Drivers and determinants of strain dynamics following fecal microbiota transplantation.
Journal
Nature medicine
ISSN: 1546-170X
Titre abrégé: Nat Med
Pays: United States
ID NLM: 9502015
Informations de publication
Date de publication:
09 2022
09 2022
Historique:
received:
05
10
2021
accepted:
23
06
2022
pubmed:
16
9
2022
medline:
28
9
2022
entrez:
15
9
2022
Statut:
ppublish
Résumé
Fecal microbiota transplantation (FMT) is a therapeutic intervention for inflammatory diseases of the gastrointestinal tract, but its clinical mode of action and subsequent microbiome dynamics remain poorly understood. Here we analyzed metagenomes from 316 FMTs, sampled pre and post intervention, for the treatment of ten different disease indications. We quantified strain-level dynamics of 1,089 microbial species, complemented by 47,548 newly constructed metagenome-assembled genomes. Donor strain colonization and recipient strain resilience were mostly independent of clinical outcomes, but accurately predictable using LASSO-regularized regression models that accounted for host, microbiome and procedural variables. Recipient factors and donor-recipient complementarity, encompassing entire microbial communities to individual strains, were the main determinants of strain population dynamics, providing insights into the underlying processes that shape the post-FMT gut microbiome. Applying an ecology-based framework to our findings indicated parameters that may inform the development of more effective, targeted microbiome therapies in the future, and suggested how patient stratification can be used to enhance donor microbiota colonization or the displacement of recipient microbes in clinical practice.
Identifiants
pubmed: 36109636
doi: 10.1038/s41591-022-01913-0
pii: 10.1038/s41591-022-01913-0
pmc: PMC9499871
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1902-1912Commentaires et corrections
Type : CommentIn
Informations de copyright
© 2022. The Author(s).
Références
Borody, T. J. et al. Bacteriotherapy using fecal flora: toying with human motions. J. Clin. Gastroenterol. 38, 475–483 (2004).
pubmed: 15220681
doi: 10.1097/01.mcg.0000128988.13808.dc
Rossen, N. G. et al. Fecal microbiota transplantation as novel therapy in gastroenterology: a systematic review. World J. Gastroenterol. 21, 5359–5371 (2015).
pubmed: 25954111
pmcid: 4419078
doi: 10.3748/wjg.v21.i17.5359
Hanssen, N. M. J., de Vos, W. M. & Nieuwdorp, M. Fecal microbiota transplantation in human metabolic diseases: from a murky past to a bright future? Cell Metab. 33, 1098–1110 (2021).
pubmed: 34077717
doi: 10.1016/j.cmet.2021.05.005
Gough, E., Shaikh, H. & Manges, A. R. Systematic review of intestinal microbiota transplantation (fecal bacteriotherapy) for recurrent Clostridium difficile infection. Clin. Infect. Dis. 53, 994–1002 (2011).
pubmed: 22002980
doi: 10.1093/cid/cir632
van Nood, E. et al. Duodenal infusion of donor feces for recurrent Clostridium difficile. N. Engl. J. Med. 368, 407–415 (2013).
pubmed: 23323867
doi: 10.1056/NEJMoa1205037
Narula, N. et al. Systematic review and meta-analysis fecal microbiota transplantation for treatment of active ulcerative colitis. Inflamm. Bowel Dis. 23, 1702–1709 (2017).
pubmed: 28906291
doi: 10.1097/MIB.0000000000001228
Haifer, C., Leong, R. W. & Paramsothy, S. The role of fecal microbiota transplantation in the treatment of inflammatory bowel disease. Curr. Opin. Pharmacol. 55, 8–16 (2020).
pubmed: 33035780
pmcid: 7538387
doi: 10.1016/j.coph.2020.08.009
Suez, J. et al. Post-antibiotic gut mucosal microbiome reconstitution is impaired by probiotics and improved by autologous FMT. Cell 174, 1406–1423 (2018).
pubmed: 30193113
doi: 10.1016/j.cell.2018.08.047
Baruch, E. N. et al. Fecal microbiota transplant promotes response in immunotherapy-refractory melanoma patients. Science 371, 602–609 (2021).
