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Origin of microbial biomineralization and magnetotaxisduring the ArcheanWei Lina,b,1,2, Greig A. Patersona,2, Qiyun Zhuc, Yinzhao Wanga,b, Evguenia Kopylovad, Ying Lie, Rob Knightd,f,Dennis A. Bazylinskig, Rixiang Zhuh, Joseph L. Kirschvinki,j,1, and Yongxin Pana,b,1
aKey Laboratory of Earth and Planetary Physics, Institute of Geology and Geophysics, Chinese Academy of Sciences, Beijing 100029, China; bFrance–ChinaBio-Mineralization and Nano-Structures Laboratory, Chinese Academy of Sciences, Beijing 100029, China; cGenomic Medicine, J. Craig Venter Institute, LaJolla, CA 92037; dDepartment of Pediatrics, University of California, San Diego, La Jolla, CA 92037; eCollege of Biological Sciences, China AgriculturalUniversity, Beijing 100193, China; fDepartment of Computer Science and Engineering, University of California, San Diego, La Jolla, CA 92037; gSchool of LifeSciences, University of Nevada, Las Vegas, NV 89154-4004; hState Key Laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, ChineseAcademy of Sciences, Beijing 100029, China; iDivision of Geological and Planetary Sciences, California Institute of Technology, Pasadena, CA 91125;and jEarth–Life Science Institute, Tokyo Institute of Technology, Meguro, Tokyo 152-8551, Japan
Edited by Donald E. Canfield, Institute of Biology and Nordic Center for Earth Evolution, University of Southern Denmark, Odense M, Denmark, and approvedJanuary 10, 2017 (received for review September 3, 2016)
Microbes that synthesize minerals, a process known as microbialbiomineralization, contributed substantially to the evolution ofcurrent planetary environments through numerous importantgeochemical processes. Despite its geological significance, theorigin and evolution of microbial biomineralization remain poorlyunderstood. Through combined metagenomic and phylogeneticanalyses of deep-branching magnetotactic bacteria from the Nitro-spirae phylum, and using a Bayesian molecular clock-datingmethod, we show here that the gene cluster responsible for bio-mineralization of magnetosomes, and the arrangement of magne-tosome chain(s) within cells, both originated before or near theArchean divergence between the Nitrospirae and Proteobacteria.This phylogenetic divergence occurred well before the Great Oxy-genation Event. Magnetotaxis likely evolved due to environmen-tal pressures conferring an evolutionary advantage to navigationvia the geomagnetic field. Earth’s dynamo must therefore havebeen sufficiently strong to sustain microbial magnetotaxis in theArchean, suggesting that magnetotaxis coevolved with the geo-dynamo over geological time.
Archean | microbial biomineralization | magnetotaxis |magnetotactic bacteria | geodynamo
Magnetotactic bacteria (MTB) are a polyphyletic group ofmicroorganisms that biomineralize intracellular nano-sized
magnetosomes of magnetite (Fe3O4) and/or greigite (Fe3S4) (1).Magnetosomes are normally organized into chain-like structures tofacilitate the navigation of MTB using Earth’s magnetic field, abehavior known as magnetotaxis (2). Because of their ubiquitousdistribution, MTB play key roles in global iron, nitrogen, sulfur,and carbon cycling (3). Magnetosome crystals can be preservedas magnetofossils after MTB die and lyse, and these crystals canbe used as reliable biomarkers and are major contributors tosedimentary paleomagnetic records (4–7). Evidence suggeststhat magnetofossils as old as ∼1.9 Ga may be preserved (4).Molecular and genetic studies have identified a group of
clustered genes that control magnetosome biomineralization inMTB (8–10). However, the origin and evolution of these mag-netosome gene clusters (MGCs) remain controversial, and severalscenarios have been posited to explain the patchy distribution ofmagnetosome formation over a broad phylogenetic range. Suchscenarios include multiple evolutionary origins (11), extensive hor-izontal gene transfers (12), and vertical gene transfer (13, 14). MTBin the Nitrospirae phylum represent one of the deep-branchingMTB groups (15, 16). Therefore, analysis of MGCs from NitrospiraeMTB could yield insights into the origin and evolution of magne-tosome biomineralization and magnetotaxis. However, no Nitro-spirae MTB has been successfully cultured, and only three draftgenomes from this phylum are currently available (17, 18). Recentadvances in high-throughput sequencing combined with improving
computational methods are enabling the successful recovery ofhigh-quality population genomes directly from metagenomic data(19, 20). Here, we assess whether the phylogenies of key magne-tosome genes from MTB of the Nitrospirae and Proteobacteria phylaare consistent with their taxonomic phylogeny using a metagenomicapproach to acquire the population genome and MGC-containingcontigs from environmental Nitrospirae MTB.
ResultsWe sampled MTB from two freshwater locations in China: thecity moat of Xi’an in Shaanxi province (HCH) and Lake Miyunnear Beijing (MY). MTB belonging to the Nitrospirae phylum wereidentified in both samples (Fig. S1). Recovered metagenomic DNAwas sequenced and assembled into contigs, which generated∼13 Mb of 3,042 contigs ≥1 kb for HCH and ∼32 Mb of 7,893
Significance
A wide range of organisms sense Earth’s magnetic field fornavigation. For some organisms, like magnetotactic bacteria,magnetic particles form inside cells and act like a compass.However, the origin of magnetotactic behavior remains a mys-tery. We report that magnetotaxis evolved in bacteria during theArchean, before or near the divergence between the Nitrospiraeand Proteobacteria phyla, suggesting that magnetotactic bacteriaare one of the earliest magnetic-sensing and biomineralizing or-ganisms on Earth. The early origin for magnetotaxis would haveprovided evolutionary advantages in coping with environmentalchallenges faced by microorganisms on early Earth. The persis-tence of magnetotaxis in separate lineages implies the temporalcontinuity of geomagnetic field, and this biological evidenceprovides a constraint on the evolution of the geodynamo.
Author contributions: W.L., J.L.K., and Y.P. designed research; W.L. and Y.W. performedresearch; Q.Z. contributed new reagents/analytic tools; W.L. and Y.W. collected samples;W.L., G.A.P., and Q.Z. analyzed data; andW.L., G.A.P., Q.Z., E.K., Y.L., R.K., D.A.B., R.Z., J.L.K.,and Y.P. wrote the paper.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
Freely available online through the PNAS open access option.
Data deposition: The draft genome of Candidatus Magnetominusculus xianensis strainHCH-1 reported in this paper has been deposited in the DNA Data Bank of Japan (DDBJ)/European Molecular Biology Laboratory (EMBL)/GenBank database (accession no.LNQR00000000; the version described in this paper is LNQR01000000). The magnetosomegene cluster-containing contigs reported in this paper have been deposited in the DDBJ/EMBL/GenBank database (accession nos. KU221504–KU221507).1To whom correspondence may be addressed. Email: [email protected], [email protected], or [email protected].
2W.L. and G.A.P. contributed equally to this work.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.1073/pnas.1614654114/-/DCSupplemental.
