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Gut microbiome remodeling and metabolomic profile improves in response to protein pacing with intermittent fasting versus continuous caloric restriction

Mohr, Alex E., Sweazea, Karen L., Bowes, Devin A., Jasbi, Paniz, Whisner, Corrie M., Sears, Dorothy D., Krajmalnik-Brown, Rosa, Jin, Yan, Gu, Haiwei, Klein-Seetharaman, Judith, Arciero, Karen M., Gumpricht, Eric, Arciero, Paul J.·2024·Nature Communications

Abstract

The gut microbiome (GM) modulates body weight/composition and gastrointestinal functioning; therefore, approaches targeting resident gut microbes have attracted considerable interest. Intermittent fasting (IF) and protein pacing (P) regimens are effective in facilitating weight loss (WL) and enhancing body composition. However, the interrelationships between IF- and P-induced WL and the GM are unknown. The current randomized controlled study describes distinct fecal microbial and plasma metabolomic signatures between combined IF-P (n = 21) versus a heart-healthy, calorie-restricted (CR, n = 20) diet matched for overall energy intake in free-living human participants (women = 27; men = 14) with overweight/obesity for 8 weeks. Gut symptomatology improves and abundance of Christensenellaceae microbes and circulating cytokines and amino acid metabolites favoring fat oxidation increase with IF-P (p < 0.05), whereas metabolites associated with a longevity-related metabolic pathway increase with CR (p < 0.05). Differences indicate GM and metabolomic factors play a role in WL maintenance and body composition. This novel work provides insight into the GM and metabolomic profile of participants following an IF-P or CR diet and highlights important differences in microbial assembly associated with WL and body composition responsiveness. These data may inform future GM-focused precision nutrition recommendations using larger sample sizes of longer duration. Trial registration, March 6, 2020 (ClinicalTrials.gov as NCT04327141), based on a previous randomized intervention trial.

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  • Arciero et al. have shown superior body composition (reduced total body, fat, and visceral fat mass) with twice-weekly fasting compared with continuous energy restriction.

    “In contrast to these findings, Arciero et al. [4,70,71] have shown superior body composition (reduced total body, fat, and visceral fat mass) with TWF compared with CER.”

    From International Society of Sports Nutrition position stand: diets for body weight reduction (2026) · cites this paper as [4]

    The Results report greater losses of body weight and total, abdominal, and visceral fat mass with intermittent fasting–protein pacing than with continuous caloric restriction. But the intervention was a single 36–60-hour modified fasting period each week alongside higher protein intake, not twice-weekly fasting alone; the comparison does not isolate fasting from protein pacing. (LLM, conf=0.85)

    Experimental — accuracy not yet measured
  • For the general population, a daily protein intake of 1.2-1.6 g/kg is appropriate for supporting physical activity and imparting preventive/clinical benefits to musculoskeletal, gut microbiome, and cardiometabolic health.

    “For the general population, a daily protein intake of 1.2–1.6 g/kg is appropriate for supporting physical activity and imparting preventive/clinical benefits to musculoskeletal, gut microbiome, and cardiometabolic health [4,92,101,105].”

    From International Society of Sports Nutrition position stand: diets for body weight reduction (2026) · cites this paper as [4]

    The Results report changes in body composition and gut-microbiome measures with intermittent fasting plus protein pacing in adults with overweight or obesity. The Methods describe protein as a percentage of calories, not a recommended daily intake of 1.2–1.6 g/kg. This intervention does not establish that the stated intake is appropriate for the general population or supports physical activity and all the listed health benefits. (LLM, conf=0.86)

    Experimental — accuracy not yet measured
  • More recent trials by Arciero et al. found that a high-protein/high-frequency approach combined with 1-2 weekly modified fasting days (~500 kcal/day) was superior to conventional control diets for improving body composition in a caloric deficit, most likely driven by enhanced gut microbiome diversity and metabolomic signatures.

    “More recent trials by Arciero et al. [71,91] found that the latter approach (high-protein/high-frequency) combined with 1–2 weekly modified fasting days (~500 kcal/day) was superior to the conventional control diets for improving body composition in a caloric deficit, most likely driven by enhanced gut microbiome diversity and metabolomic signatures [4].”