Davar, D. et al. Fecal microbiota transplant overcomes resistance to anti-PD-1 therapy in melanoma patients. Science 371, 595–602 (2021).
pubmed: 33542131
pmcid: 8097968
doi: 10.1126/science.abf3363
Burrello, C. et al. Therapeutic fecal microbiota transplantation controls intestinal inflammation through IL10 secretion by immune cells. Nat. Commun. 9, 5184 (2018).
pubmed: 30518790
pmcid: 6281577
doi: 10.1038/s41467-018-07359-8
Seekatz, A. M. et al. Restoration of short chain fatty acid and bile acid metabolism following fecal microbiota transplantation in patients with recurrent Clostridium difficile infection. Anaerobe 53, 64–73 (2018).
pubmed: 29654837
pmcid: 6185828
doi: 10.1016/j.anaerobe.2018.04.001
Zuo, T. et al. Bacteriophage transfer during fecal microbiota transplantation is associated with treatment response in Clostridium difficile infection. Gastroenterology 152, S140–S141 (2017).
doi: 10.1016/S0016-5085(17)30798-9
Manrique, P. et al. Gut bacteriophage dynamics during fecal microbial transplantation in subjects with metabolic syndrome. Gut Microbes 13, 1–15 (2021).
pubmed: 33794724
doi: 10.1080/19490976.2021.1897217
Wilson, B. C., Vatanen, T., Cutfield, W. S. & O’Sullivan, J. M. The super-donor phenomenon in fecal microbiota transplantation. Front. Cell. Infect. Microbiol. 9, 2 (2019).
pubmed: 30719428
pmcid: 6348388
doi: 10.3389/fcimb.2019.00002
Duvallet, C. et al. Framework for rational donor selection in fecal microbiota transplant clinical trials. PloS ONE 14, e0222881 (2019).
Olesen, S. W. & Gerardin, Y. Re-evaluating the evidence for fecal microbiota transplantation “super-donors” in inflammatory bowel disease. J. Crohns Colitis 15, 453–461 (2021).
pubmed: 32808030
doi: 10.1093/ecco-jcc/jjaa170
Kootte, R. S. et al. Improvement of insulin sensitivity after lean donor feces in metabolic syndrome is driven by baseline intestinal imcrobiota composition. Cell Metab. 26, 611–619 (2017).
pubmed: 28978426
doi: 10.1016/j.cmet.2017.09.008
Danne, C., Rolhion, N. & Sokol, H. Recipient factors in fecal microbiota transplantation: one stool does not fit all. Nat. Rev. Gastroenterol. Hepatol. 18, 503–513 (2021).
Fujimoto, K. et al. Functional restoration of bacteriomes and viromes by fecal microbiota transplantation. Gastroenterology 160, 2089–2102 (2021).
pubmed: 33577875
doi: 10.1053/j.gastro.2021.02.013
Peri, R. et al. The impact of technical and clinical factors on fecal microbiota transfer outcomes for the treatment of recurrent Clostridioides difficile infections in Germany. United European Gastroenterol. J. 7, 716–722 (2019).
pubmed: 31210950
pmcid: 6545715
doi: 10.1177/2050640619839918
Draper, L. A. et al. Long-term colonisation with donor bacteriophages following successful fecal microbial transplantation. Microbiome 6, 220 (2018).
pubmed: 30526683
pmcid: 6288847
doi: 10.1186/s40168-018-0598-x
Leonardi, I. et al. Fungal trans-kingdom dynamics linked to responsiveness to fecal microbiota transplantation (FMT) therapy in ulcerative colitis. Cell Host Microbe 27, 823–829 (2020).