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contigs ≥1 kb for MY (Table S1). In HCH, only a single populationbelonging to the phylum Nitrospirae was found and comprised∼19% of the sampled MTB community (Fig. S1). The pop-ulation genome of this Nitrospirae was recovered using a com-bination of similarity- and composition-based approaches (Table1). Only a single copy of an rRNA operon was identified, whichhad a 16S rRNA gene sequence with <92% similarity to thegenera Candidatus Magnetobacterium (17, 18) and CandidatusMagnetoovum (18). This MTB population was named as “Can-didatus Magnetominusculus xianensis” strain HCH-1 (HCH-1hereafter). One contig (18,138 bp) of HCH-1 contained a nearlycomplete MGC including homologs to known magnetosomegenes (Fig. 1A and Table S2). Despite their phylogenetic dis-tance, the gene content and gene order of the MGC from HCH-1and available Nitrospirae MGCs were highly conserved (>76%,Fig. 1A).To explore the evolutionary history of the MGCs between the
Nitrospirae and Proteobacteria phyla, we performed a phyloge-netic analysis of five core magnetosome proteins (MamABEKP)from HCH-1 and published MTB strains. These proteins wereselected because they were the only bidirectional best hits betweenthe complete MGC of the Nitrospirae MTB strain “CandidatusMagnetobacterium casensis” (Mcas) and that of representativeProteobacteria MTB. These five proteins from the Nitrospirae phy-lum form a monophyletic group (Fig. S2). Branches with >75%bootstrap values have similar topology and agree with those in thetree based on concatenated magnetosome proteins (Fig. 1B). This isconsistent with the pattern in the phylogenomic tree that is gener-ated based on a concatenated alignment of up to 400 highlyconserved proteins (Fig. 1B), suggesting that these magnetosomegenes coevolved via vertical transmission with the genome. Fur-thermore, comparison of magnetosome genes to three housekeep-ing genes (recA, gyrB, and pyrH) revealed that the codon use biaswas not significantly different (P > 0.05 by t test) betweenmagnetosome genes and the vertically transmitted housekeepinggenes. Similarly, the number of synonymous substitutions persynonymous site was also not significantly different (P > 0.05 by ttest; Fig. 1C). The results of the codon use test are consistentwith that of the phylogenetic-based analysis, which rules outuncertainty in the reliability of the codon analysis alone (21), andstrongly suggest that the magnetosome genes were inheritedthrough vertical transfer (22). Together, these results indicatethat magnetosome biomineralization and magnetotaxis is anancient metabolic process and was present before the separationof the Nitrospirae and Proteobacteria phyla, or transferred unde-tectably early between the base of Nitrospirae and Proteobacteriasoon after divergence.
Considering the deep-branching lineage of Nitrospirae MTBand their tightly packed magnetosome genes (Fig. 1A), thecontent and order of magnetosome genes in Nitrospirae are likelyconserved and represent an ancestral MGC. To test this, wecompared the implicit phylogenetic pattern of the core magne-tosome genes to all other genes in HCH-1 and available Nitro-spirae MTB genomes. The magnetosome genes are clusteredtoward the majority of other genes (Fig. 2A), suggesting that theevolutionary history of magnetosome genes in Nitrospirae is notdistinct from the genomic background. Analysis of metagenomicdata from MY yielded four contigs containing nearly completeNitrospirae MGCs (Fig. 2B). Of these, contig MY-22 (44,819 bp)was >99.99% identical to the MGC of previously identified Mcasisolated from the same lake (17), indicating the high-quality as-sembly of metagenomic contigs in this study. All four MGCshave a high level of conservation with HCH-1, Mcas, “Candi-datus Magnetobacterium bavaricum” (Mbav), and “CandidatusMagnetoovum chiemensis” strain CS-04 (Mchi) (Fig. 2B). Phy-logenetic trees of concatenated magnetosome proteins (Fig. 2B)and each of MamABEKP (Fig. S3) from the Nitrospirae MGCsform a monophyletic group with consistent topology, whichfurther indicates the coevolution of magnetosome genes andtheir antiquity and suggests the origin of magnetotaxis is earlierthan previously thought (13). Considering that all known Nitro-spirae MTB biomineralize bullet-shaped magnetite magneto-somes, a crystal morphology that has not yet been observed inmagnetite as a result of abiotic processes (3), our results indicatethat bullet-shaped magnetite may be the first type of magneto-some (13) and may represent reliable microbial fossils.There are very few geological constraints on the timing of the
separation of the major clades within the Bacterial domain.Earlier evidence, based on organic biomarkers and the followingphylogenetic analysis, suggested an Archean origin of the Pro-teobacteria (23) and the divergence of the Nitrospirae and Pro-teobacteria before ∼2.7 Ga (24). However, the biomarkers uponwhich those inferences were based are now known to be con-taminants (25). A global phylogenomic reconstruction of theevolution of gene families suggests that the Proteobacteria phy-lum diverged during the Archean Eon (26). We calculate the ageof divergence for the Nitrospirae and Proteobacteria by phyloge-nomic and Bayesian relaxed molecular clock analyses (Figs. S4and S5). Two different relaxed clock models (log normal auto-correlated clock and uncorrelated gamma multipliers clock) withtwo different combinations of time calibrations were imple-mented (SI Materials and Methods). Results are consistent acrossclock modes and time calibrations, and all analyses suggest thatthe Nitrospirae and Proteobacteria phyla diverged before 3.0 Ga(∼3.38–3.21 Ga) (Fig. S4). Hence, MTB likely evolved in themid-Archean, and, as previously suggested (4), may be one of theearliest biomineralizing and magnetotactic organisms on Earth.
DiscussionMolecular O2 is abundant in the atmosphere (∼21%) and oceanson the present Earth. The early Earth, however, was character-ized by a reducing system, and the ocean chemistry in theArchean was different from today [e.g., with a scarcity of molecularO2 and abundant dissolved Fe(II) (∼40–120 μmol/L) (27, 28)].Multiple lines of evidence have suggested that, through volcanicprocesses, Archean oceans likely had sufficient nutrients (e.g.,CO2, H2, SO2, H2S, NO, NO−
3 , NO−2 , NH+
4 , etc.) to sustain mi-croorganisms with anaerobic or microaerobic metabolisms (29, 30).All known present-day MTB are microaerophilic and anaerobic,and, according to their metabolic and genomic analyses, it seemsthat the nutrients available in Archean oceans could support thesurvival and growth of MTB. For example, many extant MTB arechemolithoautotrophic and have the ability to fix CO2 either via theCalvin–Benson–Bassham cycle, the reverse tricarboxylic acid cycle,or the reductive acetyl-CoA (Wood–Ljungdahl) pathway (1, 17, 18).
