Publications

Years

This page lists publications that are most reflective of our interests. For a complete list, please see Meren’s Google Scholar page.

2023

 

Metabolic independence drives gut microbial colonization and resilience in health and disease Watson AR☯, Fuessel J☯, Veseli I☯, DeLongchamp JZ, Silva M, Trigodet F, Lolans K, Shaiber A, Fogarty E, Runde JM, Quince C, Yu MK, Söylev A, Morrison HG, Lee STM, Kao D, Rubin DT, Jabri B, Louie T, Eren AM ☯Co-first authors
- A Fecal Microbiota Transplantation (FMT) study that reveals unexpected parallels between the adaptive ecological processes that shape the recipient gut microbial composition after FMT and those that influence microbial diversity in patients with Inflammatory Bowel Disease (IBD).
- Includes an observation that links the presence of superior metabolic competence in bacterial populations to their expansion in IBD.
- Here is a Twitter thread by Andrea that explains the key points of the study, and here is another one by Meren that details what are the critical learnings from it.
📚 Genome Biology, 24(78) | 🔍 Google Scholar | 🔗 doi:10.1186/s13059-023-02924-x

 

A highly conserved and globally prevalent cryptic plasmid is among the most numerous mobile genetic elements in the human gut Fogarty EC, Schechter MS, Lolans K, Sheahan ML, Veseli I, Moore R, Kiefl E, Moody T, Rice PA, Yu MK, Mimee M, Chang EB, Mclellan SL, Willis AD, Comstock LE, Eren AM
- A study that describes one of the most prevalent and numerous cryptic plasmid in the gut microbiomes of people who live in the industrialized world that is composed of only two genes (for its own replication and mobilization) in its native form.
- Here is a Twitter thread that explains some of the interesting aspects of pBI143 ecology as well as the practical implications having a human gut-specific and highly conserved genetic entity, copy-number of which responds to stress.
- You can find the plasmid sequences to look for pBI143 in your metagenomes, reproducible data items to re-investigate metagenomic read recruitment results, and bioinformatics workflows to elucidate population genetics of pBI143 here.
📚 bioRxiv | 🔍 Google Scholar | 🔗 doi:10.1101/2023.03.25.534219

 

Structure-informed microbial population genetics elucidate selective pressures that shape protein evolution Kiefl E, Esen ÖC, Miller SE, Kroll KL, Willis AD, Rappé MS, Pan T, Eren AM
- A study that describes an approach to integrate environmental microbiology with recent advances in protein structure prediction, and illustrates the tight association between intra-population genetic variants, environmental selective pressures, and structural properties of proteins.
- Demonstrates a quantifiable link between (1) the magnitude of selective pressures over key metabolic genes (e.g., glutamine synthase of the central nitrogen metabolism), (2) the availability of key nutrients in the environment (e.g., nitrate), and (3) the maintenance of nonsynonymous variants near protein active sites.
- Comes with a reproducible bioinformatics workflow that offers detailed access to computational steps used in the study that spans from metagenomic read recruitment and profiling to the integration of environmental variants and predicted protein structures.
📚 Science Advances, 9(8):eabq4632 | 🔍 Google Scholar | 🔗 doi:10.1126/sciadv.abq4632

2022

 

Microbial metabolites in the marine carbon cycle Moran MA‡, Kujawinski EB‡, Schroer WF, Amin SA, Bates NR, Bertrand EM, Braakman R, Brown CT, Covert MW, Doney SC, Dyhrman ST, Edison AS, Eren AM, Levine NM, Li L, Ross AC, Saito MA, Santoro AE, Segrè D, Shade A, Sullivan MB, Vardi A ‡Co-senior authors
- A review that happens to be the study number 001 for the Center for Chemical Currencies of a Microbial Planet, or C-CoMP, an NSF-funded Science and Technology Center that aims to promote 'a deeper understanding of chemicals and chemical processes that underpin ocean ecosystems and the global carbon cycle by leveraging recent advances in analytical and data sciences, incorporating new ocean sampling technologies, using an open-science framework, and engaging educators and policy-makers'.
📚 Nature Microbiology, 7:508–523 | 🔍 Google Scholar | 🔗 doi:10.1038/s41564-022-01090-3

 

