diversity in commensal protists regulates intestinal immunity and trans-kingdom competition. Cell Gerrick, E. R., Zlitni, S., West, P. T., Carter, M. M., Mechler, C. M., Olm, M. R., Caffrey, E. B., Li, J. A., Higginbottom, S. K., Severyn, C. J., Kracke, F., Spormann, A. M., Sonnenburg, J. L., Bhatt, A. S., Howitt, M. R. 2023

    Abstract

    The microbiota influences intestinal health and physiology, yet the contributions of commensal protists to the gut environment have been largely overlooked. Here, we discover human- and rodent-associated parabasalid protists, revealing substantial diversity and prevalence in nonindustrialized human populations. Genomic and metabolomic analyses of murine parabasalids from the genus Tritrichomonas revealed species-level differences in excretion of the metabolite succinate, which results in distinct small intestinal immune responses. Metabolic differences between Tritrichomonas species also determine their ecological niche within the microbiota. By manipulating dietary fibers and developing in vitro protist culture, we show that different Tritrichomonas species prefer dietary polysaccharides or mucus glycans. These polysaccharide preferences drive trans-kingdom competition with specific commensal bacteria, which affects intestinal immunity in a diet-dependent manner. Our findings reveal unappreciated diversity in commensal parabasalids, elucidate differences in commensal protist metabolism, and suggest how dietary interventions could regulate their impact on gut health.

    View details for DOI 10.1016/j.cell.2023.11.018

    View details for PubMedID 38096822

  • Ultra-deep sequencing of Hadza hunter-gatherers recovers vanishing gut microbes. Cell Carter, M. M., Olm, M. R., Merrill, B. D., Dahan, D., Tripathi, S., Spencer, S. P., Yu, F. B., Jain, S., Neff, N., Jha, A. R., Sonnenburg, E. D., Sonnenburg, J. L. 2023

    Abstract

    The gut microbiome modulates immune and metabolic health. Human microbiome data are biased toward industrialized populations, limiting our understanding of non-industrialized microbiomes. Here, we performed ultra-deep metagenomic sequencing on 351 fecal samples from the Hadza hunter-gatherers of Tanzania and comparative populations in Nepal and California. We recovered 91,662 genomes of bacteria, archaea, bacteriophages, and eukaryotes, 44% of which are absent from existing unified datasets. We identified 124 gut-resident species vanishing in industrialized populations and highlighted distinct aspects of the Hadza gut microbiome related to in situ replication rates, signatures of selection, and strain sharing. Industrialized gut microbes were found to be enriched in genes associated with oxidative stress, possibly a result of microbiome adaptation to inflammatory processes. This unparalleled view of the Hadza gut microbiome provides a valuable resource, expands our understanding of microbes capable of colonizing the human gut, and clarifies the extensive perturbation induced by the industrialized lifestyle.

    View details for DOI 10.1016/j.cell.2023.05.046

    View details for PubMedID 37348505

  • Butyrate Differentiates Permissiveness to Clostridioides difficile Infection and Influences Growth of Diverse C. difficile Isolates. Infection and immunity Pensinger, D. A., Fisher, A. T., Dobrila, H. A., Van Treuren, W., Gardner, J. O., Higginbottom, S. K., Carter, M. M., Schumann, B., Bertozzi, C. R., Anikst, V., Martin, C., Robilotti, E. V., Chow, J. M., Buck, R. H., Tompkins, L. S., Sonnenburg, J. L., Hryckowian, A. J. 2023: e0057022