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  1. Asnicar, F. et al. Microbiome connections with host metabolism and habitual diet from 1,098 deeply phenotyped individuals. Nat. Med. 27, 321–332 (2021). · DOI · Paper page
  2. Li, M. et al. Gut microbiota-bile acid crosstalk contributes to the rebound weight gain after calorie restriction in mice. Nat. Commun. 13, 2060 (2022). · DOI · Paper page
  3. Machado, A. C. D. et al. Diet and feeding pattern modulate diurnal dynamics of the ileal microbiome and transcriptome. Cell Rep. 40, 111008 (2022). · DOI
  4. von Schwartzenberg R.J. et al. Caloric restriction disrupts the microbiota and colonization resistance. Nature 595, 272–277 (2021). · DOI
  5. Maifeld, A. et al. Fasting alters the gut microbiome reducing blood pressure and body weight in metabolic syndrome patients. Nat. Commun. 12, 1970 (2021). · DOI
  6. Corbin, K. D. et al. Host-diet-gut microbiome interactions influence human energy balance: a randomized clinical trial. Nat. Commun. 14, 3161 (2023). · DOI
  7. Arciero, P. J. et al. Increased protein intake and meal frequency reduces abdominal fat during energy balance and energy deficit. Obesity 21, 1357–1366 (2013). · DOI · Paper page
  8. Arciero, P. J. et al. Protein-pacing caloric-restriction enhances body composition similarly in obese men and women during weight loss and sustains efficacy during long-term weight maintenance. Nutrients 8, 476 (2016). · DOI · Paper page
  9. Mohr, A. E. et al. Exploratory analysis of one versus two-day intermittent fasting protocols on the gut microbiome and plasma metabolome in adults with overweight/obesity. Front. Nutr. 9, 1036080 (2022). · DOI
  10. He, F., Zuo, L., Ward, E. & Arciero, P. J. Serum polychlorinated biphenyls increase and oxidative stress decreases with a protein-pacing caloric restriction diet in obese men and women. Int. J. Environ. Res. Public Health 14, 59 (2017). · DOI
  11. Zuo, L. et al. Comparison of high-protein, intermittent fasting low-calorie diet and heart healthy diet for vascular health of the obese. Front. Physiol. 7, 350 (2016). · DOI
  12. Zhong, W. et al. High-protein diet prevents fat mass increase after dieting by counteracting Lactobacillus-enhanced lipid absorption. Nat. Metab. 4, 1713–1731 (2022). · DOI
  13. Arciero, P. J. et al. Intermittent fasting and protein pacing are superior to caloric restriction for weight and visceral fat loss. Obesity 31, 139–149 (2023). · DOI · Paper page
  14. Lichtenstein, A. H. et al. 2021 Dietary guidance to improve cardiovascular health: a scientific statement from the american heart association. Circulation 144, e472–e487 (2021). · DOI · Paper page
  15. Lozupone, C. A., Stombaugh, J. I., Gordon, J. I., Jansson, J. K. & Knight, R. Diversity, stability and resilience of the human gut microbiota. Nature 489, 220–230 (2012). · DOI · Paper page
  16. Waters, J. L. & Ley, R. E. The human gut bacteria Christensenellaceae are widespread, heritable, and associated with health. BMC Biol. 17, 83 (2019). · DOI
  17. Tavella, T. et al. Elevated gut microbiome abundance of Christensenellaceae, Porphyromonadaceae and Rikenellaceae is associated with reduced visceral adipose tissue and healthier metabolic profile in Italian elderly. Gut Microbes 13, 1880221 (2021). · DOI
  18. Bischoff, S. C. et al. Gut microbiota patterns predicting long-term weight loss success in individuals with obesity undergoing nonsurgical therapy. Nutrients 14, 3182 (2022). · DOI
  19. Vieira-Silva, S. et al. Species–function relationships shape ecological properties of the human gut microbiome. Nat. Microbiol. 1, 16088 (2016). · DOI
  20. Cummings, J. H. & Macfarlane, G. T. The control and consequences of bacterial fermentation in the human colon. J. Appl. Bacteriol. 70, 443–459 (1991). · DOI · Paper page
