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. 2016 Jul 5;3:160050. doi: 10.1038/sdata.2016.50

A catalogue of 136 microbial draft genomes from Red Sea metagenomes

Mohamed F Haroon 1,a, Luke R Thompson 1,2, Donovan H Parks 3, Philip Hugenholtz 3,4, Ulrich Stingl 1,b
PMCID: PMC4932879  PMID: 27377622

Abstract

Earth is expected to continue warming and the Red Sea is a model environment for understanding the effects of global warming on ocean microbiomes due to its unusually high temperature, salinity and solar irradiance. However, most microbial diversity analyses of the Red Sea have been limited to cultured representatives and single marker gene analyses, hence neglecting the substantial uncultured majority. Here, we report 136 microbial genomes (completion minus contamination is ≥50%) assembled from 45 metagenomes from eight stations spanning the Red Sea and taken from multiple depths between 10 to 500 m. Phylogenomic analysis showed that most of the retrieved genomes belong to seven different phyla of known marine microbes, but more than half representing currently uncultured species. The open-access data presented here is the largest number of Red Sea representative microbial genomes reported in a single study and will help facilitate future studies in understanding the physiology of these microorganisms and how they have adapted to the relatively harsh conditions of the Red Sea.

Subject terms: Water microbiology, Marine biology, Genome informatics

Background & Summary

The Red Sea is an ideal marine environment to study microbial adaptation to physical conditions atypical of global oceans: high temperature, high salinity, and high irradiance. In late summer 2011, we undertook the King Abdullah University of Science and Technology (KAUST) Red Sea Expedition (KRSE2011) in the eastern Red Sea in order to map its diversity along environmental gradients that occur with changes in latitude, longitude, and depth1. This time of year is not only when temperatures and evaporation (and hence salinity) are highest, but also when a foreign water mass called the Gulf of Aden Intermediate Water (GAIW) intrudes into the Red Sea1,2 (Fig. 1). The GAIW brings nutrient-rich water to the Red Sea, providing nitrogen, phosphorus, and other elements to this otherwise oligotrophic sea, and is likely to introduce important microbial diversity.

Figure 1. Experimental workflow for this study.

Figure 1

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The circles superimposed on the Red Sea 3D map shows the sampling points during the King Abdullah University of Science and Technology Red Sea Expedition 2011. The green lines represent the three Gulf of Aden Intermediate Water (GAIW) sampling points. The numbers within the circles represent the number of genomes recovered from each of the sample. Colors represent the high (dark red) to low (dark blue) water temperature. A total of 45 samples of 20 l each were collected and filtered through a series of filters. For this study, DNA extraction was performed on the small microbial fractions (between 0.1 to 1.2 μm). Extracted DNA was sequenced on the Illumina HiSeq 2,000 generating paired-end reads (2×93 bp). Reads from each metagenome were cleaned and assembled individually. Genomes were binned based on tetranucleotide and coverage-based method, refined and quality checked. All 136 genomes were annotated by IMG/ER and taxonomically assigned based on genome trees inferred from single-copy genes.

Insights into the taxonomic, evolutionary, and functional diversity of the Red Sea have largely been based on studies of pure cultures3–5 and single marker genes such as the 16S rRNA6,7, or internal transcribed spacer8. Recently, investigations of microbial ecology have steered towards whole genome-based culture-independent methods notably single-cell genomics and metagenomics9,10. Single-cell genomics is an exciting field that recovers complete and partial single cell genomes from complex environments, albeit the need of specialised equipment, high cost and relatively low throughput11–13. Metagenomics is paving the way forward by harnessing the recent wave of sequencing technology and bioinformatics advancements to recover genomes of individual populations or populations of closely related organisms14–16. Application of these methods has resulted in the recovery of numerous genomes of uncultivated microorganisms that have provided surprising insights into the diversity and function of microbial communities10,14,17–19.

During the KRSE2011, eight stations were sampled along a cruise track from south to north, capturing gradients in temperature, salinity, oxygen, and nutrients, including the unique GAIW water mass (Fig. 1 and Table 1 (available online only)). At each station, samples were collected from the surface to mesopelagic depths (10, 25, 50, 100, 200, and 500 m), except for stations 12 and 34, which had depths shallower than 500 m (Fig. 1 and Table 1 (available online only)), in order to capture a greater variation in environmental parameters and microbial diversity. Here, we successfully reconstructed 136 genomes from 45 individually assembled metagenomes (Figs 1 and 2, Tables 1 and 2 (available online only), Data Citation 1) by differential read coverage and tetranucleotide frequency methods. Of these, 43 were ‘near-complete’ with an estimated completion minus contamination of ≥90%, while the other 93 draft genomes had completion minus contamination of ≥50% (Table 2 (available online only)). To our knowledge, this is the largest number of microbial genomes from the Red Sea to be reported in a single study.

Table 1. Characteristics of the 45 Red Sea metagenomic samples.

