1. bookVolume 71 (2022): Issue 2 (June 2022)
Journal Details
License
Format
Journal
eISSN
2544-4646
First Published
04 Mar 1952
Publication timeframe
4 times per year
Languages
English
access type Open Access

Growth Behavior and Transcriptome Profile Analysis of Proteus mirabilis Strain Under Long- versus Short-Term Simulated Microgravity Environment

Published Online: 23 May 2022
Volume & Issue: Volume 71 (2022) - Issue 2 (June 2022)
Page range: 161 - 171
Received: 31 Dec 2021
Accepted: 07 Mar 2022
Journal Details
License
Format
Journal
eISSN
2544-4646
First Published
04 Mar 1952
Publication timeframe
4 times per year
Languages
English
Abstract

Spaceflight missions affect the behavior of microbes that are inevitably introduced into space environments and may impact astronauts’ health. Current studies have mainly focused on the biological characteristics and molecular mechanisms of microbes after short-term or long-term spaceflight, but few have compared the impact of various lengths of spaceflight missions on the characteristics of microbes. Researchers generally agree that microgravity (MG) is the most critical factor influencing microbial physiology in space capsules during flight missions. This study compared the growth behavior and transcriptome profile of Proteus mirabilis cells exposed to long-term simulated microgravity (SMG) with those exposed to short-term SMG. The results showed that long-term SMG decreased the growth rate, depressed biofilm formation ability, and affected several transcriptomic profiles, including stress response, membrane transportation, metal ion transportation, biological adhesion, carbohydrate metabolism, and lipid metabolism in contrast to short-term SMG. This study improved the understanding of long-term versus short-term SMG effects on P. mirabilis behavior and provided relevant references for analyzing the influence of P. mirabilis on astronaut health during spaceflights.

Keywords

Introduction

The field of space life science has become a new research frontier following the advent of space exploration and the development of space technology (Belobrajdic et al. 2021; Macaulay et al. 2021). During space exploration, microbes are inevitably introduced into space habitats by astronauts and may grow on surfaces in the space capsule (Singh et al. 2018; Checinska Sielaff et al. 2019). Due to extreme environmental factors, such as microgravity (MG), high vacuum, and intense radiation, microbes in space undergo a series of changes in gene expression at the transcriptional level and eventually perform global physiological alterations, including metabolism, growth rate, motility, virulence, and biofilm formation (Taylor 2015; Senatore et al. 2018). For instance, strains of Candida albicans exposed to a short-duration spaceflight showed enhanced cell aggregation and random budding under the differential expression of transcriptional regulators involved in oxidative stress resistance, aggregation, and random budding (Crabbé et al. 2013). Escherichia coli strains grew at higher antibiotic concentrations within 49 h of being cultured in a space environment compared to the Earth and differentially expressed genes (DEGs) related to starvation and oxidative stress responses (Aunins et al. 2018). Acinetobacter baumannii subjected to long-duration spaceflight showed decreased biofilm formation ability than the ground controls, coinciding with down-regulated type IV pili-related genes (Zhao et al. 2018). Overall, these data strongly suggest that microbes’ biological characteristics and molecular mechanisms were affected during or immediately following spaceflights, regardless of mission duration. However, much less is known regarding the precise impact of different mission durations on microbial growth behavior and transcriptome profiles.

MG is defined as a state of weightlessness that occurs due to decreased physical force exerted by gravity, where gravity ranges from 10–3 to 10–6 g (Bijlani et al. 2020). There is general agreement that MG is a crucial factor influencing microbial physiology in the space capsule during flight missions (Tesei et al. 2021). Due to technological and logistical hurdles, the microbial experiments under true MG in space stations are minimal. Therefore, different types of ground-based bioreactors, such as clinostats, rotating wall vessels (RWVs), and random positioning machines (RPMs), have been designed to develop a simulated microgravity (SMG) environment to analyze microbial responses to space MG (Acres et al. 2021). A high aspect ratio vessel (HARV) is a typical RWV that creates a low-fluid shear and weightless environment by revolving around an axis perpendicular to the gravitational vector (Sheet et al. 2019). Specifically, it simulates the true MG environment of spaceflight and has been used extensively to analyze the physiological response of bacteria to SMG (Hauserman et al. 2021). Since the invention of the HARV, the effects of SMG have been studied in several microbial species including E. coli, Pseudomonas aeruginosa, and Staphylococcus aureus (Crabbé et al. 2010; Castro et al. 2011; Tirumalai et al. 2019).

Moreover, several studies have shown that results obtained from HARV experiments are similar to those obtained in a true MG. For example, Salmonella Typhimurium cultivated in a true MG environment showed increased virulence in mice and revealed a role for its global regulator Hfq (Wilson et al. 2007). This phenomenon was shown due to a prior ground-based experiment that utilized the HARV and had previously produced similar results (Nickerson et al. 2000).

Proteus mirabilis is a common opportunistic pathogen frequently isolated from patients with urinary tract infections (UTIs), particularly in the elderly population at nursing homes and patients undergoing longterm catheterization (Matthews and Lancaster 2011; Armbruster et al. 2018). This pathogen primarily differentiates into elongated swarm forms, migrates to the epithelial cells of the urinary tract, and finally induces UTIs (Armbruster et al. 2012). In addition, P. mirabilis expresses fimbriae to mediate catheter attachment and biofilm maturation, which protects bacteria from the host immune response and the antibiotic inhibitory effect (Fusco et al. 2017). P. mirabilis has already been found in samples from human space habitats or post-flight astronauts, and it is likely to induce infectious diseases in the space environment given that the immune system of astronauts is significantly impaired during spaceflight (Klaus and Howard 2006; Crucian et al. 2018). Therefore, it is necessary to study the biological characteristics and genetic features of P. mirabilis in MG. To date, multiomics analysis has already been developed to study the molecular mechanisms of microbial survival and adaption in MG and SMG environments (Milojevic and Weckwerth 2020). Although a recent study has analyzed the phenotype and transcriptome of P. mirabilis after short-term exposure to SMG, long-term SMG exposure and varying lengths of SMG exposure to P. mirabilis remain unclear (Wang et al. 2021). In this study, the growth behavior and transcriptome profile of P. mirabilis exposed to long-term SMG were compared with those exposed to short-term SMG to analyze the effect of MG exposure duration on its characteristics. This study is expected to improve the understanding of long-term versus short-term SMG on P. mirabilis and provide relevant references for analyzing the influence of P. mirabilis on astronaut health during spaceflights.

Experimental
Materials and Methods

Bacterial strain and culture conditions. The original P. mirabilis strain, used in this study, was obtained from the Space Biomedical Laboratory of the Second Medical Center of the Chinese PLA General Hospital and has already been described many times (Wang et al. 2021). The strain was cultivated at 37°C for 24 h under constant shaking (200 rpm) in Luria-Bertani (LB) medium.

HARV experiment. The bacterial culture was adjusted to a turbidity of 1.0 and inoculated at 1:100 in the HARV bioreactor chambers (Synthecon Inc., USA). The chambers were filled with the culture medium, and air bubbles in the chambers were carefully removed through valves. The bacterial cultures were grown in rotated chambers around the horizontal axis at 37°C with a rotation rate of 25 rpm (Fig. 1). After 24 h, the bacterial cultures were poured out from the chambers, diluted to a turbidity of 1.0, and added into the new chambers at a volume ratio of 1:100 in LB medium. The bacterial suspension was cultivated at 37°C and 25 rpm for another 24 h. Experimental operations of bacterial inoculation in the chambers of HARV bioreactors were successively repeated three times for three days (short-term exposure to SMG, designated as PMS) and 21 times for three weeks (long-term exposure to SMG, designated as PML).

Growth rate assay. The growth rates of PML and PMS were determined using the Bioscreen C system and BioLink software (Lab Systems, Finland). Approximately, 200 μl of PMS and PML was taken from each chamber at every 2 h interval on the 3rd day and 21st day, respectively. Then the samples were inoculated into a 96-well microtiter plate. The growth rates of PML and PMS were monitored by measuring the optical density at 600 nm (OD600) every 2 h. A blank well containing 200 μl of LB medium was used as a negative control. This experiment was performed in three replicates.