  21. Atzeni, A. et al. Taxonomic and functional fecal microbiota signatures associated with insulin resistance in non-diabetic subjects with overweight/obesity within the frame of the PREDIMED-plus study. Front. Endocrinol. 13, 804455 (2022). · DOI
  22. Oliver, A. et al. High-fiber, whole-food dietary intervention alters the human gut microbiome but not fecal short-chain fatty acids. Msystems 6, e00115–e00121 (2021). · DOI · Paper page
  23. Bendiks, Z. A., Knudsen, K. E. B., Keenan, M. J. & Marco, M. L. Conserved and variable responses of the gut microbiome to resistant starch type 2. Nutr. Res. 77, 12–28 (2020). · DOI
  24. Boulangé, C. L., Neves, A. L., Chilloux, J., Nicholson, J. K. & Dumas, M.-E. Impact of the gut microbiota on inflammation, obesity, and metabolic disease. Genome Med 8, 42 (2016). · DOI · Paper page
  25. Shiau, M.-Y. et al. Mechanism of interleukin-4 reducing lipid deposit by regulating hormone-sensitive lipase. Sci. Rep. 9, 11974 (2019). · DOI
  26. Bruun, J. M., Pedersen, S. B., Kristensen, K. & Richelsen, B. Opposite regulation of interleukin‐8 and tumor necrosis factor‐α by weight loss. Obes. Res. 10, 499–506 (2002). · DOI
  27. Steensberg, A. et al. Production of interleukin‐6 in contracting human skeletal muscles can account for the exercise‐induced increase in plasma interleukin‐6. J. Physiol. 529, 237–242 (2000). · DOI · Paper page
  28. Hall et al. Interleukin-6 stimulates lipolysis and fat oxidation in humans. J. Clin. Endocrinol. Metab. 88, 3005–3010 (2003). · DOI · Paper page
  29. Wueest, S. et al. Interleukin-6 contributes to early fasting-induced free fatty acid mobilization in mice. Am. J. Physiol. Regul. Integr. Comp. Physiol. 306, R861–R867 (2014). · DOI
  30. Wu, D. et al. Interleukin-13 (IL-13)/IL-13 receptor α1 (IL-13Rα1) signaling regulates intestinal epithelial cystic fibrosis transmembrane conductance regulator channel-dependent Cl− secretion. J. Biol. Chem. 286, 13357–13369 (2011). · DOI
  31. Gamage, H. K. A. H. et al. Intermittent fasting has a diet-specific impact on the gut microbiota and colonic mucin O-glycosylation of mice. Preprint at bioRxiv https://doi.org/10.1101/2022.09.15.508181 (2022). · DOI
  32. Song, E.-J., Shin, N. R., Jeon, S., Nam, Y.-D. & Kim, H. Lorcaserin and phentermine exert anti-obesity effects with modulation of the gut microbiota. Front. Microbiol. 13, 1109651 (2023). · DOI
  33. Wang, M. et al. Olive fruit extracts supplement improve antioxidant capacity via altering colonic microbiota composition in mice. Front. Nutr. 8, 645099 (2021). · DOI
  34. Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010). · DOI · Paper page
  35. Mohr, A. E., Crawford, M., Jasbi, P., Fessler, S. & Sweazea, K. L. Lipopolysaccharide and the gut microbiota: considering structural variation. FEBS Lett. 596, 849–875 (2022). · DOI
  36. Teruya, T., Chaleckis, R., Takada, J., Yanagida, M. & Kondoh, H. Diverse metabolic reactions activated during 58-hr fasting are revealed by non-targeted metabolomic analysis of human blood. Sci. Rep. 9, 854 (2019). · DOI
  37. Collet, T.-H. et al. A metabolomic signature of acute caloric restriction. J. Clin. Endocrinol. Metab. 102, 4486–4495 (2017). · DOI
  38. Vázquez-Fresno, R. et al. Metabolomic pattern analysis after mediterranean diet intervention in a nondiabetic population: a 1- and 3-year follow-up in the PREDIMED study. J. Proteome Res. 14, 531–540 (2015). · DOI
  39. Sankaranarayanan, R., Kumar, D. R., Patel, J. & Bhat, G. J. Do aspirin and flavonoids prevent cancer through a common mechanism involving hydroxybenzoic acids?—The metabolite hypothesis. Molecules 25, 2243 (2020). · DOI
  40. Aon, M. A. et al. Untangling determinants of enhanced health and lifespan through a multi-omics approach in mice. Cell Metab. 32, 100–116.e4 (2020). · DOI
