Ecology

Fennoscandian shield genomic database (FSGD)The Fennoscandian Shield bedrock contains an abundance of fracture zones with different groundwater characteristics that vary in water source, retention time, chemistry, and connectivity to surface-fed organic compounds (see Supplementary Data 1). The Äspö Hard Rock Laboratory (HRL) and Olkiluoto drillholes were sampled over time, covering a diversity of aquifers representing waters of differing ages and both planktonic and biofilm-associated communities. In order to provide a genome-resolved view of the Fennoscandian Shield bedrock Archaeal and bacterial communities, collected samples were used for an integrated analysis by combining metagenomes (n = 44), single-cell genomes (n = 564), and metatranscriptomes (n = 9) (see detailed statistics for the generated datasets in the Supplementary Data 1 and Supplementary Information). Assembly and binning of the 44 metagenomes (~1.3 TB sequenced data) resulted in the reconstruction of 1278 metagenome-assembled genomes (MAGs; ≥ 50% completeness and ≤ 5% contamination). By augmenting this dataset with 564 sequenced single-cell amplified genomes (SAGs; 114 of which were ≥ 50% complete with ≤ 5% contamination), we present a comprehensive genomic database for the archaeal and bacterial diversity of these oligotrophic deep groundwaters, hereafter referred to as the Fennoscandian Shield genomic database (FSGD; statistics in Fig. 1A & Supplementary Data 2). Phylogenomic reconstruction using reference genomes in the Genome Taxonomy Database (GTDB-TK; release 86) shows that the FSGD MAGs/SAGs span most branches on the prokaryotic tree of life (Fig. 2). Harboring representatives from 53 phyla (152 archaeal MAGs/SAGs in 7 phyla and 1240 bacterial MAGs/SAGs in 46 phyla), the FSGD highlights the remarkable diversity of these oligotrophic deep groundwaters. Apart from the exceptional case of a single-species ecosystem composed of ‘Candidatus Desulforudis audaxviator’ in the fracture fluids of an African gold mine17, other studies of deep groundwaters as well as aquifer sediments have also revealed a notable phylogenetic diversity of the Archaea and Bacteria10,11,18. For example, metagenomic and single-cell genomic analysis of the CO2-driven Crystal geyser (Colorado Plateau, Utah, USA) resulted in reconstructed genomes of 503 archaeal and bacterial species distributed across 104 different phylum-level lineages11.Fig. 1: Overview of the FSGD MAGs and SAGs.Statistics of the metagenome-assembled genomes (MAGs) and single-cell amplified genomes (SAGs) of the Fennoscandian Shield Genomic Database (a). The number of genome clusters present in borehole samples (centerline, median; hinge limits, 25 and 75% quartiles; whiskers, 1.5x interquartile range; points, outliers). Numbers on top of each box plot represent the number of metagenomes generated for borehole samples (b). NMDS plot of unweighted binary Jaccard beta-diversities of presence/absence of all FSGD reconstructed MAGs/SAGs (c) and MAG and SAG clusters belonging to the common core microbiome present in both Äspö HRL and Olkiluoto (d). Numbers in the parenthesis show the number of overlapping points. The data used to generate these plots are available in Supplementary Data 4 and the Source Data.Full size imageFig. 2: Phylogenetic diversity of reconstructed MAGs and SAGs of the fennoscandian shield genomic database (FSGD).Genomes present in genome taxonomy database (GTDB) release 86 were used as reference. Archaea and Bacteria phylogenies are represented separately in the top and bottom panels, respectively. MAGs and SAGs of the FSGD are highlighted in red. Legend in front of each number at the bottom of the figure shows the list of taxa in the tree that are marked with the same number.Full size imageClustering reconstructed FSGD MAGs/SAGs into operationally defined prokaryotic species (≥ 95% average nucleotide identity (ANI) and ≥ 70% coverage) produced 598 genome clusters. Based on the GTDB-TK affiliated taxonomy, a single FSGD cluster may represent a novel phylum, whereas at the lower taxonomic levels, the FSGD harbors genome clusters representing seven novel taxa at class, 58 at order, 123 at family, and 345 at the genus levels. In addition, more than 94% of the reconstructed MAGs/SAGs clusters (n = 568) represent novel species with no existing representative in public databases (Supplementary Data 2). Mapping metagenomic reads against genome clusters represented exclusively by SAGs (n = 38, Fig. 1A) revealed that 14 genome clusters (20 SAGs) were not detectable in the metagenomes, suggesting they might represent rare species in the microbial community of the investigated deep groundwaters (Supplementary Data 3).To explore the community composition of different groundwaters and their temporal dynamics, presence/absence patterns were computed by competitively mapping the metagenomics reads against all reconstructed MAGs/SAGs of the FSGD. Contigs were discarded from the mapping results if More