Table 1. General genomic features of the genome ofCandidatus Magnetominusculus xianensis strain HCH-1
ParameterCa. Magnetominusculusxianensis strain HCH-1
Total genome size, Mb 3.593273GC content, % 45.40No. of contigs 152N50, kb 45.767Maximum contig length, kb 150.216No. of coding sequences (CDS) 3,415No. of RNAs 47No. of copies of 5S rRNA 1No. of copies of 16S rRNA 1No. of copies of 23S rRNA 1Estimated completeness, % 98.18Estimated contamination, % 0.91
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They are also capable of reducing NO−3 , NO−
2 , and NO throughthe denitrification pathway and capable of oxidizing H2S throughthe sulfur oxidation pathway (e.g., refs. 17, 18, and 31–33). Thetemperature of Archean ocean water is still debated, with esti-mates ranging from values comparable to modern tropical waters(26–35 °C) (34) to as warm as 55–85 °C (35). Thermophilic MTB,living at temperatures of 32–63 °C, have been discovered inpresent-day hot springs (36), supporting the possibility of thesebacteria surviving in a hot Archean ocean.Extant MTB respond to vertical redox gradients in the water
or sediment columns, particularly that of O2 and H2S, presumablyexploiting these gradients to maintain their optimal positions withintheir microenvironments (1, 37). Archean oceans are traditionally
thought to have been uniformly anoxic and therefore devoid of theredox gradients similar to today. Under such conditions, abundantferrous iron would have been prevalent throughout the entire Ar-chean water column, except in the euphotic zone near the surfacewhere iron-oxidizing photosynthetic bacteria would presumablyrapidly remove it from solution (38). The resultant ferric precipi-tates resulted in the production of the banded iron formations,yielding an “upside-down” biosphere (39), in which the sedimentswere rich in ferric iron but overlain by water rich in dissolved ferrousiron. This might have produced enough of a vertical redoxgradient to provide MTB an environmental niche. Recently,however, there is growing evidence that early oceans mightnot be uniformly anoxic but were redox stratified, likely in
MY3-11A (HM454282)HCH-1 (LNQR00000000)MY2-1F (HM454279)MY4-5C (HM454283)
MHB-1 (AJ863136)MY3-5B (HM454281)
MY2-3C (HM454280)Mbav (X71838)Mcas (JMFO00000000)
Mchi (JX402654)LO-1 (GU979422)
MWB-1 (JN630580)HSMV-1 (GU289667)
AMB-1 (D17514)MSR-1 (Y10109)
QH-2 (EU675666)MC-1 (L06456)
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AlphaproteobacteriaGammaproteobacteriaDeltaproteobacteriaNitrospiraceae
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Fig. 1. (A) Maximum-likelihood phylogenetic tree of 16S rRNA gene sequences showing the relationship between Candidatus Magnetominusculus xianensisstrain HCH-1 (HCH-1) and related magnetotactic bacteria. Bootstrap values at nodes are percentages of 100 replicates. On the right-hand side, comparison ofmagnetosome gene clusters between HCH-1 and other reported Nitrospirae MTB. (B) Bootstrap consensus trees based on concatenated protein alignment offive magnetosome proteins (MamABEKP) and phylogenomic tree based on concatenated ubiquitous amino acid sequences. Only bootstrap values of morethan 75% are shown, and branches of the trees are proportionally transformed. MSR-1, Magnetospirillum gryphiswaldense MSR-1; AMB-1, Magnetospirillummagneticum AMB-1; QH-2, Magnetospira sp. QH-2; MC-1, Magnetococcus marinus MC-1; BW-1, “Candidatus Desulfamplus magnetomortis BW-1”; MMP,“Candidatus Magnetoglobus multicellularis”; RS-1, Desulfovibrio magneticus RS-1; ML-1, alkaliphilic magnetotactic strain ML-1; MV-1, Magnetovibrio bla-kemorei MV-1; IT-1, “Candidatus Magnetofaba australis strain IT-1”; SS-5, Gammaproteobacteria magnetotactic strain SS-5. (C) Comparison of sequencedivergence of five magnetosome genes and three housekeeping genes (recA, gyrB, and pyrH). Nc, the codon use bias; dS, the number of synonymoussubstitutions per synonymous site.
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shallow water, and that “oxygen oases” may have existed as farback as 2.8–3.2 Ga (40–42). These redox-stratified waterscould also provide potential habitable environments for theorigin and evolution of ancient MTB.
Typically, bacteria use a 3D “run-and-tumble” search strategyfor finding their preferred microenvironments. For MTB, mag-netotaxis reduces this 3D search to an optimized 1D search alonggeomagnetic field lines in chemically stratified water or sediment
mam gene mad gene
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Candidatus Magnetominusculus xianensis Candidatus Magnetobacterium bavaricum
Candidatus Magnetobacterium casensis Candidatus Magnetoovum chiemensis
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Fig. 2. (A) Implicit phylogenetic pattern of magnetosome core genes (mamABEIKMOPQ) of four Nitrospirae MTB in their genomic background. Each pointrepresents a protein-coding gene in the genome, with magnetosome core genes highlighted in red. The x axis represents the sum of the relative bit scores ofall hits within the phylum Nitrospirae, and the y axis represents that outside the phylum Nitrospirae. Typically, genes that were vertically transmitted have amoderate-to-high x value, representing its homologs in closely related taxonomic groups. Genes with a horizontal origin outside this phylum have a zero-to-low x value along with a moderate-to-high y value, representing homologs in distant taxonomic groups instead of close ones. Genes without traceableevolutionary history are located close to the origin, suggesting a lack of homologs in the database. (B) Maximum-likelihood tree based on a concatenation ofMamABEP and schematic comparison of the Nitrospirae MGCs recovered from metagenomic data of MY with those of HCH-1, Mcas, Mbav, and Mchi.
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columns (2). Previous observations that magnetofossil concen-trations in marine sediments plummet during weak-field intervalssurrounding geomagnetic reversals implies that magnetotaxis con-fers a selective advantage in field strengths of ∼6 μT or greater (43).Recent analysis of reliable Archean paleointensity data suggeststhat field strengths of 20–50 μT are observed (44), indicating thatthe Archean geodynamo was sufficient to support magnetotaxis. AnArchean origin of magnetotaxis, and its persistence in multiplelineages since their divergence during Archean time, implies bothtemporal continuity of Earth’s dynamo and persistent environ-mental stratification.The present study suggests an ancient origin of MTB in the
Archean Eon that is much earlier than previously reported. MTBtherefore represent one of the earliest magnetic-sensing andbiomineralizing organisms on Earth. The Archean origin ofMTB indicates that magnetotaxis is an evolutionarily ancientcharacteristic and that evolved in response to gradients in theArchean environment.
Materials and MethodsSite Description and MTB Sample Preparation. Surface sediments (depths of5–10 cm) were sampled from the following two freshwater locations in China:the city moat of Xi’an in Shaanxi province (HCH) (34.25287, 108.92187), andLake Miyun near Beijing (MY) (40.48874, 117.00714). The collected sedi-ments were transferred to 600-mL plastic flasks, transported to the labora-tory (in Beijing), and incubated at room temperature without disturbance.MTB cells from HCH were magnetically enriched using a double-ended openmagnetic separation apparatus known as the “MTB trap” (45). The collectedcells were washed twice and resuspended in sterile distilled water. MTBsamples from MY used in this work were collected by Lin et al. (46) and hadbeen stored at −80 °C. Genomic DNA was extracted from the enriched MTBby using the TIANamp Bacteria DNA Kit (Tiangen) following the manufac-turer’s instructions.
16S rRNA Gene Sequences Generation and Analysis. 16S rRNA gene sequenceswere amplified using the bacteria/archaeal universal primers 515F/806R thattarget the V4 region (47). The purified PCR products were cloned into thepMD19-T vector (TaKaRa) and chemically DH5a competent cells (Tiangen),following the manufacturers’ instructions. Clones were randomly selectedand were sequenced using an ABI 3730 genetic analyzer (Beijing GenomicsInstitute, Beijing, China). Sequences were processed, aligned, and clusteredinto operational taxonomic units (OTUs) using the QIIME pipeline (48).
Shotgun Metagenomic Sequencing and Data Analysis. The metagenomic DNAwas amplified using multiple displacement amplification. Shotgun sequencing ofmetagenomic DNA was performed using Illumina HiSeq 2000 using the pair-end125 × 125 library with a 600-bp inset size (Beijing Genomics Institute, Beijing,China). Metagenomic reads were assembled into contigs using Velvet, version1.2.10, assembler (49). Resulting contigs were filtered by a minimal length cutoffof 1 kb. For details, see SI Materials and Methods.
Population Genome Binning of a Magnetotactic Nitrospirae from HCH. Becauseonly a single population of Nitrospirae MTB with high relative abundancewas identified in the metagenome of HCH, its population genome was re-covered from the assemblies using a combination of similarity- [MEGAN,version 5 (50)] and composition-based [CLARK, version 1.1.2 (51)] ap-proaches. The quality and accuracy of the acquired population genome wereassessed using CheckM (52), using the lineage-specific workflow. For details,see SI Materials and Methods.
