Search

ABSTRACT During microbial surveillance of the Mars 2020 spacecraft assembly facility, two novel bacterial strains, potentially capable of producing lasso peptides, were identified. Characterization using a polyphasic taxonomic approach, whole-genome sequencing and phylogenomic analyses revealed a close genetic relationship among two strains from Mars 2020 cleanroom floors (179-C4-2-HS, 179-J1A1-HS), one strain from the Agave plant (AT2.8), and another strain from wheat-associated soil (V4I25). All four strains exhibited high 16S rRNA gene sequence similarity (>99.2%) and low average nucleotide identity (ANI) with Neobacillus niacini NBRC 15566T, delineating new phylogenetic branches within the genus. Detailed molecular analyses, including gyrB (90.2%), ANI (86.4%), average amino acid identity (87.8%) phylogenies, digital DNA–DNA hybridization (32.6%), and percentage of conserved proteins (77.7%) indicated significant divergence from N. niacini NBRC 15566T. Consequently, these strains have been designated Neobacillus driksii sp. nov., with the type strain 179-C4-2-HST (DSM 115941T = NRRL B-65665T). N. driksii grew at 4°C to 45°C, pH range of 6.0 to 9.5, and 0.5% to 5% NaCl. The major cellular fatty acids are iso-C15:0 and anteiso-C15:0. The dominant polar lipids include diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, and an unidentified aminolipid. Metagenomic analysis within NASA cleanrooms revealed that N. driksii is scarce (17 out of 236 samples). Genes encoding the biosynthesis pathway for lasso peptides were identified in all N. driksii strains and are not commonly found in other Neobacillus species, except in 7 out of 26 recognized species. This study highlights the unique metabolic capabilities of N. driksii, underscoring their potential in antimicrobial research and biotechnology.IMPORTANCEThe microbial surveillance of the Mars 2020 assembly cleanroom led to the isolation of novel N. driksii with potential applications in cleanroom environments, such as hospitals, pharmaceuticals, semiconductors, and aeronautical industries. N. driksii genomes were found to possess genes responsible for producing lasso peptides, which are crucial for antimicrobial defense, communication, and enzyme inhibition. Isolation of N. driksii from cleanrooms, Agave plants, and dryland wheat soils, suggested niche-specific ecology and resilience under various environmentally challenging conditions. The discovery of potent antimicrobial agents from novel N. driksii underscores the importance of genome mining and the isolation of rare microorganisms. Bioactive gene clusters potentially producing nicotianamine-like siderophores were found in N. driksii genomes. These siderophores can be used for bioremediation to remove heavy metals from contaminated environments, promote plant growth by aiding iron uptake in agriculture, and treat iron overload conditions in medical applications.

Abstract Background The International Space Station (ISS) stands as a testament to human achievement in space exploration. Despite its highly controlled environment, characterised by microgravity, increased CO $$_{2}$$ 2 levels, and elevated solar radiation, microorganisms occupy a unique niche. These microbial inhabitants play a significant role in influencing the health and well-being of astronauts on board. One microorganism of particular interest in our study is Enterobacter bugandensis, primarily found in clinical specimens including the human gastrointestinal tract, and also reported to possess pathogenic traits, leading to a plethora of infections. Results Distinct from their Earth counterparts, ISS E. bugandensis strains have exhibited resistance mechanisms that categorise them within the ESKAPE pathogen group, a collection of pathogens recognised for their formidable resistance to antimicrobial treatments. During the 2-year Microbial Tracking 1 mission, 13 strains of multidrug-resistant E. bugandensis were isolated from various locations within the ISS. We have carried out a comprehensive study to understand the genomic intricacies of ISS-derived E. bugandensis in comparison to terrestrial strains, with a keen focus on those associated with clinical infections. We unravel the evolutionary trajectories of pivotal genes, especially those contributing to functional adaptations and potential antimicrobial resistance. A hypothesis central to our study was that the singular nature of the stresses of the space environment, distinct from any on Earth, could be driving these genomic adaptations. Extending our investigation, we meticulously mapped the prevalence and distribution of E. bugandensis across the ISS over time. This temporal analysis provided insights into the persistence, succession, and potential patterns of colonisation of E. bugandensis in space. Furthermore, by leveraging advanced analytical techniques, including metabolic modelling, we delved into the coexisting microbial communities alongside E. bugandensis in the ISS across multiple missions and spatial locations. This exploration revealed intricate microbial interactions, offering a window into the microbial ecosystem dynamics within the ISS. Conclusions Our comprehensive analysis illuminated not only the ways these interactions sculpt microbial diversity but also the factors that might contribute to the potential dominance and succession of E. bugandensis within the ISS environment. The implications of these findings are twofold. Firstly, they shed light on microbial behaviour, adaptation, and evolution in extreme, isolated environments. Secondly, they underscore the need for robust preventive measures, ensuring the health and safety of astronauts by mitigating risks associated with potential pathogenic threats. Video Abstract