Fig. 1

Schematic diagram of mechanical principle of HARV. MG is simulated by rotating the samples around a plane perpendicular to the gravity vector.

Biofilm formation assay. About 200 μl of each sample was added to a 96-well honeycomb microtiter plate and statically cultivated at 37°C for 24 h. After removing unattached cells with PBS, the 96-well microtiter plate was cultured at a temperature of 80°C for 15 min to fix the biofilm. The adhered cells were stained with 200 μl of 0.1% crystal violet for 15 min. Subsequently, the 96-well microtiter plate was washed with PBS and dried for another 10 min. Finally, the stained wells were dissolved in 95% ethanol to digest the biofilm, and the optical density at 570 nm (OD570) for each well was measured using a Thermo Multiskan Ascent (Thermo, USA). This experiment was performed in three replicates.

Swarming motility assay. The swarming motility of P. mirabilis was analyzed using Petri dishes containing a swarming medium (0.5% agar, 0.5% glucose, and 0.8% nutrient broth). Bacterial cultures were adjusted to a 108 CFU/ml density and inoculated in the dishes using a sterile needle. After incubation at 37°C for 24 h, the swarming motility of the strains was determined by measuring the diameter of the circular turbid zone formed by the bacterial suspension migrating away from the point of inoculation. This experiment was performed in three replicates.

RNA extraction, cDNA synthesis, and sequencing. The exponential growth phase of samples was determined according to the growth curves, and cultures at the exponential phase were used for transcriptome analysis. Briefly, total RNAs of samples were extracted by TRIZOL and purified using RNeasy Mini Kit (Qiagen, German) following the manufacturer’s instructions. The quality and quantity of RNAs were checked by capillary electrophoresis (Agilent Bioanalyzer 2100, USA) and with a spectrophotometer (Nanodrop 2000, USA). The RIN/RQN values ranged from 8.2 to 9.5. Subsequently, the ribosomal RNA (rRNA) was removed from the total RNA using a Ribo-Zero RNA Removal Kit (Illumina, USA). The purified RNA samples were then subjected to cDNA library construction using TruSeqTM Stranded Total RNA Library Prep Kit (Illumina, USA). Fragmentation buffer was added to cleave the mRNA into ~ 200 bp fragments, and the fragments were reverse transcribed into the first strand of cDNA by random primer. The second strand of cDNA was synthesized using DNA polymerase I and RNase H. Next, the samples were resolved with the End Repair Mix for end repair and Poly (A) addition for adapter ligation. After adapter ligation, the second strand of cDNA was degraded by the UNG enzyme, and the suitable fragments were selected for PCR amplification. Finally, TBS380 (Picogreen) samples were quality-checked and sequenced using Illumina HiSeq System.

Read processing, alignment, and quantification. All raw reads for RNA-seq were filtered, and clean reads were obtained by removing reads with adaptors, unknown nucleotides ≥ 5%, and low-quality bases (< Q10) number ≥ 20%. The RNA-seq reads were then mapped to the reference genome (P. mirabilis HI4320) using HISAT and Bowtie tools. The gene expression levels of each sample were analyzed using RESM software. Gene expression values were calculated using FPKM. Differential gene expression was analyzed using the DESeq2 method, and genes with log2 (FoldChange) ≥ 1 and adjusted p‐value ≤ 0.05 were defined as differentially expressed genes (DEGs). The function of each DEG was analyzed using the Kyoto Encyclopedia of Gene and Genomes (KEGG) database.

Data and statistical analyses. Phenotypic experiments and RNA sequencing were conducted in triplicate and the values were represented as mean ± standard deviation. A statistical comparison of data was evaluated by the two-tailed Student’s t-test. Statistical significance between PML and PMS was defined as p < 0.05.

Results

The growth rate of PML versus PMS. The growth rates of PML and PMS were measured, and growth rate data are shown in Table I. When grown in LB medium, the maximum specific growth rates of PML and PMS were 0.167 h–1 and 0.196 h–1, respectively. In terms of growth ability, PML exhibited a lower OD600 value than PMS, suggesting that growth ability decreased with increasing SMG exposure time (Fig. 2).

Fig. 2

Growth curve of PML (red) and PMS (blue). The growth curves of PML and PMS were quantified by measuring the OD600 values every 2 h for 24 h.

OD600 value of PML and PMS.

Time (h) PML PMS
0 0.548 ± 0.005 0.547 ± 0.006
2 0.581 ± 0.008 0.591 ± 0.005
4 0.674 ± 0.010 0.726 ± 0.005
6 0.863 ± 0.026 0.955 ± 0.012
8 1.206 ± 0.018 1.411 ± 0.026
10 1.560 ± 0.022 1.636 ± 0.013
12 1.709 ± 0.019 1.806 ± 0.027
14 1.776 ± 0.016 1.872 ± 0.024
16 1.826 ± 0.021 1.938 ± 0.025
18 1.876 ± 0.018 1.983 ± 0.015
20 1.927 ± 0.018 1.955 ± 0.014
22 1.900 ± 0.019 1.957 ± 0.028
24 1.889 ± 0.018 1.916 ± 0.014

Biofilm formation ability of PML versus PMS. The biofilm formation ability of PML and PMS was assessed by the crystal violet staining, and optical density at 570 nm (OD570) was measured for each strain

to determine the quantity of the biofilm. The results showed that PML decreased the OD570 value in contrast to PMS (0.096 ± 0.006 vs. 0.118 ± 0.011, p = 0.032), suggesting that the biofilm formation ability of the strain decreased as SMG exposure time increased (Fig. 3).

Fig. 3

Biofilm formation ability of PML (red) and PMS (blue). Biofilm formation ability of PML and PMS was examined by measuring the OD570 values in microtiter plates.

Swarming motility of PML versus PMS. The swarming motility of PML and PMS was determined by measuring the diameter of the circular turbid zone formed by the strains on the Petri dishes. The results showed that a similar circular zone developed in PML and PMS (33.667 ± 3.215 mm vs. 37.333 ± 0.058 mm, p = 0.124), suggesting that swarming motility of the strain was unchanged with increasing exposure time to SMG (Fig. 4).

Fig. 4

Swarming motility of PML (red) and PMS (blue). Swarming motility of PML and PMS was determined by measuring the translucent zone diameters in swarming agar.

Transcriptome profile analysis of PML versus PMS. Comparative transcriptomic analysis of PML and PMS was performed to reveal the impact of different time lengths of SMG on the molecular characteristics of the strain. The accession number of transcriptomic data for PML is SAMN23475021 and SAMN23509825, and for PMS is SAMN23498564. The percentage of total reads for PML and PMS mapped to the reference strain P. mirabilis HI4320 were 94.31% and 95.36%, respectively. The correlation of gene expression levels between PML and PMS was evaluated using the Pearson correlation coefficient. In this study, the R2 between samples was 0.987, suggesting that the sample selection was reasonable and that the findings were reliable. A Venn diagram of common and specific genes in PML and PMS is shown in Fig. 5. A total of 3,085 common genes were identified in both PML and PMS, while 16 and 12 specific genes were detected in PML and PMS, respectively.

Fig. 5

The Venn diagram of common and specific genes in PML and PMS.

DEGs were determined using the criteria of abs log2 (FoldChange) ≥ 1 and adjusted p-value ≤ 0.05. As shown in Table II, a total of 50 genes were differentially expressed between PML and PMS, including 19 upregulated genes and 31 downregulated genes. A scatter plot of PML versus PMS is shown in Fig. 6.

Fig. 6

Scatter plot of DEGs. The x-axis and y-axis represent the logarithm of the gene expression for PML and PMS, respectively. Red spots and blue spots represent upregulated and downregulated genes, respectively.

Statistics of differentially expressed genes (DEGs).