Implicit Phylogenomic Analysis of Nitrospirae MTB Genes. The global implicitphylogenetic pattern of the magnetotactic Nitrospirae genomes of HCH-1,Mcas, Mbav, and Mchi was inferred using HGTector 0.2.0 (53), a sequencesimilarity-based HGT prediction pipeline. For details, see SI Materialsand Methods.
Identification of Nitrospirae MGC-Containing Contigs. To detect NitrospiraeMGC-containing contigs, magnetosome protein sequences from Mcas (17),Mchi (18), and Mbav (18) were used as queries in tBLASTn analyses againstthe assembled contigs of each sample. All matches (E value ≤ 1e-5) werethen manually verified.
Phylogenetic Analysis of Magnetosome Proteins. Magnetosome gene ortho-logs between the complete MGC of Mcas and MGCs of representative MTBpopulations including HCH-1, MSR-1, AMB-1, QH-2, MV-1, MC-1, IT-1, BW-1,MMP, and RS-1 were calculated by bidirectional best-hit analysis through theSEED viewer (54). The amino acid sequences of magnetosome proteins werealigned by MUSCLE algorithms (55) using MEGA, version 6.06 (56), andpoorly conserved regions were trimmed by using the Gblocks method (57).Appropriate protein models of substitution were selected using the FindBest DNA/Protein Models implemented in MEGA, version 6.06 (56), andmaximum-likelihood phylogenetic trees were constructed using MEGA,version 6.06, with a GTR and Gamma model (56) for 16S rRNA genes andRAxML, version 8.0.19, with a LG and Gamma model (58) for magnetosomeproteins. Phylogenomic tree construction was performed using PhyloPhlAn(59), which uses USEARCH (60) and MUSCLE (55) to extract up to 400 con-served ubiquitous proteins (Table S3) coded in genomes and perform indi-vidual protein alignments. The universally conserved and phylogeneticallydiscriminative positions in each protein alignment were then concatenatedinto a single long sequence through PhyloPhlAn. PhyML, version 3.0 (initialtree: BioNJ; tree topology search: NNIs) (61), was used to generate a maxi-mum-likelihood tree. Confidence in phylogenetic results was assessed usingthe 100 bootstrap resampling approaches.
Sequence Divergence. The average number of synonymous substitutions persynonymous site (dS) of the five magnetosome genes and three house-keeping genes (recA, gyrB, and pyrH) were calculated using MEGA, version6.06 (56). The effective number of codons (Nc) was calculated with CodonWtool (version 1.4.4 at codonw.sourceforge.net/) (62). Nc varies between 21 formaximum codon bias and 61 for minimum codon bias. MTB involved in thisanalysis were AMB-1, MSR-1, MC-1, QH-2, RS-1, MMP, Mbav, Mcas, Mchi,and HCH-1.
Divergence Time Estimation. Sequence data from 64 genomes were used toestimate the divergence time between phyla Nitrospirae and Proteobacteria.A subset of up to 400 core proteins was extracted and aligned using Phy-loPhlAn (59). Maximum likelihood tree and bootstrap values were per-formed using RAxML, version 8.0.19, with a VT and Gamma model (58).Divergence times were estimated using PhyloBayes, version 4.1c (63). Fordetails, see SI Materials and Methods.
ACKNOWLEDGMENTS. We thank Longfei Wu for valuable comments andsuggestions. W.L. and Y.P. acknowledge financial support from NationalNatural Science Foundation of China (NSFC) Grants 41330104, 41621004, and41374074. W.L. acknowledges support from the Youth Innovation Pro-motion Association of the Chinese Academy of Sciences. G.A.P. acknowl-edges funding from NSFC Grants 41374072 and 41574063. D.A.B. issupported by US National Science Foundation Grant EAR-1423939. J.L.K. issupported by US National Aeronautics and Space Administration ExobiologyGrant EXO14_2-0176.
1. Bazylinski D, Lefèvre C, Schüler D (2013) Magnetotactic bacteria. The Prokaryotes, eds
Rosenberg E, DeLong E, Lory S, Stackebrandt E, Thompson F (Springer, Berlin), pp
453–494.2. Frankel RB, Bazylinski DA, Johnson MS, Taylor BL (1997) Magneto-aerotaxis in marine
coccoid bacteria. Biophys J 73(2):994–1000.3. Lin W, Bazylinski DA, Xiao T, Wu L-F, Pan Y (2014) Life with compass: Diversity and
biogeography of magnetotactic bacteria. Environ Microbiol 16(9):2646–2658.4. Chang SBR, Kirschvink JL (1989) Magnetofossils, the magnetization of sediments, and
the evolution of magnetite biomineralization. Annu Rev Earth Planet Sci 17:169–195.5. Roberts AP, et al. (2013) Magnetic properties of pelagic marine carbonates. Earth Sci
Rev 127:111–139.6. Kopp RE, Kirschvink JL (2008) The identification and biogeochemical interpretation of
fossil magnetotactic bacteria. Earth Sci Rev 86(1-4):42–61.
7. Pan Y, et al. (2005) The detection of bacterial magnetite in recent sediments of Lake
Chiemsee (southern Germany). Earth Planet Sci Lett 232(1-2):109–123.8. Grünberg K, Wawer C, Tebo BM, Schüler D (2001) A large gene cluster encoding
several magnetosome proteins is conserved in different species of magnetotactic
bacteria. Appl Environ Microbiol 67(10):4573–4582.9. Murat D, Quinlan A, Vali H, Komeili A (2010) Comprehensive genetic dissection of the
magnetosome gene island reveals the step-wise assembly of a prokaryotic organelle.
Proc Natl Acad Sci USA 107(12):5593–5598.10. Lohsse A, et al. (2011) Functional analysis of the magnetosome island in Magneto-
spirillum gryphiswaldense: The mamAB operon is sufficient for magnetite bio-
mineralization. PLoS One 6(10):e25561.11. Delong EF, Frankel RB, Bazylinski DA (1993) Multiple evolutionary origins of mag-
netotaxis in bacteria. Science 259(5096):803–806.
Lin et al. PNAS Early Edition | 5 of 6
EART
H,A
TMOSP
HER
IC,
ANDPL
ANET
ARY
SCIENCE
S
12. Jogler C, Schüler D (2009) Genomics, genetics, and cell biology of magnetosomeformation. Annu Rev Microbiol 63(1):501–521.
13. Lefèvre CT, et al. (2013) Monophyletic origin of magnetotaxis and the first magne-tosomes. Environ Microbiol 15(8):2267–2274.
14. Zeytuni N, et al. (2015) MamA as a model protein for structure-based insight into theevolutionary origins of magnetotactic bacteria. PLoS One 10(6):e0130394.
15. Jogler C, et al. (2011) Conservation of proteobacterial magnetosome genes andstructures in an uncultivated member of the deep-branching Nitrospira phylum. ProcNatl Acad Sci USA 108(3):1134–1139.
16. Spring S, et al. (1993) Dominating role of an unusual magnetotactic bacterium in themicroaerobic zone of a freshwater sediment. Appl Environ Microbiol 59(8):2397–2403.
17. Lin W, et al. (2014) Genomic insights into the uncultured genus “Candidatus Mag-netobacterium” in the phylum Nitrospirae. ISME J 8(12):2463–2477.
18. Kolinko S, Richter M, Glöckner FO, Brachmann A, Schüler D (2016) Single-cell geno-mics of uncultivated deep-branching magnetotactic bacteria reveals a conserved setof magnetosome genes. Environ Microbiol 18(1):21–37.
19. Evans PN, et al. (2015) Methane metabolism in the archaeal phylum Bathyarchaeotarevealed by genome-centric metagenomics. Science 350(6259):434–438.
20. Brown CT, et al. (2015) Unusual biology across a group comprising more than 15% ofdomain Bacteria. Nature 523(7559):208–211.