Eco-evolutionary significance of domesticated retroelements in microbial genomes Paul BG, Eren AM
- A short review on retrons and diversity-generating retro elements, some of the most beautiful and mysterious ways for life to beat the boring means of evolution and skip ahead.
- Demonstrates a workflow that gives access to the extent intra-population hypervariability of DGRs and their ecology through the analysis of metagenomes.
- A complete bioinformatics workflow that uses anvi'o and oligotyping to study DGR activity in metageomes is available here.
📚 Mobile DNA, 13(6) | 🔍 Google Scholar | 🔗 doi:10.1186/s13100-022-00262-6

 

The genetic and ecological landscape of plasmids in the human gut Yu MK☯, Fogarty EC☯, Eren AM ☯Co-first authors
- A study that aims to shed light on the ecology and evolution of one of the most critical yet poorly studied aspects of microbial life -- naturally occurring plasmids.
- Uses state-of-the-art machine learning strategies to identify over 60,000 plasmids from human gut metagenomes, which represents a 200-fold increase in the number of known plasmids to date that were detectable in healthy humans.
- Defines hundreds of 'plasmid systems', and demonstrates that naturally occurring plasmids are not static entities, but their evolution is driven by the need to respond to the environment, and their ecology cannot be simply explained by bacterial taxonomy and distribution patterns of their putative hosts.
📚 bioRxiv | 🔍 Google Scholar | 🔗 doi:10.1101/2020.11.01.361691

 

tRNA modification dynamics from individual organisms to metaepitranscriptomics of microbiomes Zhang W, Foo M, Eren AM, Pan T
- A review that summarizes recent advances in the studies of tRNA modification dynamics in biological processes
- Defines 'metaepitranscriptomics' as a strategy to study modification dynamics in complex environmental populations.
📚 Molecular Cell | 🔍 Google Scholar | 🔗 doi:10.1016/j.molcel.2021.12.007

2021

 

Community-led, integrated, reproducible multi-omics with anvi'o Eren AM, Kiefl E, Shaiber A, Veseli I, Miller SE, Schechter MS, Fink I, Pan JN, Yousef M, Fogarty EC, Trigodet F, Watson AR, Esen ÖC, Moore RM, Clayssen Q, Lee MD, Kivenson V, Graham ED, Merrill BD, Karkman A, Blankenberg D, Eppley JM, Sjödin A, Scott JJ, Vázquez-Campos X, McKay LJ, McDaniel EA, Stevens SLR, Anderson RE, Fuessel J, Fernandez-Guerra A, Maignien L, Delmont TO, Willis AD
- A summary of the progress of anvi'o during the past five years.
- The PDF of the publication (which was supposed to be open access, yet somehow the Nature Publishing Group was unable to do so, so here it is).
📚 Nature Microbiology, 6(1):186 | 🔍 Google Scholar | 🔗 doi:10.1038/s41564-020-00834-3

 

High molecular weight DNA extraction strategies for long-read sequencing of complex metagenomes Trigodet F, Lolans K, Fogarty EC, Shaiber A, Morrison HG, Barreiro L, Jabri B, Eren AM
- A study that benchmarks six high molecular weight DNA extraction strategies (commercially available kits, phenol-chloroform extraction, and agarose encasement followed by agarase digestion) for long-read sequencing of metagenomes with MinION.
- It turns out the protocol that works best for sequencing DNA from microbial isolates may not be the most effetive method for long-read sequencing of metagenomes ¯\_(ツ)_/¯
- A reproducible bioinformatics workflow is available here. Detailed lab protocols for HMW DNA extraction methods mentioned in the study are here.
📚 Molecular Ecology Resources, 22(5):1786-1802 | 🔍 Google Scholar | 🔗 doi:10.1111/1755-0998.13588

2020

 

Functional and genetic markers of niche partitioning among enigmatic members of the human oral microbiome Shaiber A, Willis AD, Delmont TO, Roux S, Chen L, Schmid AC, Yousef M, Watson AR, Lolans K, Esen ÖC, Lee STM, Downey N, Morrison HG, Dewhirst FE, Welch JLM‡, Eren AM‡ ‡Co-senior authors
- A multi-omics study that combines genome-resolved metagenomics, pangenomics, phylogenomics, and microbial population genetics to investigate the ecology and evolution of Saccharibacteria (TM7) in the human oral cavity, and offers a formal description of 'functional enrichment' statistic for phylogenomics and pangenomics.
- Demonstrates that TM7s split into tongue specialists and plaque specialists, and plaque TM7s group with environmental TM7s, leading to an hypothesis that the dental plaque may have served as a stepping stone for environmental microbes to adapt to host environments at least for some clades of microbes
- A news article by Alison Caldwell, PhD: Microbes in dental plaque look more like relatives in soil than those on the tongue.
- Public raw and intermediate data. Reviewer comments and responses.
📚 Genome Biology, 21(292) | 🔍 Google Scholar | 🔗 doi:10.1186/s13059-020-02195-w

