Prabakaran S, Lippens G, Steen H, Gunawardena J. Post‐translational modification: nature’s escape from genetic imprisonment and the basis for dynamic information encoding. Wiley Interdiscip Rev Syst Biol Med. 2012;4:565–83.
Google Scholar
Khoury GA, Baliban RC, Floudas CA. Proteome-wide post-translational modification statistics: frequency analysis and curation of the swiss-prot database. Sci Rep. 2011;1:90.
Google Scholar
den Ridder M, Daran-Lapujade P, Pabst M. Shot-gun proteomics: why thousands of unidentified signals matter. FEMS Yeast Res. 2020;20:foz088.
Google Scholar
Spoel SH. Orchestrating the proteome with post-translational modifications. Oxford University Press UK. 2018;19:4499–4503.
Varki A, Cummings RD, Esko JD, Freeze HH, Stanley P, Bertozzi CR, et al. Essentials of glycobiology. 3rd edition. (Cold Spring Harbor Laboratory Press, New York, 2015–2017).
Varki A. Evolutionary forces shaping the Golgi glycosylation machinery: why cell surface glycans are universal to living cells. Cold Spring Harb Perspect Biol. 2011;3:a005462.
Google Scholar
Varki A, Lowe JB. Biological roles of glycans. In: Varki A. Essentials of glycobiology. 2nd edition (Cold Spring Harbor Laboratory Press, New York, 2009). pp 75–88.
Herget S, Toukach PV, Ranzinger R, Hull WE, Knirel YA, Von der Lieth C-W. Statistical analysis of the Bacterial Carbohydrate Structure Data Base (BCSDB): characteristics and diversity of bacterial carbohydrates in comparison with mammalian glycans. BMC Struct Biol. 2008;8:1–20.
Google Scholar
Schäffer C, Messner P. Emerging facets of prokaryotic glycosylation. FEMS Microbiol Rev. 2017;41:49–91.
Google Scholar
Eichler J, Koomey M. Sweet new roles for protein glycosylation in prokaryotes. Trends Microbiol. 2017;25:662–72.
Google Scholar
Eichler J. Extreme sweetness: protein glycosylation in archaea. Nat Rev Microbiol. 2013;11:151.
Google Scholar
Kleikamp HB, Lin YM, McMillan DG, Geelhoed JS, Naus-Wiezer SN, Van Baarlen P, et al. Tackling the chemical diversity of microbial nonulosonic acids–a universal large-scale survey approach. Chem Sci. 2020;11:3074–80.
Google Scholar
Boleij M, Kleikamp H, Pabst M, Neu TR, Van Loosdrecht MC, Lin Y. Decorating the anammox house: sialic acids and sulfated glycosaminoglycans in the extracellular polymeric substances of anammox granular sludge. Environ Sci Technol. 2020;54:5218–26.
Google Scholar
Bucci M. A gut reaction. Nat Chem Biol. 2020;16:363-.
Google Scholar
Conrad R. The global methane cycle: recent advances in understanding the microbial processes involved. Environ Microbiol Rep. 2009;1:285–92.
Google Scholar
Lam P, Lavik G, Jensen MM, van de Vossenberg J, Schmid M, Woebken D, et al. Revising the nitrogen cycle in the Peruvian oxygen minimum zone. Proc Natl Acad Sci. 2009;106:4752–7.
Google Scholar
Strous M, Pelletier E, Mangenot S, Rattei T, Lehner A, Taylor MW, et al. Deciphering the evolution and metabolism of an anammox bacterium from a community genome. Nature. 2006;440:790.
Google Scholar
Kartal B, Kuenen JV, Van Loosdrecht M. Sewage treatment with anammox. Science. 2010;328:702–3.
Google Scholar
van Niftrik L, Jetten MS. Anaerobic ammonium-oxidizing bacteria: unique microorganisms with exceptional properties. Microbiol Mol Biol Rev. 2012;76:585–96.
Google Scholar
Fuerst JA, Sagulenko E. Beyond the bacterium: planctomycetes challenge our concepts of microbial structure and function. Nat Rev Microbiol. 2011;9:403.
Google Scholar
Van Teeseling MC, Mesman RJ, Kuru E, Espaillat A, Cava F, Brun YV, et al. Anammox Planctomycetes have a peptidoglycan cell wall. Nat Commun. 2015;6:6878.
Google Scholar
Jeske O, Schüler M, Schumann P, Schneider A, Boedeker C, Jogler M, et al. Planctomycetes do possess a peptidoglycan cell wall. Nat Commun. 2015;6:7116.
