ウイルスは、密集した熱水マット内の遠縁の微生物ドメインにまたがる宿主と相互作用する

Nature Microbiology volume 8、pages 946–957 (2023)この記事を引用

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自然界の多くの微生物は、代謝的に相互依存する密集したコミュニティに存在しています。私たちは、バイオマス密度の高い深海の熱水マットにおける微生物とウイルスの相互作用を調べることにより、微生物の密度とシントロフィーに関連した微生物とウイルスの相互作用の性質と範囲を調査しました。メタゲノム配列決定を使用して、系統発生的に遠い（ドメインレベルまで）微生物がマット内の同じウイルスに対するCRISPRに基づく免疫をコードしている例を多数発見しました。微生物ドメインを横断する宿主とのウイルス相互作用の証拠は、既知の共栄養パートナー、例えば嫌気性メタノトロフィーに関与するパートナー間で特に顕著である。これらのパターンは、近接ライゲーションベース (Hi-C) 推論によって裏付けられます。公開データセットの調査により、共生バイオフィルムを保有することが知られている多様な生態系のドメインを越えて宿主と相互作用する追加のウイルスが明らかになりました。私たちは、ウイルス粒子および/または DNA の非一次宿主細胞への侵入は、人口密度の高い生態系では一般的な現象であり、共生微生物と CRISPR を介した集団間のウイルスに対する回復力の強化に対する生態進化的な意味合いを伴う可能性があると提案します。

自然界のほとんどの細菌と古細菌は、集合体またはバイオフィルムとして見られます1。これらの微生物の集合体は、多くの場合、相互依存的な代謝 (シントロフィーなど) に関与する系統発生的に離れた生物で構成されます。しかし、ほとんどの宿主-ウイルス相互作用は均質な液体培養で研究されており、高密度で基質に結合した不均質なバイオフィルムにおける宿主-ウイルス相互作用の理解には多くのギャップが残っています3。特に、遺伝的に多様で系統的に遠い微生物が非常に近接して共存し、高度に入れ子状の代謝を行う複雑な微生物群集における宿主範囲、ウイルスのライフサイクル、分散様式、宿主ウイルスの共進化に関して大きな疑問が存在する。

一般に、ウイルスは狭い範囲の宿主に感染すると考えられています。しかし、最近の研究では、宿主範囲が広いウイルスが自然界ではより一般的であり、栽培上の偏りにより見落とされている可能性があることが示唆されています4。これまでのところ、ウイルスが複数の細菌種 5、目 6、そしておそらく門 7、8、9 に感染するという報告が存在します。さらに、ウイルスの宿主範囲も動的形質であることが示されています10。特に、最近の研究 11 では、ファージの吸着と細胞への侵入は溶解サイクルの完全な完了と同等ではないことが報告されており、ウイルスが完全な感染サイクルを実行できるより多様な細胞セットと相互作用する可能性があることが示されています。

我々は、系統学的に多様な微生物との長期にわたる接触、ならびに細胞外高分子物質（EPS）および空間的不均一性によって引き起こされる宿主およびウイルスの分散および/または生息範囲の制限により、より広い宿主範囲のウイルスが共栄養代謝が支配的なバイオフィルムで蔓延している可能性があると仮説を立てた。この仮説に対処するために、我々は、深海の熱水微生物マットにおけるウイルスゲノムおよびウイルスと細菌または古細菌との相互作用（以下、宿主ウイルス相互作用と呼ぶ）を特徴づけた。これらのマットは、熱水噴出孔の周囲に遍在する化学合成独立栄養性バイオフィルムである。これらのマットは、非常に高密度で代謝的に結合した細菌と古細菌のコミュニティで構成されており 12、温度と地球化学の急激な空間勾配と時間変動を特徴としています 13。われわれは、おそらく共栄養的な代謝能力を持つ、系統発生的に離れた微生物（つまり、異なる門やさらにはドメインに由来する分類群）が、マット内の同じウイルスに対するClustered Regularly Interspaced Short Palindromicrepeats（CRISPR）に基づく免疫をコードしていることが多いことを示す。このパターンは、代謝的に類似したコミュニティのより低いバイオマスを特徴とする、物理的に隣接する熱水プルームのサンプルからは検出されません。さらに、これらの微生物ゲノムは、Hi-C 近接ライゲーション配列決定に基づいて、同じウイルスゲノムとの共局在を示します。公開されているメタゲノムを調べることで、共栄養性バイオフィルムを保有することが知られている他の生態系において、ウイルスが細菌分類群と古細菌分類群の両方と相互作用していることも発見しました。さらに、ウイルスゲノム内の代謝補助遺伝子（AMG）を調べ、選択を受けているウイルスおよび微生物の遺伝子を特定することにより、これらの宿主ウイルス相互作用の生態進化への影響を調査しました。最後に、ウイルスの共栄養宿主との多価相互作用の 4 つのモデルを提案し、微生物の進化、特に遺伝子の水平伝播、遺伝子の多様化、CRISPR を介したコミュニティ全体の免疫記憶に関するそれらの影響について議論します。