 

Metapangenomics of the oral microbiome provides insights into habitat adaptation and cultivar diversity Utter DR, Borisy GG, Eren AM, Cavanaugh CM, Welch JLM
- An application of metapangenomics that links the gene pool of two major oral microbial taxa, Haemophilus parainfluenzae and the genus Rothia, to their ecology using the Human Microbiome Project metageonomes generated from tongue, buccal mucosa, and dental plaque samples.
- Reveals that seemingly generalist organisms are composed of cryptic subpopulations with distinct ecology that is associated with only a small number of genes.
- Reviewer comments and responses. Reproducible bioinformatics workflow.
📚 Genome Biology, 21(293) | 🔍 Google Scholar | 🔗 doi:10.1186/s13059-020-02200-2

 

Droplet-based high-throughput cultivation for accurate screening of antibiotic resistant gut microbes Watterson WJ, Tanyeri M, Watson AR, Cham CM, Shan Y, Chang EB, Eren AM, Tay S
- An aneorobic microfluidics platform for high-throughput cultivation of microbes that grows single microbial cells in millions of picoliter droplets.
- Populations of gut microbes that compete poorly in plates grow well in droplets regardless of culture media. Furthermore, taxonomic profile of droplets resembles droplets much better than plate scrapings even at the level of oligotypes.
- Demonstrates that not detecting microbes in plate-based screening of antibiotic resistance may not mean that the original sample does not contain microbes resistant to antibiotics.
📚 eLife, 9(e56998) | 🔍 Google Scholar | 🔗 doi:10.7554/eLife.56998

 

Accurate and complete genomes from metagenomes Chen L, Anantharaman K, Shaiber A, Eren AM‡, Banfield JF‡ ‡Co-senior authors
- A review on genome-resolved metagenomics that discusses the importance of using assembly and careful binning strategies to study metagenomes.
- Case studies include a demonstration of how single-copy core genes can fail to predict the quality of metagenome-assembled genomes, and automated strategies that yield tens of thousands of metagenome-assembled genomes will include extensive contamination.
- Promotes approaches to reconstruct 'complete' genomes from metagenomes and the use of GC skew as a metric for checking genome correctness.
- Tutorial on scaffold extension and gap closing, reproducible workflow for binning and phylogenomics of a Parcubacterium genome from human blood metagenomes.
📚 Genome Research, 30(3):315-333 | 🔍 Google Scholar | 🔗 doi:10.1101/gr.258640.119

2019

 

Single-amino acid variants reveal evolutionary processes that shape the biogeography of a global SAR11 subclade Delmont TO☯, Kiefl E☯, Kilinc O, Esen ÖC, Uysal I, Rappé MS, Giovannoni S, Eren AM ☯Co-first authors
- A study that introduces 'single-amino acid variants' (SAAVs) and demonstrates the use of SAAVs to tease apart evolutionary processes that shape the biogeography and genomic heterogeneity within a SAR11 population through metagenomics.
- A first attempt to link population genetics and the predicted protein structures to explore in silico the intersection beetween protein biochemistry and evolutionary processes acting on an environmental microbe.
- An application of metapangenomics to define subclades of SAR11 based on gene content and ecology.
- Reproducible bioinformatics workflow is here. Reviewer criticism and our responses are also available.
📚 eLife, 8(e46497) | 🔍 Google Scholar | 🔗 doi:10.7554/eLife.46497

 

Composite Metagenome-Assembled Genomes Reduce the Quality of Public Genome Repositories Shaiber A, Eren AM
- A letter that stresses that the composite metagenome-assembled genomes influence phylogenomic, pangenomic, and ecological insights (peer reviews and responses).
- A reproducible workflow to detail the steps of genome refinement and make available the refined versions of some key genomes.
📚 mBio, 10(3):e00725-19 | 🔍 Google Scholar | 🔗 doi:10.1128/mBio.00725-19