Gene ID Expression (up/down) Log2 FoldChang (PML/PMS) Adjusted p-value Gene products
csdA up 1.308 < 0.001 cysteine sulfinate desulfinase
csdE up 1.156 < 0.001 cysteine desulfuration protein
cutC up 1.323 0.004 choline trimethylamine-lyase
phoA up 1.686 0.002 alkaline phosphatase
pspA up 1.077 0.003 phage shock protein A
pspB up 1.107 0.002 phage shock protein B
pstB up 1.423 0.049 phosphate transport system ATP-binding protein
rplT up 1.060 0.023 large subunit ribosomal protein
ugpA up 1.439 0.002 phosphate transport system ATP-binding protein
ugpB up 1.377 < 0.001 phosphate transport system ATP-binding protein
ugpC up 1.228 0.010 phosphate transport system ATP-binding protein
ugpE up 1.575 0.002 phosphate transport system ATP-binding protein
PMI_RS02645 up 1.148 < 0.001 fimbria/pilus periplasmic chaperon
PMI_RS09180 up 1.031 0.022 cysteine desulfurase
PMI_RS09250 up 1.064 0.009 sensor histidine kinase
PMI_RS13360 up 2.720 < 0.001 small multidrug resistance pump
PMI_RS13370 up 1.424 0.017 putative phosphotransacetylase
PMI_RS14325 up 1.473 0.023 amino acid transport system substrate-binding protein
PMI_RS17915 up 1.520 < 0.001 Cd2+/Zn2+-exporting ATPase
artP down –1.009 < 0.001 arginine transport system ATP-binding protein
cyoB down –1.290 0.022 cytochrome o ubiquinol oxidase subunit I
epd down –1.011 0.007 D-erythrose 4-phosphate dehydrogenase
fadB down –1.330 0.016 3-hydroxyacyl-CoA dehydrogenase
fadE down –1.045 0.047 acyl-CoA dehydrogenase
feoA down –1.277 < 0.001 ferrous iron transport protein A
glpA down –1.465 0.005 glycerol-3-phosphate dehydrogenase
glpB down –1.348 0.023 glycerol-3-phosphate dehydrogenase
glpT down –1.221 0.003 glycerol-3-phosphate transporter
ilvN down –1.080 0.018 acetolactate synthase I/III small subunit
metI down –1.178 0.003 D-methionine transport system permease protein
msrB down –1.021 < 0.001 peptide-methionine oxide reductase
phsA down –1.181 0.046 thiosulfate reductase
ptsG down –1.099 < 0.001 PTS system, glucose-specific IIB component
PMI_RS00340 down –1.105 < 0.001 protein NrfC
PMI_RS00505 down –1.210 0.048 cytochrome ubiquinol oxidase subunit III
PMI_RS00510 down –1.283 0.036 cytochrome ubiquinol oxidase subunit IV
PMI_RS07940 down –1.255 0.028
PMI_RS09930 down –1.008 0.048 toxin CptA
PMI_RS10955 down –2.137 < 0.001 major pilin subunit PapA
PMI_RS13425 down –1.001 < 0.001 phosphorelay signal transduction system
PMI_RS13430 down –1.190 < 0.001 TetR/AcrR family transcriptional regulator
PMI_RS14090 down –1.029 < 0.001 putative transport protein
PMI_RS14825 down –1.315 0.017 Mat/Ecp fimbriae adhesion
PMI_RS14830 down –1.430 0.012 Mat/Ecp fimbriae outer membrane usher protein
PMI_RS14835 down –1.349 0.037 Mat/Ecp fimbriae periplasmic chaperone
PMI_RS14840 down –2.151 0.048 Mat/Ecp fimbriae adhesion
PMI_RS15035 down –1.003 0.027 cation/acetate symporter
PMI_RS15880 down –1.250 < 0.001 glycerol uptake facilitator protein
PMI_RS17135 down –1.018 0.020 minor fimbrial subunit
PMI_RS18425 down – 1.060 0.023 putative oxidoreductase

Fourteen categories, including 50 DEGs (identical DEGs may fall into different categories), were identified between PML and PMS according to the KEGG pathway classification (Fig. 7). Compared with PMS, PML is characterized by regulating genes related to cellular community, membrane transport, energy metabolism, carbohydrate metabolism, lipid metabolism, and amino acid metabolism.

Fig. 7

KEGG pathway analysis of DEGs. The x-axis and y-axis represent the numbers of DEGs and KEGG pathway category, respectively.

Notably, some DEGs were found to belong to diverse functional categories including stress response (pspAB, msrB, PMI_RS13425), membrane transportation (artP, metI, pstB, ugpABCE, PMI_RS14325), metal ion transportation (feoA, PMI_RS14090, PMI_RS15035, PMI_RS17915), biological adhesion (PMI_RS02645, PMI_RS10955, PMI_RS14825, PMI_RS14830, PMI_ RS14835, PMI_RS14840, PMI_RS17135), carbohydrate metabolism (fadB, ilvN, ptsG, PMI_RS13370), and lipid metabolism (fadBE, glpAB) and selected for further analysis between PML and PMS. The variation between PML and PMS at the transcriptomic level might lead to physiological changes in P. mirabilis and help bacteria survive better in a prolonged SMG environment.

Discussion

It is the first study to analyze the growth behavior and transcriptome profile of P. mirabilis exposed to long-term versus short-term SMG. The results showed that P. mirabilis exhibited a decreased growth rate and impaired biofilm formation ability under long-term SMG compared to short-term SMG. Further transcriptomic profiling demonstrated that the relevant molecular mechanisms of physiological alteration might be attributed to the differential expression of genes associated with membrane transportation, metal ion transportation, carbohydrate metabolism, lipid metabolism, and biological adhesion. This study improved the understanding of the various lengths of MG exposure on P. mirabilis behavior and provided relevant references for analyzing the influence of P. mirabilis on astronaut health during spaceflights.

The effects of MG on the growth rate and final cell density of microorganisms are controversial. Previous studies have shown that microorganisms have an increased growth rate, with a growth curve characterized by a shorter lag phase and a more prolonged exponential phase under MG or SMG. For example, C. albicans has been reported to have a slightly shorter generation time and higher growth propensity in spaceflights than those cultivated under NG (Nielsen et al. 2021). Similarly, another experiment demonstrated that Lactobacillus acidophilus showed a shorter lag phase and faster growth rate in the early stage of SMG in HARVs (Shao et al. 2017). Another study showed that the final cell population of Vibrio natriegens (Garschagen et al. 2019) increased significantly under SMG using a clinostat. A common explanation is that the lack of sedimentation occurring in MG led to a uniform distribution of cells with abundant utilization of nutrients, enabling denser microbial growth (Senatore et al. 2018). However, a contrasting study reported that S. aureus exhibited a reduced growth rate under SMG compared to NG (Hauserman et al. 2021). A recent experiment also showed that E. coli showed a decreased growth profile under SMG compared with that under NG, and the growth difference might be due to several factors involved in cell fitness (Yim et al. 2020). Following the above, a flight mutant strain of Bacillus cereus was found to have a decreased growth rate compared with the ground control, which may have been due to downregulated genes involved in lipid biosynthesis and energy transportation (Su et al. 2014). In addition, some experiments demonstrated that microbes grown in SMG or space conditions did not differ in growth rate cell size and shape from the controls. Researchers reported no significant differences in final OD600 for Rhodospirillum rubrum between the SMG and the control samples (Mastroleo et al. 2013). An experiment focused on Lactobacillus reuteri showed no difference in the growth rate and cell size between two SMG systems and normal gravity controls (Senatore et al. 2020). Recently, an investigation conducted on the ISS focused on Cupriavidus metallidurans, Bacillus subtilis, and Sphingomonas desiccabilis. The experiment verified the effect of different gravity regimens on the final cell density of all bacteria on the ISS, and no differences in final cell count and optical density were identified within any of the three strains despite different sedimentation rates (Santomartino et al. 2020). The most plausible explanation was that all species had reached the stationary phase, leading to a similar cell count for each bacterial species. In this study, the OD600 value of cell cultures was used to determine the growth rate of P. mirabilis under different SMG exposure durations, and the strain grew slower in long-term versus short-term SMG environments. The results suggested that P. mirabilis decreased its growth ability with increasing exposure time to SMG. The overlap of several factors caused the growth variation, and the downregulated genes involved in lipid metabolism, carbohydrate metabolism, and metal ion transportation might take an essential role in the decreased growth ability of the long-term SMG exposure strain.