  41. Sekhar, R. V. et al. Glutathione synthesis is diminished in patients with uncontrolled diabetes and restored by dietary supplementation with cysteine and glycine. Diabetes Care 34, 162–167 (2011). · DOI
  42. Nguyen, D., Hsu, J. W., Jahoor, F. & Sekhar, R. V. Effect of increasing glutathione with cysteine and glycine supplementation on mitochondrial fuel oxidation, insulin sensitivity, and body composition in older HIV-infected patients. J. Clin. Endocrinol. Metab. 99, 169–177 (2014). · DOI
  43. Chen, L. et al. Glycine transporter-1 and glycine receptor mediate the antioxidant effect of glycine in diabetic rat islets and INS-1 cells. Free Radic. Biol. Med. 123, 53–61 (2018). · DOI
  44. Breum, L., Rasmussen, M. H., Hilsted, J. & Fernstrom, J. D. Twenty-four–hour plasma tryptophan concentrations and ratios are below normal in obese subjects and are not normalized by substantial weight reduction 1, 2, 3. Am. J. Clin. Nutr. 77, 1112–1118 (2003). · DOI
  45. Fernstrom, J. D. et al. Diurnal variations in plasma concentrations of tryptophan, tryosine, and other neutral amino acids: effect of dietary protein intake. Am. J. Clin. Nutr. 32, 1912–1922 (1979). · DOI
  46. Chen, L. et al. Influence of the microbiome, diet and genetics on inter-individual variation in the human plasma metabolome. Nat. Med. 28, 2333–2343 (2022). · DOI · Paper page
  47. Argelaguet, R. et al. Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets. Mol. Syst. Biol. 14, e8124 (2018). · DOI · Paper page
  48. Anderson, E. M. et al. Temporal dynamics of the intestinal microbiome following short-term dietary restriction. Nutrients 14, 2785 (2022). · DOI
  49. Gerritsen, J. et al. A comparative and functional genomics analysis of the genus Romboutsia provides insight into adaptation to an intestinal lifestyle. Preprint at bioRxiv https://doi.org/10.1101/845511 (2019). · DOI
  50. Caldovic, L. et al. N-acetylglutamate synthase: structure, function and defects. Mol. Genet. Metab. 100, S13–S19 (2010). · DOI
  51. Parker, B. J., Wearsch, P. A., Veloo, A. C. M. & Rodriguez-Palacios, A. The genus Alistipes: gut bacteria with emerging implications to inflammation, cancer, and mental health. Front. Immunol. 11, 906 (2020). · DOI
  52. Yang, J. et al. Oscillospira - a candidate for the next-generation probiotics. Gut Microbes 13, 1987783 (2021). · DOI
  53. Gomez-Arango, L. F. et al. Low dietary fiber intake increases Collinsella abundance in the gut microbiota of overweight and obese pregnant women. Gut Microbes 9, 189–201 (2018). · DOI
  54. Astbury, S. et al. Lower gut microbiome diversity and higher abundance of proinflammatory genus Collinsella are associated with biopsy-proven nonalcoholic steatohepatitis. Gut Microbes 11, 569–580 (2020). · DOI
  55. Lim, R. R. X. et al. Gut microbiome responses to dietary intervention with hypocholesterolemic vegetable oils. npj Biofilms Microbiomes 8, 24 (2022). · DOI
  56. Louis, P. & Flint, H. J. Diversity, metabolism and microbial ecology of butyrate‐producing bacteria from the human large intestine. FEMS Microbiol. Lett. 294, 1–8 (2009). · DOI · Paper page
  57. Bui, T. P. N. et al. Mutual metabolic interactions in co-cultures of the intestinal Anaerostipes rhamnosivorans with an acetogen, methanogen, or pectin-degrader affecting butyrate production. Front. Microbiol. 10, 2449 (2019). · DOI
  58. Kaci, G. et al. Anti-inflammatory properties of streptococcus salivarius, a commensal bacterium of the oral cavity and digestive tract. Appl. Environ. Microbiol. 80, 928–934 (2014). · DOI
  59. Couvigny, B. et al. Commensal streptococcus salivarius modulates PPARγ transcriptional activity in human intestinal epithelial cells. PLoS ONE 10, e0125371 (2015). · DOI