The rapidly growing global energy demand, environmental concerns, and the urgent need to reduce carbon footprints have made sustainable household energy consumption a critical priority. This study aims to analyze household energy data to predict the electricity self-sufficiency rate of households and extract meaningful insights that can enhance it. For this purpose, we use LightGBM (Light Gradient Boosting Machine)-, SHAP (SHapley Additive exPlanations)-, and correlation-heatmap-based approaches to analyze 12 months of energy and questionnaire survey data collected from over 200 smart houses in Kitakyushu, Japan. First, we use LightGBM to predict the ESSR of households and identify the key features that impact the prediction model. By using LightGBM, we demonstrated that the key features are the housing type, average monthly electricity bill, presence of floor heating system, average monthly gas bill, electricity tariff plan, electrical capacity, number of TVs, cooking equipment used, number of washing and drying machines, and the frequency of viewing home energy management systems (HEMSs). Furthermore, we adopted the LightGBM classifier with ℓ1 regularization to extract the most significant features and established a statistical correlation between these features and the electricity self-sufficiency rate. This LightGBM-based model can also predict the electricity self-sufficiency rate of households that did not participate in the questionnaire survey. The LightGBM-based model offers a global view of feature importance but lacks detailed explanations for individual predictions. For this purpose, we used SHAP analysis to identify the impact-wise order of key features that influence the electricity self-sufficiency rate (ESSR) and evaluated the contribution of each feature to the model’s predictions. A heatmap is also used to analyze the correlation among household variables and the ESSR. To evaluate the performance of the classification model, we used a confusion matrix showing a good F1 score (Weighted Avg) of 0.90. The findings discussed in this article offer valuable insights for energy policymakers to achieve the objective of developing energy-self-sufficient houses.

Microbial diversity estimation involves extracting nucleic acids from intricate sample matrices. Preparing nucleic acid samples is time-consuming, necessitating effective cell lysis and obtaining pure, inhibitor-free nucleic acid purifications before further use. An automated system offers advantages for field deployment due to its ease of use and quick autonomous results. This is especially beneficial for rapid measurement of in situ microbial diversity in remote areas. Our study aimed to assess microbial diversity of Yellowstone hot springs using a field-deployable lab in a resource-limited remote setting and demonstrate on-site nucleic acid sample processing and sequencing. We collected microbial mat and sediment samples from several Yellowstone National Park hot springs, focusing on the Five Sister Springs (FSS), spring LNN010, and Octopus Spring (OS). The samples were processed for DNA extraction on-site and further sequenced in the lab for microbial diversity. In addition, DNA extracted from one sample was sequenced and analyzed on-site as proof-of-concept. Using either Illumina or Oxford Nanopore Technology sequencing, we found similar microbial diversities. Bacteria (over 90%) were predominant at the FSS and OS sites, with archaea accounting for less than 10%. Metagenomic results were taxonomically categorized based on the closest known organism with a sequenced genome. The dominant archaeal community member was Candidatus Caldiarchaeum subterraneum, and among bacteria, Roseiflexus sp. RS-1 was abundant in mat samples. Interestingly, Bacterium HR17 was also frequently found, suggesting the need for more research on this newly recognized bacterial community member. The presence of Bacterium HR17 in these hot springs suggests its potential role in nitrogen cycling, informing both ecological understanding and industrial potential. This pioneering study assessed the microbiome of Yellowstone hot springs in about 8-9 hours using an automated system for nucleic acid extraction. By its deployment, the system’s value in elucidating the microbial diversity of extreme environments without the need to bring samples to the lab for processing had been highlighted. Sample processing and sequencing had been included in the benefits of the field-deployable lab, and the Nanopore platform had been utilized.