0.05) between microbial and viral compositions was identified. The rep_vMAGs recovered from this study exhibited very high taxonomic and gene content diversity relative to the genetic diversity space occupied by the reference viral genomes (Extended Data Fig. 2). Only 4 rep_vMAGs could be clustered at the ‘genus’ level20 with reference viral genomes, and could be classified as two (previously designated) Podoviridae, one Myoviridae and one Siphoviridae (Supplementary Table 4). Notably, a taxonomic cluster consisting of 7 rep_vMAGs was distantly associated with Flavobacterium phages, and 3 of the rep_vMAGs formed a novel genus-level cluster that shared no similar genes with any of the characterized reference viral sequences. A majority (29 out of 49) did not share high similarity in gene content with the reference or with each other. Many of the viral genomes contained novel auxiliary metabolic genes (AMGs) such as Rubisco large domain-containing protein, aldolase II domain-containing protein, nitroreductase domain-containing protein, phosphate starvation-inducible protein PhoH and terillium resistance protein TerD (Extended Data Fig. 3a,b). We also detected evidence of host-virus arms race, with some viral genomes encoding defence machinery such as RelE/StbE family toxin, HigA family antidote and a putative abortive infection protein (Extended Data Fig. 3c). A complete list of the annotated AMGs and other notable viral genes is provided in Supplementary Table 5./p>95% nucleotide identity (ID)) into 102 clusters. Most (91%) of the detected CRISPRs were specific to a population and 80% of the CRISPR-encoding populations were associated with at most 2 unique CRISPRs. However, we observed identical or near identical (>95% ID) CRISPR repeats shared among phylogenetically distant populations. It is possible that these CRISPR loci were horizontally transferred21, but we cannot rule out the possibility of binning errors resulting from their repetitive and divergent nature. Such CRISPR repeats detected across taxa were excluded from spacer-based host-virus matching due to the ambiguity in assigning a specific host taxon to a repeat. Additionally, we identified populations (Gammaproteobacteria_17_1, Desulfobacteria_193_1, Desulfobacteria_189_1) encoding as many as 6 distinct CRISPR repeats, probably representing within-population diversity of CRISPR loci. No correlation was found between the number of unique CRISPRs and the rep_mMAG size, relative abundance or habitat range./p> 0.05). We binned 168 mid- to high-quality rep_mMAGs (see Supplementary Table 11 for the full description) across the 10 HW assemblies, and although taxonomically distinct from the rep_mMAGs recovered from the mat assemblies, the two datasets featured similar metabolic capabilities (Supplementary Table 12 and Extended Data Fig. 8a) and similar levels of species evenness (Extended Data Fig. 8b, Welch’s t-test, two-sided, n = 20, P > 0.05). The microbial communities of the HW samples were more homogeneous than the mat samples (Extended Data Fig. 8c) despite the larger physical distances between the HW samples. Similar to the mat samples, HW samples were dominated by two sulfur oxidizing Gammaproteobacteria (HW_Gammaproteobacteria_164_1, HW_Gammaproteobacteria_163_1; Extended Data Fig. 9a). Interestingly, we observed an order of magnitude less frequent detection of CRISPR loci in the HW assemblies compared with the mat assemblies (Supplementary Table 13, Welch’s t-test, two-sided, n = 20, P = 0.001). Furthermore, only 12 of the CRISPRs in the HW assemblies could be associated with medium- to high-quality MAGs (Supplementary Table 14), resulting in a much sparser and less robust CRISPR-based immunity network (Extended Data Fig. 5b and Supplementary Table 15), with only one confident interaction between an SOB (HW_Gammaproteobacterira_162_1) and a virus. The similarities between the plume and mat samples, such as geographical proximity, community metabolic capabilities and sequencing depth, provide a rationale and opportunity for comparison. Lower abundances of the CRISPRs in the plume samples indicate that the plume communities are less reliant on CRISPR-based adaptive immunity. The transferability and specificity of CRISPR-based immunity confer ecological significance to this observation, raising the question of how such immunological memory is selected for in different environments. While this comparison illuminates key differences in the nature and extent of host-virus interactions between the mat and the plume, there are some caveats to consider for further interpretation: first, the sparseness in the plume CRISPR-based immunity network is likely due in part to the lower abundance and diversity of recovered viral contigs (Supplementary Table 16 and Extended Data Fig. 9b), where only the fraction of viruses that were infecting microbes and/or were attached to particles larger than 0.022 µm were recovered. Second, differences in the CRISPR-based immunity do not necessarily reflect the patterns of the underlying networks of in situ host and virus interactions./p> 2.5); however, most could not be annotated with a function. Interestingly, 3 of the 4 annotated genes undergoing diversifying selection were involved in DNA and RNA metabolism, such as genes encoding DNA-directed RNA polymerase (RNAP) beta and beta prime (rep_vMAG_21), DNA ligase (rep_vMAG_31) and Superfamily II DNA/RNA helicase (rep_vMAG_6). We also detected a LamG domain-containing protein (vMAG_4), possibly involved in signalling and cell adhesion, to be undergoing diversifying selection. The gene encoding RNAP in rep_vMAG_21 (RNAP1; Extended Data Fig. 10a) featured the highest pN/pS ratio of 4.9, with 8 non-synonymous mutations scattered throughout the protein (Extended Data Fig. 10b). Notably, rep_vMAG_21 featured a second RNAP gene fragment encoding the beta subunit (RNAP2) (Extended Data Fig. 10a) that is not homologous to RNAP1 and not seemingly undergoing selection, possibly contributing to the relaxation of purifying selection on RNAP1. RNAP1 was highly divergent from the previously characterized RNAP sequences and was rooted at the base of the Caudoviricetes multimeric RNAP clade38 (Extended Data Fig. 10c). This example of diversifying selection on RNAP1 suggests that these viruses may play an important role in expediting the evolution of housekeeping proteins that typically undergo purifying selection in cellular organisms. Microbial genes undergoing diversifying selection (pN/pS > 2) included genes encoding products involved in various defence systems, such as type II toxin-antitoxin system RelE/ParE toxin, HindIII family type II restriction endonuclease, Type III-B CRISPR module RAMP protein Cmr1, as well as genes involved in more recently characterized PARIS and Septu anti-phage arsenal39./p>70% completeness and <10% contamination) MAGs were used for subsequent analysis. Mid- to high-quality MAGs were dereplicated at 97% ANI using dRep v3.0.1 (ref. 54) and were designated as representative MAGs (rep_mMAGs). rep_mMAGs were taxonomically classified using GTDB-Tk v1.7.0 (ref. 55). Genes were predicted using Prodigal v2.6.3 (ref. 56) and annotated by aligning them using Diamond v2.0.7.145 (ref. 57) against the UniRef100 database58 with an e-value cut-off 1 × 10−5. Additionally, METABOLIC v4 (ref. 59) and DefenseFinder v1 (ref. 60) were used to identify potential metabolic and antiviral genes, respectively./p>