Zuo, T. et al. Gut fungal dysbiosis correlates with reduced efficacy of fecal microbiota transplantation in Clostridium difficile infection. Nat. Commun. 9, 3663 (2018).
pubmed: 30202057
pmcid: 6131390
doi: 10.1038/s41467-018-06103-6
Li, S. S. et al. Durable coexistence of donor and recipient strains after fecal microbiota transplantation. Science 352, 586–589 (2016).
pubmed: 27126044
doi: 10.1126/science.aad8852
Smillie, C. S. et al. Strain tracking reveals the determinants of bacterial engraftment in the human gut following fecal microbiota transplantation. Cell Host Microbe 23, 229–240 (2018).
pubmed: 29447696
pmcid: 8318347
doi: 10.1016/j.chom.2018.01.003
Podlesny, D. et al. Metagenomic strain detection with SameStr: identification of a persisting core gut microbiota transferable by fecal transplantation. Microbiome 10, 53 (2022).
pubmed: 35337386
pmcid: 8951724
doi: 10.1186/s40168-022-01251-w
Aggarwala, V. et al. Precise quantification of bacterial strains after fecal microbiota transplantation delineates long-term engraftment and explains outcomes. Nat. Microbiol. 6, 1309–1318 (2021).
pubmed: 34580445
pmcid: 8993687
doi: 10.1038/s41564-021-00966-0
Lee, S. T. M. et al. Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics. Microbiome 5, 50 (2017).
pubmed: 28473000
pmcid: 5418705
doi: 10.1186/s40168-017-0270-x
Wilson, B. C. et al. Strain engraftment competition and functional augmentation in a multi-donor fecal microbiota transplantation trial for obesity. Microbiome 9, 107 (2021).
pubmed: 33985595
pmcid: 8120839
doi: 10.1186/s40168-021-01060-7
Ng, S. C. et al. Microbiota engraftment after fecal microbiota transplantation in obese subjects with type 2 diabetes: a 24-week, double-blind, randomised controlled trial. Gut 71, 716–723 (2022).
pubmed: 33785557
doi: 10.1136/gutjnl-2020-323617
Watson, A. R., Fuessel, J., Veseli, I. & DeLongchamp, J. Z. Adaptive ecological processes and metabolic independence drive microbial colonization and resilience in the human gut. Preprint at https://doi.org/10.1101/2021.03.02.433653 (2021).
Walter, J., Maldonado-Gómez, M. X. & Martínez, I. To engraft or not to engraft: an ecological framework for gut microbiome modulation with live microbes. Curr. Opin. Biotechnol. 49, 129–139 (2018).
pubmed: 28866242
doi: 10.1016/j.copbio.2017.08.008
Schmidt, T. S. B., Raes, J. & Bork, P. The human gut microbiome: from association to modulation. Cell 172, 1198–1215 (2018).
pubmed: 29522742
doi: 10.1016/j.cell.2018.02.044
Xiao, Y., Angulo, M. T., Lao, S., Weiss, S. T. & Liu, Y.-Y. An ecological framework to understand the efficacy of fecal microbiota transplantation. Nat. Commun. 11, 3329 (2020).
pubmed: 32620839
pmcid: 7334230
doi: 10.1038/s41467-020-17180-x
Moss, E. L. et al. Long-term taxonomic and functional divergence from donor bacterial strains following fecal microbiota transplantation in immunocompromised patients. PLoS ONE 12, e0182585 (2017).
pubmed: 28827811
pmcid: 5565110
doi: 10.1371/journal.pone.0182585
Singh, R. et al. Fecal microbiota transplantation against intestinal colonization by extended spectrum beta-lactamase producing Enterobacteriaceae: a proof of principle study. BMC Res. Notes 11, 190 (2018).
pubmed: 29566738
pmcid: 5863815
doi: 10.1186/s13104-018-3293-x
Bar-Yoseph, H. et al. Oral capsulized fecal microbiota transplantation for eradication of carbapenemase-producing Enterobacteriaceae colonization with a metagenomic perspective. Clin. Infect. Dis. 73, e166–e175 (2020).
Leo, S. et al. Metagenomic characterization of gut microbiota of carriers of extended-spectrum beta-lactamase or carbapenemase-producing Enterobacteriaceae following treatment with oral antibiotics and fecal microbiota transplantation: results from a multicenter randomized trial. Microorganisms 8, 941 (2020).
Koopen, A. M. et al. Effect of fecal microbiota transplantation combined with Mediterranean diet on insulin sensitivity in subjects with metabolic syndrome. Front. Microbiol. 12, 662159 (2021).
pubmed: 34177842
pmcid: 8222733
doi: 10.3389/fmicb.2021.662159
Rossen, N. G. et al. Findings from a randomized controlled trial of fecal transplantation for patients with ulcerative colitis. Gastroenterology 149, 110–118 (2015).
pubmed: 25836986
doi: 10.1053/j.gastro.2015.03.045
Nusbaum, D. J. et al. Gut microbial and metabolomic profiles after fecal microbiota transplantation in pediatric ulcerative colitis patients. FEMS Microbiol. Ecol. 94, fiy133 (2018).