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Thirty-five years after the explosion and meltdown at the Chernobyl Nuclear Power Plant in Ukraine, I study how amphibians in the region have changed, physically and genetically. In 2016, I joined an international research team to do this; since then, I have obtained various grants to continue the work. Chernobyl is a phenomenal place to study rapid evolution. I typically spend two to three weeks in the forests during the frogs’ spring breeding season.When I work in the ‘exclusion zone’, the 4,700 square kilometres around the reactor, I stay in a hostel in Chernobyl (20 kilometres from the reactor site), where we have a field laboratory inside an abandoned building. The radiation in the exclusion zone is roughly 1,000 times lower than at the time of the accident, and there are now two hostels, a bar, a couple of restaurants and a cash machine. In this image, I’m running a blood analysis on one of the tree frogs we have collected. The contamination maps on the wall behind me show that some hotspots of radiation persist.Around 8 p.m., we listen for male tree frogs calling in the field. Wearing chest waders and head lamps, we enter the ponds to gather frogs until 1 or 2 a.m.. Frogs in the exclusion zone are darker than those outside it, thanks to higher levels of melanin, which might be an adaptation that protects them from ionizing radiation. We analyse how much radiation their bodies contain, and tend to find damage to some, often to the liver.Once expected to become a wasteland, the Chernobyl area is now a nature reserve. New species have arrived, including European bison (Bison bonasus) and the wild Przewalski’s horse (Equus ferus przewalskii). We’re beginning to monitor these horses, originally from the Asian steppes: the effects on their health could be a proxy for what happens when humans return. The first 31 horses were released here in 1998, 12 years after the disaster, and it is one of the few places where they continue to live freely.

Nature 595, 464 (2021)
doi: https://doi.org/10.1038/d41586-021-01883-2

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Genetic analyses of Rhinolophus species identified as reservoirs of viruses closely related to SARS-CoV-2Until now, SCoV2rCs have been found in four bat species of the genus Rhinolophus: R. acuminatus, R. affinis, R. malayanus, and R. shameli. The haplotype networks constructed using CO1 sequences of these four species are shown in Fig. 3. A star-like genetic pattern, characterized by one dominant haplotype and several satellite haplotypes was found for the two bat species endemic to Southeast Asia, i.e. R. acuminatus and R. shameli.Figure 3Haplotype networks based on CO1 sequences of the four Rhinolophus species found positive for viruses closely related to SARS-CoV-2 (SCoV2rCs). The networks were constructed with the median joining method available in PopART 1.513 and modified under Adobe Illustrator CS6 (version 16.0). The codes used for the countries are the following: B (Myanmar), C (Cambodia), Ch (China), I (Indonesia), L (Laos), M (Malaysia), T (Thailand), and V (Vietnam). Colours indicate the geographic origin of haplotypes according to Fig. 2 (see online supplementary Table S1). The circles indicate haplotypes separated by at least one mutation. The black lines on the branches show the number of mutations ≥ 2. Black circles represent missing haplotypes. Circle size is proportional to the number of haplotypes. Haplogroups separated by more than seven mutations (pairwise nucleotide distances  > 1%) are highlighted by dotted lines. The red arrows show the positions of the nine bats found positive for SCoV2rCs.Full size imageIn the network of R. acuminatus, the most common haplotype (named Rac1 in online supplementary Table S1) was found in northern Cambodia, southern Laos, eastern Thailand and southern Vietnam, indicating recent gene flow among these populations. Since a virus related to SARS-CoV-2 (91.8% of genome identity), named RacCS203, was detected in five R. acuminatus bats caught in eastern Thailand in June 20206, the genetic pattern obtained for this species suggests that viruses closely related to RacCS203 may have circulated in most southern regions of mainland Southeast Asia. In contrast, R. acuminatus bats collected in Borneo (M5) showed a divergent haplotype (separated by 12 mutations; haplogroup II), suggesting that the South China Sea between mainland Southeast Asia and Borneo constitutes a barrier to gene flow. Isolated populations of R. acuminatus described in northern Myanmar, Indonesia (Java and Sumatra) and the Philippines14 should be further studied.The network of R. shameli shows a typical star-like pattern, the most common haplotype (named Rsh1 