21. Friedman R, Ely B (2012) Codon usage methods for horizontal gene transfer detectiongenerate an abundance of false positive and false negative results. Curr Microbiol65(5):639–642.
22. Wallau GL, Ortiz MF, Loreto EL (2012) Horizontal transposon transfer in Eukarya:Detection, bias, and perspectives. Genome Biol Evol 4(8):689–699.
23. Sheridan PP, Freeman KH, Brenchley JE (2003) Estimated minimal divergence times ofthe major bacterial and archaeal phyla. Geomicrobiol J 20(1):1–14.
24. Brocks JJ, Summons RE (2003) Sedimentary hydrocarbons, biomarkers for early life.Treatise on Geochemistry, eds Holland HD, Turekian KK (Pergamon, Oxford), pp63–115.
25. French KL, et al. (2015) Reappraisal of hydrocarbon biomarkers in Archean rocks. ProcNatl Acad Sci USA 112(19):5915–5920.
26. David LA, Alm EJ (2011) Rapid evolutionary innovation during an Archaean geneticexpansion. Nature 469(7328):93–96.
27. Canfield DE (2005) The early history of atmospheric oxygen: Homage to Robert M.Garrels. Annu Rev Earth Planet Sci 33(1):1–36.
28. Habicht KS, Gade M, Thamdrup B, Berg P, Canfield DE (2002) Calibration of sulfatelevels in the archean ocean. Science 298(5602):2372–2374.
29. Canfield DE, Rosing MT, Bjerrum C (2006) Early anaerobic metabolisms. Philos Trans RSoc Lond B Biol Sci 361(1474):1819–1834, discussion 1835–1836.
30. Buick R (2012) Geobiology of the Archean Eon. Fundamentals of Geobiology, edsKnoll AH, Canfield DE, Konhauser KO (Wiley, Chichester, UK), pp 351–370.
31. Williams TJ, Zhang CL, Scott JH, Bazylinski DA (2006) Evidence for autotrophy via thereverse tricarboxylic acid cycle in the marine magnetotactic coccus strain MC-1. ApplEnviron Microbiol 72(2):1322–1329.
32. Ji B, et al. (2014) Comparative genomic analysis provides insights into the evolutionand niche adaptation of marine Magnetospira sp. QH-2 strain. Environ Microbiol16(2):525–544.
33. Schübbe S, et al. (2009) Complete genome sequence of the chemolithoautotrophicmarine magnetotactic coccus strain MC-1. Appl Environ Microbiol 75(14):4835–4852.
34. Blake RE, Chang SJ, Lepland A (2010) Phosphate oxygen isotopic evidence for atemperate and biologically active Archaean ocean. Nature 464(7291):1029–1032.
35. Knauth LP (2005) Temperature and salinity history of the Precambrian ocean: Impli-cations for the course of microbial evolution. Palaeogeogr Palaeoclimatol Palaeoecol219(1-2):53–69.
36. Bazylinski DA, Lefèvre CT (2013) Magnetotactic bacteria from extreme environments.Life (Basel) 3(2):295–307.
37. Spring S, Bazylinski DA (2006) Magnetotactic bacteria. The Prokaryotes: An EvolvingElectronic Resource for the Microbiological Community, ed Dworkin M (Springer,New York), pp 842–862.
38. Kappler A, Pasquero C, Konhauser KO, Newman DK (2005) Deposition of banded ironformations by anoxygenic phototrophic Fe(II)-oxidizing bacteria. Geology 33(11):865–868.
39. Walker JCG (1987) Was the Archaean biosphere upside down? Nature 329(6141):710–712.
40. Planavsky NJ, et al. (2014) Evidence for oxygenic photosynthesis half a billion yearsbefore the Great Oxidation Event. Nat Geosci 7(4):283–286.
41. Riding R, Fralick P, Liang L (2014) Identification of an Archean marine oxygen oasis.Precambrian Res 251(9):232–237.
42. Satkoski AM, Beukes NJ, Li W, Beard BL, Johnson CM (2015) A redox-stratified ocean3.2 billion years ago. Earth Planet Sci Lett 430:43–53.
43. Kirschvink JL (1982) Paleomagnetic evidence for fossil biogenic magnetite in westernCrete. Earth Planet Sci Lett 59(2):388–392.
44. Biggin AJ, et al. (2015) Palaeomagnetic field intensity variations suggest Meso-proterozoic inner-core nucleation. Nature 526(7572):245–248.
45. Jogler C, et al. (2009) Toward cloning of the magnetotactic metagenome: Identifi-cation of magnetosome island gene clusters in uncultivated magnetotactic bacteriafrom different aquatic sediments. Appl Environ Microbiol 75(12):3972–3979.
46. Lin W, Jogler C, Schüler D, Pan Y (2011) Metagenomic analysis reveals unexpectedsubgenomic diversity of magnetotactic bacteria within the phylum Nitrospirae. ApplEnviron Microbiol 77(1):323–326.
47. Caporaso JG, et al. (2012) Ultra-high-throughput microbial community analysis on theIllumina HiSeq and MiSeq platforms. ISME J 6(8):1621–1624.
48. Caporaso JG, et al. (2010) QIIME allows analysis of high-throughput community se-quencing data. Nat Methods 7(5):335–336.
49. Zerbino DR, Birney E (2008) Velvet: Algorithms for de novo short read assembly usingde Bruijn graphs. Genome Res 18(5):821–829.
50. Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data.Genome Res 17(3):377–386.
51. Ounit R, Wanamaker S, Close TJ, Lonardi S (2015) CLARK: Fast and accurate classifi-cation of metagenomic and genomic sequences using discriminative k-mers. BMCGenomics 16:236.
52. Parks DH, Imelfort M, Skennerton CT, Hugenholtz P, Tyson GW (2015) CheckM: As-sessing the quality of microbial genomes recovered from isolates, single cells, andmetagenomes. Genome Res 25(7):1043–1055.
53. Zhu Q, Kosoy M, Dittmar K (2014) HGTector: An automated method facilitating ge-nome-wide discovery of putative horizontal gene transfers. BMC Genomics 15(1):717.
54. Overbeek R, et al. (2014) The SEED and the rapid annotation of microbial genomesusing subsystems technology (RAST). Nucleic Acids Res 42(Database issue, D1):D206–D214.
55. Edgar RC (2004) MUSCLE: Multiple sequence alignment with high accuracy and highthroughput. Nucleic Acids Res 32(5):1792–1797.
56. Tamura K, Stecher G, Peterson D, Filipski A, Kumar S (2013) MEGA6: Molecular evo-lutionary genetics analysis version 6.0. Mol Biol Evol 30(12):2725–2729.
57. Castresana J (2000) Selection of conserved blocks from multiple alignments for theiruse in phylogenetic analysis. Mol Biol Evol 17(4):540–552.
58. Stamatakis A (2014) RAxML version 8: A tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30(9):1312–1313.
59. Segata N, Börnigen D, Morgan XC, Huttenhower C (2013) PhyloPhlAn is a newmethod for improved phylogenetic and taxonomic placement of microbes. NatCommun 4:2304.
60. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST.Bioinformatics 26(19):2460–2461.
61. Guindon S, et al. (2010) New algorithms and methods to estimate maximum-likeli-hood phylogenies: Assessing the performance of PhyML 3.0. Syst Biol 59(3):307–321.
62. Peden JF (1999) Analysis of codon usage. PhD dissertation (University of Nottingham,Nottingham, UK).
63. Lartillot N, Lepage T, Blanquart S (2009) PhyloBayes 3: A Bayesian software packagefor phylogenetic reconstruction and molecular dating. Bioinformatics 25(17):2286–2288.