Damman, C. J. et al. Low level engraftment and improvement following a single colonoscopic administration of fecal microbiota to patients with ulcerative colitis. PLoS ONE 10, e0133925 (2015).
pubmed: 26288277
pmcid: 4544847
doi: 10.1371/journal.pone.0133925
Goll, R. et al. Effects of fecal microbiota transplantation in subjects with irritable bowel syndrome are mirrored by changes in gut microbiome. Gut Microbes 12, 1794263 (2020).
pubmed: 32991818
pmcid: 7583512
doi: 10.1080/19490976.2020.1794263
Vaughn, B. P. et al. Increased intestinal microbial diversity following fecal microbiota transplant for active Crohn’s disease. Inflamm. Bowel Dis. 22, 2182–2190 (2016).
pubmed: 27542133
doi: 10.1097/MIB.0000000000000893
Ianiro, G. et al. Fecal microbiota transplantation for the treatment of diarrhoea induced by tyrosine-kinase inhibitors in patients with metastatic renal cell carcinoma. Nat. Commun. 11, 4333 (2020).
pubmed: 32859933
pmcid: 7455693
doi: 10.1038/s41467-020-18127-y
Zhao, H.-J. et al. The efficacy of fecal microbiota transplantation for children with Tourette syndrome: a preliminary study. Front. Psychiatry 11, 554441 (2020).
pubmed: 33424650
pmcid: 7793740
doi: 10.3389/fpsyt.2020.554441
Goloshchapov, O. V. et al. Long-term impact of fecal transplantation in healthy volunteers. BMC Microbiol. 19, 312 (2019).
pubmed: 31888470
pmcid: 6938016
doi: 10.1186/s12866-019-1689-y
Tian, L. et al. Deciphering functional redundancy in the human microbiome. Nat. Commun. 11, 6217 (2020).
pubmed: 33277504
pmcid: 7719190
doi: 10.1038/s41467-020-19940-1
Hildebrand, F. et al. Dispersal strategies shape persistence and evolution of human gut bacteria. Cell Host Microbe 29, 1167–1176 (2021).
pubmed: 34111423
pmcid: 8288446
doi: 10.1016/j.chom.2021.05.008
Lahti, L., Salojärvi, J., Salonen, A., Scheffer, M. & de Vos, W. M. Tipping elements in the human intestinal ecosystem. Nat. Commun. 5, 4344 (2014).
pubmed: 25003530
doi: 10.1038/ncomms5344
Scheffer, M., Carpenter, S. R., Dakos, V. & van Nes, E. H. Generic indicators of ecological resilience: inferring the chance of a critical transition. Annu. Rev. Ecol. Evol. Syst. 46, 145–167 (2015).
Gonze, D., Lahti, L., Raes, J. & Faust, K. Multi-stability and the origin of microbial community types. ISME J. 11, 2159–2166 (2017).
pubmed: 28475180
pmcid: 5607358
doi: 10.1038/ismej.2017.60
Costea, P. I. et al. Enterotypes in the landscape of gut microbial community composition. Nat. Microbiol. 3, 8–16 (2018).
pubmed: 29255284
doi: 10.1038/s41564-017-0072-8
Debray, R. et al. Priority effects in microbiome assembly. Nat. Rev. Microbiol. 20, 109–121 (2021).