Isolation source Water mass Date and Time Assembly size (Mbps) No. of scaffolds Largest scaffold size (Mbps) N50 Depth (m) BioProject BioSample NCBI accession (assembled) NCBI SRA accession (raw reads)
Red Sea water column Station 12 Red Sea 18/09/2011 10:26 44.11 29555 0.120 2072 10 PRJNA289734 SAMN03860258 LUMR00000000 SRR2102994
Red Sea water column Station 12 Red Sea   75.83 46146 0.102 2508 25 PRJNA289734 SAMN03860259 LUMQ00000000 SRR2102995
Red Sea water column Station 12 GAIW   37.84 23158 0.157 2720 47 PRJNA289734 SAMN03860260 LUMP00000000 SRR2103006
Red Sea water column Station 22 Red Sea 19/09/2011 08:53 47.49 38508 0.060 1415 10 PRJNA289734 SAMN03860261 LUMO00000000 SRR2103017
Red Sea water column Station 22 Red Sea   40.79 27718 0.072 1973 25 PRJNA289734 SAMN03860262 LUMN00000000 SRR2103028
Red Sea water column Station 22 Red Sea   41.68 29846 0.090 1775 50 PRJNA289734 SAMN03860263 LUMM00000000 SRR2103034
Red Sea water column Station 22 Red Sea   41.80 33190 0.129 1457 100 PRJNA289734 SAMN03860264 LUML00000000 SRR2103035
Red Sea water column Station 22 Red Sea   47.47 33409 0.133 1876 200 PRJNA289734 SAMN03860265 LUMK00000000 SRR2103036
Red Sea water column Station 22 Red Sea   80.71 45186 0.179 3201 500 PRJNA289734 SAMN03860266 LUMJ00000000 SRR2103037
Red Sea water column Station 34 Red Sea 20/09/2011 04:10 77.82 46638 0.221 2646 10 PRJNA289734 SAMN03860267 LUMI00000000 SRR2103038
Red Sea water column Station 34 Red Sea   42.51 28685 0.221 2018 25 PRJNA289734 SAMN03860268 LUMH00000000 SRR2102996
Red Sea water column Station 34 GAIW   38.78 27506 0.253 1843 50 PRJNA289734 SAMN03860269 LUMG00000000 SRR2102997
Red Sea water column Station 34 GAIW   39.04 35615 0.037 1167 100 PRJNA289734 SAMN03860270 LUMF00000000 SRR2102998
Red Sea water column Station 34 Red Sea   63.41 42929 0.125 1962 200 PRJNA289734 SAMN03860271 LUME00000000 SRR2102999
Red Sea water column Station 34 Red Sea   64.65 37057 0.263 2832 258 PRJNA289734 SAMN03860272 LUMD00000000 SRR2103000
Red Sea water column Station 91 Red Sea 24/09/2011 20:54 35.42 26110 0.116 1716 10 PRJNA289734 SAMN03860273 LUMC00000000 SRR2103001
Red Sea water column Station 91 Red Sea   28.80 21238 0.079 1783 25 PRJNA289734 SAMN03860274 LUMB00000000 SRR2103002
Red Sea water column Station 91 Red Sea   21.35 18107 0.070 1293 50 PRJNA289734 SAMN03860275 LUMA00000000 SRR2103003
Red Sea water column Station 91 Red Sea   51.35 45910 0.141 1194 100 PRJNA289734 SAMN03860276 LULZ00000000 SRR2103004
Red Sea water column Station 91 Red Sea   49.04 43484 0.129 1239 200 PRJNA289734 SAMN03860277 LULY00000000 SRR2103005
Red Sea water column Station 91 Red Sea   68.61 45543 0.194 2011 500 PRJNA289734 SAMN03860278 LULX00000000 SRR2103007
Red Sea water column Station 108 Red Sea 27/09/2011 21:03 68.31 39235 1.199 2885 10 PRJNA289734 SAMN03860279 LULW00000000 SRR2103008
Red Sea water column Station 108 Red Sea   59.60 40690 0.160 1948 25 PRJNA289734 SAMN03860280 LULV00000000 SRR2103009
Red Sea water column Station 108 Red Sea   58.23 49013 0.058 1334 50 PRJNA289734 SAMN03860281 LULU00000000 SRR2103010
Red Sea water column Station 108 Red Sea   36.51 27461 0.142 1626 100 PRJNA289734 SAMN03860282 LULT00000000 SRR2103011
Red Sea water column Station 108 Red Sea   58.51 45536 0.079 1553 200 PRJNA289734 SAMN03860283 LULS00000000 SRR2103012
Red Sea water column Station 108 Red Sea   63.24 41604 0.139 2136 500 PRJNA289734 SAMN03860284 LULR00000000 SRR2103013
Red Sea water column Station 149 Red Sea 01/10/2011 05:00 56.10 31577 1.198 2984 10 PRJNA289734 SAMN03860285 LULQ00000000 SRR2103014
Red Sea water column Station 149 Red Sea   62.95 34995 0.416 3178 25 PRJNA289734 SAMN03860286 LULP00000000 SRR2103015
Red Sea water column Station 149 Red Sea   79.82 47255 0.314 2763 50 PRJNA289734 SAMN03860287 LULO00000000 SRR2103016
Red Sea water column Station 149 Red Sea   38.33 25062 0.170 2222 100 PRJNA289734 SAMN03860288 LULN00000000 SRR2103018
Red Sea water column Station 149 Red Sea   66.80 52078 0.105 1503 200 PRJNA289734 SAMN03860289 LULM00000000 SRR2103019
Red Sea water column Station 149 Red Sea   85.38 54665 0.289 2146 500 PRJNA289734 SAMN03860290 LULL00000000 SRR2103020
Red Sea water column Station 169 Red Sea 03/10/2011 04:55 99.91 54636 1.199 3019 10 PRJNA289734 SAMN03860291 LULK00000000 SRR2103021
Red Sea water column Station 169 Red Sea   83.57 45217 0.308 3232 25 PRJNA289734 SAMN03860292 LULJ00000000 SRR2103022
Red Sea water column Station 169 Red Sea   84.94 53578 0.158 2309 50 PRJNA289734 SAMN03860293 LULI00000000 SRR2103023
Red Sea water column Station 169 Red Sea   73.95 54373 0.149 1685 100 PRJNA289734 SAMN03860294 LULH00000000 SRR2103024
Red Sea water column Station 169 Red Sea   73.59 57258 0.155 1530 200 PRJNA289734 SAMN03860295 LULG00000000 SRR2103025
Red Sea water column Station 169 Red Sea   79.59 58308 0.400 1655 500 PRJNA289734 SAMN03860296 LULF00000000 SRR2103026
Red Sea water column Station 192 Red Sea 05/10/2011 10:56 98.63 57007 1.199 2789 10 PRJNA289734 SAMN03860297 LULE00000000 SRR2103027
Red Sea water column Station 192 Red Sea   58.15 34483 0.321 2666 25 PRJNA289734 SAMN03860298 LUMS00000000 SRR2103029
Red Sea water column Station 192 Red Sea   87.61 47563 1.358 3315 50 PRJNA289734 SAMN03860299 LUMT00000000 SRR2103030
Red Sea water column Station 192 Red Sea   50.63 34015 0.680 2014 100 PRJNA289734 SAMN03860300 LUMU00000000 SRR2103031
Red Sea water column Station 192 Red Sea   45.78 30314 0.295 2337 200 PRJNA289734 SAMN03860301 LUMV00000000 SRR2103032
Red Sea water column Station 192 Red Sea   73.78 44069 0.278 2528 500 PRJNA289734 SAMN03860302 LUMW00000000 SRR2103033
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Figure 2. Phylogenetic trees for the archaeal (green lines; top left) and bacterial (blue lines; bottom right) domains based on 122 and 120 single-copy marker genes, respectively.

Figure 2

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The clades represented by the triangles are collapsed at the phylum (P) level except for phyla containing genomes from this study which are expanded at the class (C) level and highlighted in red. Certain phyla have genome representatives only at the phylum level (Thaumarchaeota, Marinimicrobia, Cyanobacteria, and Bdellovibrionaeota). Numbers in parentheses indicate the count of recovered genomes from a particular taxonomic level. Dashed lines indicate nodes for class level. Robustness of the tree is indicated by black circles (size of circles scaled from 80 to 100% bootstrap support values). Trees were inferred independently. The archaeal tree was rooted with the DPANN superphylum9 while the bacterial tree was ‘arbitrarily’ rooted with the phylum Chloroflexi42 but should be treated as unrooted.

Table 2. Characteristics of the 136 genomes reported in this study.