in online supplementary Table S1) being detected in northern Cambodia and Laos. Since a virus related to SARS-CoV-2 (93.1% of genome identity), named RshSTT200, was recently discovered in two R. shameli bats collected in northern Cambodia in December 20107, the genetic pattern obtained for this species suggests that viruses closely related to RshSTT200 may have circulated, at least in the zone between northern Cambodia and central Laos. The bats sampled south to the Tonle Sap lake (n = 4; southern Cambodia and Vietnamese island of Phu Quoc) were found to be genetically isolated from northern populations (four mutations). However, further sampling in the south is required to confirm this result, as it may reveal CO1 sequences identical to the haplotypes detected in the north.For the two species distributed in both China and Southeast Asia, i.e. R. affinis and R. malayanus, the genetic patterns are more complex with different haplogroups showing more than 1% of nucleotide divergence. In the network of R. affinis, there are three major haplogroups (named I, II and III in Fig. 3) separated by a minimum of seven mutations. The results are therefore in agreement with those previously published using CO1 and D-loop mitochondrial sequences15. The CO1 haplotypes detected in the localities sampled in southern China (ch1, ch4, ch5) are distantly related to the single haplotype available for central China (ch6), but they are also found in Laos, northern and central Vietnam, northern Thailand and northeastern Myanmar. This result suggests recent gene flow between populations from southern Yunnan and those from northern mainland Southeast Asia. Since a virus related to SARS-CoV-2 (96.2% of genome identity), named RaTG13, was detected in one R. affinis bat captured in southern Yunnan in 20131, the genetic pattern obtained for this species suggests that viruses closely related to RaTG13 may have circulated in the zone comprising southern Yunnan and northern mainland Southeast Asia.In the network of R. malayanus, there are four major haplogroups (named I, II, III and IV in Fig. 3) separated by a minimum of seven mutations. The CO1 haplotypes detected in the localities sampled in southern China (ch2 and ch3) were also found in northern Laos (L1 and L3), suggesting recent gene flow between populations from these two countries. Since a virus related to SARS-CoV-2 (93.7% of genome identity), named RmYN02, was recently isolated from one R. malayanus bat collected in southern Yunnan in June 20195, the genetic pattern obtained for this species suggests that viruses closely related to RmYN02 may have circulated, at least between southern Yunnan and northern Laos. In contrast, the bats sampled in Myanmar were found to be genetically isolated from other geographic populations (haplogroup II in Fig. 3).Two different ecological niches for bat viruses related to either SARS-CoV or SARS-CoV-2In the wild, sarbecoviruses were generally detected after examining fecal samples collected on dozens of bats. For instance, two sarbecoviruses were found7 among the total 59 bats collected at the same cave entrance in northern Cambodia in 2010 (unpublished data). However, this does not mean necessarily that sarbecoviruses were absent in negative samples, as degradation of RNA molecules and very low viral concentrations may prevent the detection of RNA viruses. Despite these difficulties, full genomes of Sarbecovirus have been sequenced from a wide diversity of horseshoe bat species collected in Asia, Africa and Europe5,6,7,8,9,10. Therefore, there is no doubt that Rhinolophus species constitute the natural reservoir host of all sarbecoviruses3,8. The genus Rhinolophus currently includes between 9211 and 10916 insectivorous species that inhabit temperate and tropical regions of the Old World, with a higher biodiversity in Asia (63–68 out of the 92–109 described species) than in Africa (34–38 species), Europe (5 species) and Oceania (5 species). Although some Rhinolophus species are solitary, most of them are gregarious and live in large colonies or small groups generally in caves and hollow trees, but also in burrows, tunnels, abandonned mines, and old buildings11,16. However, they prefer large caves with total darkness, where temperatures are stable and less affected by diurnal and seasonal climatic variations. Importantly, all Rhinolophus species in which sarbecoviruses were detected in previous studies1,5,6,7,8,9,17 are cave species that form small groups or colonies (up to several hundreds)11,18,19.In China, many SCoVrCs were previously detected in several horseshoe bat species, including Rhinolophus sinicus, Rhinolophus ferrumequinum (currently R. nippon)16, Rhinolophus macrotis (currently R. episcopus)16, Rhinolophus pearsoni, and Rhinolophus pusillus, and it has been shown that they circulate not only among conspecific bats from the same colony, but