  60. Barcenilla, A. et al. Phylogenetic relationships of butyrate-producing bacteria from the human gut. Appl. Environ. Microbiol. 66, 1654–1661 (2000). · DOI
  61. Scott, K. P. et al. Substrate-driven gene expression in Roseburia inulinivorans: importance of inducible enzymes in the utilization of inulin and starch. Proc. Natl Acad. Sci. USA 108, 4672–4679 (2011). · DOI
  62. Hosomi, K. et al. Oral administration of Blautia wexlerae ameliorates obesity and type 2 diabetes via metabolic remodeling of the gut microbiota. Nat. Commun. 13, 4477 (2022). · DOI
  63. Bui, T. P. N. et al. Conversion of dietary inositol into propionate and acetate by commensal Anaerostipes associates with host health. Nat. Commun. 12, 4798 (2021). · DOI
  64. Brahe, L. K. et al. Specific gut microbiota features and metabolic markers in postmenopausal women with obesity. Nutr. Diabetes 5, e159–e159 (2015). · DOI
  65. Deaver, J. A., Eum, S. Y. & Toborek, M. Circadian disruption changes gut microbiome taxa and functional gene composition. Front Microbiol 09, 737 (2018). · DOI
  66. Ze, X., Duncan, S. H., Louis, P. & Flint, H. J. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon. ISME J. 6, 1535–1543 (2012). · DOI · Paper page
  67. Ngai, P. H. K., Zhao, Z. & Ng, T. B. Agrocybin, an antifungal peptide from the edible mushroom Agrocybe cylindracea. Peptides 26, 191–196 (2005). · DOI
  68. Sánchez, M. et al. Modulatory effect of intestinal polyamines and trace amines on the spontaneous phasic contractions of the isolated ileum and colon rings of mice. Food Nutr. Res. 61, 1321948 (2017). · DOI
  69. Lassen, P. B. et al. Protein supplementation during an energy-restricted diet induces visceral fat loss and gut microbiota amino acid metabolism activation: a randomized trial. Sci. Rep. 11, 15620 (2021). · DOI
  70. Mazier, W. et al. A new strain of christensenella minuta as a potential biotherapy for obesity and associated metabolic diseases. Cells 10, 823 (2021). · DOI
  71. Salazar, N. et al. Fecal metabolome and bacterial composition in severe obesity: impact of diet and bariatric surgery. Gut Microbes 14, 2106102 (2022). · DOI
  72. Svedlund, J., Sjödin, I. & Dotevall, G. GSRS—clinical rating scale for gastrointestinal symptoms in patients with irritable bowel syndrome and peptic ulcer disease. Dig. Dis. Sci. 33, 129–134 (1988). · DOI
  73. Kulich, K. R. et al. Reliability and validity of the Gastrointestinal Symptom Rating Scale (GSRS) and Quality of Life in Reflux and Dyspepsia (QOLRAD) questionnaire in dyspepsia: a six-country study. Health Qual. Life Out. 6, 12 (2008). · DOI
  74. Riegler, G. & Esposito, I. Bristol scale stool form. A still valid help in medical practice and clinical research. Tech. Coloproctol. 5, 163–164 (2001). · DOI
  75. Yang, Y.-W. et al. Use of 16S rRNA gene-targeted group-specific primers for real-time PCR analysis of predominant bacteria in mouse feces. Appl. Environ. Microbiol. 81, 6749–6756 (2015). · DOI
  76. Gregoris, T. B. D., Aldred, N., Clare, A. S. & Burgess, J. G. Improvement of phylum- and class-specific primers for real-time PCR quantification of bacterial taxa. J. Microbiol. Methods 86, 351–356 (2011). · DOI
  77. Caporaso, J. G. et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl Acad. Sci. USA 108, 4516–4522 (2010). · DOI
  78. Caporaso, J. G. et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 6, 1621–1624 (2012). · DOI · Paper page
  79. Bokulich, N. A. et al. Optimizing taxonomic classification of marker-gene amplicon sequences with QIIME 2’s q2-feature-classifier plugin. Microbiome 6, 90 (2018). · DOI
  80. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590–D596 (2012). · DOI · Paper page
  81. McKnight, D. T. et al. Methods for normalizing microbiome data: an ecological perspective. Methods Ecol. Evol. 10, 389–400 (2019). · DOI