Genome bins Genome size (Mbps) No. of scaffolds IMG Gene count GC (%) Marker lineage for CheckM Completeness (%) Contamination (%) Comp-Cont % Isolation source Depth (m) Latitude/Longtitude BioProject BioSample NCBI accession IMG genome ID
Acidimicrobiia bacterium REDSEA-S09_B7 2.02 226 1884 71.62 k__Bacteria (UID1453) 84.25 2.23 82.02 Red Sea water column Station 22 500 17.996 N 39.799 E PRJNA289734 SAMN04534547 LUMX00000000 2651870138
Acidimicrobiia bacterium REDSEA-S14_B4 2.10 257 1654 71.6 k__Bacteria (UID1453) 85.86 2.56 83.3 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534548 LUMY00000000 2651870139
Acidimicrobiia bacterium REDSEA-S20_B6 1.76 338 2064 71.41 k__Bacteria (UID1453) 81.36 1.59 79.77 Red Sea water column Station 91 200 20.525 N 38.781 E PRJNA289734 SAMN04534549 LUMZ00000000 2651870140
Acidimicrobiia bacterium REDSEA-S21_B10 1.73 328 2037 71.37 k__Bacteria (UID1453) 64.31 0.43 63.88 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534550 LUNA00000000 2651870141
Acidimicrobiia bacterium REDSEA-S33_B8N9 2.15 262 2380 71.46 k__Bacteria (UID1453) 80.48 5.56 74.92 Red Sea water column Station 149 500 23.604 N 37.054 E PRJNA289734 SAMN04534551 LUNB00000000 2651870142
Acinetobacter sp. REDSEA-S21_B14 2.58 517 3085 39.1 f__Moraxellaceae (UID4680) 71.54 4.32 67.22 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534552 LUNC00000000 2651870143
Actinobacteria bacterium REDSEA-S36_B12 1.37 255 1734 62.57 o__Actinomycetales (UID1663) 60.63 0 60.63 Red Sea water column Station 169 50 25.772 N 36.116 E PRJNA289734 SAMN04534553 LUND00000000 2651870144
Aeromicrobium sp. REDSEA-S32_B7 3.52 333 3794 71.86 o__Actinomycetales (UID1697) 95.73 6.23 89.5 Red Sea water column Station 149 200 23.604 N 37.054 E PRJNA289734 SAMN04534555 LUNF00000000 2651870146
Aeromicrobium sp. REDSEA-S35_B1 3.56 83 3609 72.12 o__Actinomycetales (UID1697) 98.06 2.8 95.26 Red Sea water column Station 169 25 25.772 N 36.116 E PRJNA289734 SAMN04534556 LUNG00000000 2651870147
Aeromicrobium sp. REDSEA-S38_B2 3.49 104 3608 72.12 o__Actinomycetales (UID1697) 98.53 1.9 96.63 Red Sea water column Station 169 200 25.772 N 36.116 E PRJNA289734 SAMN04534557 LUNH00000000 2651870148
Aeromicrobium sp. REDSEA-S42_B4 3.47 54 3538 72.15 o__Actinomycetales (UID1697) 98.45 0.86 97.59 Red Sea water column Station 192 50 27.897 N 34.507 E PRJNA289734 SAMN04534558 LUNI00000000 2651870149
Aeromicrobium sp. REDSEA-S44_B1 3.47 44 3560 72.09 o__Actinomycetales (UID1697) 98.91 0.95 97.96 Red Sea water column Station 192 200 27.897 N 34.507 E PRJNA289734 SAMN04534559 LUNJ00000000 2651870150
Alteromonas macleodii str. REDSEA-S09_B2 4.34 102 3190 44.52 c__Gammaproteobacteria (UID4761) 98.83 0.51 98.32 Red Sea water column Station 22 500 17.996 N 39.799 E PRJNA289734 SAMN04534560 LUNK00000000 2651870151
Alteromonas macleodii str. REDSEA-S10_B9 2.55 490 1239 44.64 c__Gammaproteobacteria (UID4761) 59.71 0.57 59.14 Red Sea water column Station 34 10 18.58 N 40.743 E PRJNA289734 SAMN04534561 LUNL00000000 2651870152
Alteromonas macleodii str. REDSEA-S12_B5 2.64 514 2355 43.98 c__Gammaproteobacteria (UID4761) 59.42 2.39 57.03 Red Sea water column Station 34 50 18.58 N 40.743 E PRJNA289734 SAMN04534562 LUNM00000000 2651870153
Alteromonas macleodii str. REDSEA-S14_B11 3.11 543 2135 44.58 c__Gammaproteobacteria (UID4761) 73.75 1.24 72.51 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534563 LUNN00000000 2651870154
Alteromonas macleodii str. REDSEA-S15_B11 3.79 457 3227 44.59 c__Gammaproteobacteria (UID4761) 89.9 1.25 88.65 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534564 LUNO00000000 2651870155
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S14_B6 1.43 234 2855 54.35 k__Bacteria (UID2495) 72.35 0.18 72.17 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534578 LUOC00000000 2651870223
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S15_B10 1.65 233 4044 54.08 k__Bacteria (UID2495) 71.03 0.1 70.93 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534579 LUOD00000000 2651870224
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S15_B13 1.48 201 3478 41.84 k__Bacteria (UID2495) 71.59 3.3 68.29 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534580 LUOE00000000 2651870225
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S27_B1N12 1.36 280 1643 51.44 k__Bacteria (UID2495) 60.19 2.2 57.99 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534581 LUOF00000000 2651870226
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S33_B13 1.27 264 1462 54.33 k__Bacteria (UID2495) 56.03 1.65 54.38 Red Sea water column Station 149 500 23.604 N 37.054 E PRJNA289734 SAMN04534582 LUOG00000000 2651870227
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S38_B13 1.15 217 1313 41.56 k__Bacteria (UID2495) 58.34 1.2 57.14 Red Sea water column Station 169 200 25.772 N 36.116 E PRJNA289734 SAMN04534583 LUOH00000000 2651870228
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S39_B11 1.09 225 1203 54.56 k__Bacteria (UID2495) 52.97 0.1 52.87 Red Sea water column Station 169 500 25.772 N 36.116 E PRJNA289734 SAMN04534584 LUOI00000000 2651870229
Candidatus Marinimicrobia (SAR406 cluster) bacterium REDSEA-S39_B7 0.24 15 229 38.13 k__Bacteria (UID2495) 78.5 6.89 71.61 Red Sea water column Station 169 500 25.772 N 36.116 E PRJNA289734 SAMN04534585 LUOJ00000000 2651870230
Candidatus Thioglobus (SUP05 cluster) sp. REDSEA-S03_B1 1.58 97 2264 38.39 p__Proteobacteria (UID3880) 87.92 3.86 84.06 Red Sea water column Station 12 47 17.662 N 40.905 E PRJNA289734 SAMN04534667 LURM00000000 2651870213
Candidatus Thioglobus (SUP05 cluster) sp. REDSEA-S12_B1 1.61 77 1540 38.35 p__Proteobacteria (UID3880) 88.91 1.32 87.59 Red Sea water column Station 34 50 18.58 N 40.743 E PRJNA289734 SAMN04534668 LURN00000000 2651870214
Candidatus Thioglobus (SUP05 cluster) sp. REDSEA-S14_B12 1.83 262 2336 39.85 p__Proteobacteria (UID3880) 67.29 7.86 59.43 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534669 LURO00000000 2651870215