    Abstract

    A disrupted "dysbiotic" gut microbiome engenders susceptibility to the diarrheal pathogen Clostridioides difficile by impacting the metabolic milieu of the gut. Diet, in particular the microbiota-accessible carbohydrates (MACs) found in dietary fiber, is one of the most powerful ways to affect the composition and metabolic output of the gut microbiome. As such, diet is a powerful tool for understanding the biology of C. difficile and for developing alternative approaches for coping with this pathogen. One prominent class of metabolites produced by the gut microbiome is short-chain fatty acids (SCFAs), the major metabolic end products of MAC metabolism. SCFAs are known to decrease the fitness of C. difficile in vitro, and high intestinal SCFA concentrations are associated with reduced fitness of C. difficile in animal models of C. difficile infection (CDI). Here, we use controlled dietary conditions (8 diets that differ only by MAC composition) to show that C. difficile fitness is most consistently impacted by butyrate, rather than the other two prominent SCFAs (acetate and propionate), during murine model CDI. We similarly show that butyrate concentrations are lower in fecal samples from humans with CDI than in those from healthy controls. Finally, we demonstrate that butyrate impacts growth in diverse C. difficile isolates. These findings provide a foundation for future work which will dissect how butyrate directly impacts C. difficile fitness and will lead to the development of diverse approaches distinct from antibiotics or fecal transplant, such as dietary interventions, for mitigating CDI in at-risk human populations. IMPORTANCE Clostridioides difficile is a leading cause of infectious diarrhea in humans, and it imposes a tremendous burden on the health care system. Current treatments for C. difficile infection (CDI) include antibiotics and fecal microbiota transplant, which contribute to recurrent CDIs and face major regulatory hurdles, respectively. Therefore, there is an ongoing need to develop new ways to cope with CDI. Notably, a disrupted "dysbiotic" gut microbiota is the primary risk factor for CDI, but we incompletely understand how a healthy microbiota resists CDI. Here, we show that a specific molecule produced by the gut microbiota, butyrate, is negatively associated with C. difficile burdens in humans and in a mouse model of CDI and that butyrate impedes the growth of diverse C. difficile strains in pure culture. These findings help to build a foundation for designing alternative, possibly diet-based, strategies for mitigating CDI in humans.

    View details for DOI 10.1128/iai.00570-22

    View details for PubMedID 36692308

  • A Microbiome-targeting Fiber-enriched Nutritional Formula is Well Tolerated and Improves Quality of Life and Hemoglobin A1c in Type 2 Diabetes: A Double-Blind, Randomized, Placebo-Controlled Trial. Diabetes, obesity & metabolism Frias, J. P., Lee, M. L., Carter, M. M., Ebel, E. R., Lai, R., Rikse, L., Washington, M. E., Sonneburg, J. L., Damman, C. J. 2023

    Abstract

    AIMS: To investigate a prebiotic fiber-enriched nutritional formula on health-related quality of life and metabolic control in type 2 diabetes.MATERIALS AND METHODS: This was a 12-week, double-blind, placebo-controlled study with an unblinded dietary advice only comparator arm. Participants were randomized 2:1:1 to a prebiotic fiber-enriched nutritional formula (Active), a placebo fiber-absent nutritional formula (Placebo), or non-blinded dietary advice alone (Diet). Primary endpoint was change in core Type 2 Diabetes Distress Assessment System (cT2-DDAS) at week 12. HbA1c change was a key secondary endpoint.RESULTS: 192 participants were randomized. Mean age was 54.3years, HbA1c 7.8%, and BMI 35.9 kg/m2 . At week 12, cT2-DDAS reduced significantly in Active versus Placebo (-0.4, p=0.03), and HbA1c was reduced significantly in Active vs Placebo (-0.64%, p=0.01). Gut microbiome sequencing revealed that the relative abundance of two species of butyrate-producing bacteria (Roseburia faecis and Anaerostipes hadrus) increased significantly in Active vs Placebo.CONCLUSIONS: A microbiome-targeting nutritional formula significantly improved cT2-DDAS and HbA1c, suggesting the potential for prebiotic fiber as a complement to lifestyle and/or pharmaceutical interventions for managing type 2 diabetes. This article is protected by copyright. All rights reserved.

    View details for DOI 10.1111/dom.14967

    View details for PubMedID 36594522

  • Assessing the effects of alternative plant-based meats v. animal meats on biomarkers of inflammation: a secondary analysis of the SWAP-MEAT randomized crossover trial JOURNAL OF NUTRITIONAL SCIENCE Crimarco, A., Landry, M. J., Carter, M. M., Gardner, C. D. 2022; 11
  • Robust variation in infant gut microbiome assembly across a spectrum of lifestyles. Science (New York, N.Y.) Olm, M. R., Dahan, D., Carter, M. M., Merrill, B. D., Yu, F. B., Jain, S., Meng, X., Tripathi, S., Wastyk, H., Neff, N., Holmes, S., Sonnenburg, E. D., Jha, A. R., Sonnenburg, J. L. 2022; 376 (6598): 1220-1223

    Abstract

    Infant microbiome assembly has been intensely studied in infants from industrialized nations, but little is known about this process in nonindustrialized populations. We deeply sequenced infant stool samples from the Hadza hunter-gatherers of Tanzania and analyzed them in a global meta-analysis. Infant microbiomes develop along lifestyle-associated trajectories, with more than 20% of genomes detected in the Hadza infant gut representing novel species. Industrialized infants-even those who are breastfed-have microbiomes characterized by a paucity of Bifidobacterium infantis and gene cassettes involved in human milk utilization. Strains within lifestyle-associated taxonomic groups are shared between mother-infant dyads, consistent with early life inheritance of lifestyle-shaped microbiomes. The population-specific differences in infant microbiome composition and function underscore the importance of studying microbiomes from people outside of wealthy, industrialized nations.

