Three deep-sea deployments of “Phoenix” lander equipped with MISNAC were conducted in May, 2019. The sampling started 30 min after the landing of the lander, and video record showed clearance of turbidity plume by bottom water current. All the sampling tools and sensors were at least one meter over the seafloor. Six working units of MISNAC in “Phoenix” deployment No. 21 (hereafter FH21-5 to FH21-10) were used to filter bottom waters for about 1 h and in situ collect nucleic acids at sites in depth of about 1 000 m in the SCS (17°31.337'N, 110°27.522'E) (Table 1 and Fig. S1). Before the start of the fourth working unit, a plastic bag was filled up with 40 L sea water at speed of 500 mL/min for 80 min by an ISMIFF. The bag had been carefully cleaned with 1 L 70% ethanol and subsequently distilled water to avoid contamination before the experiment. Approximate 40 mL 100 mmol/L NaHCO₃ was injected into the bag for cultivation of 40 min. Such NaHCO₃ concentration would not result in precipitation at 4℃. The seventh working unit was initiated after the cultivation to filter the microbes from the cultivation in the plastic bag on a 0.22 μm membrane (Millipore, Bedford, MA, USA) in the filtration chamber, followed by cell lysis, nucleic acids precipitation and collection controlled by MISNAC (Fig. 1). After the lander was recalled on board, the polymer columns of seven working units were immediately collected and washed with distilled water by centrifuge at 4 000 r/min (Xiangrui, Changsha, China). The quality and quantity of the nucleic acids were measured by Qubit 2.0 fluorometer before storage of the extractions in −20℃ on board until further processing. A 10 L Niskin bottle was used to collect bottom waters at the same sites in “Phoenix” deployments No. 18 and No. 22 (FH18-N; FH22-N). Ten liter water samples were filtered through 0.22 μm membrane (Millipore, Bedford, MA, USA) immediately in the laboratory of the vessel. The membranes were stored in −20℃.

A CO₂ sensor (Pro-Oceanus, Bridgewater, NS, Canada) and conductivity, temperature and depth instrument (Sea-Bird, Bellevue, WA, USA) carried by the lander were used to monitor environmental changes during the deployments.

Genomic DNA of Niskin samples was extracted from the filtration membranes using MO BIO Powersoil DNA isolation kit (Qiagen, Carlsbad, CA, USA). The quality and quantity of the extractions were checked by Qubit 2.0 fluorometer. RNA in the nucleic acids collected by MISNAC was digested with RNaseA (TaKaRa, Dalian, China) with a final concentration of 0.1 ng/μL for 1 h in 37℃ incubation. The V3−V4 regions were targeted to amplify 16S rRNA gene fragments with a set of universal primers 341F (5'-CCTAYGGGRBGCASCAG-3') and 802R (5'-TACNVGGGTATCTAATCC-3') (Wang and Qian, 2009) using 1 ng DNA as template. The PCR conditions of 16S rRNA amplification were as following: initial denaturation at 98℃ for 10 s; 30 cycles of denaturation at 98℃ for 10 s, annealing at 50℃ for 15 s, and extension at 72℃ for 30 s; and a final extension at 72℃ for 5 min. The amplicons were used for library preparation with TruSeq Nano DNA LT kit (Illumina, San Diego, USA) and were then sequenced on an Illumina Miseq platform for 2×300 bp paired-end sequencing (Illumina, San Diego, USA).

The sequencing data of 16S rRNA gene amplicons were evaluated using FASTQC (v0.11.8) (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and merged by join_paired_ends.py integrated in QIIME 1 workflow (Caporaso et al., 2010). The adaptors and low-quality reads were removed by NGS QC Toolkit (v2.3.3) (Patel and Jain, 2012). The sub-libraries for barcoded amplicon reads were trained by emp in QIIME 1 to standardize the original files into a format for QIIME 2 processing (Bolyen et al., 2019). The deblur method was employed for accusation process. All the data were merged using merge model in QIIME 2. Amplicon sequence variants (ASVs) were selected at 97% similarity between the qualified reads. Taxonomic classification of the ASVs was accomplished with Vsearch v2.15.0 (Rognes et al., 2016) at 97% similarity against with SILVA database (132) (Quast et al., 2013). Principal Coordinates Analysis (PCoA) of the microbial communities at genus level was performed using vegan in R package (Dixon, 2003). The raw data of amplicon reads were deposited in NCBI database under accession number of PRJNA734086.

The representative sequence of an ASV was used for construction of a maximum-likelihood phylogenetic tree. Reference 16S rRNA sequences of the closest relatives were downloaded from NCBI. All the sequences were aligned with MAFFT (v.7.407) (Katoh and Standley, 2013) and optimized with trimAl (v.1.4) (Capella-Gutiérrez et al., 2009). RAxML (v.8.2.12) (Stamatakis, 2014) was used to build a 16S rRNA phylogenetic tree (GTRGAMMA model) with bootstrap values based on 1 000 replicates. The phylogenetic tree was visualized by iTOL (Letunic and Bork, 2007).