Erythrobacter sp. REDSEA-S22_B4 2.69 10 2897 63.73 o__Sphingomonadales (UID3310) 99.93 0.43 99.5 Red Sea water column Station 108 10 22.046 N 37.929 E PRJNA289734 SAMN04534565 LUNP00000000 2651870156
Erythrobacter sp. REDSEA-S28_B2 2.69 8 2894 63.71 o__Sphingomonadales (UID3310) 99.9 0.43 99.47 Red Sea water column Station 149 10 23.604 N 37.054 E PRJNA289734 SAMN04534566 LUNQ00000000 2654587888
Erythrobacter sp. REDSEA-S34_B3 2.69 7 2893 63.73 o__Sphingomonadales (UID3310) 99.93 0.43 99.5 Red Sea water column Station 169 10 25.772 N 36.116 E PRJNA289734 SAMN04534567 LUNR00000000 2654587889
Erythrobacter sp. REDSEA-S36_B6 2.93 99 3035 63.57 o__Sphingomonadales (UID3310) 97.09 2.53 94.56 Red Sea water column Station 169 50 25.772 N 36.116 E PRJNA289734 SAMN04534568 LUNS00000000 2654587890
Erythrobacter sp. REDSEA-S37_B3 2.79 94 2968 63.54 o__Sphingomonadales (UID3310) 97.59 1 96.59 Red Sea water column Station 169 100 25.772 N 36.116 E PRJNA289734 SAMN04534569 LUNT00000000 2654587891
Erythrobacter sp. REDSEA-S40_B1 2.69 7 2897 63.72 o__Sphingomonadales (UID3310) 99.93 0.43 99.5 Red Sea water column Station 192 10 27.897 N 34.507 E PRJNA289734 SAMN04534570 LUNU00000000 2654587892
Erythrobacter sp. REDSEA-S41_B1 2.93 23 2933 63.59 o__Sphingomonadales (UID3310) 99.54 0.63 98.91 Red Sea water column Station 192 25 27.897 N 34.507 E PRJNA289734 SAMN04534571 LUNV00000000 2654587893
Erythrobacter sp. REDSEA-S42_B5 2.68 12 2905 63.72 o__Sphingomonadales (UID3310) 99.83 0.43 99.4 Red Sea water column Station 192 50 27.897 N 34.507 E PRJNA289734 SAMN04534572 LUNW00000000 2654587894
Erythrobacter sp. REDSEA-S43_B2 2.87 18 2918 63.64 o__Sphingomonadales (UID3310) 99.84 0.94 98.9 Red Sea water column Station 192 100 27.897 N 34.507 E PRJNA289734 SAMN04534573 LUNX00000000 2651870157
Erythrobacter sp. REDSEA-S45_B7 2.89 285 3139 63.54 o__Sphingomonadales (UID3310) 89.24 1.25 87.99 Red Sea water column Station 192 500 27.897 N 34.507 E PRJNA289734 SAMN04534574 LUNY00000000 2651870158
Idiomarina sp. REDSEA-S21_B4 2.26 60 2451 47.2 c__Gammaproteobacteria (UID4761) 95.29 0.42 94.87 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534575 LUNZ00000000 2651870159
Idiomarina sp. REDSEA-S27_B4 2.38 57 2550 47.27 c__Gammaproteobacteria (UID4761) 98.14 0.74 97.4 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534576 LUOA00000000 2651870160
Marine group II euryarchaeote REDSEA-S03_B6 1.32 210 1400 45.47 p__Euryarchaeota (UID3) 65.01 2.3 62.71 Red Sea water column Station 12 47 17.662 N 40.905 E PRJNA289734 SAMN04534670 LURP00000000 2651870292
Marine group II euryarchaeote REDSEA-S10_B2 1.23 29 3698 50.45 p__Euryarchaeota (UID3) 76.13 1.2 74.93 Red Sea water column Station 34 10 18.58 N 40.743 E PRJNA289734 SAMN04534671 LURQ00000000 2651870293
Marine group II euryarchaeote REDSEA-S11_B3N4 1.30 35 2197 50.98 p__Euryarchaeota (UID3) 81.96 0 81.96 Red Sea water column Station 34 25 18.58 N 40.743 E PRJNA289734 SAMN04534672 LURR00000000 2651870294
Marine group II euryarchaeote REDSEA-S19_B7N8 1.17 155 1796 52.04 p__Euryarchaeota (UID3) 70.4 0.8 69.6 Red Sea water column Station 91 100 20.525 N 38.781 E PRJNA289734 SAMN04534673 LURS00000000 2651870295
Marine group II euryarchaeote REDSEA-S25_B4N5 1.10 167 1272 52.14 p__Euryarchaeota (UID3) 58.43 0.27 58.16 Red Sea water column Station 108 100 22.046 N 37.929 E PRJNA289734 SAMN04534674 LURT00000000 2651870296
Marine group II euryarchaeote REDSEA-S29_B8N9 1.10 131 1244 50.19 p__Euryarchaeota (UID3) 59.47 0 59.47 Red Sea water column Station 149 25 23.604 N 37.054 E PRJNA289734 SAMN04534675 LURU00000000 2651870297
Marine group II euryarchaeote REDSEA-S30_B12 1.27 137 1374 36.9 p__Euryarchaeota (UID3) 67.79 0.8 66.99 Red Sea water column Station 149 50 23.604 N 37.054 E PRJNA289734 SAMN04534676 LURV00000000 2651870298
Marine group II euryarchaeote REDSEA-S37_B2N9 1.21 6 155 49.08 p__Euryarchaeota (UID3) 76.47 0.06 76.41 Red Sea water column Station 169 100 25.772 N 36.116 E PRJNA289734 SAMN04534677 LURW00000000 2651870299
Marine group II euryarchaeote REDSEA-S40_B11N13 1.24 118 1300 50.09 p__Euryarchaeota (UID3) 71.96 0 71.96 Red Sea water column Station 192 10 27.897 N 34.507 E PRJNA289734 SAMN04534678 LURX00000000 2651870300
Marine group II euryarchaeote REDSEA-S41_B6 1.13 122 1216 49.97 p__Euryarchaeota (UID3) 71.35 1.92 69.43 Red Sea water column Station 192 25 27.897 N 34.507 E PRJNA289734 SAMN04534679 LURY00000000 2651870301
Marine group II euryarchaeote REDSEA-S42_B7 1.19 43 1202 49.72 p__Euryarchaeota (UID3) 75.73 0 75.73 Red Sea water column Station 192 50 27.897 N 34.507 E PRJNA289734 SAMN04534680 LURZ00000000 2651870302
Marine group II euryarchaeote REDSEA-S43_B8 1.10 105 1213 50.28 p__Euryarchaeota (UID3) 72.13 0 72.13 Red Sea water column Station 192 100 27.897 N 34.507 E PRJNA289734 SAMN04534681 LUSA00000000 2651870303
Marinobacter sp. REDSEA-S15_B16 2.89 527 2873 57.64 c__Gammaproteobacteria (UID4444) 72.81 0.89 71.92 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534586 LUOK00000000 2651870218
Marinobacter sp. REDSEA-S21_B2N3 4.37 262 4343 57.01 c__Gammaproteobacteria (UID4444) 88.75 2.59 86.16 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534587 LUOL00000000 2651870219
Marinobacter sp. REDSEA-S27_B10 3.27 500 3781 57.24 k__Bacteria (UID203) 70 0 70 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534588 LUOM00000000 2651870220
Maritimibacter sp. REDSEA-S28_B5 4.25 122 4632 64.32 f__Rhodobacteraceae (UID3356) 97.93 0.68 97.25 Red Sea water column Station 149 10 23.604 N 37.054 E PRJNA289734 SAMN04534590 LUOO00000000 2651870216
Maritimibacter sp. REDSEA-S40_B3 3.87 28 4511 64.35 f__Rhodobacteraceae (UID3356) 99.7 0.68 99.02 Red Sea water column Station 192 10 27.897 N 34.507 E PRJNA289734 SAMN04534591 LUOP00000000 2651870217
Moraxellaceae bacterium REDSEA-S29_B6 2.23 154 2327 41.94 c__Gammaproteobacteria (UID4201) 91.59 0 91.59 Red Sea water column Station 149 25 23.604 N 37.054 E PRJNA289734 SAMN04534592 LUOQ00000000 2651870134