 

The Wolbachia mobilome in Culex pipiens includes a putative plasmid Reveillaud J☯, Bordenstein SR☯, Cruaud C, Shaiber A, Esen ÖC, Weill M, Makoundou P, Lolans K, Watson AR, Rakotoarivony I, Bordenstein SR☯, Eren AM ☯Co-first authors
- The first report of a Wolbachia plasmid through genome-resolved metagenomics on microsurgically removed individual mosquito ovary samples (peer reviews and responses).
- Yet another application of metapangenomics and an applicatoin of minION long-read sequencing on extremely low-biomass samples.
- Reproducible bioinformatics workflow with all data items, a 'behind the paper' blog post by Julie Reveillaud, and a press release from the Marine Biological Laboratory.
📚 Nature Communications, 10(1):1051 | 🔍 Google Scholar | 🔗 doi:10.1038/s41467-019-08973-w

 

Genome-resolved insights into a novel Spiroplasma symbiont of the Wheat Stem Sawfly (Cephus cinctus) Yeoman CJ, Brutscher LM, Esen ÖC, Ibaoglu F, Fowler C, Eren AM, Wanner K, Weaver DK
- A study that uses (1) genome-resolved metagenomics to reconstruct a population genome from fly metagenomes that resolves to the genus Spiroplasma, (2) pangenomics to put this genome in the context of other Spiroplasma genomes, (3) phylogenomics to infer ancestral relationships between Spiroplasma genomes, and (4) includes an ANI-based distance estimation between all genomes for comprehensive reporting.
- It is a particularly good example that demonstrates how pangenomics can reveal appropriate targets for high-resolution phylogenomics.
- A fully reproducible bioinformatics workflow for this multi'omics analysis is here. Anvi'o databases to interactively reproduce and explore the Spiroplasma pangenome is also available.
📚 PeerJ, 7(e7548) | 🔍 Google Scholar | 🔗 doi:10.7717/peerj.7548

 

Global phylogeography and ancient evolution of the widespread human gut virus crAssphage Edwards RA, Vega AA, Norman HM, Ohaeri M, Levi K, Dinsdale EA, Cinek O, Aziz RK, McNair K, Barr JJ, Bibby K, Brouns SJJ, Cazares A, Jonge PAd, Desnues C, Muñoz SLD, Fineran PC, Kurilshikov A, Lavigne R, Mazankova K, McCarthy DT, Nobrega FL, Muñoz AR, Tapia G, Trefault N, Tyakht AV, Vinuesa P, Wagemans J, Zhernakova A, Aarestrup FM, Ahmadov G, Alassaf A, Anton J, Asangba A, Billings EK, Cantu VA, Carlton JM, Cazares D, Cho G, Condeff T, Cortés P, Cranfield M, Cuevas DA, Iglesia RDl, Decewicz P, Doane MP, Dominy NJ, Dziewit L, Elwasila BM, Eren AM, Franz C, Fu J, Garcia-Aljaro C, Ghedin E, Gulino KM, Haggerty JM, Head SR, Hendriksen RS, Hill C, Hyöty H, Ilina EN, Irwin MT, Jeffries TC, Jofre J, Junge RE, Kelley ST, Mirzaei MK, Kowalewski M, Kumaresan D, Leigh SR, Lipson D, Lisitsyna ES, Llagostera M, Maritz JM, Marr LC, McCann A, Molshanski-Mor S, Monteiro S, Moreira-Grez B, Morris M, Mugisha L, Muniesa M, Neve H, Nguyen N, Nigro OD, Nilsson AS, O’Connell T, Odeh R, Oliver A, Piuri M, II AJP, Qimron U, Quan Z, Rainetova P, Ramírez-Rojas A, Raya R, Reasor K, Rice GAO, Rossi A, Santos R, Shimashita J, Stachler EN, Stene LC, Strain R, Stumpf R, Torres PJ, Twaddle A, Ibekwe MU, Villagra N, Wandro S, White B, Whiteley A, Whiteson KL, Wijmenga C, Zambrano MM, Zschach H, Dutilh BE
- A monumental effort lead by Rob Edwards and Bas Dutilh to explore with the help of 114 scientists from around the world the global phylogeorgraphy and evolution of crAssphage, one of the most numerous viruses in the human gut that infect bacteria.
- A curated list of press coverage of this study is available on Rob Edwards' web site.
📚 Nature Microbiology, 4(10):1727 | 🔍 Google Scholar | 🔗 doi:10.1038/s41564-019-0494-6