Biofilms produced by microbes in the water system and device surface of the spacecraft cabin represent a significant phenotype concerning virulence and antibiotic resistance and induce corrosion of metals and structural materials (Novikova et al. 2006; Liu 2017). Therefore, it is necessary to analyze the biofilm formation ability of microbes under real and simulated MG. A representative investigation demonstrated that the biofilm of P. aeruginosa exhibited an atypical structure composed of columns overlapped with a canopy during spaceflights, which has not been observed on Earth (Kim et al. 2013). During short-term spaceflight, enhanced biofilm formation was also observed in Klebsiella pneumoniae (Li et al. 2014). The SMG environment also influences the biofilm formation ability of microbes by providing low shear forces of cellular fluid (Yamaguchi et al. 2014). For example, K. pneumoniae grown under SMG in HARVs exhibited increased biofilm formation compared to those grown under NG after two weeks of subculture, and the overexpressed genes related to type 3 fimbriae (mrkABCDF)-mediated biofilm formation on abiotic surfaces (Wang et al. 2016). Similarly, in a more recent experiment, Stenotrophomonas maltophilia cultivated under SMG in HARVs also produced more biofilm biomass than those under NG condition after two weeks of subculture, and upregulated genes responsible for type 4 fimbriae (pilAG) participated in this process (Su et al. 2021). In this study, the biofilm formation ability of the two groups was quantified using the OD570 values of crystal violet staining. The results showed that P. mirabilis under long-term SMG exposure decreased its biofilm formation ability compared with the identical strain under short-term SMG exposure, suggesting that P. mirabilis impaired its biofilm formation ability with increasing exposure time to SMG. Further transcriptomic profiling revealed that some genes related to fimbriae adhesion were downregulated under long-term versus short-term SMG. P. mirabilis encodes 17 putative chaperone-usher fimbrial operons and the role of five fimbriae, including urothelial cell adhesin (UCA), P. mirabilis fimbria (PMF), mannose resistant Proteus-like (MR/P), ambient temperature fimbria (ATF), and P. mirabilis-like pili (PMP), has been clearly identified (Pearson et al. 2008). It has been reported that P. mirabilis fimbriae have different roles in biofilm generation, and the UCA and PMF mutants improved biofilm formation ability compared to the wild-type strain, whereas the MR/P and ATF mutants formed significantly less biofilm than the wild-type strain (Scavone et al. 2016). Therefore, we preliminarily concluded that the downregulated genes encoded by other chaperone-usher fimbrial operons first decreased the activity of Mat/Ecp fimbriae protein, subsequently impairing biological adhesion and finally reducing the biofilm formation ability of P. mirabilis with increasing exposure time to SMG.

Motility is a critical microbial behavior that plays a crucial role in nutrient absorption, tissue localization and invasion, biofilm formation, virulence, and survival (Acres et al. 2021). Alterations in microbial motility often originate from changes in the gene expression of the flagella-related system (Morgenstein et al. 2010). Although few studies have focused explicitly on the effects of spaceflight and SMG on the phenotype of microbial motility, genetic and transcriptomic analyses have provided a general understanding of gene expression that can predict microbial motility according to the genes involved in flagella function (Milojevic and Weckwerth 2020). E. coli cultured in minimal MOPS medium upregulated its motility genes (fliCDZ and flgBDEK) in HARVs compared with NG rotation (Tucker et al. 2007). Consistent with this, P. aeruginosa cultured in LB medium also overexpressed motility genes, including fliACDGS, fleLNP, and flgM in HARVs in contrast to NG (Crabbé et al. 2010). In opposite, Salmonella Typhimurium grown in LB medium exhibited downregulated expression of flagellar genes, including fimA and fliB, in HARVs compared with NG rotation (Wilson et al. 2002). In this study, no significant difference in the flagella-related genes at the transcriptomic level was detected between long-term and short-term SMG exposure, and swarming motility of P. mirabilis was unchanged with increasing exposure time to SMG.

Conclusion

This study presents the only data available to compare long-term versus short-term SMG exposure effects on P. mirabilis cultured in HARVs. The results indicate that P. mirabilis modified its growth behavior to better adapt to the SMG environment with increasing exposure time. The transcriptomic analysis provides a practical and comprehensive strategy for identifying the effects of different lengths of SMG exposure on biological processes and pathways. This phenomenon may help understand how microbes adapt to spaceflight missions over different durations.

China’s space station will be completed in the early 2020s, and spaceflight missions will require astronauts to remain on the space station for long periods. With the reality of long-duration missions lasting years, avoiding infectious diseases induced by microbes and maintaining the safety of the space station are of great significance in the future. Due to the challenges of sending microbial samples into the space environment, most research still needs to be done in laboratories using ground-based bioreactors under SMG. Considering that one of the new challenges facing astronauts is reaching increasingly long-duration spaceflight targets, studying the influences of long-term versus short-time SMG exposure on the growth behavior of P. mirabilis is necessary to predict possible pathogenesis mechanisms and develop treatments for infectious diseases under spaceflight conditions. In the future, more studies are needed to establish a space microbiological safety assessment system to protect crew members and ensure the safe operation of space stations.

Fig. 1

Schematic diagram of mechanical principle of HARV. MG is simulated by rotating the samples around a plane perpendicular to the gravity vector.
Schematic diagram of mechanical principle of HARV. MG is simulated by rotating the samples around a plane perpendicular to the gravity vector.

Fig. 2

Growth curve of PML (red) and PMS (blue). The growth curves of PML and PMS were quantified by measuring the OD600 values every 2 h for 24 h.
Growth curve of PML (red) and PMS (blue). The growth curves of PML and PMS were quantified by measuring the OD600 values every 2 h for 24 h.

Fig. 3

Biofilm formation ability of PML (red) and PMS (blue). Biofilm formation ability of PML and PMS was examined by measuring the OD570 values in microtiter plates.
Biofilm formation ability of PML (red) and PMS (blue). Biofilm formation ability of PML and PMS was examined by measuring the OD570 values in microtiter plates.

Fig. 4

Swarming motility of PML (red) and PMS (blue). Swarming motility of PML and PMS was determined by measuring the translucent zone diameters in swarming agar.
Swarming motility of PML (red) and PMS (blue). Swarming motility of PML and PMS was determined by measuring the translucent zone diameters in swarming agar.

Fig. 5

The Venn diagram of common and specific genes in PML and PMS.
The Venn diagram of common and specific genes in PML and PMS.

Fig. 6

Scatter plot of DEGs. The x-axis and y-axis represent the logarithm of the gene expression for PML and PMS, respectively. Red spots and blue spots represent upregulated and downregulated genes, respectively.
Scatter plot of DEGs. The x-axis and y-axis represent the logarithm of the gene expression for PML and PMS, respectively. Red spots and blue spots represent upregulated and downregulated genes, respectively.

Fig. 7

KEGG pathway analysis of DEGs. The x-axis and y-axis represent the numbers of DEGs and KEGG pathway category, respectively.
KEGG pathway analysis of DEGs. The x-axis and y-axis represent the numbers of DEGs and KEGG pathway category, respectively.

Statistics of differentially expressed genes (DEGs).