Moraxellaceae bacterium REDSEA-S32_B1 2.38 80 2272 42.07 c__Gammaproteobacteria (UID4201) 98.13 0 98.13 Red Sea water column Station 149 200 23.604 N 37.054 E PRJNA289734 SAMN04534593 LUOR00000000 2654587887
Moraxellaceae bacterium REDSEA-S35_B9 1.60 306 1900 41.91 c__Gammaproteobacteria (UID4201) 71.1 0.77 70.33 Red Sea water column Station 169 25 25.772 N 36.116 E PRJNA289734 SAMN04534594 LUOS00000000 2651870137
Moraxellaceae bacterium REDSEA-S38_B3 2.41 100 2293 41.98 c__Gammaproteobacteria (UID4201) 97.33 0 97.33 Red Sea water column Station 169 200 25.772 N 36.116 E PRJNA289734 SAMN04534595 LUOT00000000 2651870132
Moraxellaceae bacterium REDSEA-S42_B15 1.88 270 2124 41.99 c__Gammaproteobacteria (UID4201) 78.54 0.57 77.97 Red Sea water column Station 192 50 27.897 N 34.507 E PRJNA289734 SAMN04534596 LUOU00000000 2651870135
Moraxellaceae bacterium REDSEA-S44_B2 2.35 95 2324 42.04 c__Gammaproteobacteria (UID4201) 97.13 1.15 95.98 Red Sea water column Station 192 200 27.897 N 34.507 E PRJNA289734 SAMN04534597 LUOV00000000 2651870133
Moraxellaceae bacterium REDSEA-S45_B11 1.71 287 1938 42.04 c__Gammaproteobacteria (UID4201) 78.09 2.04 76.05 Red Sea water column Station 192 500 27.897 N 34.507 E PRJNA289734 SAMN04534598 LUOW00000000 2651870136
Nitrosopelagicus sp. REDSEA-S08_B1 0.58 92 1823 35.43 k__Archaea (UID2) 58.9 5.83 53.07 Red Sea water column Station 22 200 17.996 N 39.799 E PRJNA289734 SAMN04534599 LUOX00000000 2651870205
Nitrosopelagicus sp. REDSEA-S19_B12N3 1.51 307 1226 36.28 k__Archaea (UID2) 85.74 5.34 80.4 Red Sea water column Station 91 100 20.525 N 38.781 E PRJNA289734 SAMN04534600 LUOY00000000 2651870206
Nitrosopelagicus sp. REDSEA-S25_B3 0.89 116 1294 34.1 k__Archaea (UID2) 74.76 1.94 72.82 Red Sea water column Station 108 100 22.046 N 37.929 E PRJNA289734 SAMN04534601 LUOZ00000000 2651870207
Nitrosopelagicus sp. REDSEA-S27_B13N2 1.51 273 2009 37.26 k__Archaea (UID2) 69.84 4.85 64.99 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534602 LUPA00000000 2651870208
Nitrosopelagicus sp. REDSEA-S31_B2 1.01 86 1387 34.05 k__Archaea (UID2) 92.64 2.02 90.62 Red Sea water column Station 149 100 23.604 N 37.054 E PRJNA289734 SAMN04534603 LUPB00000000 2651870209
Nitrosopelagicus sp. REDSEA-S32_B2 0.45 55 604 33.9 k__Archaea (UID2) 53.4 1.94 51.46 Red Sea water column Station 149 200 23.604 N 37.054 E PRJNA289734 SAMN04534604 LUPC00000000 2651870210
Nitrosopelagicus sp. REDSEA-S37_B6 0.87 104 1233 34.05 k__Archaea (UID2) 89.81 1.94 87.87 Red Sea water column Station 169 100 25.772 N 36.116 E PRJNA289734 SAMN04534605 LUPD00000000 2651870211
Nitrosopelagicus sp. REDSEA-S43_B1 0.98 115 1403 33.94 k__Archaea (UID2) 84.95 4.53 80.42 Red Sea water column Station 192 100 27.897 N 34.507 E PRJNA289734 SAMN04534606 LUPE00000000 2651870212
Nocardioides sp. REDSEA-S22_B2 3.76 94 4050 71.84 o__Actinomycetales (UID1697) 94.43 1.38 93.05 Red Sea water column Station 108 10 22.046 N 37.929 E PRJNA289734 SAMN04534607 LUPF00000000 2651870231
Nocardioides sp. REDSEA-S25_B9 2.25 485 2643 71.44 o__Actinomycetales (UID1697) 57.78 1.17 56.61 Red Sea water column Station 108 100 22.046 N 37.929 E PRJNA289734 SAMN04534608 LUPG00000000 2651870232
Nocardioides sp. REDSEA-S28_B4 3.90 313 4194 71.71 o__Actinomycetales (UID1697) 94.91 3.54 91.37 Red Sea water column Station 149 10 23.604 N 37.054 E PRJNA289734 SAMN04534609 LUPH00000000 2651870233
Nocardioides sp. REDSEA-S30_B4 3.68 104 3857 71.94 o__Actinomycetales (UID1697) 96.89 0.86 96.03 Red Sea water column Station 149 50 23.604 N 37.054 E PRJNA289734 SAMN04534610 LUPI00000000 2651870234
Nocardioides sp. REDSEA-S31_B4 3.44 387 3841 71.68 o__Actinomycetales (UID1697) 83.54 1.21 82.33 Red Sea water column Station 149 100 23.604 N 37.054 E PRJNA289734 SAMN04534611 LUPJ00000000 2651870235
Nocardioides sp. REDSEA-S33_B3 3.56 61 3796 72.09 o__Actinomycetales (UID1697) 98.19 0 98.19 Red Sea water column Station 149 500 23.604 N 37.054 E PRJNA289734 SAMN04534612 LUPK00000000 2651870236
Nocardioides sp. REDSEA-S34_B5 4.17 291 4427 71.75 o__Actinomycetales (UID1697) 94.13 4.13 90 Red Sea water column Station 169 10 25.772 N 36.116 E PRJNA289734 SAMN04534613 LUPL00000000 2651870237
Nocardioides sp. REDSEA-S36_B10 2.34 439 2744 71.08 o__Actinomycetales (UID1697) 59.33 1.26 58.07 Red Sea water column Station 169 50 25.772 N 36.116 E PRJNA289734 SAMN04534614 LUPM00000000 2651870238
Nocardioides sp. REDSEA-S37_B12 2.85 503 3278 71.42 o__Actinomycetales (UID1697) 77.85 0.6 77.25 Red Sea water column Station 169 100 25.772 N 36.116 E PRJNA289734 SAMN04534615 LUPN00000000 2651870239
Nocardioides sp. REDSEA-S39_B2 3.48 56 3796 72.16 o__Actinomycetales (UID1697) 97.67 0.05 97.62 Red Sea water column Station 169 500 25.772 N 36.116 E PRJNA289734 SAMN04534616 LUPO00000000 2651870240
Nocardioides sp. REDSEA-S40_B4 3.70 116 3967 71.95 o__Actinomycetales (UID1697) 91.19 1.11 90.08 Red Sea water column Station 192 10 27.897 N 34.507 E PRJNA289734 SAMN04534617 LUPP00000000 2651870241
Nocardioides sp. REDSEA-S43_B3 3.68 164 3948 71.9 o__Actinomycetales (UID1697) 96.07 0.35 95.72 Red Sea water column Station 192 100 27.897 N 34.507 E PRJNA289734 SAMN04534618 LUPQ00000000 2651870242
Prochlorococcus sp. REDSEA-S17_B1 1.07 152 2041 30.99 p__Cyanobacteria (UID2143) 63.12 4.65 58.47 Red Sea water column Station 91 25 20.525 N 38.781 E PRJNA289734 SAMN04534620 LUPS00000000 2651870162
Prochlorococcus sp. REDSEA-S22_B1 1.01 113 1338 31.11 p__Cyanobacteria (UID2143) 60.42 7.38 53.04 Red Sea water column Station 108 10 22.046 N 37.929 E PRJNA289734 SAMN04534621 LUPT00000000 2651870163
Prochlorococcus sp. REDSEA-S23_B1 1.06 123 1381 30.87 p__Cyanobacteria (UID2143) 61.61 7.2 54.41 Red Sea water column Station 108 25 22.046 N 37.929 E PRJNA289734 SAMN04534622 LUPU00000000 2651870164