5× and breadth (fraction of the rep_mMAG covered by at least one read) of >0.7, relative abundances in each sample were determined using the genome-wide average read-mapping coverage. For rep_vMAGs with an average coverage of >5× and breadth >0.7, normalized abundances in each sample were calculated by normalizing the average coverage of viral scaffolds in each rep_vMAG by the number of reads in each sample./p>

20 bp) than in Fig. 3 (spacer length >25 bp and each edge representing two distinct matches). Only interaction with spacer length >25 bp is highlighted with the red edge. Viral nodes are scaled to the rep_vMAG length, and rep_mMAGs with genomic capacity to carry out sulfur oxidation are colored in blue./p>5, breadth >0.7). Viral nodes (circular) are labeled according to the corresponding rep_vMAG ID. microbial nodes are colored according to the taxon, using the same color scheme as the main Fig. 3. Node sizes correspond to the sample-specific read-mapping coverages. Thickness of the edges represent the number of contig-to-contig linkages, while the darkness of the edges correlates to the maximal normalized strength of the Hi-C contacts between any two contigs in a host-virus pair. Host-virus pairs that were previously detected using CRISPR-spacer matches are colored in red. Identified Hi-C linkages between viruses are noted with blue edges./p> 0.05). Box plot shows the quartiles (25, 50, 75 percentiles) with the upper and lower whiskers showing the max and min value within 1.5 times the interquartile respectively. (C) Principal coordinate analyses of the rep_mMAGs in the two datasets; hydrothermal mat samples are colored in red and hydrothermal water samples are colored in blue. The percentage of variance explained by each axis is shown in the axis label./p>5 coverage and >0.7 breadth using read mapping are shown and proviruses are excluded./p>25 with at most two mismatches. Supplementary Table 9. Hi-C library statistics. Supplementary Table 10. Hi-C normalized linkage between rep_vMAG and rep_mMAG. Contig-to-contig linkage information was consolidated by count of linkage, average residual (normalized ‘strength’) of the linkage and maximum residual of the linkage. Supplementary Table 11. Statistics of the rep_mMAGs binned across the ten hydrothermal water samples. Supplementary Table 12. Genome-based metabolic capabilities and other genetic features of rep_mMAGs in the hydrothermal water samples. Supplementary Table 13. Number of high-confidence (evidence level = 4) CRISPR repeats binned across environments. For hydrothermal mat samples and hydrothermal mat samples from this study, we include information on the total number of evidence level 4 CRISPRs detected across environments as well as those that were binned in mid- to high-quality MAGs. Supplementary Table 14. Binned CRISPR repeats in hydorthermal water samples. Supplementary Table 15. All CRISPR-spacer to protospacer matches in hydrothermal water samples with spacer length >20 with at most two mismatches. Supplementary Table 16. Information of the high-quality and complete rep_vMAGs binned across the ten hydorthermal water samples. Supplementary Table 17. List of UViG ID and their putative hosts and host-prediction methods./p>