Gene ID Expression (up/down) Log2 FoldChang (PML/PMS) Adjusted p-value Gene products
csdA up 1.308 < 0.001 cysteine sulfinate desulfinase
csdE up 1.156 < 0.001 cysteine desulfuration protein
cutC up 1.323 0.004 choline trimethylamine-lyase
phoA up 1.686 0.002 alkaline phosphatase
pspA up 1.077 0.003 phage shock protein A
pspB up 1.107 0.002 phage shock protein B
pstB up 1.423 0.049 phosphate transport system ATP-binding protein
rplT up 1.060 0.023 large subunit ribosomal protein
ugpA up 1.439 0.002 phosphate transport system ATP-binding protein
ugpB up 1.377 < 0.001 phosphate transport system ATP-binding protein
ugpC up 1.228 0.010 phosphate transport system ATP-binding protein
ugpE up 1.575 0.002 phosphate transport system ATP-binding protein
PMI_RS02645 up 1.148 < 0.001 fimbria/pilus periplasmic chaperon
PMI_RS09180 up 1.031 0.022 cysteine desulfurase
PMI_RS09250 up 1.064 0.009 sensor histidine kinase
PMI_RS13360 up 2.720 < 0.001 small multidrug resistance pump
PMI_RS13370 up 1.424 0.017 putative phosphotransacetylase
PMI_RS14325 up 1.473 0.023 amino acid transport system substrate-binding protein
PMI_RS17915 up 1.520 < 0.001 Cd2+/Zn2+-exporting ATPase
artP down –1.009 < 0.001 arginine transport system ATP-binding protein
cyoB down –1.290 0.022 cytochrome o ubiquinol oxidase subunit I
epd down –1.011 0.007 D-erythrose 4-phosphate dehydrogenase
fadB down –1.330 0.016 3-hydroxyacyl-CoA dehydrogenase
fadE down –1.045 0.047 acyl-CoA dehydrogenase
feoA down –1.277 < 0.001 ferrous iron transport protein A
glpA down –1.465 0.005 glycerol-3-phosphate dehydrogenase
glpB down –1.348 0.023 glycerol-3-phosphate dehydrogenase
glpT down –1.221 0.003 glycerol-3-phosphate transporter
ilvN down –1.080 0.018 acetolactate synthase I/III small subunit
metI down –1.178 0.003 D-methionine transport system permease protein
msrB down –1.021 < 0.001 peptide-methionine oxide reductase
phsA down –1.181 0.046 thiosulfate reductase
ptsG down –1.099 < 0.001 PTS system, glucose-specific IIB component
PMI_RS00340 down –1.105 < 0.001 protein NrfC
PMI_RS00505 down –1.210 0.048 cytochrome ubiquinol oxidase subunit III
PMI_RS00510 down –1.283 0.036 cytochrome ubiquinol oxidase subunit IV
PMI_RS07940 down –1.255 0.028
PMI_RS09930 down –1.008 0.048 toxin CptA
PMI_RS10955 down –2.137 < 0.001 major pilin subunit PapA
PMI_RS13425 down –1.001 < 0.001 phosphorelay signal transduction system
PMI_RS13430 down –1.190 < 0.001 TetR/AcrR family transcriptional regulator
PMI_RS14090 down –1.029 < 0.001 putative transport protein
PMI_RS14825 down –1.315 0.017 Mat/Ecp fimbriae adhesion
PMI_RS14830 down –1.430 0.012 Mat/Ecp fimbriae outer membrane usher protein
PMI_RS14835 down –1.349 0.037 Mat/Ecp fimbriae periplasmic chaperone
PMI_RS14840 down –2.151 0.048 Mat/Ecp fimbriae adhesion
PMI_RS15035 down –1.003 0.027 cation/acetate symporter
PMI_RS15880 down –1.250 < 0.001 glycerol uptake facilitator protein
PMI_RS17135 down –1.018 0.020 minor fimbrial subunit
PMI_RS18425 down – 1.060 0.023 putative oxidoreductase

OD600 value of PML and PMS.

Time (h) PML PMS
0 0.548 ± 0.005 0.547 ± 0.006
2 0.581 ± 0.008 0.591 ± 0.005
4 0.674 ± 0.010 0.726 ± 0.005
6 0.863 ± 0.026 0.955 ± 0.012
8 1.206 ± 0.018 1.411 ± 0.026
10 1.560 ± 0.022 1.636 ± 0.013
12 1.709 ± 0.019 1.806 ± 0.027
14 1.776 ± 0.016 1.872 ± 0.024
16 1.826 ± 0.021 1.938 ± 0.025
18 1.876 ± 0.018 1.983 ± 0.015
20 1.927 ± 0.018 1.955 ± 0.014
22 1.900 ± 0.019 1.957 ± 0.028
24 1.889 ± 0.018 1.916 ± 0.014

Acres JM, Youngapelian MJ, Nadeau J. The influence of spaceflight and simulated microgravity on bacterial motility and chemotaxis. NPJ Microgravity. 2021 Feb;7(1):7. https://doi.org/10.1038/s41526-021-00135-x Acres JM Youngapelian MJ Nadeau J The influence of spaceflight and simulated microgravity on bacterial motility and chemotaxis NPJ Microgravity 2021 Feb7 1 7 10.1038/s41526-021-00135-x790023033619250Open DOISearch in Google Scholar

Armbruster CE, Mobley HLT, Pearson MM. Pathogenesis of Proteus mirabilis infection. EcoSal Plus. 2018 Feb;8(1):10.1128/ecosalplus.ESP-0009-2017. https://doi.org/10.1128/ecosalplus.ESP-0009-2017 Armbruster CE Mobley HLT Pearson MM Pathogenesis of Proteus mirabilis infection EcoSal Plus 2018 Feb8 1 10 1128/ecosalplus.ESP-0009-2017 10.1128/ecosalplus.ESP-0009-2017588032829424333Open DOISearch in Google Scholar

Armbruster CE, Mobley HL. Merging mythology and morphology: the multifaceted lifestyle of Proteus mirabilis. Nat Rev Microbiol. 2012 Nov;10(11):743–754. https://doi.org/10.1038/nrmicro2890 Armbruster CE Mobley HL Merging mythology and morphology: the multifaceted lifestyle of Proteus mirabilis Nat Rev Microbiol 2012 Nov10 11 743 754 10.1038/nrmicro2890362103023042564Open DOISearch in Google Scholar

Aunins TR, Erickson KE, Prasad N, Levy SE, Jones A, Shrestha S, Mastracchio R, Stodieck L, Klaus D, Zea L, et al. Spaceflight modifies Escherichia coli gene expression in response to antibiotic exposure and reveals role of oxidative stress response. Front Microbiol. 2018 Mar;9:310. https://doi.org/10.3389/fmicb.2018.00310 Aunins TR Erickson KE Prasad N Levy SE Jones A Shrestha S Mastracchio R Stodieck L Klaus D Zea L et al Spaceflight modifies Escherichia coli gene expression in response to antibiotic exposure and reveals role of oxidative stress response Front Microbiol 2018 Mar9310 10.3389/fmicb.2018.00310586506229615983Open DOISearch in Google Scholar

Belobrajdic B, Melone K, Diaz-Artiles A. Planetary extravehicular activity (EVA) risk mitigation strategies for long-duration space missions. NPJ Microgravity. 2021 May;7(1):16. https://doi.org/10.1038/s41526-021-00144-w Belobrajdic B Melone K Diaz-Artiles A Planetary extravehicular activity (EVA) risk mitigation strategies for long-duration space missions NPJ Microgravity 2021 May7 1 16 10.1038/s41526-021-00144-w811502833980866Open DOISearch in Google Scholar

Bijlani S, Stephens E, Singh NK, Venkateswaran K, Wang CCC. Advances in space microbiology. iScience. 2021 Apr;24(5):102395. https://doi.org/10.1016/j.isci.2021.102395 Bijlani S Stephens E Singh NK Venkateswaran K Wang CCC Advances in space microbiology iScience 2021 Apr24 5 102395 10.1016/j.isci.2021.102395809105633997680Open DOISearch in Google Scholar

Castro SL, Nelman-Gonzalez M, Nickerson CA, Ott CM. Induction of attachment-independent biofilm formation and repression of hfq expression by low-fluid-shear culture of Staphylococcus aureus. Appl Environ Microbiol. 2011 Sep;77(18):6368–6378. https://doi.org/10.1128/AEM.00175-11 Castro SL Nelman-Gonzalez M Nickerson CA Ott CM Induction of attachment-independent biofilm formation and repression of hfq expression by low-fluid-shear culture of Staphylococcus aureus Appl Environ Microbiol 2011 Sep77 18 6368 6378 10.1128/AEM.00175-11318717021803898Open DOISearch in Google Scholar

Checinska Sielaff A, Urbaniak C, Mohan GBM, Stepanov VG, Tran Q, Wood JM, Minich J, McDonald D, Mayer T, Knight R, et al. Characterization of the total and viable bacterial and fungal communities associated with the International Space Station surfaces. Microbiome. 2019 Apr;7(1):50. https://doi.org/10.1186/s40168-019-0666-x Checinska Sielaff A Urbaniak C Mohan GBM Stepanov VG Tran Q Wood JM Minich J McDonald D Mayer T Knight R et al Characterization of the total and viable bacterial and fungal communities associated with the International Space Station surfaces Microbiome 2019 Apr7 1 50 10.1186/s40168-019-0666-x645251230955503Open DOISearch in Google Scholar