also between bat species inhabiting the same caves17,20,21. The ecological niche predicted for bat SCoVrCs using a data set of 19 points (see online supplementary Table S2) is shown in Fig. 4. The AUC was 0.81. The value was  > 95% CI null-model’s AUCs (0.68), indicating that the model performs significantly better than a random model (see online supplementary Fig. S1). The highest probabilities of occurrence (highlighted in green in Fig. 4) were found in Nepal, Bhutan, Bangladesh, northeastern India, northern Myanmar, northern Vietnam, most regions of China south of the Yellow River, Taiwan, North and South Korea, and southern Japan.Figure 4Ecological niche of bat viruses related to SARS-CoV (SCoVrCs). The geographic distribution of suitable environments was predicted using the Maxent algorithm in ENMTools (see “Methods” section for details). AUC = 0.81. Black circles indicate localities used to build the distribution model (see geographic coordinates in online supplementary Table S2).Full size imageIn Southeast Asia and southern China, SCoV2rCs have currently been found in four Rhinolophus species (R. acuminatus, R. affinis, R. malayanus and R. shameli)1,6,7,8, but the greatest diversity of horseshoe bat species in mainland Southeast Asia (between 28 and 36 species)11,16 suggests that many sarbecoviruses will be discovered soon. Despite the limited data currently available on SCoV2rCs, several arguments support that bat intraspecific and interspecific transmissions also occur with SCoV2rCs. Firslty, recent genomic studies have revealed that SCoV2rCs circulate and evolve among horseshoe bats of the same colony, as five very similar genomes (nucleotide distances between 0.03% and 0.10%) were sequenced from five R. acuminatus bats collected from the same colony in eastern Thailand6, and as two genomes differing at only three nucleotide positions (distance = 0.01%) were sequenced from two R. shameli bats collected at the same cave entrance on the same night7. Secondly, the discovery of four viruses closely related to SARS-CoV-2 (between 96.2 and 91.8% of genome identity) in four different species of Rhinolophus is a strong evidence that interspecific transmission occurred several times in the past. As detailed in online supplementary Table S1, these species were collected together in several localities of Cambodia (three species in C1, C2, and C5; two species in C8), Laos (four species in L10; three species in L9; two species in L1, L5, L8, L11), and Vietnam (two speciess in V10, V9, V17, V18). These data corroborate previous studies suggesting that sarbecoviruses can be transmitted, at least occasionally, between Rhinolophus species sharing the same caves.The ecological niche of bat SCoV2rCs was firstly predicted using the four localities where bat viruses were previously detected1,6,7,8 (Fig. 5a). The highest probabilities of occurrence (highlighted in green in Fig. 5a) were found in Southeast Asia rather than in China. However, the AUC was only 0.58, and the value was  95% CI null-model’s AUCs (0.81), indicating that the model performs significantly better than a random model (see online supplementary Fig. S3). The areas showing the highest probabilities of occurrence (highlighted in green in Fig. 5b) include four main geographic areas: (i) southern Yunnan, northern Laos and bordering regions in northern Thailand and northwestern Vietnam; (ii) southern Laos, southwestern Vietnam, and northeastern Cambodia; (iii) the Cardamom Mountains in southwestern Cambodia and the East region of Thailand; and (iv) the Dawna Range in central Thailand and southeastern Myanmar.Figure 5Ecological niches of bat viruses closely related to SARS-CoV-2 (SCoV2rCs) predicted using 4 points (a) (AUC = 0.58) and 21 points (b) (AUC = 0.96). The geographic distributions of suitable environments were predicted using the Maxent algorithm in ENMTools (see “Methods” section for details). Black circles indicate localities used to build the distribution model (see geographic coordinates in online supplementary Table S1).Full size imageOur results show that bat SCoVrCs and SCoV2rCs have different ecological niches: that of SCoVrCs covers mainly China and several adjacent countries and extends to latitudes between 18° and 43°N, whereas that of SCoV2rCs covers northern mainland Southeast Asia and extends to latitudes between 10° and 24°N. Most Rhinolophus species involved in the ecological niche of SCoVrCs have to hibernate in winter when insect populations become significantly less abundant. This may be different for most Rhinolophus species involved in the ecological niche of SCoVrC2s. Since this ecological difference may be crucial for the dynamics of viral transmission among bat populations, it needs to be further studied through comparative field surveys in different regions of China and Southeast Asia. The ecological niches of SCoVrCs