64. Surget-Groba Y, Montoya-Burgos JI (2010) Optimization of de novo transcriptomeassembly from next-generation sequencing data. Genome Res 20(10):1432–1440.
65. Li W, Godzik A (2006) Cd-hit: A fast program for clustering and comparing large setsof protein or nucleotide sequences. Bioinformatics 22(13):1658–1659.
66. Buchfink B, Xie C, Huson DH (2015) Fast and sensitive protein alignment using DI-AMOND. Nat Methods 12(1):59–60.
67. Bekker A, et al. (2004) Dating the rise of atmospheric oxygen. Nature 427(6970):117–120.
68. Crowe SA, et al. (2013) Atmospheric oxygenation three billion years ago. Nature501(7468):535–538.
69. Hofmann HJ (1976) Precambrian microflora, Belcher Islands, Canada; significance andsystematics. J Paleontol 50(6):1040–1073.
70. Shih PM, Hemp J, Ward LM, Matzke NJ, Fischer WW (2017) Crown group Oxy-photobacteria postdate the rise of oxygen. Geobiology 15(1):19–29.
71. Blank CE, Sánchez-Baracaldo P (2010) Timing of morphological and ecological inno-vations in the cyanobacteria—a key to understanding the rise in atmospheric oxygen.Geobiology 8(1):1–23.
6 of 6 | www.pnas.org/cgi/doi/10.1073/pnas.1614654114 Lin et al.
Supporting InformationLin et al. 10.1073/pnas.1614654114SI Materials and MethodsShotgun Metagenomic Sequencing and Data Analysis. To obtainsufficient DNA for shotgun metagenomic sequencing, multipledisplacement amplification was performed using the GenomiPhiV2 DNA Amplification Kit (GE Healthcare) following themanufacturer’s instructions. Briefly, 1 μL of DNA was used asthe template and was mixed with 9 μL of sample buffer. Themixed DNA was heated at 95 °C for 3 min and cooled to 4 °C,before incubation at 30 °C for 90 min with 1 μL of enzymemixture and 9 μL of reaction buffer. To terminate the reaction,the sample was heated at 65 °C for 10 min. For each sample, nineamplifications were pooled to reduce potential bias. These werepurified using TIANquik Maxi Purification Kit (Tiangen).Shotgun sequencing of metagenomic DNA was performed
using Illumina HiSeq 2000 using the pair-end 125 × 125 librarywith a 600-bp inset size (Beijing Genomics Institute, Beijing,China). The entire dataset of two samples is ∼5.55 Gb. Illuminareads were trimmed to remove the adapter sequences and low-quality bases, after which 86–88% of paired reads were retainedfor each sample. Trimmed, paired-end reads were assembledusing a multiple k-mer–based assemblies (64). Briefly, metagenomicreads of each sample were individually assembled into contigs usingthe Velvet, version 1.2.10, assembler (49) with a range of k-mers(41, 51, 61, 71, 81, and 91). The different assembles were sub-sequently merged, and the duplicated and suboptimal contigswere removed through CD-HIT-EST (65) using a sequenceidentity threshold of 0.95 and a word length of 8 to get the finalassembly for each sample. Resulting contigs were filtered by aminimal length cutoff of 1 kb.
Population Genome Binning of a Magnetotactic Nitrospirae from HCH.Contigs of sample HCH were sorted using BLASTn alignmentagainst the NCBI genomes database (version May 2015) togetherwith previously sequenced MTB draft genomes of Mcas (17),Mchi (18), and Mbav (18). BLASTn alignment hits with E valueslarger than 1 × 10−5 were filtered, and the taxonomical level ofeach contig was determined by the lowest common ancestor al-gorithm implemented in MEGAN, version 5 (50). All contigsbinned to known Nitrospirae MTB species of Mcas, Mbav, andMchi were selected. Due to the incomplete nature of availablemagnetotactic Nitrospirae draft genomes, the remaining contigswere further classified using CLARK, version 1.1.2 (51), basedon reduced sets of k-mers by comparison with available genomesor draft genomes of MTB strains. The measure of conservationof gene content and gene order of MGCs between HCH-1 and
three available Nitrospirae MTB (Mcas, Mbav, and Mchi) is theratio between the number of genes located in conserved contentand order and the total number of bidirectional best-hits genesbetween MGCs of HCH-1 and three Nitrospirae MTB.
Implicit Phylogenomic Analysis of Nitrospirae MTB Genes. The globalimplicit phylogenetic pattern of the magnetotactic Nitrospiraegenomes of HCH-1, Mcas, Mbav, and Mchi was inferred usingHGTector 0.2.0 (53). Protein sequence similarity search wasperformed using DIAMOND 0.9.7 (66) against a database (gen-erated by HGTector) that contains one representative per speciesfrom all available nonredundant RefSeq prokaryotic proteomes(October 2015), plus the MTB proteomes reconstructed in thisstudy. Quality cutoffs for valid hits were E value ≤ 1e-20, percent-age identity ≥ 30%, and query coverage ≥ 50%. For each protein-coding gene, the top 250 highest-scoring hits from different specieswere retained. For each hit, a “relative bit score” was calculatedas the original bit score of the hit divided by the bit score of thequery sequence aligned against itself. The overall distributionpattern of all genes in a genome was visualized by plotting thesum of the bit scores of hits within phylum Nitrospirae againstthat outside this phylum per gene.
Divergence Time Estimation. Molecular-dating analyses were per-formed using PhyloBayes, version 4.1c (63). The CAT-GTR modelwas implemented for amino acid replacement, and analyses were rununder either the log-normal autocorrelated relaxed clock (-ln) or theuncorrelated gamma multipliers (-ugam). For each condition, tworeplicate chains with 20,000 generations were run. Dates wereassessed by running the readdiv with the first 20% of generationsremoved as burn-in for each analysis. Two different combinations ofage constraints were used for the divergence time estimation. For thefirst combination of age constraints, the minimum age of the root ofOxyphotobacteria (oxygenic Cyanobacteria) was set at 2.32 Ga (therise in atmospheric oxygen) (67), and the maximum age was set at3.0 Ga (40, 68). For the second combination, a minimum age of1.9 Ga (the first widely accepted fossil oxygenic Cyanobacteria) (69)and a maximum age of 2.32 Ga (postdating the rise of oxygenaccording to ref. 70) were implemented as the oxyphotobacterial root.In addition, for the second combination another time constraint, thedivergence time betweenOxyphotobacteria andMelainabacteria, wasincluded, which was set from 2.5 Ga (70) to 3.8 Ga (the end of lateheavy bombardment). For all analyses, the age calibration for thelast common ancestor of all taxa used in this study was set between2.32 and 3.8 Ga (71).