Crabbé A, Pycke B, Van Houdt R, Monsieurs P, Nickerson C, Leys N, Cornelis P. Response of Pseudomonas aeruginosa PAO1 to low shear modelled microgravity involves AlgU regulation. Environ Microbiol. 2010 Jun;12(6):1545–1564. https://doi.org/10.1111/j.1462-2920.2010.02184.x Crabbé A Pycke B Van Houdt R Monsieurs P Nickerson C Leys N Cornelis P Response of Pseudomonas aeruginosa PAO1 to low shear modelled microgravity involves AlgU regulation Environ Microbiol 2010 Jun12 6 1545 1564 10.1111/j.1462-2920.2010.02184.x20236169Open DOISearch in Google Scholar

Crabbé A, Nielsen-Preiss SM, Woolley CM, Barrila J, Buchanan K, McCracken J, Inglis DO, Searles SC, Nelman-Gonzalez MA, Ott CM, et al. Spaceflight enhances cell aggregation and random budding in Candida albicans. PLoS One. 2013 Dec;8(12):e80677. https://doi.org/10.1371/journal.pone.0080677 Crabbé A Nielsen-Preiss SM Woolley CM Barrila J Buchanan K McCracken J Inglis DO Searles SC Nelman-Gonzalez MA Ott CM et al Spaceflight enhances cell aggregation and random budding in Candida albicans PLoS One 2013 Dec8 12 e80677 10.1371/journal.pone.0080677385176224324620Open DOISearch in Google Scholar

Crucian BE, Choukèr A, Simpson RJ, Mehta S, Marshall G, Smith SM, Zwart SR, Heer M, Ponomarev S, Whitmire A, et al. Immune system dysregulation during spaceflight: potential countermeasures for deep space exploration missions. Front Immunol. 2018 Jun;9:1437. https://doi.org/10.3389/fimmu.2018.01437 Crucian BE Choukèr A Simpson RJ Mehta S Marshall G Smith SM Zwart SR Heer M Ponomarev S Whitmire A et al Immune system dysregulation during spaceflight: potential countermeasures for deep space exploration missions Front Immunol 2018 Jun91437 10.3389/fimmu.2018.01437603833130018614Open DOISearch in Google Scholar

Fusco A, Coretti L, Savio V, Buommino E, Lembo F, Donnarumma G. Biofilm formation and immunomodulatory activity of Proteus mirabilis clinically isolated strains. Int J Mol Sci. 2017 Feb; 18(2):414. https://doi.org/10.3390/ijms18020414 Fusco A Coretti L Savio V Buommino E Lembo F Donnarumma G Biofilm formation and immunomodulatory activity of Proteus mirabilis clinically isolated strains Int J Mol Sci 2017 Feb; 18 2 414 10.3390/ijms18020414534394828212280Open DOISearch in Google Scholar

Garschagen LS, Mancinelli RL, Moeller R. Introducing Vibrio natriegens as a microbial model organism for microgravity research. Astrobiology. 2019 Oct;19(10):1211–1220. https://doi.org/10.1089/ast.2018.2010 Garschagen LS Mancinelli RL Moeller R Introducing Vibrio natriegens as a microbial model organism for microgravity research Astrobiology 2019 Oct19 10 1211 1220 10.1089/ast.2018.201031486680Open DOISearch in Google Scholar

Hauserman MR, Rice KC. Growth of Staphylococcus aureus using a rotary cell culture system. In: Rice KC, editor. Staphylococcus aureus. Methods in Molecular Biology. New York (USA): Humana; 2021. p. 79–88. https://doi.org/10.1007/978-1-0716-1550-8_10 Hauserman MR Rice KC Growth of Staphylococcus aureus using a rotary cell culture system. In: Rice KC, editor. Staphylococcus aureus. Methods in Molecular Biology New York (USA) Humana 2021 p 7988 10.1007/978-1-0716-1550-8_1034264463Open DOISearch in Google Scholar

Kim W, Tengra FK, Young Z, Shong J, Marchand N, Chan HK, Pangule RC, Parra M, Dordick JS, Plawsky JL, et al. Spaceflight promotes biofilm formation by Pseudomonas aeruginosa. PLoS One. 2013 Apr;8(4):e62437. https://doi.org/10.1371/journal.pone.0062437 Kim W Tengra FK Young Z Shong J Marchand N Chan HK Pangule RC Parra M Dordick JS Plawsky JL et al Spaceflight promotes biofilm formation by Pseudomonas aeruginosa PLoS One 2013 Apr8 4 e62437 10.1371/journal.pone.0062437363916523658630Open DOISearch in Google Scholar

Klaus DM, Howard HN. Antibiotic efficacy and microbial virulence during space flight. Trends Biotechnol. 2006 Mar;24(3):131–136. https://doi.org/10.1016/j.tibtech.2006.01.008 Klaus DM Howard HN Antibiotic efficacy and microbial virulence during space flight Trends Biotechnol 2006 Mar24 3 131 136 10.1016/j.tibtech.2006.01.00816460819Open DOISearch in Google Scholar

Li J, Liu F, Wang Q, Ge P, Woo PC, Yan J, Zhao Y, Gao GF, Liu CH, Liu C. Genomic and transcriptomic analysis of NDM-1 Klebsiella pneumoniae in spaceflight reveal mechanisms underlying environmental adaptability. Sci Rep. 2014 Aug;4:6216. https://doi.org/10.1038/srep06216 Li J Liu F Wang Q Ge P Woo PC Yan J Zhao Y Gao GF Liu CH Liu C Genomic and transcriptomic analysis of NDM-1 Klebsiella pneumoniae in spaceflight reveal mechanisms underlying environmental adaptability Sci Rep 2014 Aug46216 10.1038/srep06216414736425163721Open DOISearch in Google Scholar

Liu C. The theory and application of space microbiology: China’s experiences in space experiments and beyond. Environ Microbiol. 2017 Feb;19(2):426–433. https://doi.org/10.1111/1462-2920.13472 Liu C The theory and application of space microbiology: China’s experiences in space experiments and beyond Environ Microbiol 2017 Feb19 2 426 433 10.1111/1462-2920.1347227459305Open DOISearch in Google Scholar

Macaulay TR, Peters BT, Wood SJ, Clément GR, Oddsson L, Bloomberg JJ. Developing proprioceptive countermeasures to mitigate postural and locomotor control deficits after long-duration spaceflight. Front Syst Neurosci. 2021 Apr;15:658985. https://doi.org/10.3389/fnsys.2021.658985 Macaulay TR Peters BT Wood SJ Clément GR Oddsson L Bloomberg JJ Developing proprioceptive countermeasures to mitigate postural and locomotor control deficits after long-duration spaceflight Front Syst Neurosci 2021 Apr15658985 10.3389/fnsys.2021.658985811117133986648Open DOISearch in Google Scholar

Mastroleo F, Van Houdt R, Atkinson S, Mergeay M, Hendrickx L, Wattiez R, Leys N. Modelled microgravity cultivation modulates N-acylhomoserine lactone production in Rhodospirillum rubrum S1H independently of cell density. Microbiology. 2013 Dec; 159(Pt_12): 2456–2466. https://doi.org/10.1099/mic.0.066415-0 Mastroleo F Van Houdt R Atkinson S Mergeay M Hendrickx L Wattiez R Leys N Modelled microgravity cultivation modulates N-acylhomoserine lactone production in Rhodospirillum rubrum S1H independently of cell density Microbiology 2013 Dec; 159 Pt_12 2456 2466 10.1099/mic.0.066415-024025602Open DOISearch in Google Scholar

Matthews SJ, Lancaster JW. Urinary tract infections in the elderly population. Am J Geriatr Pharmacother. 2011 Oct;9(5):286–309. https://doi.org/10.1016/j.amjopharm.2011.07.002 Matthews SJ Lancaster JW Urinary tract infections in the elderly population Am J Geriatr Pharmacother 2011 Oct9 5 286 309 10.1016/j.amjopharm.2011.07.00221840265Open DOISearch in Google Scholar

Milojevic T, Weckwerth W. Molecular mechanisms of microbial survivability in outer space: A systems biology approach. Front Microbiol. 2020 May;11:923. https://doi.org/10.3389/fmicb.2020.00923 Milojevic T Weckwerth W Molecular mechanisms of microbial survivability in outer space: A systems biology approach Front Microbiol 2020 May11923 10.3389/fmicb.2020.00923724263932499769Open DOISearch in Google Scholar