Google Scholar
van Teeseling MC, Maresch D, Rath CB, Figl R, Altmann F, Jetten MS, et al. The S-layer protein of the anammox bacterium Kuenenia stuttgartiensis is heavily O-glycosylated. Front Microbiol. 2016;7:1721.
Google Scholar
van Teeseling MC, de Almeida NM, Klingl A, Speth DR, den Camp HJO, Rachel R, et al. A new addition to the cell plan of anammox bacteria:“Candidatus Kuenenia stuttgartiensis” has a protein surface layer as the outermost layer of the cell. J Bacteriol. 2014;196:80–9.
Google Scholar
Boleij M, Pabst M, Neu TR, van Loosdrecht MC, Lin Y. Identification of glycoproteins isolated from extracellular polymeric substances of full-scale anammox granular sludge. Environ Sci Technol. 2018;52:13127–35.
Google Scholar
Gerbino E, Carasi P, Mobili P, Serradell M, Gómez-Zavaglia A. Role of S-layer proteins in bacteria. World J Microbiol Biotechnol. 2015;31:1877–87.
Google Scholar
Sleytr UB, Schuster B, Egelseer E-M, Pum D. S-layers: principles and applications. FEMS Microbiol Rev. 2014;38:823–64.
Google Scholar
Schuster B, Sleytr UB. Relevance of glycosylation of S-layer proteins for cell surface properties. Acta biomaterialia. 2015;19:149–57.
Google Scholar
Tamir A, Eichler J N-Glycosylation is important for proper Haloferax volcanii S-layer stability and function. Appl Environ Microbiol. 2017;83:e03152-16.
Wang F, Cvirkaite-Krupovic V, Kreutzberger MA, Su Z, de Oliveira GA, Osinski T, et al. An extensively glycosylated archaeal pilus survives extreme conditions. Nat Microbiol. 2019;4:1401–10.
Li P-N, Herrmann J, Tolar BB, Poitevin F, Ramdasi R, Bargar JR, et al. Nutrient transport suggests an evolutionary basis for charged archaeal surface layer proteins. ISME J. 2018;12:2389–402.
Google Scholar
Posch G, Pabst M, Brecker L, Altmann F, Messner P, Schäffer C. Characterization and scope of S-layer protein O-glycosylation in Tannerella forsythia. J Biol Chem. 2011;286:38714–24.
Google Scholar
Benz I, Schmidt MA. Never say never again: protein glycosylation in pathogenic bacteria. Mol Microbiol. 2002;45:267–76.
Google Scholar
Sekot G, Posch G, Messner P, Matejka M, Rausch-Fan X, Andrukhov O, et al. Potential of the Tannerella forsythia S-layer to delay the immune response. J Dent Res. 2011;90:109–14.
Google Scholar
Szymanski CM, Burr DH, Guerry P. Campylobacter protein glycosylation affects host cell interactions. Infect Immun. 2002;70:2242.
Google Scholar
Drickamer K, Taylor ME. Evolving views of protein glycosylation. Trends Biochem Sci. 1998;23:321–4.
Google Scholar
Koomey M. O-linked protein glycosylation in bacteria: snapshots and current perspectives. Curr Opin Struct Biol. 2019;56:198–203.
Google Scholar
Wang N, Anonsen JH, Hadjineophytou C, Reinar WB, Børud B, Vik Å, et al. Allelic polymorphisms in a glycosyltransferase gene shape glycan repertoire in the O-linked protein glycosylation system of Neisseria. Glycobiology. 2021;31:477–91.
Google Scholar
Stadlmann J, Taubenschmid J, Wenzel D, Gattinger A, Dürnberger G, Dusberger F, et al. Comparative glycoproteomics of stem cells identifies new players in ricin toxicity. Nature. 2017;549:538–42.
Google Scholar
Polasky DA, Yu F, Teo GC, Nesvizhskii AI. Fast and comprehensive N- and O-glycoproteomics analysis with MSFragger-Glyco. Nat Methods. 2020;17:1125–32.
Google Scholar
Lu L, Riley NM, Shortreed MR, Bertozzi CR, Smith LM. O-Pair Search with MetaMorpheus for O-glycopeptide characterization. Nat Methods. 2020;17:1133–8.
Google Scholar
Fulton KM, Li J, Tomas JM, Smith JC, Twine SM. Characterizing bacterial glycoproteins with LC-MS. Expert Rev Proteom. 2018;15:203–16.