  82. Langmead, B. & Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357–359 (2012). · DOI · Paper page
  83. Bapat, A. et al. Hypoxia promotes erythroid differentiation through the development of progenitors and proerythroblasts. Exp. Hematol. 97, 32–46.e35 (2021). · DOI
  84. Jasbi, P. et al. Metabolic profiling of neocortical tissue discriminates Alzheimer’s disease from mild cognitive impairment, high pathology controls, and normal controls. J. Proteome Res. 20, 4303–4317 (2021). · DOI
  85. Jasbi, P. et al. Microbiome and metabolome profiles of high screen time in a cohort of healthy college students. Sci. Rep. 12, 3452 (2022). · DOI
  86. Basile, A. J. et al. A four-week white bread diet does not alter plasma glucose concentrations, metabolic or vascular physiology in mourning doves, Zenaida macroura. Comp. Biochem. Physiol. Part A Mol. Integr. Physiol. 247, 110718 (2020). · DOI
  87. Johnston, C. S. et al. Daily vinegar ingestion improves depression scores and alters the metabolome in healthy adults: a randomized controlled trial. Nutrients 13, 4020 (2021). · DOI
  88. Gu, H., Shi, X., Jasbi, P. & Patterson, J. Viruses as therapeutics, methods and protocols. Methods Mol. Biol. 2225, 179–197 (2020). · DOI
  89. He, H. et al. An integrative cellular metabolomic study reveals downregulated tricarboxylic acid cycle and potential biomarkers induced by tetrabromobisphenol A in human lung A549 cells. Environ. Toxicol. 38, 7–16 (2023). · DOI
  90. Mohr, A. E. et al. Association of food insecurity on gut microbiome and metabolome profiles in a diverse college-based sample. Sci. Rep. 12, 14358 (2022). · DOI
  91. Gu, H., Jasbi, P., Patterson, J. & Jin, Y. Enhanced detection of short‐chain fatty acids using gas chromatography mass spectrometry. Curr. Protoc. 1, e177 (2021). · DOI
  92. Qi, Y. et al. Metabolomics study of resina draconis on myocardial ischemia rats using ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry combined with pattern recognition methods and metabolic pathway analysis. Évid. Based Complement. Altern. Med. 2013, 438680 (2013).
  93. Yao, W. et al. Integrated plasma and urine metabolomics coupled with HPLC/QTOF-MS and chemometric analysis on potential biomarkers in liver injury and hepatoprotective effects of Er-Zhi-Wan. Anal. Bioanal. Chem. 406, 7367–7378 (2014). · DOI
  94. Wei, Y. et al. Early breast cancer detection using untargeted and targeted metabolomics. J. Proteome Res. 20, 3124–3133 (2021). · DOI
  95. Haak, B. W. et al. Integrative transkingdom analysis of the gut microbiome in antibiotic perturbation and critical illness. mSystems 6, e01148–20 (2021). · DOI
  96. McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLos One 8, e61217 (2013). · DOI
  97. Bokulich, N. A. et al. q2-longitudinal: longitudinal and paired-sample analyses of microbiome data. Msystems 3, e00219–18 (2018). · DOI
  98. Pang, Z. et al. MetaboAnalyst 5.0: narrowing the gap between raw spectra and functional insights. Nucleic Acids Res. 49, W388–W396 (2021). · DOI
  99. Kanehisa, M. & Goto, S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 28, 27–30 (2000). · DOI · Paper page
  100. Mirzayi, C. et al. Reporting guidelines for human microbiome research: the STORMS checklist. Nat. Med. 27, 1885–1892 (2021). · DOI

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Metadata

Authors
Mohr, A. E., Sweazea, K. L., Bowes, D. A., Jasbi, P., Whisner, C. M., Sears, D. D., Krajmalnik-Brown, R., Jin, Y., Gu, H., Klein-Seetharaman, J., Arciero, K. M., Gumpricht, E., & Arciero, P. J.
Venue
Nature Communications
Published
2024-05-28
Volume
15
Issue
1
ISSN
2041-1723
Cited by
80
References
13
Language
en
Funders
Isagenix International LLC

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