    View details for DOI 10.1126/science.abj2972

    View details for PubMedID 35679413

  • The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans. Science (New York, N.Y.) Jones, R. C., Karkanias, J., Krasnow, M. A., Pisco, A. O., Quake, S. R., Salzman, J., Yosef, N., Bulthaup, B., Brown, P., Harper, W., Hemenez, M., Ponnusamy, R., Salehi, A., Sanagavarapu, B. A., Spallino, E., Aaron, K. A., Concepcion, W., Gardner, J. M., Kelly, B., Neidlinger, N., Wang, Z., Crasta, S., Kolluru, S., Morri, M., Pisco, A. O., Tan, S. Y., Travaglini, K. J., Xu, C., Alcántara-Hernández, M., Almanzar, N., Antony, J., Beyersdorf, B., Burhan, D., Calcuttawala, K., Carter, M. M., Chan, C. K., Chang, C. A., Chang, S., Colville, A., Crasta, S., Culver, R. N., Cvijović, I., D'Amato, G., Ezran, C., Galdos, F. X., Gillich, A., Goodyer, W. R., Hang, Y., Hayashi, A., Houshdaran, S., Huang, X., Irwin, J. C., Jang, S., Juanico, J. V., Kershner, A. M., Kim, S., Kiss, B., Kolluru, S., Kong, W., Kumar, M. E., Kuo, A. H., Leylek, R., Li, B., Loeb, G. B., Lu, W. J., Mantri, S., Markovic, M., McAlpine, P. L., de Morree, A., Morri, M., Mrouj, K., Mukherjee, S., Muser, T., Neuhöfer, P., Nguyen, T. D., Perez, K., Phansalkar, R., Pisco, A. O., Puluca, N., Qi, Z., Rao, P., Raquer-McKay, H., Schaum, N., Scott, B., Seddighzadeh, B., Segal, J., Sen, S., Sikandar, S., Spencer, S. P., Steffes, L. C., Subramaniam, V. R., Swarup, A., Swift, M., Travaglini, K. J., Van Treuren, W., Trimm, E., Veizades, S., Vijayakumar, S., Vo, K. C., Vorperian, S. K., Wang, W., Weinstein, H. N., Winkler, J., Wu, T. T., Xie, J., Yung, A. R., Zhang, Y., Detweiler, A. M., Mekonen, H., Neff, N. F., Sit, R. V., Tan, M., Yan, J., Bean, G. R., Charu, V., Forgó, E., Martin, B. A., Ozawa, M. G., Silva, O., Tan, S. Y., Toland, A., Vemuri, V. N., Afik, S., Awayan, K., Botvinnik, O. B., Byrne, A., Chen, M., Dehghannasiri, R., Detweiler, A. M., Gayoso, A., Granados, A. A., Li, Q., Mahmoudabadi, G., McGeever, A., de Morree, A., Olivieri, J. E., Park, M., Pisco, A. O., Ravikumar, N., Salzman, J., Stanley, G., Swift, M., Tan, M., Tan, W., Tarashansky, A. J., Vanheusden, R., Vorperian, S. K., Wang, P., Wang, S., Xing, G., Xu, C., Yosef, N., Alcántara-Hernández, M., Antony, J., Chan, C. K., Chang, C. A., Colville, A., Crasta, S., Culver, R., Dethlefsen, L., Ezran, C., Gillich, A., Hang, Y., Ho, P. Y., Irwin, J. C., Jang, S., Kershner, A. M., Kong, W., Kumar, M. E., Kuo, A. H., Leylek, R., Liu, S., Loeb, G. B., Lu, W. J., Maltzman, J. S., Metzger, R. J., de Morree, A., Neuhöfer, P., Perez, K., Phansalkar, R., Qi, Z., Rao, P., Raquer-McKay, H., Sasagawa, K., Scott, B., Sinha, R., Song, H., Spencer, S. P., Swarup, A., Swift, M., Travaglini, K. J., Trimm, E., Veizades, S., Vijayakumar, S., Wang, B., Wang, W., Winkler, J., Xie, J., Yung, A. R., Artandi, S. E., Beachy, P. A., Clarke, M. F., Giudice, L. C., Huang, F. W., Huang, K. C., Idoyaga, J., Kim, S. K., Krasnow, M., Kuo, C. S., Nguyen, P., Quake, S. R., Rando, T. A., Red-Horse, K., Reiter, J., Relman, D. A., Sonnenburg, J. L., Wang, B., Wu, A., Wu, S. M., Wyss-Coray, T. 2022; 376 (6594): eabl4896