and SCoV2rCs slightly overlap in the zone including southern Yunnan, northern Laos, and northern Vietnam (Figs. 4, 5b). This zone corresponds to the northern edge of tropical monsoon climate23. Highly divergent sarbecoviruses of the two main lineages SCoVrCs and SCoV2rCs are expected to be found in sympatry in this area. This is confirmed by the discovery of both SCoVrCs and SCoV2rCs in horseshoe bats collected in southern Yunnan1,6,21. Collectively, these data suggest that genomic recombination between viruses of the two divergent lineages are more likely to occur in bats roosting, at least seasonally, in the caves of these regions. Since highly recombinant viruses can threaten the benefit of vaccination campaigns, southern Yunnan, northern Laos, and northern Vietnam should be the targets of closer surveillance.Mainland Southeast Asia is the cradle of diversification of bat SCoV2rCsChinese researchers have actively sought sarbecoviruses in all Chinese provinces after the 2002–2004 SARS outbreak. They found many bat SCoVrCs16,20,21 but only two SCoV2rCs1,5 and both of them were discovered in southern Yunnan, the Chinese province bordering Southeast Asia. The ecological niches predicted herein for bat sarbecoviruses suggest that SCoVrCs are dominant in China (Fig. 4) while SCoV2rCs are present mostly in Southeast Asia (Fig. 5). This means that viruses similar to SARS-CoV-2 have been circulating for several decades throughout Southeast Asia, and that different species of bats have exchanged these viruses in the caves they inhabit. The data available on human cases and deaths caused by the COVID-19 pandemic2 indirectly support the hypothesis that the cradle of diversification of bat SCoV2rCs is mainland Southeast Asia, and in particular the areas highlighted in green in Fig. 5b. Indeed, human populations in Cambodia, Laos, Thailand, and Vietnam appear to be much less affected by the COVID-19 pandemic than other countries of the region, such as Indonesia, Malaysia, Myanmar, and the Philippines (Fig. 6). This suggests that some human populations of Cambodia, Laos, Thailand, and Vietnam, in particular rural populations living in contact with wild animals for several generations, have a better immunity against SCoV2rCs because they have been regularly contaminated by bats and/or infected secondary hosts such as pangolins.Figure 6Number of COVID-19 patients per million inhabitants (in blue) and deaths per million inhabitants (in red) for the different countries of Southeast Asia. Data extracted from the Worldometers website2 on June 08, 2021. The figure was drawn in Microsoft Excel and PowerPoint (version 16.16.27).Full size imagePangolins contaminated by bats in Southeast AsiaApart from bats, the Sunda pangolin (Manis javanica) and Chinese pangolin (Manis pentadactyla) are the only wild animals in which viruses related to SARS-CoV-2 have been found so far. However, these discoveries were made in a rather special context, that of pangolin trafficking. Several sick pangolins were seized by Chinese customs in Yunnan province in 2017 (unpublished data), in Guangxi province in 2017–201824 and in Guangdong province in 201925. Even if the viruses sequenced in pangolins are not that close to SARS-CoV-2 (one was 85% identical and the other 90%), they indicate that at least two sarbecoviruses could have been imported into China well before the emergence of COVID-19 epidemic. Indeed, it has been shown that Sunda pangolins collected from different Southeast Asian regions have contaminated each other while in captivity on Chinese territory3. It has been estimated that 43% of seized pangolins were infected by at least one SARS-CoV-2-like virus3. Such a high level of viral prevalence and the symptoms of acute interstitial pneumonia detected in most dead pangolins24 indicate that captive pangolins are highly permissive to infection by SARS-CoV-2-like viruses. The question remained on how the Sunda pangolins became infected initially. Could it have been in their natural Southeast Asian environment, before being captured? The discovery of two new viruses close to SARS-CoV-2 in bats from Cambodia and Thailand7,8 supports this hypothesis, as Rhinolophus bats and pangolins can meet, at least occasionally, in forests of Southeast Asia, possibly in caves, tree hollows or burrows. Further substantiating this hypothesis, the geographic distribution of Manis javanica26 overlaps the ecological niche here predicted for bat SCoV2rCs (Fig. 5), and SARS-CoV-2 neutralizing antibodies have been recently detected in one of the ten pangolin sera sampled from February to July 2020 from three wildlife checkpoint stations in Thailand6. Collectively, these data strengthen the hypothesis that pangolin trafficking is responsible for multiple exports of viruses related to SARS-CoV-2 to China3. More

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