The temperature of the sampling site and bicarbonate cultivation was about 4.4℃ and dissolved CO₂ was (984±169)×10⁻⁶ ((22.36±3.84) μmol/L) of the deep-sea sites in May of 2019. The depth of the site for MISNAC sampling and cultivation was 1 030 m. Genomic DNA of the deep-sea microbes was collected by MISNAC and Niskin bottle, separately. Six working units (FH21-5 to FH21-10) were used to collect nucleic acids from 10:00 pm of May 22 to 8:00 am of 23, each lasting one hour to filter about 30 L water. Two samplings by Niskin bottle (FH18-N and FH22-N) were carried out on May 21 and 24, respectively. In situ cultivation with addition of NaHCO₃ at a final concentration of 0.1 mmol/L was conducted within a 40 L plastic bag (FH21-C), followed by in situ nucleic acids extraction in the last working unit of MISNAC (Fig. 1). A part of the ${\rm{HCO}}_3^- $ would be precipitated by Ca²⁺ and Mg²⁺ ions in the natural sea water (Li and Tsui, 1971), while the extra ${\rm{HCO}}_3^- $ would change the equilibrium of CO₂ and ${\rm{HCO}}_3^- $. In this study, we could not calculate the exact increase of CO₂ level in the cultivation bag, since a CO₂ sensor could not be set up in the cultivation bag. Considering the average dissolved CO₂ (~0.22 μmol/L) in the deep waters, the addition of 0.1 mmol/L ${\rm{HCO}}_3^- $ (if fully transformed to CO₂) might result in four-fold increment of CO₂ concentration in the cultivation.

Using Illumina high-throughput sequencing of 16S rRNA gene amplicons, we obtained 19 478 qualified amplicon reads for the nine samples (Table S1). For the cultivation sample FH21-C, 2 673 qualified reads were grouped into 245 ASVs. Rarefaction curves of the observed ASVs showed that the sequencing depth is not sufficient to capture all the species in the samples (Fig. S2), but the detection of microbial communities was not affected by the sequencing depth (see below). Chao1 as an estimate of biodiversity factor showed the lowest biodiversity of the cultivation sample (Table S1), suggesting the bicarbonate cultivation simplified the microbial consortia. The different samples (from FH21-5 to FH21-10) collected by working units of MISNAC demonstrated differences in diversity estimates, suggesting variations of microbial communities driven by deep-sea environmental changes such as oxygen and sinking organic matter flux. The microbial communities of this study differed notably from those in the samples collected by MISNAC in June–July of 2018 (Wei et al., 2020b). Particularly, the percentage of Proteobacteria and Euryarchaeota increased, while Nanoarchaeota and Omnitrophicaeota were also absent from the communities in this study, compared with the previous study conducted at the same area (Wei et al., 2020b). Our result indicates strong dynamics of deep-sea microbial communities in the deep-sea zones of the SCS.

The classification of the amplicon reads of the present study demonstrated the highest relative abundance of Proteobacteria in all the samples (Fig. S3 and Table S2). For the MISNAC samples, there were also high relative abundances of Euryarchaeota, Chloroflexi and Bacteroidetes, which were almost absent in the Niskin (FH18-N and FH22-N) and cultivation (FH21-C) samples. Variations in community structures were also exhibited among the MISNAC samples. Decrease of Proteobacteria and increase of Actinobacteria and Planctomycetes were obvious between PH21-6 and PH21-7, suggesting a microbial compositional change occurred within early morning time periods. Despite the small number of sequencing reads (<1 000) for PH21-5 and PH21-8, the microbial community structures of the two samples resembled those of other MISNAC samples.

