Koropatkin, N. M., Cameron, E. A. & Martens, E. C. How glycan metabolism shapes the human gut microbiota. Nat. Rev. Microbiol. 10, 323–335 (2012).
Fan, Y. & Pedersen, O. Gut microbiota in human metabolic health and disease. Nat. Rev. Microbiol. 19, 55–71 (2021).
Hamaker, B. R. & Tuncil, Y. E. A perspective on the complexity of dietary fiber structures and their potential effect on the gut microbiota. J. Mol. Biol. 426, 3838–3850 (2014).
Morrison, D. J. & Preston, T. Formation of short chain fatty acids by the gut microbiota and their impact on human metabolism. Gut Microbes 7, 189–200 (2016).
Koh, A., De Vadder, F., Kovatcheva-Datchary, P. & Bäckhed, F. From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 165, 1332–1345 (2016).
Huttenhower, C. et al. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).
Nikaido, H. Molecular basis of bacterial outer membrane permeability revisited. Microbiol. Mol. Biol. Rev. 67, 593–656 (2003).
Martens, E. C., Koropatkin, N. M., Smith, T. J. & Gordon, J. I. Complex glycan catabolism by the human gut microbiota: the Bacteroidetes Sus-like paradigm. J. Biol. Chem. 284, 24673–24677 (2009).
Bolam, D. N. & van den Berg, B. TonB-dependent transport by the gut microbiota: novel aspects of an old problem. Curr. Opin. Struct. Biol. 51, 35–43 (2018).
Glenwright, A. J. et al. Structural basis for nutrient acquisition by dominant members of the human gut microbiota. Nature 541, 407–411 (2017).
Madej, M. et al. Structural and functional insights into oligopeptide acquisition by the RagAB transporter from Porphyromonas gingivalis. Nat. Microbiol. 5, 1016–1025 (2020).
Gray, D. A. et al. Insights into SusCD-mediated glycan import by a prominent gut symbiont. Nat. Commun. 12, 44 (2021).
Terrapon, N. et al. PULDB: the expanded database of polysaccharide utilization loci. Nucleic Acids Res. 46, D677–D683 (2018).
Sonnenburg, E. D. et al. Specificity of polysaccharide use in intestinal bacteroides species determines diet-induced microbiota alterations. Cell 141, 1241–1252 (2010).
Öner, E. T., Hernández, L. & Combie, J. Review of Levan polysaccharide: from a century of past experiences to future prospects. Biotechnol. Adv. 34, 827–844 (2016).
Mardo, K. et al. A highly active endo-levanase BT1760 of a dominant mammalian gut commensal Bacteroides thetaiotaomicron cleaves not only various bacterial levans, but also levan of timothy grass. PLoS ONE 12, e0169989 (2017).
Bolam, D. N. & Sonnenburg, J. L. Mechanistic insight into polysaccharide use within the intestinal microbiota. Gut Microbes 2, 86–90 (2011).
Reeves, A. R., Wang, G. R. & Salyers, A. A. Characterization of four outer membrane proteins that play a role in utilization of starch by Bacteroides thetaiotaomicron. J. Bacteriol. 179, 643–649 (1997).
Cho, K. H. & Salyers, A. A. Biochemical analysis of interactions between outer membrane proteins that contribute to starch utilization by Bacteroides thetaiotaomicron. J. Bacteriol. 183, 7224–7230 (2001).
Karunatilaka, K. S., Cameron, E. A., Martens, E. C., Koropatkin, N. M. & Biteen, J. S. Superresolution imaging captures carbohydrate utilization dynamics in human gut symbionts. mBio 5, e02172 (2014).
Tuson, H. H., Foley, M. H., Koropatkin, N. M. & Biteen, J. S. The starch utilization system assembles around stationary starch-binding proteins. Biophys. J. 115, 242–250 (2018).
Schwanhüusser, B. et al. Global quantification of mammalian gene expression control. Nature 473, 337–342 (2011).
Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021).
Tamura, K. & Brumer, H. Glycan utilization systems in the human gut microbiota: a gold mine for structural discoveries. Curr. Opin. Struct. Biol. 68, 26–40 (2020).
Nilaweera, T. D., Nyenhuis, D. A. & Cafiso, D. S. Structural intermediates observed only in intact Escherichia coli indicate a mechanism for TonB-dependent transport. eLife 10, e68548 (2021).
Zmyslowski, A. M., Baxa, M. C., Gagnon, I. A. & Sosnick, T. R. HDX-MS performed on BtuB in E. coli outer membranes delineates the luminal domain’s allostery and unfolding upon B12 and TonB binding. Proc. Natl Acad. Sci. USA 119, e2119436119 (2022).
Cuyvers, S., Dornez, E., Delcour, J. A. & Courtin, C. M. Occurrence and functional significance of secondary carbohydrate binding sites in glycoside hydrolases. Crit. Rev. Biotechnol. 32, 93–107 (2011).
Ernits, K., Eek, P., Lukk, T., Visnapuu, T. & Alamäe, T. First crystal structure of an endo-levanase – the BT1760 from a human gut commensal Bacteroides thetaiotaomicron. Sci. Rep. 9, 8443 (2019).
Tamura, K. et al. Surface glycan-binding proteins are essential for cereal beta-glucan utilization by the human gut symbiont Bacteroides ovatus. Cell. Mol. Life Sci. 76, 4319–4340 (2019).