 

Co-occurring genomic capacity for anaerobic methane and dissimilatory sulfur metabolisms discovered in the Korarchaeota McKay LJ, Dlakić M, Fields MW, Delmont TO, Eren AM, Jay ZJ, Klingelsmith KB, Rusch DB, Inskeep WP
- Yellowstone National Park, archaeal evolution, genome-resolved metagenomics, phylogenomics, and pangenomics (cool stuff all over).
- First description of a microbial population with both anaerobic methane and dissimilatory sulfur metabolisms.
- A news article by Montana State University with the photographs of cools scientists: 'An organism in Yellowstone hot spring potentially linked to earliest life on Earth'
📚 Nature Microbiology, 4(4):614-622 | 🔍 Google Scholar | 🔗 doi:10.1038/s41564-019-0362-4

 

Transcriptome-wide reprogramming of N 6-methyladenosine modification by the mouse microbiome Wang X, Li Y, Chen W, Shi H, Eren AM, Morozov A, He C, Luo G, Pan T
- N6-methyladenosine (m6A) is the most abundant mesenger RNA modification in mammalian cells, occurring at ~3 modified adenosine residues per transcript.
- Using liquid chromatography/mass spectrometry, this study shows differential occurrence of m6A modifications in brain, liver, and intestinal cells between germ-free and conventional mice, demonstrating that the microbiome has a strong effect on host m6A mRNA modification.
📚 Cell Research, 29:167–170 | 🔍 Google Scholar | 🔗 doi:10.1038/s41422-018-0127-2

 

B cell superantigens in the human intestinal microbiota Bunker JJ, Drees C, Watson AR, Plunkett CH, Nagler CR, Schneewind O, Eren AM, Bendelac A 📚 Science Translational Medicine, 11(507):eaau9356 | 🔍 Google Scholar | 🔗 doi:10.1126/scitranslmed.aau9356

2018

 

Microbiome characterization by high-throughput transfer RNA sequencing and modification analysis Schwartz MH, Wang H, Pan JN, Clark WC, Cui S, Eckwahl MJ, Pan DW, Parisien M, Owens SM, Cheng BL, Martinez K, Xu J, Chang EB, Pan T‡, Eren AM‡ ‡Co-senior authors
- The first application of tRNA sequencing to environmental microbiomes (peer reviews and responses).
- Reveals taxon- and diet-dependent variations in tRNA modifications, and provides first in situ insights into 'metaepitranscriptomics' through tRNA gene expression dynamics and post-transcriptional modifications.
- New RNA sequencing strategy provides insight into microbiomes, by Matt Wood.
- RNA sequencing offers novel insights into the microbiome, by Liji Thomas, MD, and Kate Anderton, B.Sc.
📚 Nature Communications, 9(1):5353 | 🔍 Google Scholar | 🔗 doi:10.1038/s41467-018-07675-z

 

Nitrogen-fixing populations of Planctomycetes and Proteobacteria are abundant in surface ocean metagenomes Delmont TO, Quince C, Shaiber A, Esen ÖC, Lee STM, Rappé MS, McLellan SL, Lücker S, Eren AM
- First genomic evidence for abundant and widespread non-cyanobacterial nitrogen-fixing populations in the surface ocean.
- Nearly 1,000 non-redundant, high-quality bacterial, archaeal, and eukaryotic population genomes from TARA Oceans metagenomes.
- A "behind the paper" blog post by Meren, a press release by the MBL, and an extensive description of the bioinformatics workflow.
📚 Nature Microbiology, 3(7):804-813 | 🔍 Google Scholar | 🔗 doi:10.1038/s41564-018-0176-9

 

Linking pangenomes and metagenomes -- the Prochlorococcus metapangenome Delmont TO, Eren AM
- A big-data study in which a pangenome of 31 Prochlorococcus isolates meets 31 billion Tara Oceans metagenomic sequences (Peer-review history).
- Metapangenomes reveal to what extent genes that may be linked to the ecology and fitness of microbes are conserved within a phylogenetic clade.
- Reproducible bioinformatics workflow.
📚 PeerJ, 6(e4320) | 🔍 Google Scholar | 🔗 doi:10.7717/peerj.4320