Prochlorococcus sp. REDSEA-S28_B1 0.93 101 1181 31.35 p__Cyanobacteria (UID2143) 55.19 4.71 50.48 Red Sea water column Station 149 10 23.604 N 37.054 E PRJNA289734 SAMN04534623 LUPV00000000 2651870165
Rhodobacteraceae bacterium REDSEA-S02_B3 2.07 113 2195 39.74 f__Rhodobacteraceae (UID3340) 80.46 1.04 79.42 Red Sea water column Station 12 25 17.662 N 40.905 E PRJNA289734 SAMN04534625 LUPX00000000 2651870273
Rhodobacteraceae bacterium REDSEA-S03_B4 2.03 202 1380 39.69 f__Rhodobacteraceae (UID3340) 77.8 4.86 72.94 Red Sea water column Station 12 47 17.662 N 40.905 E PRJNA289734 SAMN04534626 LUPY00000000 2651870274
Rhodobacteraceae bacterium REDSEA-S11_B6 1.89 192 2900 39.63 k__Bacteria (UID203) 77.43 8.62 68.81 Red Sea water column Station 34 25 18.58 N 40.743 E PRJNA289734 SAMN04534628 LUQA00000000 2651870277
Rhodobacteraceae bacterium REDSEA-S29_B10 1.79 357 2262 40.1 f__Rhodobacteraceae (UID3340) 57.51 3.99 53.52 Red Sea water column Station 149 25 23.604 N 37.054 E PRJNA289734 SAMN04534629 LUQB00000000 2651870278
Rhodobacteraceae bacterium REDSEA-S34_B6 2.41 111 2606 40.44 f__Rhodobacteraceae (UID3340) 89.51 1.57 87.94 Red Sea water column Station 169 10 25.772 N 36.116 E PRJNA289734 SAMN04534630 LUQC00000000 2651870280
SAR116 cluster alphaproteobacterium REDSEA-S02_B12 1.51 247 2215 63.03 c__Alphaproteobacteria (UID3305) 74.63 0.44 74.19 Red Sea water column Station 12 25 17.662 N 40.905 E PRJNA289734 SAMN04534631 LUQD00000000 2654587886
SAR116 cluster alphaproteobacterium REDSEA-S10_B10N8 1.58 247 2222 62.96 c__Alphaproteobacteria (UID3305) 78.7 0 78.7 Red Sea water column Station 34 10 18.58 N 40.743 E PRJNA289734 SAMN04534632 LUQE00000000 2651870131
SAR324 cluster deltaproteobacterium REDSEA-S05_B4 1.75 357 2060 46.78 k__Bacteria (UID3187) 54.11 0.94 53.17 Red Sea water column Station 22 25 17.996 N 39.799 E PRJNA289734 SAMN04534633 LUQF00000000 2654587902
SAR324 cluster deltaproteobacterium REDSEA-S06_B4 1.73 373 873 47.26 k__Bacteria (UID3187) 54.22 0.05 54.17 Red Sea water column Station 22 50 17.996 N 39.799 E PRJNA289734 SAMN04534634 LUQG00000000 2651870251
SAR324 cluster deltaproteobacterium REDSEA-S08_B7 2.12 328 1504 43.26 k__Bacteria (UID2495) 55.09 4.09 51 Red Sea water column Station 22 200 17.996 N 39.799 E PRJNA289734 SAMN04534635 LUQH00000000 2651870252
SAR324 cluster deltaproteobacterium REDSEA-S09_B3 3.35 83 1823 42.85 k__Bacteria (UID3187) 92.1 0 92.1 Red Sea water column Station 22 500 17.996 N 39.799 E PRJNA289734 SAMN04534636 LUQI00000000 2651870253
SAR324 cluster deltaproteobacterium REDSEA-S10_B5 3.49 290 2962 47.12 k__Bacteria (UID3187) 90.84 0 90.84 Red Sea water column Station 34 10 18.58 N 40.743 E PRJNA289734 SAMN04270322 LNZD00000000 2651870254
SAR324 cluster deltaproteobacterium REDSEA-S11_B7 2.54 416 1743 47.48 k__Bacteria (UID3187) 73.12 3.78 69.34 Red Sea water column Station 34 25 18.58 N 40.743 E PRJNA289734 SAMN04534638 LUQJ00000000 2651870255
SAR324 cluster deltaproteobacterium REDSEA-S14_B10 1.95 455 3426 42.39 k__Bacteria (UID3187) 62 3.12 58.88 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534639 LUQK00000000 2651870256
SAR324 cluster deltaproteobacterium REDSEA-S15_B6 2.79 191 1471 42.4 k__Bacteria (UID3187) 86.18 1.73 84.45 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534640 LUQL00000000 2651870257
SAR324 cluster deltaproteobacterium REDSEA-S21_B5 3.05 128 3061 42.86 k__Bacteria (UID3187) 89.51 0.22 89.29 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534641 LUQM00000000 2651870258
SAR324 cluster deltaproteobacterium REDSEA-S26_B7 2.26 415 2573 42.53 k__Bacteria (UID3187) 69.56 1.05 68.51 Red Sea water column Station 108 200 22.046 N 37.929 E PRJNA289734 SAMN04534642 LUQN00000000 2651870259
SAR324 cluster deltaproteobacterium REDSEA-S27_B3 3.30 80 3134 42.85 k__Bacteria (UID3187) 92.1 0 92.1 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534643 LUQO00000000 2651870260
SAR324 cluster deltaproteobacterium REDSEA-S33_B4 3.12 94 3069 42.82 k__Bacteria (UID3187) 92.1 0 92.1 Red Sea water column Station 149 500 23.604 N 37.054 E PRJNA289734 SAMN04534644 LUQP00000000 2651870261
SAR324 cluster deltaproteobacterium REDSEA-S36_B13 1.37 323 1640 46.89 k__Bacteria (UID3187) 51.76 1.68 50.08 Red Sea water column Station 169 50 25.772 N 36.116 E PRJNA289734 SAMN04534645 LUQQ00000000 2651870262
SAR324 cluster deltaproteobacterium REDSEA-S39_B5 3.04 266 3057 43 k__Bacteria (UID3187) 88.88 2.6 86.28 Red Sea water column Station 169 500 25.772 N 36.116 E PRJNA289734 SAMN04534646 LUQR00000000 2651870263
SAR324 cluster deltaproteobacterium REDSEA-S45_B3 3.17 89 3038 42.89 k__Bacteria (UID3187) 92.1 0 92.1 Red Sea water column Station 192 500 27.897 N 34.507 E PRJNA289734 SAMN04534647 LUQS00000000 2651870264
SAR86 cluster gammaproteobacterium REDSEA-S08_B3 1.56 177 2329 36.99 c__Gammaproteobacteria (UID4443) 61.92 4.16 57.76 Red Sea water column Station 22 200 17.996 N 39.799 E PRJNA289734 SAMN04534648 LUQT00000000 2651870265
SAR86 cluster gammaproteobacterium REDSEA-S09_B4 1.67 107 1534 37.05 c__Gammaproteobacteria (UID4443) 68.13 2.49 65.64 Red Sea water column Station 22 500 17.996 N 39.799 E PRJNA289734 SAMN04534649 LUQU00000000 2651870266
SAR86 cluster gammaproteobacterium REDSEA-S20_B12N4 1.70 364 2043 38.32 c__Gammaproteobacteria (UID4201) 63.97 8.96 55.01 Red Sea water column Station 91 200 20.525 N 38.781 E PRJNA289734 SAMN04534650 LUQV00000000 2651870267
SAR86 cluster gammaproteobacterium REDSEA-S21_B7 1.52 187 1781 37.04 c__Gammaproteobacteria (UID4201) 75.21 2.87 72.34 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534651 LUQW00000000 2651870268
SAR86 cluster gammaproteobacterium REDSEA-S45_B6 1.57 123 1781 37 k__Bacteria (UID203) 83.07 6.58 76.49 Red Sea water column Station 192 500 27.897 N 34.507 E PRJNA289734 SAMN04534654 LUQZ00000000 2651870271
Sphingopyxis sp. REDSEA-S22_B5 3.06 103 3606 65.03 o__Sphingomonadales (UID3310) 98.03 0.73 97.3 Red Sea water column Station 108 10 22.046 N 37.929 E PRJNA289734 SAMN04534655 LURA00000000 2651870196
