Bacterial microbial load and community structure of drinking water used in the International Space Station

PWD water sampling in the ISS

On January 8, 2021, an astronaut collected 350ml of drinking water from the PWD on the United States Orbiting Segment (USOS) of the ISS into NASA’s post-flight analysis bag. It is made of fluorinated ethylene propylene (FEP) with female polypropylene Luer Lock ports and is used for NASA water sample collection and analysis. The ISS drinking water sample bag was loaded onto the SpaceX cargo dragon capsule CRS-21 (SpX-21), which crashed in the Gulf of Mexico on January 14, 2021 and was transported at NASA’s Kennedy Space Center (KSC) at room temperature. After arriving at KSC, the bag was stored at 4°C and transported from KSC to Tsukuba Space Center, JAXA, Japan, arriving on January 21, 2021. Ground control water was prepared in our laboratory by collecting ultrapure water in the same bag at the same time as the PWD water sample and was stored under the same conditions until measurement.

Total direct count and CFU count

The bacteria present in the PWD water were filtered through a black polycarbonate filter (0.2 µm pore size, ADVANTEC). The filters were rinsed twice with bacteria-free distilled water. Then 1 µg/ml DAPI in distilled water or 150 µg/ml 6-CFDA in phosphate buffer (0.3 M phosphate (pH 8.5), 15% NaCl, 1.5 mM EDTA) was applied to the filters and incubated for 3 min at room temperature in the dark. Filters were rinsed twice, mounted on glass microscope slides with non-fluorescent immersion oil, and examined using an epifluorescence microscope (DM2500, Leica Microsystems) with a water immersion objective. ‘oil. CFU counts were determined by streaking diluted ISS drinking water on BD TSA and BD BBL R2A agar plates (Becton, Dickinson and Company), which were incubated for one week prior to counting at 30°C and 22 °C, respectively.

MALDI-TOF MS spectrometry for the identification of isolated bacteria

A MALDI-TOF MS was used for the direct identification of bacteria cultured on TSA and R2A agar24. 18 and 20 isolated colonies of TSA and R2A were streaked on the MALDI MSP 96 polished steel target plate. One microliter of 70% formic acid was deposited on each sample point and allowed to dry. Then, 1 µL of matrix solution (α-cyano-4-hydroxycinnamic acid (Bruker Daltonics) dissolved in 50% acetonitrile, 47.5% water and 2.5% trifluoroacetic acid) was applied to each sample point and left to dry. Bruker Bacterial Test Standard, Escherichia coli DH5α was used for calibration. The measurements were carried out with a Microflex mass spectrometer (Bruker Daltonics) using the software flexControl version 3.4. Mass spectra were acquired in a linear positive extraction mode ranging from 2000 to 20,000 Da. Spectra were analyzed using MALDI Biotyper 3.1 software with Bruker BDAL Ver library. 6 and Filamentous Fungi Library Ver. 1.0 (Bruker Daltonics). A manufacturer-recommended cutoff score was used for identification (Supplementary Table 2).

Counting Bacterial Cells Using a Biofluorescent Particle Counter

A commercially available biofluorescent particle counter (XL-10BT1, Rion Co. Ltd.) was used in this study. It had two detectors. One was a photodiode to measure the intensity of scattered light, which indicates particle size. The other was a photomultiplier tube to measure autofluorescence intensity, which is an indicator of the physiological activity of bacteria. This made it possible to simultaneously measure the intensity of scattered light and the intensity of autofluorescence.

We have developed a protocol to measure bacterial cells without staining using the biofluorescent particle counter, identifying particles emitting autofluorescence from flavin and counting them as bacterial cells. Flavin is a ubiquitous pigment in bacterial cells, which emits autofluorescence at 510 nm when irradiated with 405 nm excitation light25. The amount of intracellular flavin is closely related to the physiological activity of bacteria25, and thus bacteria with low physiological activity may not be detected due to low autofluorescence intensities. To solve this problem, we irradiated particles with deep UV irradiation, at a wavelength of 254 nm or two wavelengths of 185 nm and 254 nm, to oxidize flavin and improve the intensity of the autofluorescence immediately before measurement under irradiation at 405 nm, which was performed using a deep UV irradiation apparatus (XL-28A, RION Co. Ltd.) equipped with a low pressure mercury lamp . Since deep UV irradiation is known to degrade organic carbon26.27, deep UV irradiation incorporated into our bacterial cell counting protocol was also used to reduce dissolved organic carbon signals in PWD water. Particle counting was performed at a flow rate of 10 mL/min and a measurement time of 60 s. The deep UV irradiation dose was greater than 1000 mJ/cm2. Prior to measuring bacterial cells, ultrapure water was used to set a cutoff for electrical noise derived from the biofluorescent particle counter, which was determined to be 133 mV. To exclude particles with extremely high autofluorescence intensity from being counted as bacteria, the upper threshold was set to 1200 mV when counting bacterial cells.