Zaneveld, J. R., McMinds, R. & Thurber, R. V. Stress and stability: applying the Anna Karenina principle to animal microbiomes. Nat. Microbiol. 2, 17121 (2017).
pubmed: 28836573
doi: 10.1038/nmicrobiol.2017.121
Basson, A. R., Zhou, Y., Seo, B., Rodriguez-Palacios, A. & Cominelli, F. Autologous fecal microbiota transplantation for the treatment of inflammatory bowel disease. Transl. Res. 226, 1–11 (2020).
pubmed: 32585148
pmcid: 7308243
doi: 10.1016/j.trsl.2020.05.008
de Groot, P. et al. Fecal microbiota transplantation halts progression of human new-onset type 1 diabetes in a randomised controlled trial. Gut 70, 92–105 (2021).
pubmed: 33106354
doi: 10.1136/gutjnl-2020-322630
Ott, S. J. et al. Efficacy of sterile fecal filtrate transfer for treating patients with Clostridium difficile infection. Gastroenterology 152, 799–811 (2017).
pubmed: 27866880
doi: 10.1053/j.gastro.2016.11.010
Bojanova, D. P. & Bordenstein, S. R. Fecal transplants: what is being transferred? PLoS Biol. 14, e1002503 (2016).
pubmed: 27404502
pmcid: 4942072
doi: 10.1371/journal.pbio.1002503
Fuentes, S. et al. Microbial shifts and signatures of long-term remission in ulcerative colitis after fecal microbiota transplantation. ISME J. 11, 1877–1889 (2017).
pubmed: 28398347
pmcid: 5520032
doi: 10.1038/ismej.2017.44
Coelho, L. P. et al. NG-meta-profiler: fast processing of metagenomes using NGLess, a domain-specific language. Microbiome 7, 84 (2019).
pubmed: 31159881
pmcid: 6547473
doi: 10.1186/s40168-019-0684-8
Milanese, A. et al. Microbial abundance, activity and population genomic profiling with mOTUs2. Nat. Commun. 10, 1014 (2019).
pubmed: 30833550
pmcid: 6399450
doi: 10.1038/s41467-019-08844-4
Coelho, L. P. et al. Towards the biogeography of prokaryotic genes. Nature 601, 252–256 (2022).
pubmed: 34912116
doi: 10.1038/s41586-021-04233-4
Huerta-Cepas, J. et al. EggNOG 5.0: a hierarchical, functionally and phylogenetically annotated orthology resource based on 5090 organisms and 2502 viruses. Nucleic Acids Res. 47, D309–D314 (2019).
pubmed: 30418610
doi: 10.1093/nar/gky1085
Vieira-Silva, S. et al. Species–function relationships shape ecological properties of the human gut microbiome. Nat. Microbiol. 1, 16088 (2016).
pubmed: 27573110
doi: 10.1038/nmicrobiol.2016.88
Darzi, Y., Falony, G., Vieira-Silva, S. & Raes, J. Towards biome-specific analysis of meta-omics data. ISME J. 10, 1025–1028 (2016).
pubmed: 26623543
doi: 10.1038/ismej.2015.188
Nurk, S., Meleshko, D., Korobeynikov, A. & Pevzner, P. A. MetaSPAdes: a new versatile metagenomic assembler. Genome Res. 27, 824–834 (2017).
pubmed: 28298430
pmcid: 5411777
doi: 10.1101/gr.213959.116
Li, H. Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. Preprint at https://doi.org/10.48550/arXiv.1303.3997 (2013).
Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ. 7, e7359 (2019).
pubmed: 31388474
pmcid: 6662567
doi: 10.7717/peerj.7359
Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676 (2015).
pubmed: 25609793
doi: 10.1093/bioinformatics/btv033
Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat. Methods 11, 1144–1146 (2014).
pubmed: 25218180
doi: 10.1038/nmeth.3103
Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat. Microbiol. 3, 836–843 (2018).
pubmed: 29807988
pmcid: 6786971
doi: 10.1038/s41564-018-0171-1
Uritskiy, G. V., DiRuggiero, J. & Taylor, J. MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis. Microbiome 6, 158 (2018).
pubmed: 30219103
pmcid: 6138922
doi: 10.1186/s40168-018-0541-1
Mende, D. R. et al. ProGenomes: a resource for consistent functional and taxonomic annotations of prokaryotic genomes. Nucleic Acids Res. 45, D529–D534 (2017).
pubmed: 28053165
doi: 10.1093/nar/gkw989
Mende, D. R. et al. ProGenomes2: an improved database for accurate and consistent habitat, taxonomic and functional annotations of prokaryotic genomes. Nucleic Acids Res. 48, D621–D625 (2020).
pubmed: 31647096
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. & Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043–1055 (2015).
pubmed: 25977477
pmcid: 4484387
doi: 10.1101/gr.186072.114
Orakov, A. et al. GUNC: detection of chimerism and contamination in prokaryotic genomes. Genome Biol. 22, 178 (2021).
pubmed: 34120611
pmcid: 8201837
doi: 10.1186/s13059-021-02393-0
Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk: a toolkit to classify genomes with the Genome Taxonomy Database. Bioinformatics 36, 1925–1927 (2019).