    Abstract

    Molecular characterization of cell types using single-cell transcriptome sequencing is revolutionizing cell biology and enabling new insights into the physiology of human organs. We created a human reference atlas comprising nearly 500,000 cells from 24 different tissues and organs, many from the same donor. This atlas enabled molecular characterization of more than 400 cell types, their distribution across tissues, and tissue-specific variation in gene expression. Using multiple tissues from a single donor enabled identification of the clonal distribution of T cells between tissues, identification of the tissue-specific mutation rate in B cells, and analysis of the cell cycle state and proliferative potential of shared cell types across tissues. Cell type-specific RNA splicing was discovered and analyzed across tissues within an individual.

    View details for DOI 10.1126/science.abl4896

    View details for PubMedID 35549404

  • Cell types of origin of the cell-free transcriptome. Nature biotechnology Vorperian, S. K., Moufarrej, M. N., Tabula Sapiens Consortium, Quake, S. R., Jones, R. C., Karkanias, J., Krasnow, M., Pisco, A. O., Quake, S. R., Salzman, J., Yosef, N., Bulthaup, B., Brown, P., Harper, W., Hemenez, M., Ponnusamy, R., Salehi, A., Sanagavarapu, B. A., Spallino, E., Aaron, K. A., Concepcion, W., Gardner, J. M., Kelly, B., Neidlinger, N., Wang, Z., Crasta, S., Kolluru, S., Morri, M., Tan, S. Y., Travaglini, K. J., Xu, C., Alcantara-Hernandez, M., Almanzar, N., Antony, J., Beyersdorf, B., Burhan, D., Calcuttawala, K., Carter, M. M., Chan, C. K., Chang, C. A., Chang, S., Colville, A., Culver, R. N., Cvijovic, I., D'Amato, G., Ezran, C., Galdos, F. X., Gillich, A., Goodyer, W. R., Hang, Y., Hayashi, A., Houshdaran, S., Huang, X., Irwin, J. C., Jang, S., Juanico, J. V., Kershner, A. M., Kim, S., Kiss, B., Kong, W., Kumar, M. E., Kuo, A. H., Leylek, R., Li, B., Loeb, G. B., Lu, W., Mantri, S., Markovic, M., McAlpine, P. L., de Morree, A., Mrouj, K., Mukherjee, S., Muser, T., Neuhofer, P., Nguyen, T. D., Perez, K., Phansalkar, R., Puluca, N., Qi, Z., Rao, P., Raquer-McKay, H., Schaum, N., Scott, B., Seddighzadeh, B., Segal, J., Sen, S., Sikandar, S., Spencer, S. P., Steffes, L., Subramaniam, V. R., Swarup, A., Swift, M., Van Treuren, W., Trimm, E., Veizades, S., Vijayakumar, S., Vo, K. C., Vorperian, S. K., Wang, W., Weinstein, H. N., Winkler, J., Wu, T. T., Xie, J., Yung, A. R., Zhang, Y., Detweiler, A. M., Mekonen, H., Neff, N. F., Sit, R. V., Tan, M., Yan, J., Bean, G. R., Charu, V., Forgo, E., Martin, B. A., Ozawa, M. G., Silva, O., Toland, A., Vemuri, V. N., Afik, S., Awayan, K., Bierman, R., Botvinnik, O. B., Byrne, A., Chen, M., Dehghannasiri, R., Gayoso, A., Granados, A. A., Li, Q., Mahmoudabadi, G., McGeever, A., Olivieri, J. E., Park, M., Ravikumar, N., Stanley, G., Tan, W., Tarashansky, A. J., Vanheusden, R., Wang, P., Wang, S., Xing, G., Xu, C., Yosef, N., Culver, R., Dethlefsen, L., Ho, P., Liu, S., Maltzman, J. S., Metzger, R. J., Sasagawa, K., Sinha, R., Song, H., Wang, B., Artandi, S. E., Beachy, P. A., Clarke, M. F., Giudice, L. C., Huang, F. W., Huang, K. C., Idoyaga, J., Kim, S. K., Kuo, C. S., Nguyen, P., Rando, T. A., Red-Horse, K., Reiter, J., Relman, D. A., Sonnenburg, J. L., Wu, A., Wu, S. M., Wyss-Coray, T. 2022