DNA extraction

Bacterial cells present in 50 ml of PWD water were trapped on an autoclaved polycarbonate membrane filter (0.2 μm pore size; Advantec, Tokyo, Japan). Bacterial DNA was extracted with the method described in Ichijo et al..2. The DNA was finally eluted with 50 µL of TE buffer.

Amplicon sequencing of the bacterial 16S rRNA gene by the ONT MinION platform

Sequencing of amplicons targeting the full length of the 16S rRNA gene was performed using MinION equipped with an R9.4.1 flow cell (Oxford Nanopore Technologies, Oxford, UK). A 16S rRNA sequencing library was constructed from 10 µL of DNA extracted using the 16S barcoding kit (Oxford Nanopore Technologies). Library construction was performed according to the manufacturer’s instructions except that DNA amplification was performed using KAPA HiFi HotStart ReadyMix (KAPA Biosystems, MA, USA) with the following thermal cycling conditions: 2 min at 95°C, 25 cycles of 20 s at 98°C, 30 s at 60°C and 2 min at 72°C and 5 min at 72°C. Sequencing was performed with Oxford’s MinKNOW software Nanopore and basic calls were made with Guppy (v. 4.3.4) in fast mode using the dna_r9.4.1_450bps_fast.cfg configuration file. The generated FASTQ files were further analyzed for taxonomic classification using the cloud-based EPI2ME FASTQ 16S workflow with a quality score of ≥7 for quality filtering.

Amplicon sequencing of the bacterial 16S rRNA gene by the Illumina MiSeq and iSeq platforms

Sequencing of amplicons targeting the V4 region of the 16S rRNA gene was performed using the MiSeq 300 bp paired-end platform with MiSeq Reagent Kit v2 and the 150 bp paired-end iSeq platform with the iSeq 100 i1 reagent (Illumina, CA, USA). A two-step PCR was performed to construct paired libraries. In the first PCR, the V4 region of the prokaryotic 16S rRNA gene was amplified from the DNA sample using primers F515 and R80628 with Illumina cantilever adapters. Initial PCR reactions were performed in triplicate in a 12 µL reaction volume containing 3 µL of template and 0.6 µM forward and reverse primers in 1 × KAPA HiFi HotStart ReadyMix (KAPA Biosystems) using thermal cycling 2 min at 95°C, 35 cycles of 20 s at 98°C, 15 s at 60°C and 30 s at 72°C and 5 min at 72°C. Triplicate PCR products were pooled and purified using Agencourt AMPure XP (Beckman Coulter, CA, USA) according to manufacturer’s instructions. A second PCR (12 cycles) was performed to attach dual indexes and Illumina sequencing adapters to the first PCR products purified using the Nextera XT Index Kit v2 Set C (Illumina). Finally, indexed amplicons were purified by electrophoresis using E-Gel SizeSelect II agarose gels (Thermo Fisher Scientific, MA, USA). DNA concentrations of indexed amplicons were quantified by a Qubit 4 fluorometer using the dsDNA HS assay kit (Thermo Fisher Scientific) and pooled in equal amounts for library construction. The library was diluted to 1 nM and spiked with 20% PhiX Control v3 (Illumina), then diluted to 50 pM, loaded into MiSeq and iSeq cartridges, and sequenced according to manufacturer’s instructions.

FASTQ files generated from MiSeq and iSeq sequencing were analyzed separately using the QIIME 2 pipeline29 (version 2021.8). Sequence denoising, paired-read merging, and chimera filtering were performed using DADA2’s qiime dada2 denoise-paired method.30.31 plugin in QIIME 2, where parameters have been adjusted from default values ​​for MiSeq and iSeq data as follows: –p-trim-left-f 19, –p-trim-left-r 20, –p-max -ee-f 1.0, and –p-max-ee-r 1.0. In addition to these adjustments, the -p-trunc-len-f and -p-trunc-len-r parameters were adjusted to 263 and 226 for the MiSeq data to truncate the forward and backward readings at the position with a score lower median quality greater than 30. For iSeq data, the forward and reverse readings were not truncated. The –p-min-overlap parameter, which controls the minimum overlap required to merge paired reads, has been reduced from the default (12) to 5 to allow merging. The non-chimeric sequences obtained, called amplicon sequence variants (ASV), were assigned to taxonomic groups using ‘qiime feature-classifier classify-sklearn’31 using a pre-trained naive Bayes classifier on the Silva 138 99% database32 for the 515F/806R region of 16S rRNA (silva-138-99-515-806-nb-classifier.qza) with a confidence level of 0.985.

About Walter J. Leslie

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