Microbial Ecology of the OSIRIS-REx Assembly Test and ...Table 1: Sample Information Sample Exposure start Exposure stop Location ATLO Processes OR-CKP-01-1-A,0 3/11/2015 4/14/2015

Table 1: Sample Information

Sample Exposure

start Exposure

stop Location ATLO Processes OR-CKP-01-1-A,0 3/11/2015 4/14/2015 LM/Denver SRC assem. & funct. test; TAGSAM assem. w/ clean qual head OR-CKP-02-1-A,0 4/14/2015 5/11/2015 LM/Denver TAGSAM funct. Develop. OR-CKP-03-1-A,0 5/11/2015 6/10/2015 LM/Denver avionics box/SRC funct. Post-vibe; OR-CKP-04-1-A,0 6/12/2015 7/14/2015 LM/Denver SARA TVAC/launch container/ TAGSAM deploy. funct. Post-vibe/OVIRS/OTES OR-CKP-05-1-A,0 7/14/2015 8/19/2015 LM/Denver TAGSAM install, deploym. OR-CKP-06-1-A,0 8/19/2015 9/18/2015 LM/Denver OCAMS install/SARA deploym. OR-CKP-07-1-A,0 9/18/2015 11/4/2015 LM/Denver SARA deploym./move to RAL OR-CKP-08-1-A,0 11/4/2015 12/9/2015 LM/Denver RAL sine-vibe/move to SSB OR-CKP-09-1-A,0 12/9/2015 1/7/2016 LM/Denver REXIS OLA install/SC moved/shipping container OR-CKP-10-1-A,0 1/8/2016 2/5/2016 LM/Denver Flt. TAGSAM/SC to RAL/ EMI-EMC/TVAC pre-cert. OR-CKP-11-1-A,0 2/5/2016 3/16/2016 LM/Denver TVAC lid opened/SC to SSL/TVAC pumpdown/lid opened 3/10/move to SSB OR-CKP-12-1-A,0 3/6/2016 4/26/2016 LM/Denver launch container/SARA OR-CKP-13-1-A,0 4/26/2016 4/27/2016 LM/Denver TAGSAM flight install OR-CKP-14-1-A,0 4/27/2016 6/17/2016 KSC SARA deploym./Flight head test/KSC OR-CKP-15-1-A,0 6/17/2016 7/14/2016 KSC SRC battery enable/TAGSAM cleaning OR-CKP-16-1-A,0 7/14/2016 8/26/2016 KSC He load/prop tests/TAGSAM bottle loads/fuel sampling/cleaning&inspection/pack&ship preps OR-GCKP-17-1-A1 JSC/Goddard Shipping Blank ORX Faring Blank – FB - 18 KSC Fairing Blank ORX Fairing CK Fck – 19 KSC Fairing CK Swab Blank – Sb 20 JSC Kit Blank – Kb -21 JSC

Range of Bacterial and Archaeal OTU’s identified from JPL Space Craft Assembly Facility(Minich et al., 2018)

Bacteria and Archaea

Fungi1212

OSIRIS-REX | LUNAR AND PLANETARY SCIENCE CONFERENCE | MARCH 2019

A. B. Regberg1, C. L. Castro2, H. C. Connoly Jr.3, R. E. Davis4, J. P. Dworkin5, D. S. Lauretta6, S. R. Messenger1, F.M. McCubbin1, K. Righter1, S. E. Stahl2, S. L. Wallace7 1Astromaterials Research and Exploration Science Division, NASA Johnson Space Center, 2101 NASA Park-way, Houston TX 77058, 2JES Tech, 16870 Royal Crest, Houston, TX 77058,3Rowan University, Glassboro, NJ 08028, 4 Jacobs@NASA/Johnson Space Center, Houston, TX 77058, 5Astrochemistry Laboratory, Goddard Space Flight Center, Greenbelt, MD 20771, 6Lunar and Planetary Laboratory, University of Arizona, 1629 E University Blvd Tucson AZ 85721-0092, 7Biomedical Research and Environmental Sciences Division, Johnson Space Center, 2101 NASA Parkway, Houston TX 77058. Email: [email protected]