Tamura, K., Dejean, G., Van Petegem, F. & Brumer, H. Distinct protein architectures mediate species-specific beta-glucan binding and metabolism in the human gut microbiota. J. Biol. Chem. 296, 100415 (2021).
Grondin, J. M., Tamura, K., Déjean, G., Abbott, D. W. & Brumer, H. Polysaccharide utilization loci: fueling microbial communities. J. Bacteriol. 199, e00860-16 (2017).
McKee, L. S. et al. Polysaccharide degradation by the Bacteroidetes: mechanisms and nomenclature. Environ. Microbiol. Rep. 13, 559–581 (2021).
Rassam, P. et al. Supramolecular assemblies underpin turnover of outer membrane proteins in bacteria. Nature 523, 333–336 (2015).
Benn, G. et al. Phase separation in the outer membrane of Escherichia coli. Proc. Natl Acad. Sci. USA 118, e2112237118 (2021).
Briliūtė, J. et al. Complex N-glycan breakdown by gut Bacteroides involves an extensive enzymatic apparatus encoded by multiple co-regulated genetic loci. Nat. Microbiol. 4, 1571–1581 (2019).
Martens, E. C. et al. Recognition and degradation of plant cell wall polysaccharides by two human gut symbionts. PLoS Biol. 9, e1001221 (2011).
Ndeh, D. et al. Complex pectin metabolism by gut bacteria reveals novel catalytic functions. Nature 544, 65–70 (2017).
Ritchie, M. E. et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res. 43, e47 (2015).
Ramlaul, K., Palmer, C. M. & Aylett, C. H. S. A local agreement filtering algorithm for transmission EM reconstructions. J. Struct. Biol. 205, 30–40 (2019).
Koropatkin, N. M., Martens, E. C., Gordon, J. I. & Smith, T. J. Starch catabolism by a prominent human gut symbiont is directed by the recognition of amylose helices. Structure 16, 1105–1115 (2008).
Zougman, A., Selby, P. J. & Banks, R. E. Suspension trapping (STrap) sample preparation method for bottom-up proteomics analysis. Proteomics 14, 1006-1000 (2014).
HaileMariam, M. et al. S-Trap, an ultrafast sample-preparation approach for shotgun proteomics. J. Proteome Res. 17, 2917–2924 (2018).
Cox, J. & Mann, M. MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 26, 1367–1372 (2008).
Cox, J. et al. Andromeda: a peptide search engine integrated into the MaxQuant environment. J. Proteome Res. 10, 1794–1805 (2011).
Winter, G. et al. DIALS: implementation and evaluation of a new integration package. Acta Crystallogr. D 74, 85–97 (2018).
Winter, G. Xia2: an expert system for macromolecular crystallography data reduction. J. Appl. Crystallogr. 43, 186–190 (2010).
Evans, P. R. & Murshudov, G. N. How good are my data and what is the resolution? Acta Crystallogr. D 69, 1204–1214 (2013).
Evans, P. Scaling and assessment of data quality. Acta Crystallogr. D 62, 72–82 (2006).
Skubak, P. et al. A new MR-SAD algorithm for the automatic building of protein models from low-resolution X-ray data and a poor starting model. Int. Union of Crystallogr. J. 5, 166–171 (2018).
Kabsch, W. XDS. Acta Crystallogr. D 66, 125–132 (2010).
Krissinel, E., Uski, V., Lebedev, A., Winn, M. & Ballard, C. Distributed computing for macromolecular crystallography. Acta Crystallogr. D 74, 143–151 (2018).
Vagin, A. A. et al. REFMAC5 dictionary: organization of prior chemical knowledge and guidelines for its use. Acta Crystallogr. D 60, 2184–2195 (2004).
Emsley, P., Lohkamp, B., Scott, W. G. & Cowtan, K. Features and development of Coot. Acta Crystallogr. D 66, 486–501 (2010).
Winn, M. D. et al. Overview of the CCP4 suite and current developments. Acta Crystallogr. D 67, 235–242 (2011).
Liebschner, D. et al. Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix. Acta Crystallogr. D 75, 861–877 (2019).
Zivanov, J. et al. New tools for automated high-resolution cryo-EM structure determination in RELION-3. eLife 7, e42166 (2018).
Zheng, S. Q. et al. MotionCor2: anisotropic correction of beam-induced motion for improved cryo-electron microscopy. Nat. Methods 14, 331–332 (2017).
Zhang, K. Gctf: real-time CTF determination and correction. J. Struct. Biol. 193, 1–12 (2016).
Wagner, T. et al. SPHIRE-crYOLO is a fast and accurate fully automated particle picker for cryo-EM. Commun. Biol. 2, 218 (2019).
Pettersen, E. F. et al. UCSF Chimera-a visualization system for exploratory research and analysis. J. Comput. Chem. 25, 1605–1612 (2004).
Rohou, A. & Grigorieff, N. CTFFIND4: fast and accurate defocus estimation from electron micrographs. J. Struct. Biol. 192, 216–221 (2015).
Hoh, S. W., Burnley, T. & Cowtan, K. Current approaches for automated model building into cryo-EM maps using Buccaneer with CCP-EM. Acta Crystallogr. D 76, 531–541 (2020).
Burnley, T., Palmer, C. M. & Winn, M. Recent developments in the CCP-EM software suite. Acta Crystallogr. D 73, 469–477 (2017).
Goddard, T. D. et al. UCSF ChimeraX: meeting modern challenges in visualization and analysis. Protein Sci. 27, 14–25 (2018).
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