Morgenstein RM, Szostek B, Rather PN. Regulation of gene expression during swarmer cell differentiation in Proteus mirabilis. FEMS Microbiol Rev. 2010 Sep;34(5):753–763. https://doi.org/10.1111/j.1574-6976.2010.00229.x Morgenstein RM Szostek B Rather PN Regulation of gene expression during swarmer cell differentiation in Proteus mirabilis FEMS Microbiol Rev 2010 Sep34 5 753 763 10.1111/j.1574-6976.2010.00229.x20497230Open DOISearch in Google Scholar

Nielsen S, White K, Preiss K, Peart D, Gianoulias K, Juel R, Sutton J, McKinney J, Bender J, Pinc G, et al. Growth and antifungal resistance of the pathogenic yeast, Candida Albicans, in the microgravity environment of the International Space Station: An aggregate of multiple flight experiences. Life (Basel). 2021 Mar;11(4):283. https://doi.org/10.3390/life11040283 Nielsen S White K Preiss K Peart D Gianoulias K Juel R Sutton J McKinney J Bender J Pinc G et al Growth and antifungal resistance of the pathogenic yeast, Candida Albicans, in the microgravity environment of the International Space Station: An aggregate of multiple flight experiences Life (Basel) 2021 Mar11 4 283 10.3390/life11040283806724533801697Open DOISearch in Google Scholar

Nickerson CA, Ott CM, Mister SJ, Morrow BJ, Burns-Keliher L, Pierson DL. Microgravity as a novel environmental signal affecting Salmonella enterica serovar Typhimurium virulence. Infect Immun. 2000 Jun;68(6):3147–3152. https://doi.org/10.1128/IAI.68.6.3147-3152.2000 Nickerson CA Ott CM Mister SJ Morrow BJ Burns-Keliher L Pierson DL Microgravity as a novel environmental signal affecting Salmonella enterica serovar Typhimurium virulence Infect Immun 2000 Jun68 6 3147 3152 10.1128/IAI.68.6.3147-3152.20009754810816456Open DOISearch in Google Scholar

Novikova N, De Boever P, Poddubko S, Deshevaya E, Polikarpov N, Rakova N, Coninx I, Mergeay M. Survey of environmental biocontamination on board the International Space Station. Res Microbiol. 2006 Jan-Feb;157(1):5–12. https://doi.org/10.1016/j.resmic.2005.07.010 Novikova N De Boever P Poddubko S Deshevaya E Polikarpov N Rakova N Coninx I Mergeay M Survey of environmental biocontamination on board the International Space Station Res Microbiol 2006 Jan-Feb157 1 5 12 10.1016/j.resmic.2005.07.01016364606Open DOISearch in Google Scholar

Pearson MM, Sebaihia M, Churcher C, Quail MA, Seshasayee AS, Luscombe NM, Abdellah Z, Arrosmith C, Atkin B, Chillingworth T, et al. Complete genome sequence of uropathogenic Proteus mirabilis, a master of both adherence and motility. J Bacteriol. 2008 Jun;190(11):4027–4037. https://doi.org/10.1128/JB.01981-07 Pearson MM Sebaihia M Churcher C Quail MA Seshasayee AS Luscombe NM Abdellah Z Arrosmith C Atkin B Chillingworth T et al Complete genome sequence of uropathogenic Proteus mirabilis, a master of both adherence and motility J Bacteriol 2008 Jun190 11 4027 4037 10.1128/JB.01981-07239503618375554Open DOISearch in Google Scholar

Santomartino R, Waajen AC, de Wit W, Nicholson N, Parmitano L, Loudon CM, Moeller R, Rettberg P, Fuchs FM, Van Houdt R, et al. No effect of microgravity and simulated mars gravity on final bacterial cell concentrations on the International Space Station: applications to space bioproduction. Front Microbiol. 2020 Oct;11:579156. https://doi.org/10.3389/fmicb.2020.579156 Santomartino R Waajen AC de Wit W Nicholson N Parmitano L Loudon CM Moeller R Rettberg P Fuchs FM Van Houdt R et al No effect of microgravity and simulated mars gravity on final bacterial cell concentrations on the International Space Station: applications to space bioproduction Front Microbiol 2020 Oct11579156 10.3389/fmicb.2020.579156759170533154740Open DOISearch in Google Scholar

Scavone P, Iribarnegaray V, Caetano AL, Schlapp G, Härtel S, Zunino P. Fimbriae have distinguishable roles in Proteus mirabilis biofilm formation. Pathog Dis. 2016 Jul;74(5):ftw033. https://doi.org/10.1093/femspd/ftw033 Scavone P Iribarnegaray V Caetano AL Schlapp G Härtel S Zunino P Fimbriae have distinguishable roles in Proteus mirabilis biofilm formation Pathog Dis 2016 Jul74 5 ftw033 10.1093/femspd/ftw03327091004Open DOISearch in Google Scholar

Senatore G, Mastroleo F, Leys N, Mauriello G. Effect of microgravity and space radiation on microbes. Future Microbiol. 2018 Jun; 13:831–847. https://doi.org/10.2217/fmb-2017-0251 Senatore G Mastroleo F Leys N Mauriello G Effect of microgravity and space radiation on microbes Future Microbiol 2018 Jun; 13831 847 10.2217/fmb-2017-025129745771Open DOISearch in Google Scholar

Senatore G, Mastroleo F, Leys N, Mauriello G. Growth of Lactobacillus reuteri DSM17938 under two simulated microgravity systems: Changes in reuterin production, gastrointestinal passage resistance, and stress genes expression response. Astrobiology. 2020 Jan;20(1):1–14. https://doi.org/10.1089/ast.2019.2082 Senatore G Mastroleo F Leys N Mauriello G Growth of Lactobacillus reuteri DSM17938 under two simulated microgravity systems: Changes in reuterin production, gastrointestinal passage resistance, and stress genes expression response Astrobiology 2020 Jan20 1 1 14 10.1089/ast.2019.208231977256Open DOISearch in Google Scholar

Shao D, Yao L, Riaz MS, Zhu J, Shi J, Jin M, Huang Q, Yang H. Simulated microgravity affects some biological characteristics of Lactobacillus acidophilus. Appl Microbiol Biotechnol. 2017 Apr; 101(8):3439–3449. https://doi.org/10.1007/s00253-016-8059-6 Shao D Yao L Riaz MS Zhu J Shi J Jin M Huang Q Yang H Simulated microgravity affects some biological characteristics of Lactobacillus acidophilus Appl Microbiol Biotechnol 2017 Apr; 101 8 3439 3449 10.1007/s00253-016-8059-628013406Open DOISearch in Google Scholar

Sheet S, Sathishkumar Y, Choi MS, Lee YS. Insight into Pseudomonas aeruginosa pyocyanin production under low-shear modeled microgravity. Bioprocess Biosyst Eng. 2019 Feb;42(2):267–277. https://doi.org/10.1007/s00449-018-2031-z Sheet S Sathishkumar Y Choi MS Lee YS Insight into Pseudomonas aeruginosa pyocyanin production under low-shear modeled microgravity Bioprocess Biosyst Eng 2019 Feb42 2 267 277 10.1007/s00449-018-2031-z30535586Open DOISearch in Google Scholar

Singh NK, Wood JM, Karouia F, Venkateswaran K. Succession and persistence of microbial communities and antimicrobial resistance genes associated with International Space Station environmental surfaces. Microbiome. 2018 Nov;6(1):204. https://doi.org/10.1186/s40168-018-0585-2 Singh NK Wood JM Karouia F Venkateswaran K Succession and persistence of microbial communities and antimicrobial resistance genes associated with International Space Station environmental surfaces Microbiome 2018 Nov6 1 204 10.1186/s40168-018-0585-2623467730424821Open DOISearch in Google Scholar

Su L, Zhou L, Liu J, Cen Z, Wu C, Wang T, Zhou T, Chang D, Guo Y, Fang X, et al. Phenotypic, genomic, transcriptomic and proteomic changes in Bacillus cereus after a short-term space flight. Adv Space Res. 2014 Jan; 53:18–29. https://doi.org/10.1016/j.asr.2013.08.001 Su L Zhou L Liu J Cen Z Wu C Wang T Zhou T Chang D Guo Y Fang X et al Phenotypic, genomic, transcriptomic and proteomic changes in Bacillus cereus after a short-term space flight Adv Space Res 2014 Jan; 5318 29 10.1016/j.asr.2013.08.001Open DOISearch in Google Scholar