Sphingopyxis sp. REDSEA-S23_B6 3.24 118 3560 65.08 o__Sphingomonadales (UID3310) 96.02 0.34 95.68 Red Sea water column Station 108 25 22.046 N 37.929 E PRJNA289734 SAMN04534656 LURB00000000 2651870197
Sphingopyxis sp. REDSEA-S24_B7 1.75 439 2156 65.3 o__Sphingomonadales (UID3310) 52.05 1.47 50.58 Red Sea water column Station 108 50 22.046 N 37.929 E PRJNA289734 SAMN04534657 LURC00000000 2651870198
Sphingopyxis sp. REDSEA-S29_B3 3.46 43 3540 65.19 o__Sphingomonadales (UID3310) 98.64 0.68 97.96 Red Sea water column Station 149 25 23.604 N 37.054 E PRJNA289734 SAMN04534659 LURE00000000 2651870200
Sphingopyxis sp. REDSEA-S34_B10 1.75 399 2178 65.03 o__Sphingomonadales (UID3310) 50.93 0.76 50.17 Red Sea water column Station 169 10 25.772 N 36.116 E PRJNA289734 SAMN04534660 LURF00000000 2651870201
Sphingopyxis sp. REDSEA-S38_B16 2.14 337 2485 64.84 o__Sphingomonadales (UID3310) 68.27 3.72 64.55 Red Sea water column Station 169 200 25.772 N 36.116 E PRJNA289734 SAMN04534661 LURG00000000 2651870202
Sphingopyxis sp. REDSEA-S40_B6 3.45 73 3558 65.18 o__Sphingomonadales (UID3310) 97.42 0.51 96.91 Red Sea water column Station 192 10 27.897 N 34.507 E PRJNA289734 SAMN04534662 LURH00000000 2651870203
Sphingopyxis sp. REDSEA-S42_B3 2.91 11 3455 65.26 o__Sphingomonadales (UID3310) 99.64 0.34 99.3 Red Sea water column Station 192 50 27.897 N 34.507 E PRJNA289734 SAMN04534663 LURI00000000 2651870204
Synechococcus sp. REDSEA-S01_B1 1.80 78 2216 62.76 p__Cyanobacteria (UID2143) 95.92 0.82 95.1 Red Sea water column Station 12 10 17.662 N 40.905 E PRJNA289734 SAMN04534664 LURJ00000000 2651870193
Synechococcus sp. REDSEA-S02_B4 1.78 81 1724 62.76 p__Cyanobacteria (UID2143) 95.02 0.27 94.75 Red Sea water column Station 12 25 17.662 N 40.905 E PRJNA289734 SAMN04534665 LURK00000000 2651870194
Unclassified gammaproteobacterium REDSEA-S03_B5 1.17 129 1411 38.75 p__Proteobacteria (UID3880) 67.34 1.22 66.12 Red Sea water column Station 12 47 17.662 N 40.905 E PRJNA289734 SAMN04534682 LUSB00000000 2651870282
Unclassified gammaproteobacterium REDSEA-S08_B8 1.22 235 2798 51.01 p__Proteobacteria (UID3882) 55.59 0.61 54.98 Red Sea water column Station 22 200 17.996 N 39.799 E PRJNA289734 SAMN04534683 LUSC00000000 2651870283
Unclassified gammaproteobacterium REDSEA-S09_B13 2.28 371 4019 51.81 p__Proteobacteria (UID3880) 73.03 1.22 71.81 Red Sea water column Station 22 500 17.996 N 39.799 E PRJNA289734 SAMN04534684 LUSD00000000 2651870284
Unclassified gammaproteobacterium REDSEA-S12_B4 1.30 146 3073 38.79 p__Proteobacteria (UID3880) 71.75 4.27 67.48 Red Sea water column Station 34 50 18.58 N 40.743 E PRJNA289734 SAMN04534685 LUSE00000000 2651870285
Unclassified gammaproteobacterium REDSEA-S14_B7 2.48 348 1860 52.09 p__Proteobacteria (UID3880) 83.9 1.37 82.53 Red Sea water column Station 34 200 18.58 N 40.743 E PRJNA289734 SAMN04534686 LUSF00000000 2651870286
Unclassified gammaproteobacterium REDSEA-S15_B12 2.90 309 1677 52.01 p__Proteobacteria (UID3880) 89.74 1.93 87.81 Red Sea water column Station 34 258 18.58 N 40.743 E PRJNA289734 SAMN04534687 LUSG00000000 2651870287
Unclassified gammaproteobacterium REDSEA-S21_B8 2.72 374 3048 52.02 p__Proteobacteria (UID3880) 89.65 2.44 87.21 Red Sea water column Station 91 500 20.525 N 38.781 E PRJNA289734 SAMN04534688 LUSH00000000 2651870288
Unclassified gammaproteobacterium REDSEA-S26_B10 1.41 345 1799 52.17 p__Proteobacteria (UID3882) 54.2 1.88 52.32 Red Sea water column Station 108 200 22.046 N 37.929 E PRJNA289734 SAMN04534689 LUSI00000000 2651870289
Unclassified gammaproteobacterium REDSEA-S27_B14 1.43 327 1742 52.05 p__Proteobacteria (UID3880) 57.13 2.44 54.69 Red Sea water column Station 108 500 22.046 N 37.929 E PRJNA289734 SAMN04534690 LUSJ00000000 2654587903
Unclassified gammaproteobacterium REDSEA-S33_B15 1.53 372 1853 52.31 p__Proteobacteria (UID3882) 56 1.02 54.98 Red Sea water column Station 149 500 23.604 N 37.054 E PRJNA289734 SAMN04534691 LUSK00000000 2651870290
Unclassified gammaproteobacterium REDSEA-S45_B9 2.31 340 2626 51.86 p__Proteobacteria (UID3880) 70.43 2.03 68.4 Red Sea water column Station 192 500 27.897 N 34.507 E PRJNA289734 SAMN04534692 LUSL00000000 2651870291
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Phylogenomic analysis based on sets of single-copy marker genes universal to either the bacterial or archaeal domain showed that the 136 genomes encompassed seven phyla across these domains: Thaumarchaeota, Euryarchaeota, Actinobacteria, Cyanobacteria, Bdellovibrionaeota, Proteobacteria, and Marinimicrobia (Fig. 2 and Table 2 (available online only)). As expected, most of the recovered genomes were affiliated with known marine microorganisms such as phototrophic Prochlorococcus20,21 and Synechococcus22,23; representative of clades first discovered in the Sargasso Sea (SAR86, SAR116, SAR324 and SAR406)24–26; common marine bacteria in tropical biomes such as Alteromonas macleodii27; an ammonia oxidizing thaumarchaeon from the genus Nitrosopelagicus28; euryarchaeotal Marine Group II organisms reported to be abundant in surface waters29; members of the Alpha- and Gamma-proteobacteria such as Aeromicrobium, Erythrobacter, Maritimibacter, Idiomarina, Marinobacter, Candidatus Thioglobus (SUP05 cluster) and several unclassified Gammaproteobacteria, consistent with the high relative abundance of these two groups in the recent Tara Oceans survey30. Additionally, actinobacterial Acidiimicrobia and Nocardioides genomes thought to be responsible for secondary metabolite production in marine ecosystems31 were recovered from the metagenomes. An important strength of this dataset is the recovery of multiple, closely-related genomes from different stations or depths in the Red Sea (Data Citation 2). When complemented with physicochemical data1, genome plasticity between these organisms to confer fitness under varying conditions can be investigated in future studies.