Google Scholar
Ahrné E, Müller M, Lisacek F. Unrestricted identification of modified proteins using MS/MS. Proteomics. 2010;10:671–86.
Google Scholar
Bern M, Kil YJ, Becker C. Byonic: advanced peptide and protein identification software. Curr Protoc Bioinforma. 2012;40:13.20. 1-13.20. 14
Google Scholar
Na S, Bandeira N, Paek E. Fast multi-blind modification search through tandem mass spectrometry. Mol Cell Proteomics. 2012;11:1–13.
Devabhaktuni A, Lin S, Zhang L, Swaminathan K, Gonzalez CG, Olsson N, et al. TagGraph reveals vast protein modification landscapes from large tandem mass spectrometry datasets. Nat Biotechnol. 2019;37:469–79.
Google Scholar
Izaham ARA, Scott NE. Open database searching enables the identification and comparison of bacterial glycoproteomes without defining glycan compositions prior to searching. Mol Cell Proteom. 2020;19:1561–74.
Google Scholar
Ahmad Izaham AR, Ang C-S, Nie S, Bird LE, Williamson NA, Scott NE. What are we missing by using hydrophilic enrichment? improving bacterial glycoproteome coverage using total proteome and FAIMS analyses. J Proteome Res. 2020;20:599–612.
Kelstrup CD, Frese C, Heck AJ, Olsen JV, Nielsen ML. Analytical utility of mass spectral binning in proteomic experiments by SPectral Immonium Ion Detection (SPIID). Mol Cell Proteom. 2014;13:1914–24.
Google Scholar
Wuhrer M, Catalina MI, Deelder AM, Hokke CH. Glycoproteomics based on tandem mass spectrometry of glycopeptides. J Chromatogr B 2007;849:115–28.
Google Scholar
Hoffmann M, Marx K, Reichl U, Wuhrer M, Rapp E. Site-specific O-glycosylation analysis of human blood plasma proteins. Mol Cell Proteom. 2016;15:624–41.
Google Scholar
Singh C, Zampronio CG, Creese AJ, Cooper HJ. Higher energy collision dissociation (HCD) product ion-triggered electron transfer dissociation (ETD) mass spectrometry for the analysis of N-linked glycoproteins. J proteome Res. 2012;11:4517–25.
Google Scholar
Hoffmann M, Pioch M, Pralow A, Hennig R, Kottler R, Reichl U, et al. The fine art of destruction: a guide to in‐depth glycoproteomic analyses—exploiting the diagnostic potential of fragment ions. Proteomics 2018;18:1800282.
Google Scholar
Kosma P, Wugeditsch T, Christian R, Zayni S, Messner P. Glycan structure of a heptose-containing S-layer glycoprotein of Bacillus thermoaerophilus. Glycobiology. 1995;5:791–6.
Google Scholar
Faridmoayer A, Fentabil MA, Haurat MF, Yi W, Woodward R, Wang PG, et al. Extreme substrate promiscuity of the Neisseria oligosaccharyl transferase involved in protein O-glycosylation. J Biol Chem. 2008;283:34596–604.
Google Scholar
Harding CM, Nasr MA, Scott NE, Goyette-Desjardins G, Nothaft H, Mayer AE, et al. A platform for glycoengineering a polyvalent pneumococcal bioconjugate vaccine using E. coli as a host. Nat Commun. 2019;10:1–11.
Google Scholar
Speth DR, Guerrero-Cruz S, Dutilh BE, Jetten MS. Genome-based microbial ecology of anammox granules in a full-scale wastewater treatment system. Nat Commun. 2016;7:11172.
Google Scholar
Lawson CE, Wu S, Bhattacharjee AS, Hamilton JJ, McMahon KD, Goel R, et al. Metabolic network analysis reveals microbial community interactions in anammox granules. Nat Commun. 2017;8:1–12.
Google Scholar
Straka LL, Meinhardt KA, Bollmann A, Stahl DA, Winkler M-K. Affinity informs environmental cooperation between ammonia-oxidizing archaea (AOA) and anaerobic ammonia-oxidizing (Anammox) bacteria. ISME J. 2019;13:1997–2004.
Google Scholar
Hu Z, Wessels HJ, van Alen T, Jetten MS, Kartal B. Nitric oxide-dependent anaerobic ammonium oxidation. Nat Commun. 2019;10:1–7.
Google Scholar
Shaw DR, Ali M, Katuri KP, Gralnick JA, Reimann J, Mesman R, et al. Extracellular electron transfer-dependent anaerobic oxidation of ammonium by anammox bacteria. Nat Commun. 2020;11:1–12.