 

Gut microbes contribute to variation in solid organ transplant outcomes in mice McIntosh CM, Chen L, Shaiber A, Eren AM‡, Alegre M‡ ‡Co-senior authors
- Two groups of genetically identical mice with different microbial community structures differ in their response to skin transplants from genetically identical sources: one group rejects the skin faster than the other.
- Transferring poop from slow-rejecting mice into fast-rejecting mice turns fast-rejecting mice into slow-rejecting mice.
- These suggest that differences in 'resident microbiome' in healthy individuals may contribute to interpersonal variability in graft outcomes, and fecal microbiota transplantation may play a therapeutic role to reverse that phenotype.
- Basically, "we do not have a mechanistic understanding, but this is definitely very interesting".
📚 Microbiome, 6(96) | 🔍 Google Scholar | 🔗 doi:10.1186/s40168-018-0474-8

 

Microbial signals drive pre-leukaemic myeloproliferation in a Tet2-deficient host Meisel M, Hinterleitner R, Pacis A, Chen L, Earley ZM, Mayassi T, Pierre JF, Ernest JD, Galipeau HJ, Thuille N, Bouziat R, Buscarlet M, Ringus DL, Wang Y, Li Y, Dinh V, Kim SM, McDonald BD, Zurenski MA, Musch MW, Furtado GC, Lira SA, Baier G, Chang EB, Eren AM, Weber CR, Busque L, Godley LA, Verdú EF, Barreiro LB, Jabri B
- TET2 deficiency ➡️ deteriorating small intestinal barrier ➡️ bacterial translocation ➡️ incrased IL-6 signalling ➡️ pre-leukemic myeloproliferation (a leukemia precursor).
- ScienceDaily: Under certain conditions, bacterial signals set the stage for leukemia.
📚 Nature, 557(7706):580–584 | 🔍 Google Scholar | 🔗 doi:10.1038/s41586-018-0125-z

2017

 

Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics Lee STM☯, Kahn SA☯, Delmont TO, Shaiber A, Esen ÖC, Hubert NA, Morrison HG, Antonopoulos DA, Rubin DT, Eren AM ☯Co-first authors
- An FMT study with metagenome-assembled genomes (see public data).
- Bacteroidales: high-colonization rate. Clostridiales: low colonization rate. Colonization success is negatively correlated with the number of genes related to sporulation.
- MAGs with the same taxonomy showed different colonization properties, highlighting the importance of high-resolution analyses.
- Populations colonized both recipients were also prevalent in the HMP cohort (and the ones that did not, distribute sporadically across the HMP cohort).
📚 Microbiome, 5(50) | 🔍 Google Scholar | 🔗 doi:10.1186/s40168-017-0270-x

 

Simulations predict microbial responses in the environment? This environment disagrees retrospectively Delmont TO, Eren AM
- A letter that re-analyzes some of the findings published in Hu et al.
- Here is a rebuttal from Probst et al. challenging our findings in this letter.
- Here is our response to Probst et al., and the recovery of DWH O. Desum v2.
📚 Proceedings of the National Academy of Sciences, 114(43):E8947-E8949 | 🔍 Google Scholar | 🔗 doi:10.1073/pnas.1712186114

 

Genomic variation in microbial populations inhabiting the marine subseafloor at deep-sea hydrothermal vents Anderson RE, Reveillaud J, Reddington E, Delmont TO, Eren AM, McDermott JM, Seewald JS, Huber JA 📚 Nature Communications, 8(1):1114 | 🔍 Google Scholar | 🔗 doi:10.1038/s41467-017-01228-6

 

DESMAN: a new tool for de novo extraction of strains from metagenomes Quince C, Delmont TO, Raguideau S, Alneberg J, Darling AE, Collins G, Eren AM 📚 Genome Biology, 18(1):181 | 🔍 Google Scholar | 🔗 doi:10.1186/s13059-017-1309-9

 

Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, Schulz F, Jarett J, Rivers AR, Eloe-Fadrosh EA, Tringe SG, Ivanova NN, Copeland A, Clum A, Becraft ED, Malmstrom RR, Birren B, Podar M, Bork P, Weinstock GM, Garrity GM, Dodsworth JA, Yooseph S, Sutton G, Glöckner FO, Gilbert JA, Nelson WC, Hallam SJ, Jungbluth SP, Ettema TJG, Tighe S, Konstantinidis KT, Liu W, Baker BJ, Rattei T, Eisen JA, Hedlund B, McMahon KD, Fierer N, Knight R, Finn R, Cochrane G, Karsch-Mizrachi I, Tyson GW, Rinke C, Consortium TGS, Lapidus A, Meyer F, Yilmaz P, Parks DH, Eren AM, Schriml L, Banfield JF, Hugenholtz P, Woyke T 📚 Nature biotechnology, 35(8):725 | 🔍 Google Scholar | 🔗 doi:10.1038/nbt.3893

 

Peripartum antibiotics promote gut dysbiosis, loss of immune tolerance, and inflammatory bowel disease in genetically prone offspring Miyoshi J, Bobe AM, Miyoshi S, Huang Y, Hubert N, Delmont TO, Eren AM, Leone V, Chang EB
- Antibiotics during pregnancy promote offspring gut dysbiosis, immune dysfunction, and IBD.
- Antibiotics given after the developmental period do not increase IBD.
- Antibiotic-perturbed maternal microbiota likely contribute to neonatal gut dysbiosis.
- Press release.
📚 Cell Reports, 20(2):491-504 | 🔍 Google Scholar | 🔗 doi:10.1016/j.celrep.2017.06.060

2016

 

Identifying contamination with advanced visualization and analysis practices: metagenomic approaches for eukaryotic genome assemblies Delmont TO, Eren AM
- A holistic approach to visualize and curate genomic and metagenomic assemblies.
- A re-analysis of the first released Tardigrade genome reveals a likely symbiont among other contaminants.
- A practical approach to estimate the number bacterial genomes in an assembly.
📚 PeerJ, 4:e1839 | 🔍 Google Scholar | 🔗 doi:10.7717/peerj.1839

 

Patient-specific bacteroides genome variants in pouchitis Vineis JH, Ringus DL, Morrison HG, Delmont TO, Dalal S, Raffals LH, Antonopoulos DA, Rubin DT, Eren AM, Chang EB, Sogin ML 📚 mBio, 7(6):e01713-16 | 🔍 Google Scholar | 🔗 doi:10.1128/mBio.01713-16

 

New insights into microbial ecology through subtle nucleotide variation Eren AM, Sogin ML, Maignien L 📚 Frontiers in microbiology, 7:1318 | 🔍 Google Scholar | 🔗 doi:10.3389/fmicb.2016.01318

 

Millions of reads, thousands of taxa: microbial community structure and associations analyzed via marker genes Bálint M, Bahram M, Eren AM, Faust K, Fuhrman JA, Lindahl B, O'Hara RB, Öpik M, Sogin ML, Unterseher M, Tedersoo L 📚 FEMS Microbiology Reviews, 40(5):686-700 | 🔍 Google Scholar | 🔗 doi:10.1093/femsre/fuw017

2015

 

Anvi'o: an advanced analysis and visualization platform for ‘omics data Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, Delmont TO
- The very first description of anvi'o.
- Demonstrating its abilities in genome-resolved metagenomics, and microbial populatio genetics via single-nucleotide variant analyses across metagenomes.
- Re-analysis of cultivar genomes, metagenomes, and metatranscriptomes associated with the Deepwater Horizon oil spill.
📚 PeerJ, 3:e1319 | 🔍 Google Scholar | 🔗 doi:10.7717/peerj.1319

 

Minimum entropy decomposition: unsupervised oligotyping for sensitive partitioning of high-throughput marker gene sequences Eren AM, Morrison HG, Lescault PJ, Reveillaud J, Vineis JH, Sogin ML 📚 The ISME Journal, 9(4):968 | 🔍 Google Scholar | 🔗 doi:10.1038/ismej.2014.195

 

A single genus in the gut microbiome reflects host preference and specificity Eren AM, Sogin ML, Morrison HG, Vineis JH, Fisher JC, Newton RJ, McLellan SL 📚 The ISME Journal, 9(1):90 | 🔍 Google Scholar | 🔗 doi:10.1038/ismej.2014.97

 