To allow easy access to the genomes, all 136 genomes were functionally annotated and deposited into the National Centre for Biotechnology Information (NCBI) and Integrated Microbial Genomes (IMG) databases32. The wealth of metagenomic and genomic data described here greatly expands the repertoire of microbial genomic information from the Red Sea which might help to better understand the effects of global warming to ocean microbiomes. These datasets will also strengthen studies to better understand the drivers of marine nutrient cycling, help approaches for bioprospecting for novel thermo- and halo-philic enzymes, and allow for a better understanding of microbial adaptation strategies against high temperature, salinity and solar irradiance.

Methods

Metagenomic sequencing and assembly

Seawater samples were collected from eight stations and from different depths (10, 25, 50, 100, 200, and 500 m; locations are shown in Fig. 1) during summer as part of KRSE2011 (ref. 1). Genomic DNA was extracted from the 0.1–1.2 μm size fraction using an established phenol-chloroform extraction protocol1,33. Paired-end libraries (2×100 bp) were prepared using Nextera DNA Library Prep Kit (Illumina) and sequenced on a HiSeq 2000 (Illumina). Reads were quality checked and trimmed using PRINSEQ v0.20.4 (ref. 34) generating read lengths of ~93 bp and a total of ~10 million reads per sample with median insert sizes ranging from 183–366 bp1 (Data Citation 1). Trimmed metagenome reads were individually assembled (Table 1 (available online only)) using IDBA-UD v1.1.1 (ref. 35) using the ‘--pre-correction’ option. To obtain coverage profile of contigs from each metagenomic assembly, the trimmed reads were mapped back to contigs using BWA v0.7.12 (ref. 36) with the bwa-mem algorithm.

Genome binning, refinement, and annotation

For each metagenome, genome bins were recovered based on tetranucleotide frequencies and read coverage using MetaBAT v0.26.1 (ref. 37) with default parameters. The completeness and contamination of the bins were assessed using CheckM v1.0.3 (ref. 38) using the lineage-specific workflow (Table 2 (available online only)). Bins were further refined using the CheckM ‘merge’ and ‘outliers’ commands which merge bins with complementary sets of marker genes to improve completeness and remove contigs from bins which appear to be outliers relative to reference GC and tetranucleotide distributions in order to reduce contamination38. The FinishM v0.0.7 (https://github.com/wwood/finishm) ‘roundup’ workflow which comprise of ‘wander’ and ‘gapfill’ modes was used to scaffold contigs together and fill gaps within individual bins. The ‘wander’ mode uses a de Bruijn graph (kmer length of 51 bp and coverage cutoff of 5) to determine contig ends which are connected while the ‘gapfill’ mode align the reads to regions of ambiguous nucleotides and replaces them with the appropriate nucleotides. Genome bins that passed the quality filter of completion minus contamination of ≥50% were submitted to IMG/ER32 for gene calling and functional annotation.

Genome tree construction

The archaeal and bacterial genome trees (Fig. 2) were inferred from the concatenation of 122 and 120 proteins, respectively, identified as being present in ≥90% of the genomes in their respective domains and, when present, single-copy in ≥95% of genomes (Supplementary Tables 1 and 2). These marker genes were aligned using HMMER v3.1b1 (ref. 39) and the tree inference from the concatenated alignment with FastTree v2.1.7 (ref. 40) under the WAG+GAMMA models (Data Citation 2). Support values were determined using 100 non-parametric bootstrap replicates41. The archaeal tree was rooted with the DPANN (Diapherotrites, Parvarchaeota, Aenigmarchaeota, Nanohaloarchaeota, and Nanoarchaeota) superphylum in concordance with a recent large-scale phylogenomic study9 while the bacterial tree was ‘arbitrarily’ rooted with the phylum Chloroflexi42 but should be treated as unrooted. The trees were visualized in ARB43, annotated by iTOL44 and edited in Illustrator CC 2014 (Adobe).

Code availability

All versions of third-party software and scripts used in this study are described and referenced accordingly in the Methods sub-sections for ease of access and reproducibility.

Data Records

The raw Illumina sequencing paired-end reads (Table 1 (available online only)), 45 assembled metagenome sequences (Table 1 (available online only)) and 136 assembled genome sequences (Table 2 (available online only)), generated from the KAUST Red Sea Expedition 2011, are available from NCBI databases (Data Citation 1). The genome trees and associated fasta amino acid alignment files are available from Figshare (Data Citation 2).

Technical Validation

To validate the completeness and contamination of the genomes, we accessed the number of marker genes present in all bacterial and archaeal genomes using CheckM38. The genomes were also manually cleaned from vector contamination by comparing against the UniVec core database (ftp://ftp.ncbi.nlm.nih.gov/pub/UniVec/).

Usage Notes

The annotated genome assemblies can be downloaded and accessed via the Integrated Microbial Genomes (IMG) system (https://img.jgi.doe.gov/cgi-bin/m/main.cgi). The IMG genome IDs are provided in Table 2 (available online only).

Additional Information

How to cite this article: Haroon, M. F. et al. A catalogue of 136 microbial draft genomes from Red Sea metagenomes. Sci. Data 3:160050 doi: 10.1038/sdata.2016.50 (2016).

Supplementary Material

sdata201650-isa1.zip (4.5KB, zip)
Supplementary Tables
sdata201650-s2.doc (227.5KB, doc)

Acknowledgments

We acknowledge the people who were involved in the KAUST Red Sea Expedition 2011 and those that helped to generate the data, include, but are not limited to, those named here: Matt Cahill, Mamoon Rashid, Vinu Manikandan, David Ngugi and Ahmed Shibl. This work was supported by King Abdullah University of Science and Technology (KAUST), Saudi Basic Industries Corporation (SABIC) fellowship to L.R.T., and SABIC presidential chair to U.S.

Footnotes

The authors declare no competing financial interests.

Data Citations

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Citations

  1. Haroon M. F. 2015. National Center for Biotechnology Information (NCBI) BioProject database. PRJNA289734
  2. Haroon M. F. 2016. Figshare. https://dx.doi.org/10.6084/m9.figshare.3362899.v1

Supplementary Materials

sdata201650-isa1.zip (4.5KB, zip)
Supplementary Tables
sdata201650-s2.doc (227.5KB, doc)

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