자연 미생물학 8권, 946~957페이지(2023)이 기사 인용
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자연계의 많은 미생물은 조밀하고 대사적으로 상호의존적인 공동체에 거주합니다. 우리는 바이오매스가 밀집된 심해 열수 매트에서 미생물-바이러스 상호 작용을 조사하여 미생물 밀도 및 신트로피와 관련된 미생물-바이러스 상호 작용의 특성과 범위를 조사했습니다. 메타게놈 시퀀싱을 사용하여 우리는 계통발생학적으로 먼(도메인 수준까지) 미생물이 매트의 동일한 바이러스에 대해 CRISPR 기반 면역을 암호화하는 수많은 사례를 발견합니다. 미생물 영역을 교차하는 숙주와의 바이러스 상호작용에 대한 증거는 알려진 합성 파트너, 예를 들어 혐기성 메탄영양에 관여하는 파트너 사이에서 특히 두드러집니다. 이러한 패턴은 근접 결찰 기반(Hi-C) 추론에 의해 확증됩니다. 공개 데이터 세트를 조사한 결과 신영양 생물막이 있는 것으로 알려진 다양한 생태계의 도메인 전반에 걸쳐 숙주와 상호 작용하는 추가 바이러스가 밝혀졌습니다. 우리는 바이러스 입자 및/또는 DNA가 비1차 숙주 세포로 유입되는 것이 신영양 미생물에 대한 생태진화적 의미와 바이러스에 대한 회복력의 CRISPR 매개 인구 간 증가와 함께 인구 밀도가 높은 생태계에서 일반적인 현상일 수 있다고 제안합니다.
자연에 존재하는 대부분의 박테리아와 고세균은 집합체 또는 생물막으로 발견됩니다1. 이러한 미생물 집합체는 종종 상호의존적 대사(예: 신트로피)에 참여하는 계통발생적으로 멀리 떨어져 있는 유기체로 구성됩니다2. 그러나 대부분의 숙주-바이러스 상호작용은 균질한 액체 배양에서 연구되며 조밀하고 기질에 결합된 이질적인 생물막3에서 숙주-바이러스 상호작용을 이해하는 데에는 많은 격차가 남아 있습니다3. 특히, 유전적으로 다양하고 계통발생적으로 먼 미생물이 매우 근접하게 공존하고 고도로 중첩된 대사에 참여하는 복잡한 미생물 군집에서 숙주 범위, 바이러스 생활주기, 분산 방식 및 숙주-바이러스 공진화와 관련하여 주요 질문이 존재합니다.
일반적으로 바이러스는 좁은 범위의 호스트를 감염시키는 것으로 생각됩니다. 그러나 최근 연구에 따르면 광범위한 숙주 범위의 바이러스는 자연에서 더 흔할 수 있으며 재배 편견으로 인해 간과되었을 수 있습니다4. 지금까지 여러 박테리아 종5, 목6 및 문7,8,9을 감염시키는 바이러스에 대한 보고가 있습니다. 또한 바이러스 숙주 범위도 동적 특성인 것으로 나타났습니다10. 특히, 최근 연구11에서는 파지 흡착과 세포 내 진입이 용해 주기의 완전한 완료와 동일하지 않다고 보고했으며, 이는 바이러스가 완전한 감염 주기가 수행될 수 있는 보다 다양한 세포 세트와 상호 작용할 수 있음을 나타냅니다.
우리는 계통발생적으로 다양한 미생물과의 확장된 접촉과 세포외 고분자 물질(EPS) 및 공간적 이질성으로 인한 제한된 숙주 및 바이러스 분산 및/또는 서식지 범위로 인해 신영양 대사가 지배하는 생물막에서 더 넓은 숙주 범위의 바이러스가 만연할 수 있다는 가설을 세웠습니다. 이 가설을 해결하기 위해 우리는 심해 열수 미생물 매트에서 바이러스 게놈과 박테리아 또는 고세균과의 모든 바이러스 상호 작용(이하 호스트-바이러스 상호 작용이라고 함)을 특성화했으며, 이러한 매트는 열수 통풍구 주변에 편재된 화학 독립 영양 생물막입니다. 이 매트는 매우 조밀하고 대사적으로 결합된 박테리아와 고세균 공동체로 구성되어 있으며 온도와 지구화학에서 날카로운 공간적 구배와 시간적 가변성을 특징으로 합니다. 우리는 추정적으로 신영양성 대사 능력을 가진 계통 발생적으로 먼 미생물(즉, 다른 문과 영역의 분류군)이 종종 매트의 동일한 바이러스에 대해 CRISPR(Clustered Regularly Interspaced Short Palindromic Repeats) 기반 면역을 암호화한다는 것을 보여줍니다. 이 패턴은 대사적으로 유사한 공동체의 낮은 바이오매스를 특징으로 하는 물리적으로 인접한 열수 기둥 샘플에서는 감지되지 않습니다. 또한, 이들 미생물 게놈은 Hi-C 근접 결찰 시퀀싱을 기반으로 동일한 바이러스 게놈과 공동 위치화를 나타냅니다. 공개적으로 이용 가능한 메타게놈을 조사함으로써 우리는 합성 생물막이 있는 것으로 알려진 다른 생태계에서 박테리아 및 고세균 분류군과 상호 작용하는 바이러스도 발견했습니다. 우리는 바이러스 게놈의 보조 대사 유전자(AMG)를 조사하고 선택 중인 바이러스 및 미생물 유전자를 식별함으로써 이러한 숙주-바이러스 상호 작용의 생태 진화적 의미를 추가로 조사했습니다. 마지막으로 우리는 신트로픽 숙주와의 바이러스 다가 상호작용에 대한 4가지 모델을 제안하고 특히 수평적 유전자 전달, 유전적 다양화 및 CRISPR 매개 커뮤니티 차원의 면역학적 기억과 관련하여 미생물 진화에 대한 영향을 논의합니다.
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>
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