Since the 1970s, the Planetary Protection Group at the Jet Propulsion Laboratory (JPL) has maintained an archive of spacecraft-associated bacterial isolates. Identification of these isolates was routinely performed by sequencing the 16S rRNA gene. Although this technique is an industry standard, it is time consuming and has poor resolving power for some closely related taxa. Matrix-assisted laser desorption/ionization time of flight (MALDI-TOF) mass spectrometry is widely used in clinical diagnostics and is a promising method to substitute standard 16S rRNA sequencing. However, manufacturer-provided databases lack the bacterial diversity found in spacecraft-assembly cleanrooms. This study reports the development of the first custom database of MALDI-TOF MS profiles of bacterial isolates obtained from spacecraft and associated cleanroom environments. With the use of this in-house database, 454 bacterial isolates were successfully identified in concurrence with their 16S rRNA sequence-based classifications. Additionally, MALDI-TOF MS resolved strain-level variations, identified potential novel species and distinguished between members of taxonomic groups, which is not possible using conventional 16S rRNA sequencing. MALDI-TOF MS has proved to be an accurate, high-throughput approach for real-time identification of bacterial isolates during the spacecraft assembly process.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019, is a respiratory virus primarily transmitted person to person through inhalation of droplets or aerosols, laden with viral particles. However, as recent studies have shown, virions can remain infectious for up to 72 h on surfaces, which can lead to transmission through contact. Thus, a comprehensive study was conducted to determine the efficiency of protocols to recover SARS-CoV-2 from surfaces in built environments. This end-to-end (E2E) study showed that the effective combination for monitoring SARS-CoV-2 on surfaces includes using an Isohelix swab collection tool, DNA/RNA Shield as a preservative, an automated system for RNA extraction, and reverse transcriptase quantitative PCR (RT-qPCR) as the detection assay. Using this E2E approach, this study showed that, in some cases, noninfectious viral fragments of SARS-CoV-2 persisted on surfaces for as long as 8 days even after bleach treatment. Additionally, debris associated with specific built environment surfaces appeared to inhibit and negatively impact the recovery of RNA; Amerstat demonstrated the highest inhibition (>90%) when challenged with an inactivated viral control. Overall, it was determined that this E2E protocol required a minimum of 1,000 viral particles per 25 cm2 to successfully detect virus from test surfaces. Despite our findings of viral fragment longevity on surfaces, when this method was employed to evaluate 368 samples collected from various built environmental surfaces, all samples tested negative, indicating that the surfaces were either void of virus or below the detection limit of the assay. IMPORTANCE The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) (the virus responsible for coronavirus disease 2019 [COVID-19]) pandemic has led to a global slowdown with far-reaching financial and social impacts. The SARS-CoV-2 respiratory virus is primarily transmitted from person to person through inhalation of infected droplets or aerosols. However, some studies have shown that virions can remain infectious on surfaces for days and can lead to human infection from contact with infected surfaces. Thus, a comprehensive study was conducted to determine the efficiency of protocols to recover SARS-CoV-2 from surfaces in built environments. This end-to-end study showed that the effective combination for monitoring SARS-CoV-2 on surfaces required a minimum of 1,000 viral particles per 25 cm2 to successfully detect virus from surfaces. This comprehensive study can provide valuable information regarding surface monitoring of various materials as well as the capacity to retain viral RNA and allow for effective disinfection.

NASA planetary protection (PP) requires an assessment of the biological contamination of the potential microbial burden on spacecraft destined to explore planetary bodies that may harbor signs of life, like Mars and Europa. To help meet these goals, the performance of multiple metagenomic pipelines were compared and assessed for their ability to detect microbial diversity of a low-biomass clean room environment used to build spacecraft destined to these planetary bodies. Four vendors were chosen to implement their own metagenomic analysis pipeline on the shotgun sequences retrieved from environmental surfaces in the relevant environments at NASA’s Jet Propulsion Laboratory. None of the vendors showed the same microbial profile patterns when analyzing same raw dataset since each vendor used different pipelines, which begs the question of the validity of a single pipeline to be recommended for future NASA missions. All four vendors detected species of interest, including spore-forming and extremotolerant bacteria, that have the potential to hitch-hike on spacecraft and contaminate the planetary bodies explored. Some vendors demonstrated through functional analysis of the metagenomes that the molecular mechanisms for spore-formation and extremotolerance were represented in the data. However, relative abundances of these microorganisms varied drastically between vendor analyses, questioning the ability of these pipelines to quantify the number of PP-relevant microorganisms on a spacecraft surface. Metagenomics offers tantalizing access to the genetic and functional potential of a microbial community that may offer NASA a viable method for microbial burden assays for planetary protection purposes. However, future development of technologies such as streamlining the processing of shotgun metagenome sequence data, long read sequencing, and all-inclusive larger curated and annotated microbial genome databases will be required to validate and translate relative abundances into an actionable assessment of PP-related microbes of interest. Additionally, the future development of machine learning and artificial intelligence techniques could help enhance the quality of these metagenomic analyses by providing more accurate identification of the genetic and functional potential of a microbial community.