Su X, Guo Y, Fang T, Jiang X, Wang D, Li D, Bai P, Zhang B, Wang J, Liu C. Effects of simulated microgravity on the physiology of Stenotrophomonas maltophilia and multiomic analysis. Front Microbiol. 2021 Aug;12:701265. https://doi.org/10.3389/fmicb.2021.701265 Su X Guo Y Fang T Jiang X Wang D Li D Bai P Zhang B Wang J Liu C Effects of simulated microgravity on the physiology of Stenotrophomonas maltophilia and multiomic analysis Front Microbiol 2021 Aug12701265 10.3389/fmicb.2021.701265842979334512577Open DOISearch in Google Scholar

Taylor PW. Impact of space flight on bacterial virulence and antibiotic susceptibility. Infect Drug Resist. 2015 Jul;8:249–262. https://doi.org/10.2147/IDR.S67275 Taylor PW Impact of space flight on bacterial virulence and antibiotic susceptibility Infect Drug Resist 2015 Jul8249 262 10.2147/IDR.S67275452452926251622Open DOISearch in Google Scholar

Tesei D, Chiang AJ, Kalkum M, Stajich JE, Mohan GBM, Sterflinger K, Venkateswaran K. Effects of simulated microgravity on the proteome and secretome of the polyextremotolerant black fungus Knufia chersonesos. Front Genet. 2021 Mar;12:638708. https://doi.org/10.3389/fgene.2021.638708 Tesei D Chiang AJ Kalkum M Stajich JE Mohan GBM Sterflinger K Venkateswaran K Effects of simulated microgravity on the proteome and secretome of the polyextremotolerant black fungus Knufia chersonesos Front Genet 2021 Mar12638708 10.3389/fgene.2021.638708801268733815472Open DOISearch in Google Scholar

Tirumalai MR, Karouia F, Tran Q, Stepanov VG, Bruce RJ, Ott CM, Pierson DL, Fox GE. Evaluation of acquired antibiotic resistance in Escherichia coli exposed to long-term low-shear modeled microgravity and background antibiotic exposure. mBio. 2019 Jan;10(1):e02637-18. https://doi.org/10.1128/mBio.02637-18 Tirumalai MR Karouia F Tran Q Stepanov VG Bruce RJ Ott CM Pierson DL Fox GE Evaluation of acquired antibiotic resistance in Escherichia coli exposed to long-term low-shear modeled microgravity and background antibiotic exposure mBio 2019 Jan10 1 e02637 18 10.1128/mBio.02637-18633642630647159Open DOISearch in Google Scholar

Tucker DL, Ott CM, Huff S, Fofanov Y, Pierson DL, Willson RC, Fox GE. Characterization of Escherichia coli MG1655 grown in a low-shear modeled microgravity environment. BMC Microbiol. 2007 Mar;7:15. https://doi.org/10.1186/1471-2180-7-15 Tucker DL Ott CM Huff S Fofanov Y Pierson DL Willson RC Fox GE Characterization of Escherichia coli MG1655 grown in a low-shear modeled microgravity environment BMC Microbiol 2007 Mar715 10.1186/1471-2180-7-15185231317343762Open DOISearch in Google Scholar

Wang D, Bai P, Zhang B, Su X, Jiang X, Fang T, Wang J, Liu C. Decreased biofilm formation in Proteus mirabilis after short-term exposure to a simulated microgravity environment. Braz J Microbiol. 2021 Dec;52(4):2021–2030. https://doi.org/10.1007/s42770-021-00588-y Wang D Bai P Zhang B Su X Jiang X Fang T Wang J Liu C Decreased biofilm formation in Proteus mirabilis after short-term exposure to a simulated microgravity environment Braz J Microbiol 2021 Dec52 4 2021 2030 10.1007/s42770-021-00588-y857823334558030Open DOISearch in Google Scholar

Wang H, Yan Y, Rong D, Wang J, Wang H, Liu Z, Wang J, Yang R, Han Y. Increased biofilm formation ability in Klebsiella pneumoniae after short-term exposure to a simulated microgravity environment. Microbiologyopen. 2016 Oct;5(5):793–801. https://doi.org/10.1002/mbo3.370 Wang H Yan Y Rong D Wang J Wang H Liu Z Wang J Yang R Han Y Increased biofilm formation ability in Klebsiella pneumoniae after short-term exposure to a simulated microgravity environment Microbiologyopen 2016 Oct5 5 793 801 10.1002/mbo3.370506171627185296Open DOISearch in Google Scholar

Wilson JW, Ramamurthy R, Porwollik S, McClelland M, Hammond T, Allen P, Ott CM, Pierson DL, Nickerson CA. Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon. Proc Natl Acad Sci USA. 2002 Oct; 99(21):13807–13812. https://doi.org/10.1073/pnas.212387899 Wilson JW Ramamurthy R Porwollik S McClelland M Hammond T Allen P Ott CM Pierson DL Nickerson CA Microarray analysis identifies Salmonella genes belonging to the low-shear modeled microgravity regulon Proc Natl Acad Sci USA 2002 Oct; 99 21 13807 13812 10.1073/pnas.21238789912977912370447Open DOISearch in Google Scholar

Wilson JW, Ott CM, Höner zu Bentrup K, Ramamurthy R, Quick L, Porwollik S, Cheng P, McClelland M, Tsaprailis G, Radabaugh T, et al. Space flight alters bacterial gene expression and virulence and reveals a role for global regulator Hfq. Proc Natl Acad Sci USA. 2007 Oct;104(41):16299–16304. https://doi.org/10.1073/pnas.0707155104 Wilson JW Ott CM Höner zu Bentrup K Ramamurthy R Quick L Porwollik S Cheng P McClelland M Tsaprailis G Radabaugh T et al Space flight alters bacterial gene expression and virulence and reveals a role for global regulator Hfq Proc Natl Acad Sci USA 2007 Oct104 41 16299 16304 10.1073/pnas.0707155104204220117901201Open DOISearch in Google Scholar

Yamaguchi N, Roberts M, Castro S, Oubre C, Makimura K, Leys N, Grohmann E, Sugita T, Ichijo T, Nasu M. Microbial monitoring of crewed habitats in space-current status and future perspectives. Microbes Environ. 2014 Sep;29(3):250–260. https://doi.org/10.1264/jsme2.me14031 Yamaguchi N Roberts M Castro S Oubre C Makimura K Leys N Grohmann E Sugita T Ichijo T Nasu M Microbial monitoring of crewed habitats in space-current status and future perspectives Microbes Environ 2014 Sep29 3 250 260 10.1264/jsme2.me14031415903625130885Open DOISearch in Google Scholar

Yim J, Cho SW, Kim B, Park S, Han YH, Seo SW. Transcriptional profiling of the probiotic Escherichia coli Nissle 1917 strain under simulated microgravity. Int J Mol Sci. 2020 Apr;21(8):2666. https://doi.org/10.3390/ijms21082666 Yim J Cho SW Kim B Park S Han YH Seo SW Transcriptional profiling of the probiotic Escherichia coli Nissle 1917 strain under simulated microgravity Int J Mol Sci 2020 Apr21 8 2666 10.3390/ijms21082666721582732290466Open DOISearch in Google Scholar

Zhao X, Yu Y, Zhang X, Huang B, Bai P, Xu C, Li D, Zhang B, Liu C. Decreased biofilm formation ability of Acinetobacter baumannii after spaceflight on China’s Shenzhou 11 spacecraft. Microbiology Open. 2019 Jun;8(6):e00763. https://doi.org/10.1002/mbo3.763 Zhao X Yu Y Zhang X Huang B Bai P Xu C Li D Zhang B Liu C Decreased biofilm formation ability of Acinetobacter baumannii after spaceflight on China’s Shenzhou 11 spacecraft Microbiology Open 2019 Jun8 6 e00763 10.1002/mbo3.763656223330379419Open DOISearch in Google Scholar

Recommended articles from Trend MD

Plan your remote conference with Sciendo