Cited by 5,748Genomics and Phylogenetic StudiesBacterial Identification and Susceptibility TestingMicrobial Community Ecology and Physiology

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High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries

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Jain, Chirag, Rodriguez-R, Luis M., Phillippy, Adam M., Konstantinidis, Konstantinos T., Aluru, Srinivas·2018·Nature Communications

DOI 10.1038/s41467-018-07641-9PMC PMC6269478

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Abstract

A fundamental question in microbiology is whether there is continuum of genetic diversity among genomes, or clear species boundaries prevail instead. Whole-genome similarity metrics such as Average Nucleotide Identity (ANI) help address this question by facilitating high resolution taxonomic analysis of thousands of genomes from diverse phylogenetic lineages. To scale to available genomes and beyond, we present FastANI, a new method to estimate ANI using alignment-free approximate sequence mapping. FastANI is accurate for both finished and draft genomes, and is up to three orders of magnitude faster compared to alignment-based approaches. We leverage FastANI to compute pairwise ANI values among all prokaryotic genomes available in the NCBI database. Our results reveal clear genetic discontinuity, with 99.8% of the total 8 billion genome pairs analyzed conforming to >95% intra-species and <83% inter-species ANI values. This discontinuity is manifested with or without the most frequently sequenced species, and is robust to historic additions in the genome databases.

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Fig. 1 Correlation of FastANI and Mash-based ANI output with ANIb values for datasets D1–D5. Because FastANI assumes a probabilistic identity cutoff that is set to 80% by default, it reports 76, 570, 4271, 464, and 130 genome matches for the individual queries in datasets D1–D5 respectively. To enable a direct quality comparison against FastANI, Mash is executed for only those pairs that are reported by FastANI. Notice that each dataset encompasses a different nucleotide identity range (x-axes). Gray line represents a straight line y = x plot for reference. Pearson correlation coefficients corresponding to these plots are listed separately in Table 2. Last plot shows error of these methods w.r.t. ANIb using all five datasetsCC BY · PubMed Central

Fig. 2 Scaling up FastANI’s performance using multi-core parallel execution. We executed parallel FastANI processes on 40 physical cores, where each process was assigned an equally sized part of the reference D1–D5 databases. Left and right plots evaluate FastANI’s compute and indexing phase, respectively. FastANI achieves reasonable speedups on all datasets except the compute phase in D1 and D5, as their runtime on a single core is too small to begin with (Table 3)CC BY · PubMed Central

Fig. 3 Genetic discontinuity observed using 90 K genomes. a Histogram plot showing the distribution of ANI values among the 90 K genomes. Only ANI values in the 76–100% range are shown. Out of total 8.01 billion pairwise genome comparisons, FastANI reported only 17M ANI values (0.21%) with ANI between 83 and 95% indicating a genetic discontinuum. Multiple colors are used to show how genomes from different genera are contributing to this distribution. Few peaks in the histogram arise from genera that have been extensively sequenced and dominate the database. b Density curves of ANI values in the ANI range 76–100%. Each curve shows the density curve corresponding to the database at a particular time period. Discontinuity in all four curves is observed consistently. c. Distribution of ANI values with each comparison labeled by the nomenclature of genomes being compared. All the comparisons between Escherichia coli and Shigella spp. have been labeled separately. The 95% ANI threshold on x-axis serves as a valid classifier for comparisons belonging to same and different speciesCC BY · PubMed Central

Fig. 4 FastANI algorithm explained using synthetic and real examples. a Illustration of FastANI’s work-flow for computing ANI between a query genome and a reference genome. Five mappings are obtained from three query fragments using Mashmap24. Mforward saves the maximum identity mapping for each query fragment. In this example, Mforward = {m2, m4, m5}. From this set, Mreciprocal picks m4 and m5 as the maximum identity mapping for each reference bin. Mapping identities of orthologous mappings, thus found in Mreciprocal, are finally averaged to compute ANI. b FastANI supports visualization of the orthologous mappings Mreciprocal that are used to estimate the ANI value using genoPlotR39. In this figure, ANI is computed between Bartonella quintana strain (NC_018533.1) as query and Bartonella henselae strain (NC_005956.1) as reference. Red line segments denote the orthologous mappings computed by FastANI for ANI estimationCC BY · PubMed Central