Microbial Ecology of the OSIRIS-REx Assembly Test and Launch Environment

Introduction

Methods

• Our goal is to characterize the microbes present during different phases of the OSIRIS–REx ATLO (Assembly Test Launch Operations)

• These data can inform future planetary protection controlled missions help to understand the relationship between organic an biological cleanliness

• We extracted DNA from 17 witness foils and two blanks originally intended for amino acid characterization

• We successfully amplified and sequenced DNA from bacteria, archaea, and fungi.

• We amplified the 16S ribosomal rRNA gene to identify bacteria and ar-chaea

• We amplified the ITS region to identify fungi• We were not able to sequence DNA from any other Eukaryotes.• The DNA amplification and sequencing techniques used had a detection

limit of ~7 bacterial cells.

Witness foil Samples

DNA extracted with a QIAamp BiOstic Bacteremia kit

16S rRNA Barcode Gene for Bacteria and Archaea v4 region, 515F-806R, 27Fmod-519Rmod (Caporaso et al. 2012; Walters et al. 2015)

ITS1 region for Fungi ITS1f-ITS2

DNA ampli�cation with PCR(Polymerase Chain Reaction)

DNA ampli�cation with PCR(Polymerase Chain Reaction)

DNA Sequencing Illumina MiSeq

(Dworkin et al., 2018)

DNA Extraction and Tag Sequencing

Detection Limit = 6.759 cellsDetection Limit = 5,611 reads

Sample Information

Known concentrations of Bacillus subtilus sequenced in order to deter-mine the detection limit for this sequencing run

• Only one 16S sample had too few sequences for further analysis

• 3 fungal samples had 0 reads

• It is common for the blanks and control samples to have relatively large numbers of DNA sequences

• The number of bacterial reads appears to increase with time

• The number of fungal reads is more variable

• Sample 11 (TVAC lid opened) and sample 12 (launch container) have highest number of 16S and fungal reads respectively

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• Bacterial and Archaeal diversity is relatively low compared to a similar aerospace clean room

• Fungal diversity appears to increase slightly with time

• Sample 4 had the highest 16S diversity, Sample 15 and the fairing sample had the highest fungal diversity

64

Bacillus subtilis subsp. subtilis strain 168 16S ribosomal RNA, complete sequence

Bacillus velezensis strain FZB42 16S ribosomal RNA, complete sequence

Bacillus nakamurai strain NRRL B-41091 16S ribosomal RNA, partial sequence

Bacillus pumilus strain SBMP2 16S ribosomal RNA gene, partial sequ...

Bacillus safensis strain NBRC 100820 16S ribosomal RNA gene, part...

Bacillus axarquiensis strain LMG 22476 16S ribosomal RNA gene, partial sequence

Bacillus halotolerans strain DSM 8802 16S ribosomal RNA, partial sequence

Bacillus mojavensis strain NBRC 15718 16S ribosomal RNA gene, partial sequence

Bacillus mojavensis strain ifo 15718 16S ribosomal RNA gene, partial sequence

Bacillus mojavensis strain NRRL B-14698 16S ribosomal RNA gene, partial sequence

Bacillus axarquiensis strain CR-119 16S ribosomal RNA gene, partial sequence

Bacillus malacitensis strain CR-95 16S ribosomal RNA gene, partial sequence

lcl|Query_55793

Bacillus mojavensis strain IFO15718 16S ribosomal RNA gene, partial sequence

0.002

Bacteria Firmicutes

Actinobacteria

Proteobacteria

Bacillus OTU matches several species

AscomycotaBasidiomycota

Fungi

• Fungal DNA is relatively distinct for each sample

• Sample 12 (launch container) is dominated by Cladosporium delicatum, a saprophytic fungi