At genus level, taxonomic classification showed enrichment of Alteromonas, Hirschia, Nocardioides, Ilumatobacter and Saccharimonadales. Most of these bacterial genera were also abundant in one of Niskin samples except for Hirschia. In contrast, some common marine genera such as SAR202, SAR406, Marine group II, and SAR324 in the MISNAC samples were dramatically low in microbial communities of the Niskin and cultivation samples (Fig. 2 and Table S3). These differences in community structures were further illustrated by PCoA, which showed clustering of MISNAC samples and a large separation distance between the Niskin and cultivation samples in 2-D plotting of axes 1 and 2 (Fig. 3). Rapid growth of autotrophic microbes stimulated by bicarbonate addition might result in lower proportion of the SAR202, SAR406 and SAR324 in the community. Limited accession to detrital organic matter and lowering oxygen for respiration for the degradation probably prohibited metabolism and growth of heterotrophic SAR202, SAR406 and SAR324 (Sheik et al., 2014; Huang and Wang, 2020; Wei et al., 2020a) in the Niskin and cultivation bag. The two Niskin samples were obtained at different time points and lander deployments (Table 1), which may partially explain the discrepancy in community structure. The genera of Alteromonas and Pseudoalteromonas accounted for 79.50% of the PN22-N sample, which agrees with the predominance of Alteromonas in some samples of marine water column (Quaiser et al., 2011; Li et al., 2019) and in situ ¹⁴C-labeled bicarbonate cultivation in Niskin bottle (Yakimov et al., 2014). This is, however, due to a possible impact of environmental changes during the Niskin sampling and filtration onboard on the microbial community. The closest relatives of the Alteromonas in the NCBI were Alteromonas macleodii (identity 98.68%; 99% length coverage) and Alteromonas marina (identity 98.68%; 99% length coverage). A previous study showed a deep-sea Alteromonas ecotype was adaptive to microaerophilic conditions (Ivars-Martinez et al., 2008). In this study, we did not monitor the changes of dissolved oxygen concentration in the Niskin bottle and cultivation bag, and therefore cannot preclude the possible causal effect of low oxygen on the prevalence of Altermonas in the Niskin and cultivation samples. The percentage of Ilumatobacter in the cultivation sample and FH18-N was 2.05% and 0.82%, respectively. The representative sequence of the most abundant Ilumatobacter ASV was 99.30% similar to the 16S rRNA gene of Ilumatobacter fluminis isolated from coastal sediment with an unknown ecological function (Matsumoto et al., 2009). The ASV representing Saccharimonadales of Patescibacteria could not be further classified in SILVA database and was abundant in both the cultivation and FH18-N (11.47% and 6.99%, respectively). However, a parasitic bacterium “Candidatus Mycosynbacter amalyticus” (96.92% similar to the representative sequence of the ASVs for Saccharimonadales) was recently identified in a bioreactor and had been used to control bacteria responsible for foam formation (Batinovic et al., 2021). An uncultured strain (GenBank accession LT856719: 99% identity), a relative of the Saccharimonadales bacteria in our cultivation, enables to convert CO₂ and organic substrates into useful chemicals in a bioreactor. There were also other Saccharimonadales relatives detected in deep sea zones. As these Saccharimonadales have been applied to industrial biosynthesis with CO₂, we propose that the Saccharimonadales bacteria in our study were probably fueled by addition of bicarbonate for the cultivation experiment (Batinovic et al., 2021). In Niskin bottle, respiration of some heterotrophic microbes using organic matter in deep water might have produced CO₂ to nourish Saccharimonadales in FH18-N. On the other hand, considering their possible parasitic lifestyle, the Saccharimonadales bacteria in our cultivation were likely prevalent along with enrichment of other bicarbonate-stimulated bacteria. In the MISNAC samples, Saccharimonadales occupied 0.06%–0.18% of the MISNAC samples, indicating at least 64-fold enrichment by the in situ cultivation. This remarkable discrepancy in microbial community structures between the Niskin and MISNAC samples raises the issue regarding reliability of deep-sea metagenomics depending on traditional sampling methods. For deep-sea hydrothermal vents, in situ sampling and filtration were preferred to display spatial and temporal variations of microbial inhabitants (Perner et al., 2009, 2013). Although deep-sea waters are not as extreme as hydrothermal vents with anoxic condition and high temperature, the present studies also showed temporal differences in microbial communities among MISNAC samples and between MISNAC and Niskin samples. To capture the temporal variations of the microbial communities and determine the driving forces require future efforts for long-term in situ detection in deep ocean.

The relative abundance of Hirschia was 7.64%, much higher than that in other samples (0.9% in FH18-N and 0–0.07% in MISNAC samples) (Fig. 2). This suggests the Hirschia species was most likely activated and enriched by bicarbonate addition. However, the representative 16S rRNA amplicon of Hirschia ASV was only 91.98% to that of known species Hirschia baltica. To confirm the taxonomic assignment, we constructed a phylogenetic tree using the representative sequence of the Hirschia ASV and reference 16S rRNA sequences to determine its phylogenetic position. The tree topology exhibited that the Hirschia ASV was far from Hirschia species (Fig. 4) and stayed in an independent branch consisting of Asprobacter aquaticus and uncultured strains from forest soil, sludge, plant root and marine sediment. Although most of the strains within the Asprobacter clade were not isolated from marine environments, the most adjacent sequences were originated from marine hot spring and Baltic Sea sediment. Moreover, the ASV displayed a considerable phylogenetic distance with the Asprobacter relatives, indicating that the Asprobacter bacteria in this study had not been widely detected in deep waters, perhaps due to their low relative abundance in natural deep marine zones. The only cultivated species of the clade is A. aquaticus. High similarity (98.11%) of our Asprobacter ASV to that of A. aquaticus suggests that the Asprobacter of this study was probably a new strain of A. aquaticus (Edgar, 2018). Asprobacter as a novel genus in Hyphomonadaceae was proposed recently with respect to cultivation and characterization of A. aquaticus (Jin et al., 2017). However, currently our knowledge on A. aquaticus was restricted to its cell membrane component and aerobic respiration. How the A. aquaticus was stimulated by the bicarbonate incubation remains a question.