Google Scholar
Lewis AL, Desa N, Hansen EE, Knirel YA, Gordon JI, Gagneux P, et al. Innovations in host and microbial sialic acid biosynthesis revealed by phylogenomic prediction of nonulosonic acid structure. Proc Natl Acad Sci. 2009;106:13552–7.
Google Scholar
Fernández L, Rodríguez A, García P. Phage or foe: an insight into the impact of viral predation on microbial communities. ISME J. 2018;12:1171–9.
Google Scholar
Wang J, Cheng B, Li J, Zhang Z, Hong W, Chen X, et al. Chemical remodeling of cell‐surface sialic acids through a palladium‐triggered bioorthogonal elimination reaction. Angew Chem Int Ed. 2015;54:5364–8.
Google Scholar
Pabst M, Fischl RM, Brecker L, Morelle W, Fauland A, Köfeler H, et al. Rhamnogalacturonan II structure shows variation in the side chains monosaccharide composition and methylation status within and across different plant species. Plant J. 2013;76:61–72.
Google Scholar
Popa I, Pons A, Mariller C, Tai T, Zanetta J-P, Thomas L, et al. Purification and structural characterization of de-N-acetylated form of GD3 ganglioside present in human melanoma tumors. Glycobiology. 2007;17:367–73.
Google Scholar
Paschinger K, Wilson IB. Anionic and zwitterionic moieties as widespread glycan modifications in non-vertebrates. Glycoconj J. 2020;37:27–40.
Google Scholar
Nothaft H, Scott NE, Vinogradov E, Liu X, Hu R, Beadle B, et al. Diversity in the protein N-glycosylation pathways within the Campylobacter genus. Mol Cell Proteom. 2012;11:1203–19.
Google Scholar
Hadjineophytou C, Anonsen JH, Wang N, Ma KC, Viburiene R, Vik Å, et al. Genetic determinants of genus-level glycan diversity in a bacterial protein glycosylation system. PLoS Genet. 2019;15:e1008532.
Google Scholar
Oshiki M, Satoh H, Okabe S. Ecology and physiology of anaerobic ammonium oxidizing bacteria. Environ Microbiol. 2016;18:2784–96.
Google Scholar
Kartal B, Geerts W, Jetten MS. Cultivation, detection, and ecophysiology of anaerobic ammonium-oxidizing bacteria. Methods in enzymology. 486. Elsevier; 2011. p. 89–108.
Lotti T, Kleerebezem R, Lubello C, Van Loosdrecht M. Physiological and kinetic characterization of a suspended cell anammox culture. Water Res. 2014;60:1–14.
Google Scholar
Kleikamp HB, Pronk M, Tugui C, da Silva LG, Abbas B, Lin YM, et al. Database-independent de novo metaproteomics of complex microbial communities. Cell Syst. 2021;12:375–83.
Köcher T, Pichler P, Swart R, Mechtler K. Analysis of protein mixtures from whole-cell extracts by single-run nanoLC-MS/MS using ultralong gradients. Nat Protoc. 2012;7:882.
Google Scholar
Lawson CE, Nuijten GH, de Graaf RM, Jacobson TB, Pabst M, Stevenson DM, et al. Autotrophic and mixotrophic metabolism of an anammox bacterium revealed by in vivo 13 C and 2 H metabolic network mapping. ISME J. 2021;15:673–87.
Google Scholar
Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 2014;30:2114–20.
Google Scholar
Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824–34.
Google Scholar
Laczny CC, Kiefer C, Galata V, Fehlmann T, Backes C, Keller A. BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation. Nucleic Acids Res. 2017;45:W171–W9.
Google Scholar
Wu Y-W, Simmons BA, Singer SW. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics. 2016;32:605–7.
Google Scholar
Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165
Google Scholar
Sieber CM, Probst AJ, Sharrar A, Thomas BC, Hess M, Tringe SG, et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat Microbiol. 2018;3:836–43.
Google Scholar
Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 2015;25:1043–55.
Google Scholar
Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy T, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725–31.
Google Scholar
Tatusova T, DiCuccio M, Badretdin A, Chetvernin V, Ciufo S, Li W. Prokaryotic genome annotation pipeline. In: The NCBI Handbook. 2nd edition. (National Center for Biotechnology Information, US, 2013). pp 131–45.
Kanehisa M, Sato Y, Morishima K. BlastKOALA and GhostKOALA: KEGG tools for functional characterization of genome and metagenome sequences. J Mol Biol. 2016;428:726–31.
Google Scholar
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403–10.
Google Scholar
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