• Sample 16 is dominated by Zymoseptoria a genus containing plant pathogens

• Sample 13 (TAGSAM flight install) is dominated by the an unidentified Meruleacieae the family responsible for lignin degra-dation

• Unique organisms from the faring

• Udenimyces pyricola (yeast)

• Itersonilia pannonica (plant associated fungi)

• Articulospora proliferate (aquatic fungi)

• Phaeosphaeria caricola (plant fungi)

Results

• Only sample 13 had archaeal DNA

• Firmicutes is the dominant bacterial phyla

• This includes common clean room and human associated or-ganisms like Bacillus, Lactobacillus, Listeria and Staphylococcus

• Sample 11 is dominated by Micrococcus a type of human associ-ated actinobacteria

• Sample 19 (Fairing) appears to be different, dominated by mito-chondrial DNA from an Oomecyte (water mold)

P-value:0.0119474Equation: ln(Fungal Swab Sequences) = 5.64776*% Fe + 6.88946P-value:0.0034466

Equation: ln(Fungal Swab Sequences) = -6.09474*% C + 10.518

Conclusions

• We successfully sequenced bacterial and fungal DNA from clean room wit-ness coupons demonstrating that these types of samples can be useful for biological contamination knowledge

• Witness coupons from the TVAC testing and from the rocket fairing had distinct microbial communities

• The abundance of fungal sequences may correlate to the amount of carbon and iron bearing particles from replicate witness plates.

• Further data analysis is ongoing• Dedicated biological contamination knowledge samples should be routine-

ly collected for missions where biology could affect mission requirements e.g. Mars2020, Europa Clipper

• DNA sequences were quality filtered, trimmed analyzed using the QIIME software package.

• We utilized the Deblur pipeline to identify 100% unique OTU’s (Operational Taxonomic Units)

• OTU’s were identified using the Silva v132 database for bacteria and archaea and the UNITE database for fungi.

Quality Control and OTU clustering

Taxonomy

Bioinformatics

• There are weak relationships between the % of carbon particles and iron particles identified on witness plates and the number of fungal sequences

• There are no clear relationships between the sequencing data and the measured amino acid concentrations

References

Assuming an average of 5.14 fg of DNA per cell (Blattner et al. 1997), this is a detection limit of approximately 34 fg of DNA

Amir, Amnon et al. 2017. “Deblur Rapidly Resolves Single-Nucleotide Community Sequence Patterns.” MSystems 2(2):e00191-16.Auchtung, Jennifer M. et al. 2015. “Cultivation of Stable, Reproducible Microbial Communities from Different Fecal Donors Using Minibioreactor Arrays (MBRAs).”

Microbiome 3(1):42.Blattner, Frederick R. et al. 1997. “The Complete Genome Sequence of Escherichia Coli K-12.” Science 277(5331):1453–62.Caporaso, J. Gregory et al. 2010. “QIIME Allows Analysis of High-Throughput Community Sequencing Data.” Nature Methods 7(5):335–36.Caporaso, J. Gregory et al. 2012. “Ultra-High-Throughput Microbial Community Analysis on the Illumina HiSeq and MiSeq Platforms.” The ISME Journal 6(8):1621–24.Dworkin, J. P. et al. 2018. “OSIRIS-REx Contamination Control Strategy and Implementation.” Space Sci Rev 214(9).Minich, Jeremiah J. et al. 2018. “KatharoSeq Enables High-Throughput Microbiome Analysis from Low-Biomass Samples” edited by M. J. McFall-Ngai. MSystems

3(3):e00218-17.Nilsson, Rolf Henrik et al. 2018. “The UNITE Database for Molecular Identification of Fungi: Handling Dark Taxa and Parallel Taxonomic Classifications.” Nucleic Acids

Research.Quast, Christian et al. 2012. “The SILVA Ribosomal RNA Gene Database Project: Improved Data Processing and Web-Based Tools.” Nucleic Acids Research

41(D1):D590–96..

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