Reconstructing rare soil microbial genomes using in situ enrichments and metagenomics Delmont TO, Eren AM, Maccario L, Prestat E, Esen ÖC, Pelletier E, Paslier DL, Simonet P, Vogel TM
- Application of in situ enrichments to shape the diversity of complex metagenomes prior to sequencing.
- The first successful attempt to assemble multiple near-complete bacterial genomes directly from a soil sample.
- The abundance of reconstructed genomes ranged from rare (<0.0001%) to relatively abundant (>0.01%) in pristine soil metagenomes.
📚 Frontiers in microbiology, 6:358 | 🔍 Google Scholar | 🔗 doi:10.3389/fmicb.2015.00358

 

Extensive modulation of the fecal metagenome in children with Crohn’s disease during exclusive enteral nutrition Quince C, Ijaz UZ, Loman N, Eren AM, Saulnier D, Russell J, Haig SJ, Calus ST, Quick J, Barclay A, Bertz M, Blaut M, Hansen R, McGrogan P, Russell RK, Edwards CA, Gerasimidis K 📚 The American journal of gastroenterology, 110(12):1718 | 🔍 Google Scholar | 🔗 doi:10.1038/ajg.2015.357

 

Sewage reflects the microbiomes of human populations Newton RJ, McLellan SL, Dila DK, Vineis JH, Morrison HG, Eren AM, Sogin ML 📚 mBio, 6(2):e02574-14 | 🔍 Google Scholar | 🔗 doi:10.1128/mBio.02574-14

2014

 

Oligotyping analysis of the human oral microbiome Eren AM, Borisy GG, Huse SM, Welch aJLM 📚 Proceedings of the National Academy of Sciences, 111(28):E2875-E2884 | 🔍 Google Scholar | 🔗 doi:10.1073/pnas.1409644111

 

Discovering new indicators of fecal pollution McLellan SL, Eren AM 📚 Trends in Microbiology, 22(12):697-706 | 🔍 Google Scholar | 🔗 doi:10.1016/j.tim.2014.08.002

 

Dynamics of tongue microbial communities with single-nucleotide resolution using oligotyping Welch JLM, Utter DR, Rossetti BJ, Welch DBM, Eren AM, Borisy GG 📚 Frontiers in microbiology, 5:568 | 🔍 Google Scholar | 🔗 doi:10.3389/fmicb.2014.00568

 

Humpback whale populations share a core skin bacterial community: towards a health index for marine mammals? Apprill A, Robbins J, Eren AM, Pack AA, Reveillaud J, Mattila D, Moore M, Niemeyer M, Moore KMT, Mincer TJ 📚 PLoS One, 9(3):e90785 | 🔍 Google Scholar | 🔗 doi:10.1371/journal.pone.0090785

 

Host-specificity among abundant and rare taxa in the sponge microbiome Reveillaud J, Maignien L, Eren AM, Huber JA, Apprill A, Sogin ML, Vanreusel A 📚 The ISME Journal, 8(6):1198-209 | 🔍 Google Scholar | 🔗 doi:10.1038/ismej.2013.227

 

Ecological succession and stochastic variation in the assembly of Arabidopsis thaliana phyllosphere communities Maignien L, DeForce EA, Chafee ME, Eren AM, Simmons SL 📚 mBio, 5(1):e00682-13 | 🔍 Google Scholar | 🔗 doi:10.1128/mBio.00682-13

2013

 

Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data Eren AM, Maignien L, Sul WJ, Murphy LG, Grim SL, Morrison HG, Sogin ML 📚 Methods in Ecology and Evolution, 4(12):1111-1119 | 🔍 Google Scholar | 🔗 doi:10.1111/2041-210X.12114

 

A filtering method to generate high quality short reads using Illumina paired-end technology Eren AM, Vineis JH, Morrison HG, Sogin ML 📚 PLOS ONE, 8(6):e66643 | 🔍 Google Scholar | 🔗 doi:10.1371/journal.pone.0066643

 

DRISEE overestimates errors in metagenomic sequencing data Eren AM, Morrison HG, Huse SM, Sogin ML 📚 Briefings in Bioinformatics, 15(5):783-787 | 🔍 Google Scholar | 🔗 doi:10.1093/bib/bbt010

 

Sewage reflects the distribution of human faecal Lachnospiraceae McLellan SL, Newton RJ, Vandewalle JL, Shanks OC, Huse SM, Eren AM, Sogin ML 📚 Environmental Microbiology, 15(8):2213-2227 | 🔍 Google Scholar | 🔗 doi:10.1111/1462-2920.12092