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“…types strains with the smallest MASH distances were chosen for further analysis via average nucleotide identity (ANI) determination with fastANI (Jain et al., 2018), digital DNA-DNA hybridization (dDDH) (Meier-Kolthoff et al., 2013) and a phylogenomic reconstruction with a set of 92 bacterial…”
Method
Salvaging high-quality genomes of microbial species from a meromictic lake using a hybrid sequencing approach
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Selection of Anabaena sp. PCC 7938 as a Cyanobacterium Model for Biological ISRU on Mars
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Genome-resolved metagenomics reveals novel archaeal and bacterial genomes from Amazonian forest and pasture soils
Venturini, A. M., Gontijo, J. B., Mandro, J. A., Paula, F. S., Yoshiura, C. A., da França, A. G., & Tsai, S. M. (2022) · Microbial Genomics · doi:10.1099/mgen.0.000853 · Cited by 32
Improved gut microbiome recovery following drug therapy is linked to abundance and replication of probiotic strains
FitzGerald, J. A., Patel, S. H., Eckenberger, J., Guillemard, E., Veiga, P., Schäfer, F., Walter, J., Claesson, M. J., & Derrien, M. (2022) · Gut Microbes · doi:10.1080/19490976.2022.2094664 · Cited by 37
Long-Read-Resolved, Ecosystem-Wide Exploration of Nucleotide and Structural Microdiversity of Lake Bacterioplankton Genomes
Okazaki, Y., Nakano, S., Toyoda, A., & Tamaki, H. (2022) · mSystems · doi:10.1128/msystems.00433-22 · Cited by 29
“31) (40) and the hclust function (method = “average”) of R v4.”
Method
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Weigert, S., Pérez-García, P., Gisdon, F. J., Gagsteiger, A., Schweinshaut, K., Ullmann, G. M., Chow, J., Streit, W. R., & Höcker, B. (2022) · Protein Science · doi:10.1002/pro.4500 · Cited by 32
“ANI was calculated using FastANI.(68) For the more extensive pangenomic analysis in Figure S1, the genomes of V.”
Method
Low diversity and microdiversity of comammox bacteria in wastewater systems suggest specific adaptations within the Ca. Nitrospira nitrosa cluster
Cotto, I., Vilardi, K. J., Huo, L., Fogarty, E. C., Khunjar, W., Wilson, C., Clippeleir, H. D., Gilmore, K. R., Bailey, E., Lücker, S., et al. (2022) · Water Research · doi:10.1016/j.watres.2022.119497 · Cited by 32
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Intensive care unit sinks are persistently colonized with multidrug resistant bacteria and mobilizable, resistance-conferring plasmids
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“Those reference genomes were combined with our assembled draft genomes and compared in an all-vs-all manner using FastANI to calculate ANI between each pair of isolates (77).”
BackgroundMethod
VEBA: a modular end-to-end suite for in silico recovery, clustering, and analysis of prokaryotic, microeukaryotic, and viral genomes from metagenomes
Espinoza, J. L., & Dupont, C. L. (2022) · BMC Bioinformatics · doi:10.1186/s12859-022-04973-8 · Cited by 31
The Next Generation of Microbial Ecology and Its Importance in Environmental Sustainability
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Strain-level diversity in sulfonamide biodegradation: adaptation of Paenarthrobacter to sulfonamides
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“32) [29] and CompareM (v0.”
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Smallman, T. R., Perlaza-Jiménez, L., Wang, X., Korman, T. M., Kotsanas, D., Gibson, J. S., Turni, C., Harper, M., & Boyce, J. D. (2024) · Microbiology Spectrum · doi:10.1128/spectrum.03805-23 · Cited by 31
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“ANI was estimated with fastANI [36].”
Genetic diversity, determinants, and dissemination of Burkholderia pseudomallei lineages implicated in melioidosis in Northeast Thailand
Seng, R., Chomkatekaew, C., Tandhavanant, S., Saiprom, N., Phunpang, R., Thaipadungpanit, J., Batty, E. M., Day, N., Chantratita, W., West, T. E., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50067-9 · Cited by 31
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“As all R. gnavus genomes included here share at least 95% similarity with one another, which is often considered the species boundary 25,26 , we consider that these clades represent sub-species.”
Influential
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“Advances in whole-genome sequencing and computational methods have enabled more robust approaches, such as Average Nucleotide Identity (ANI) analysis and Multi-Locus Sequence Analysis (MLSA) [ 5–7 ].”
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“ANI values were calculated using fastANI (v.1.3.4) 82 .”
Influential
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“32 (46) and genome-to-genome distance calculator (formula 2) (47) with the recommended parameters and/or default settings, respectively.”
Background
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“Pairwise genome-wide ANI was calculated among the four Accumulibacter draft genomes and all available Accumulibacter genomes in GenBank with FastANI (40).”
BackgroundMethod
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“Three of these MAGs were of the order Bryobacteriales (1S_bin014, 1S_bin026, and 2S_bin014) but all pairwise comparisons of average nucleotide identity (ANI) (Jain et al., 2018) were between 77 and 79%.”
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“The resulting phylogenies from ASTRAL, STACEY, and FASTANI were visualized and annotated using the Interactive Tree of Life (iTOL) web portal (Letunic and Bork, 2019; URL: https://itol. embl.de).”
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“32 (Jain et al., 2018) and querying the PubMLST dedicated database (Jolley et al.”
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“Mash and FastANI both have many zeroed-out values, and therefore, the least-squares fit is not shown for these two.”
Influential
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“3.3) [37] nucleotide similarities multiplied with the ratio of aligned fractions.”
Influential
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“Thereafter, our goat kid-specific GKGMC was aligned with RGMC and GMMC using FastANI, according to previously reported genome thresholds for species and strain delineation of ≥ 95% and ≥ 99% ANI, respectively, and ≥ 60% of the genome [36].”
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“ANI scores were calculated with the FastANI tool [62].”
Method
Extracellular vesicle formation in Euryarchaeota is driven by a small GTPase
Mills, J., Mills, J., Gebhard, L., Gebhard, L., Schubotz, F., Schubotz, F., Shevchenko, A., Shevchenko, A., Speth, D., Speth, D. R., et al. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2311321121 · Cited by 34