Lin et al. www.pnas.org/cgi/content/short/1614654114 1 of 5
<1%1%-10%10%-50%50%-80%
0
Nitrospiraceae
Gammaproteobacteria
Rhodospirillaceae
Magnetococcaceae
MY2-3C (HM454280)
‘Candidatus Magnetobacterium casensis’ (JMFO00000000)
‘Candidatus Magnetobacterium bavaricum’ (X71838)
OTU_16
OTU_0
MHB-1 (AJ863136)
MY2-1F (HM454279)
MY3-11A (HM454282)
MY3-5B (HM454281)
MY4-5C (HM454283)
LO-1 (GU979422)
MWB-1 (JN630580)
‘Candidatus Magnetoovum chiemensis’ CS-04 (JX402654)
OTU_12
‘Candidatus Thermomagnetovibrio paiutensis’ HSMV-1 (GU289667)
OTU_5
BW-2 (HQ595728)
SS-5 (HQ595729)
Acinetobacter indicus strain A648 (NR 117784)
OTU_10
Acinetobacter seohaensis strain SW100 (NR 115299)
Magnetospira sp. QH-2 (EU675666)
Magnetospira thiophila MMS-1 (EU861390)
Magnetospirillum gryphiswaldense MSR-1 (Y10109)
Magnetospirillum magneticum AMB-1 (D17514)
Magnetospirillum magnetotacticum MS-1 (M58171)
Magnetovibrio blakemorei MV-1 (L06455)
OTU_7
OTU_3
OTU_6
Magneto-ovoid bacterium MO-1 (EF643520)
Magnetococcus marinus MC-1 (L06456)
OTU_13
OTU_8
OTU_15
OTU_1
OTU_11
OTU_14
OTU_2
OTU_9
OTU_4
‘Candidatus Magnetococcus yuandaducum’ (FJ667777)
99
5468
87
10074
98
7981
7797
78
98
100
56
100
90
74
77
96
93
91
96
74
99
95
100
99
81
92
99
75
99
0.02
HCH MY
Fig. S1. Phylogenetic tree of operational taxonomic units (OTUs at 97% threshold similarity) for 16S rRNA gene clone libraries of MTB communities from thecity moat of Xi’an in Shaanxi province (HCH) and Lake Miyun near Beijing (MY). The evolutionary history was inferred by using the maximum-likelihoodmethod based on the Kimura two-parameter model with 100 bootstraps. On the right-hand side, a heatmap shows the relative abundance and distribution ofeach OTU from this study.
Lin et al. www.pnas.org/cgi/content/short/1614654114 2 of 5
0.3
MS-1_KIM00482
HK-1_magnetite_KPA19039
B13_WP_041904061
MSR-1_WP_041633591
IT-1_AHG23882
AMB-1_WP_011383402
Mba
v_K
JU84
845
QH
-2_
CC
Q7
29
98
MMP_ADV17394
ML-
1_A
FX
8897
5
MC-1_WP_011713875 01760OCC_etigierg_-1WB
BW-1
_magnetite_AET24905
HK-1_greigite_KPA17996
RS-
1_BA
H77
607
HC
H-1
Mchi_K
JR43885
SS-5_A
FX88
984
SO
-1_EM
E68314
MV
-1_CA
V30810
Mca
s_A
IM41
317
100
99
100
97
100
100
9 8
98
9 2
100
10
0
MamA
0.2
Mca
s_AI
M41
319
SS-5_AFX88985
B13_WP_041904060
QH-2_WP_046020684
ML-
1_AF
Z770
14
HC
H-1
BW-1_greigite_AET24910
Mba
v_K
JU84
847
RS-1_WP_015862731
BW
-1_m
agne
tite_
CC
O06
676
36
22
68
00
_P
W_
1-S
M1
MSR
-1_AAL09999
MC-1_WP_011713872
HK-1_magnetite_KPA19045
MMP_ADV17392
AM
B-1_W
P_008622631
IT-1_AHG23879
MV-1_CAV30807
Mchi_K
JR43883
100
10
0
99
9 0
100
100
10
07 7
10
0
100
8783
90
MamB
0.2
MS
R-1_C
AE
12032
HC
H-1
Mba
v_K
JU84
843
AMB-1_WP_011383428RS-1_BAH77598
MS-1_WP_009869046
HK-1_m
agne
tite_
KPA1904
9
Mca
s_A
IM41
315
MV-1
_CAV30
818
B13
SS-5_AHY02427
SO-1_EM
E68306
ML-1_AFZ77020
BW-1_AET24915_greigite
QH-2_CCQ72990 BW-1_AET24914_magnetite
IT-1
_AH
G23
890
MC
-1_A
BK
4476
8
10
0
8 5
100 9 7
100
10
0
9 99 5
7 5
10
0
MamE
0.2
BW-1_AET24921_magnetite
MMP_ADV17397
Mba
v_K
JU84
851
MV
-1_C
AV
3081
1
BW-1_AET24922_greigite
MC
-1_A
BK
4475
5
HC
H-1
RS
-1_BA
H77600
QH-2_CCQ72997ML-1_AFX88981
IT-1_A
HG
23883
MS-1_WP_009869051
SS-5_A
FX8899
1
B13_W
P_041
9040
56
SO-1_EME68313
AMB-1_WP_011383401
HK-1_magnetite_KPA19047
Mca
s_A
IM41
323
MSR
-1_CAM
78030
100
7 5
86
83
8 29 3
9 3
76
7 7
MamP
0.2
MC-1_WP_011713881
ML-1_AFZ77032
AM
B-1
_WP
_011
3833
98
SS-5_AFX88989
SO-1_E
ME68
308
MMP_ADV17375
MS-1_WP_041039444
2
en
3194TEA_etitgam_1W-
B
HC
H-1
RS
-1_W
P_0
1586
2714
IT-1_AHG23888
18
03
VA
C_
1-V
M6
HK-1_magnetite_KPA14283
MSR-1_CAE12034
QH
-2_CC
Q72992
Mcas_A
IM41328
9 8
100
100
100
10094
83
100
98
MamK
AlphaproteobacteriaGammaproteobacteriaDeltaproteobacteriaNitrospiraceaeLatescibacteria
Fig. S2. Bootstrap consensus trees of five magnetosome proteins (MamABEKP) based on the maximum-likelihood method. Only full-length protein sequences were includedin this analysis. Bootstrap values are expressed as percentages, and only values of more than 75% are shown. MSR-1, Magnetospirillum gryphiswaldense MSR-1; AMB-1,Magnetospirillum magneticum AMB-1; SO-1, Magnetospirillum sp. SO-1; QH-2, Magnetospira sp. QH-2; MC-1, Magnetococcus marinus MC-1; BW-1, Candidatus Desulfamplusmagnetomortis BW-1; MMP, Ca. Magnetoglobus multicellularis; RS-1, Desulfovibrio magneticus RS-1; ML-1, alkaliphilic magnetotactic strain ML-1; MV-1, Magnetovibrioblakemorei MV-1; IT-1, Ca. Magnetofaba australis strain IT-1; SS-5, Gammaproteobacteria magnetotactic strain SS-5; HK-1, Ca. Magnetomorum sp. HK-1; B13, Latescibacteriabacterium SCGC AAA252-B13.
Lin et al. www.pnas.org/cgi/content/short/1614654114 3 of 5
MamA MamB
MamE MamK
MamP
MY-2
HCH-1
Mchi_KJR43885
MY-3
Mcas_AIM41317
MY-22
MY-23
Mbav_KJU8484585
96
76
91
75
100
0.2
Proteobacteria
MY-2
HCH-1
Mchi_KJR43883
MY-3
MY-23
Mcas_AIM41319
MY-22
Mbav_KJU84847
10099
97
76
100
0.2
Proteobacteria
MY-2
HCH-1
MY-3
Mcas_AIM41315
MY-22
Mbav_KJU84843
MY-23
10098
100
0.1
Proteobacteria
HCH-1
MY-2
MY-3
Mcas_AIM41323
MY-22
Mbav_KJU84851
MY-23
98
98
92
96
0.2
Proteobacteria
MY-2
HCH-1
MY-3
Mcas_AIM41328
MY-22
MY-23
99
82
99
89
0.1
Proteobacteria
Fig. S3. Bootstrap consensus trees of magnetosome proteins MamABEKP from the four additional Nitrospirae MGCs of MY and those full-length proteinsfrom all available Nitrospirae MTB based on the maximum-likelihood method. Bootstrap values are expressed as percentages, and only values of more than75% are shown.