    Abstract

    Cell-free RNA from liquid biopsies can be analyzed to determine disease tissue of origin. We extend this concept to identify cell types of origin using the Tabula Sapiens transcriptomic cell atlas as well as individual tissue transcriptomic cell atlases in combination with the Human Protein Atlas RNA consensus dataset. We define cell type signature scores, which allow the inference of cell types that contribute to cell-free RNA for a variety of diseases.

    View details for DOI 10.1038/s41587-021-01188-9

    View details for PubMedID 35132263

  • Microbiome assembly in The Gambia. Nature microbiology Carter, M. M., Olm, M. R., Sonnenburg, E. D. 1800

    View details for DOI 10.1038/s41564-021-01036-1

    View details for PubMedID 34972823

  • A randomized crossover trial on the effect of plant-based compared with animal-based meat on trimethylamine-N-oxide and cardiovascular disease risk factors in generally healthy adults: Study With Appetizing Plantfood-Meat Eating Alternative Trial (SWAP-MEAT). The American journal of clinical nutrition Crimarco, A. n., Springfield, S. n., Petlura, C. n., Streaty, T. n., Cunanan, K. n., Lee, J. n., Fielding-Singh, P. n., Carter, M. M., Topf, M. A., Wastyk, H. C., Sonnenburg, E. D., Sonnenburg, J. L., Gardner, C. D. 2020

    Abstract

    Despite the rising popularity of plant-based alternative meats, there is limited evidence of the health effects of these products.We aimed to compare the effect of consuming plant-based alternative meat (Plant) as opposed to animal meat (Animal) on health factors. The primary outcome was fasting serum trimethylamine-N-oxide (TMAO). Secondary outcomes included fasting insulin-like growth factor 1, lipids, glucose, insulin, blood pressure, and weight.SWAP-MEAT (The Study With Appetizing Plantfood-Meat Eating Alternatives Trial) was a single-site, randomized crossover trial with no washout period. Participants received Plant and Animal products, dietary counseling, lab assessments, microbiome assessments (16S), and anthropometric measurements. Participants were instructed to consume ≥2 servings/d of Plant compared with Animal for 8 wk each, while keeping all other foods and beverages as similar as possible between the 2 phases.The 36 participants who provided complete data for both crossover phases included 67% women, were 69% Caucasian, had a mean ± SD age 50 ± 14 y, and BMI 28 ± 5 kg/m2. Mean ± SD servings per day were not different by intervention sequence: 2.5 ± 0.6 compared with 2.6 ± 0.7 for Plant and Animal, respectively (P = 0.76). Mean ± SEM TMAO concentrations were significantly lower overall for Plant (2.7 ± 0.3) than for Animal (4.7 ± 0.9) (P = 0.012), but a significant order effect was observed (P = 0.023). TMAO concentrations were significantly lower for Plant among the n = 18 who received Plant second (2.9 ± 0.4 compared with 6.4 ± 1.5, Plant compared with Animal, P = 0.007), but not for the n = 18 who received Plant first (2.5 ± 0.4 compared with 3.0 ± 0.6, Plant compared with Animal, P = 0.23). Exploratory analyses of the microbiome failed to reveal possible responder compared with nonresponder factors. Mean ± SEM LDL-cholesterol concentrations (109.9 ± 4.5 compared with 120.7 ± 4.5 mg/dL, P = 0.002) and weight (78.7 ± 3.0 compared with 79.6 ± 3.0 kg, P < 0.001) were lower during the Plant phase.Among generally healthy adults, contrasting Plant with Animal intake, while keeping all other dietary components similar, the Plant products improved several cardiovascular disease risk factors, including TMAO; there were no adverse effects on risk factors from the Plant products.This trial was registered at clinicaltrials.gov as NCT03718988.

    View details for DOI 10.1093/ajcn/nqaa203

    View details for PubMedID 32780794