Authors: Jain, C., Rodriguez-R, L. M., Phillippy, A. M., Konstantinidis, K. T., & Aluru, S.
Affiliations: National Institutes of Health (US)
Georgia Institute of Technology (US)
Corresponding author: Konstantinidis, Konstantinos T.
Aluru, Srinivas
ORCID: Jain, Chirag
Rodriguez-R, Luis M.
Phillippy, Adam M.
Konstantinidis, Konstantinos T.
Aluru, Srinivas
Venue: Nature Communications
Publisher: Springer Science and Business Media LLC
Published: 2018-11-30
Volume: 9
Issue: 1
Pages: 5114-5114
ISSN: 2041-1723 (ISSN-L)
DOI: 10.1038/s41467-018-07641-9
PMC: PMC6269478
OpenAlex: W2951254987
Cited by: 5,748
References: 40
Citations by year: 2026: 1107 · 2025: 1110 · 2024: 977 · 2023: 789 · 2022: 695 · 2021: 617 · 2020: 305 · 2019: 128 · 2018: 16
FWCI: 96.11
Type: journal article
Language: en
Open access: gold
doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0 (tdm)
creativecommons.org/licenses/by/4.0 (vor)
Locations: Nature Communications (publishedVersion, cc-by)
bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
Europe PMC (PubMed Central) (publishedVersion, other-oa)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
Funders: National Science Foundation (1416259, 1816027, 1356288)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Health Sciences › Medicine › Microbiology (medical) › Bacterial Identification and Susceptibility Testing
Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
Keywords: average nucleotide identity, prokaryotic genomes, species boundaries, taxonomic classification, draft genome sequence
MeSH terms: Phylogeny, Prokaryotic Cells, Genetic Variation, Databases, Factual, Genome, Bacterial, Sequence Analysis, DNA

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High throughput ANI analysis of 90K prokaryotic genomes reveals clear species boundaries

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