Background Clean rooms of the Space Assembly Facility (SAF) at the Jet Propulsion Laboratory (JPL) at NASA are the final step of spacecraft cleaning and assembly before launching into space. Clean rooms have stringent methods of air-filtration and cleaning to minimize microbial contamination for exoplanetary research and minimize the risk of human pathogens, but they are not sterile. Clean rooms make a selective environment for microorganisms that tolerate such cleaning methods. Previous studies have attempted to characterize the microbial cargo through sequencing and culture-dependent protocols. However, there is not a standardized metagenomic workflow nor analysis pipeline for spaceflight hardware cleanroom samples to identify microbial contamination. Additionally, current identification methods fail to characterize and profile the risk of low-abundance microorganisms. Results A comprehensive metagenomic framework to characterize microorganisms relevant for planetary protection in multiple cleanroom classifications (from ISO-5 to ISO-8.5) and sample types (surface, filters, and debris collected via vacuum devices) was developed. Fifty-one metagenomic samples from SAF clean rooms were sequenced and analyzed to identify microbes that could potentially survive spaceflight based on their microbial features and whether the microbes expressed any metabolic activity or growth. Additionally, an auxiliary testing was performed to determine the repeatability of our techniques and validate our analyses. We find evidence that JPL clean rooms carry microbes with attributes that may be problematic in space missions for their documented ability to withstand extreme conditions, such as psychrophilia and ability to form biofilms, spore-forming capacity, radiation resistance, and desiccation resistance. Samples from ISO-5 standard had lower microbial diversity than those conforming to ISO-6 or higher filters but still carried a measurable microbial load. Conclusions Although the extensive cleaning processes limit the number of microbes capable of withstanding clean room condition, it is important to quantify thresholds and detect organisms that can inform ongoing Planetary Protection goals, provide a biological baseline for assembly facilities, and guide future mission planning.

A Gram-stain-positive, motile, endospore-producing, facultative anaerobic bacterial strain, designated ATCC 27380, was isolated from heat-stressed soil of Cape Canaveral, Florida, USA. Growth was observed at 20-42 °C (optimum, 37 °C), at pH 6.0-10.0 (optimum pH 7.0) and in the presence of 0.5-3 % NaCl (optimum 0.5 %). The cell wall contained meso-diaminopimelic acid as the diagnostic amino acid and the isoprenoid quinone was MK-7. The polar lipids present were phosphatidylglycerol, phosphatidylethanolamine, diphosphatidylglycerol and one unknown phospholipid. The main fatty acids were iso-C15 : 0 and anteiso-C15 : 0. Phylogenetic analysis based on 16S rRNA gene sequencing affiliated strain ATCC 27380 to the genus Paenibacillus, and showed the highest sequence similarity to Paenibacillus rigui JCM 16352 (97.0 %). The other closely related type strains exhibited 16S rRNA gene sequence similarity values below 95.9 %. The draft genome of ATCC 27380 had a size of 4,361,187 bases, with a G+C content of 51.0 %. The average nucleotide identity and in silico DNA-DNA hybridization values between strain ATCC 27380 and P. rigui JCM 16352 were 72.5% and 18.5 %, respectively, which were below the threshold suggested for species differentiation (96% and 70 %, respectively). The average amino acid identity between strain ATCC 27380 and P. rigui JCM 16352 was 68.72 %, which was above the suggested genus level demarcation of 65 %. Based on phenotypic, genotypic and chemotaxonomic data, strain ATCC 27380 represents a novel species in the genus Paenibacillus, for which the name Paenibacillusxerothermodurans sp. nov. (=DSM 520=NRRL NRS-1629=ATCC 27380) is proposed.