Hyatt, D. et al. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 11, 119 (2010).
pubmed: 20211023
pmcid: 2848648
doi: 10.1186/1471-2105-11-119
Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).
pubmed: 24642063
doi: 10.1093/bioinformatics/btu153
Huerta-Cepas, J. et al. Fast genome-wide functional annotation through orthology assignment by eggNOG-Mapper. Mol. Biol. Evol. 34, 2115–2122 (2017).
pubmed: 28460117
pmcid: 5850834
doi: 10.1093/molbev/msx148
Alcock, B. P. et al. CARD 2020: antibiotic resistome surveillance with the comprehensive antibiotic resistance database. Nucleic Acids Res. 48, D517–D525 (2020).
pubmed: 31665441
Gibson, M. K., Forsberg, K. J. & Dantas, G. Improved annotation of antibiotic resistance determinants reveals microbial resistomes cluster by ecology. ISME J. 9, 207–216 (2015).
pubmed: 25003965
doi: 10.1038/ismej.2014.106
Mende, D. R., Sunagawa, S., Zeller, G. & Bork, P. Accurate and universal delineation of prokaryotic species. Nat. Publ. Group 10, 881–884 (2013).
Schmidt, T. S. B. et al. Drivers and determinants of strain dynamics following fecal microbiota transplantation. Zenodo https://doi.org/10.5281/ZENODO.5534163 (2021).
Rodrigues, J. F. M., Schmidt, S. B. T., Tackmann, J. & von Mering, C. MAPseq: highly efficient k-mer search with confidence estimates, for rRNA sequence analysis. Bioinformatics 33, 3808–3810 (2017).
Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. DRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 11, 2864–2868 (2017).
pubmed: 28742071
pmcid: 5702732
doi: 10.1038/ismej.2017.126
Ondov, B. D. et al. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol. 17, 132 (2016).
pubmed: 27323842
pmcid: 4915045
doi: 10.1186/s13059-016-0997-x
Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T. & Aluru, S. High throughput ANI analysis of 90 K prokaryotic genomes reveals clear species boundaries. Nat. Commun. 9, 5114 (2018).
pubmed: 30504855
pmcid: 6269478
doi: 10.1038/s41467-018-07641-9
Page, A. J. et al. Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics 31, 3691–3693 (2015).
pubmed: 26198102
pmcid: 4817141
doi: 10.1093/bioinformatics/btv421
Edgar, R. C. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5, 113 (2004).
pubmed: 15318951
pmcid: 517706
doi: 10.1186/1471-2105-5-113
Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).
pubmed: 20224823
pmcid: 2835736
doi: 10.1371/journal.pone.0009490
Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078–2079 (2009).
pubmed: 19505943
pmcid: 2723002
doi: 10.1093/bioinformatics/btp352
Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841–842 (2010).
pubmed: 20110278
pmcid: 2832824
doi: 10.1093/bioinformatics/btq033
Costea, P. I. et al. MetaSNV: a tool for metagenomic strain level analysis. PLoS ONE 12, e0182392 (2017).
pubmed: 28753663
pmcid: 5533426
doi: 10.1371/journal.pone.0182392
Schmidt, T. S. B. et al. Extensive transmission of microbes along the gastrointestinal tract. eLife 8, e42693 (2019).
Friedman, J., Hastie, T. & Tibshirani, R. Regularization paths for generalized linear models via coordinate descent. J. Stat. Softw. 33, 1–22 (2010).
pubmed: 20808728
pmcid: 2929880
doi: 10.18637/jss.v033.i01
Schmidt, T. S. B. et al. Analysis data, “Drivers and Determinants of Strain Dynamics Following Fecal Microbiota Transplantation”. Zenodo https://doi.org/10.5281/ZENODO.5534163 (2021).