00.511.522.533.54 (Ga)
Mean divegence time 95% mean confidence intervals
Archean Proterozoic Phanerozoic
Calibartion constraints andmolecular clock models:
Time_constraint_2_ugam_chain2
Time_constraint_2_ugam_chain1
Time_constraint_2_ln_chain2
Time_constraint_2_ln_chain1
Time_constraint_1_ugam_chain2
Time_constraint_1_ugam_chain1
Time_constraint_1_ln_chain2
Time_constraint_1_ln_chain1 Gre
at O
xida
tion
Eve
nt (G
OE
)
Fig. S4. Summary of mean divergence dates for the Nitrospirae and Proteobacteria phyla estimated using Bayesian relaxed molecular-clock analyses with twodifferent time constraints and two different molecular clock models (see SI Materials and Methods for details). Two replicated chains were run for eachcondition. The input phylogenomic tree used here is shown in Fig. S5.
Lin et al. www.pnas.org/cgi/content/short/1614654114 4 of 5
0.9
p_Nitrospirae_LJUG00000000_Nitrospira_bacterium_SM23_35
c_Alphaproteobacteria_CP000471_Magnetococcus_marinus_MC-1
p_Cyanobacteria_c_Oxyphotobacteria_NZ_AJWF00000000_Anabaena_sp_90
p_Nitrospirae_JMFO00000000_Candidatus_Magnetobacterium_casensis
c_Alphaproteobacteria_NC_000963_Rickettsia_prowazekii_str_Madrid_E
c_Deltaproteobacteria_JPDT00000000_Candidatus_Magnetomorum_sp_HK-1
p_Cyanobacteria_c_Melainabacteria_MEL_C1
p_Nitrospirae_LN885086_Candidatus_Nitrospira_inopinata
p_Nitrospirae_NZ_AXWU00000000_Thermodesulfovibrio_islandicus_DSM_12570
c_Alphaproteobacteria_NC_007643_Rhodospirillum_rubrum_ATCC_11170
p_Nitrospirae_NC_017094_Leptospirillum_ferrooxidans_C2-3
c_Alphaproteobacteria_NC_016915_Rickettsia_rickettsii_str_Hlp
p_Cyanobacteria_c_Melainabacteria_Gastranaerophilus_phascolarctosicola
p_Cyanobacteria_Nodularia_spumigena_CCY9414_NZ_CP007203
p_Cyanobacteria_c_Melainabacteria_MEL_A1
p_Nitrospirae_NZ_CP011801_Nitrospira_moscoviensis
p_Nitrospirae_NC_011296_Thermodesulfovibrio_yellowstonii_DSM_11347
c_Deltaproteobacteria_NC_011883_Desulfovibrio_desulfuricans
c_Alphaproteobacteria_AP007255_Magnetospirillum_magneticum_AMB-1
p_Cyanobacteria_c_Melainabacteria_Gastranaerophilaceae_Zag_1
p_Nitrospirae_BBCX00000000_Thermodesulfovibrio_aggregans_JCM_13213
c_Alphaproteobacteria_HG794546_Magnetospirillum_gryphiswaldense_MSR-1
c_Deltaproteobacteria_AP010904_Desulfovibrio_magneticus_RS-1
c_Alphaproteobacteria_NC_011420_Rhodospirillum_centenum_SW
p_Nitrospirae_LJTK00000000_Nitrospira_bacterium_SG8_35_1
c_Deltaproteobacteria_NZ_AXAM00000000_Desulfosarcina_sp_BuS5
p_Cyanobacteria_c_Melainabacteria_Gastranaerophilaceae_Zag_111
p_Nitrospirae_LJTM00000000_Nitrospira_bacterium_SG8_35_4
c_Alphaproteobacteria_FO538765_Magnetospira_sp_QH-2
p_Nitrospirae_JZJI00000000_Candidatus_Magnetoovum_chiemensis
p_Aquificae_NC_015185_Desulfurobacterium_thermolithotrophump_Aquificae_NC_014926_Thermovibrio_ammonificans
c_Alphaproteobacteria_AONQ00000000_Magnetospirillum_caucaseum_SO-1
c_Deltaproteobacteria_ATBP00000000_Candidatus_Magnetoglobus_multicellularis
p_Cyanobacteria_c_Melainabacteria_MEL_B2
c_Deltaproteobacteria_NC_016629_Desulfovibrio_africanus
c_Alphaproteobacteria_JXSL00000000_Magnetospirillum_magnetotacticum_MS-1
c_Alphaproteobacteria_NC_007797_Anaplasma_phagocytophilum_str_HZ
p_Nitrospirae_NC_018649_Leptospirillum_ferriphilum_ML-04
p_Nitrospirae_NZ_AUIU00000000_Thermodesulfovibrio_thiophilus_DSM_17215
p_Nitrospirae_LACI00000000_Candidatus_Magnetobacterium_bavaricum
c_Deltaproteobacteria_NZ_ATHJ00000000_Desulfococcus_multivorans_DSM_2059
p_Cyanobacteria_Synechococcus_sp_JA-3-3Ab_637000313
p_Nitrospirae_LNDU00000000_Nitrospira_sp_Ga0074138
p_Cyanobacteria_Synechococcus_sp_JA-2-3B_NC_007776
p_Cyanobacteria_c_Melainabacteria_Caenarcanum_bioreactoricola
c_Alphaproteobacteria_NC_007940_Rickettsia_bellii_RML369-C
p_Cyanobacteria_c_Melainabacteria_MEL_B1
p_Cyanobacteria_c_Melainabacteria_Obscuribacter_phosphatisp_Cyanobacteria_Gloeobacter_violaceus_PCC_7421_NC_005125
p_Cyanobacteria_Nostoc_sp_PCC_7120_NC_003272
c_Deltaproteobacteria_NZ_BBCC00000000_Desulfosarcina_cetonica_JCM_12296
c_Deltaproteobacteria_NC_007519_Desulfovibrio_alaskensis
c_Alphaproteobacteria_NC_017059_Pararhodospirillum_photometricum_DSM_122
p_Nitrospirae_CZPZ00000000_Candidatus_Nitrospira_nitrificans
p_Aquificae_Sulfurihydrogenibium_azorense_Az-Fu1_NC_012438
c_Alphaproteobacteria_NC_003103_Rickettsia_conorii_str_Malish_7
c_Alphaproteobacteria_LN997848_Magnetospirillum_sp_XM-1
p_Nitrospirae_NC_014355_Nitrospira_defluvii
c_Deltaproteobacteria_NC_002937_Desulfovibrio_vulgaris
p_Cyanobacteria_c_Melainabacteria_Gastranaerophilaceae_MH_37
p_Cyanobacteria_Cylindrospermum_stagnale_PCC_7417_NC_019757
p_Nitrospirae_CZQA00000000_Candidatus_Nitrospira_nitrosa
p_Nitrospirae_LNQR00000000_Nitrospirae_bacterium_HCH-1
100
100
9 0
100
9 8
100
100
100
9 0
7 6
9 9
9 9
100
100
100
9 4
100
100
100
100
100
9 2
8 0
100
9 8
100100
100
100
100
100
100
100
100
100
100
100
100
100
9 8
100
100
100
9 8
100
100
100
9 9
100
100
100
100
100
Alp
hapr
oteo
bact
eria
Del
tapr
oteo
bact
eria
Nitr
ospi
rae
Oxy
phot
obac
teria
Mel
aina
bact
eria
Aqu
ifica
e
Fig. S5. Phylogenomic maximum-likelihood tree of 64 bacterial genomes. Bootstrap values are expressed as percentages, and only values of >75% are shown.Magnetotactic bacteria are displayed in blue. The Aquificae strains were used as outgroup.
Other Supporting Information Files
Table S1 (DOCX)Table S2 (DOCX)Table S3 (DOCX)
Lin et al. www.pnas.org/cgi/content/short/1614654114 5 of 5