ABSTRACT Klebsiella species, such as Klebsiella pneumoniae, Klebsiella aerogenes, and Klebsiella quasipneumoniae, are opportunistic pathogens that commonly cause infections in humans. Hypervirulent Klebsiella pneumoniae (hvKP) is a subgroup of K. pneumoniae, which has gained attention due to its global dissemination, its capacity to cause invasive infections in community settings among immunocompetent individuals, and its escalating antibiotic resistance levels. Our study presents the first comprehensive phenotypic and genotypic analysis including mobile genetic elements (MGEs) of Klebsiella isolates from the International Space Station (ISS). The genomes of K. pneumoniae, K. aerogenes, and K. quasipneumoniae offered insights into their antimicrobial resistance, virulence, thermotolerance, disinfectant resistance, and MGEs. All isolates were part of emerging pathogenic lineages with K. quasipneumoniae ST138 presenting spatial and temporal persistence aboard the ISS, possibly due to its genotypic profile encoding for numerous resistance genes to disinfectants and heavy metals. We also report on the isolation of a yersiniabactin-encoding K. pneumoniae, belonging to the emerging high-risk ST101 clone, aboard the ISS. A potential dissemination of hvKp strains on ISS might pose a risk to the immunocompromised crew members. Moreover, MGEs containing virulent loci could enable horizontal gene transfer to other benign microorganisms on the ISS, possibly enhancing their virulence potential. Additionally, some Klebsiella genomes exhibited genetic divergence from their respective lineages, which we hypothesize results from the unique spaceflight associated environmental pressures. These findings underscore the need to monitor microbial communities in space to comprehend their survival mechanisms and implications for human health. IMPORTANCE The International Space Station (ISS) is a unique, hermetically sealed environment, subject to environmental pressures not encountered on Earth, including microgravity and radiation (cosmic ionising/UV). While bacteria's adaptability during spaceflight remains elusive, recent research suggests that it may be species and even clone-specific. Considering the documented spaceflight-induced suppression of the human immune system, a deper understanding of the genomics of potential human pathogens in space could shed light on species and lineages of medical astromicrobiological significance. In this study, we used hybrid assembly methods and comparative genomics to deliver a comprehensive genomic characterization of 10 Klebsiella isolates retrieved from the ISS. Our analysis unveiled that Klebsiella quasipneumoniae ST138 demonstrates both spatial and temporal persistence aboard the ISS, showing evidence of genomic divergence from its Earth-based ST138 lineage. Moreover, we characterized plasmids from Klebsiella species of ISS origin, which harbored genes for disinfectant resistance and enhanced thermotolerance, suggestin possible adaptive advantages. Furthermore, we identified a mobile genetic element containing a hypervirulence-associated locus belonging to a Klebsiella pneumoniae isolate of the “high-risk” ST101 clone. Our work provides insights into the adaptability and persistence of Klebsiella species during spaceflight, highlighting the importance of understanding the dynamics of potential pathogenic bacteria in such environments.

ABSTRACT: Objectives: Kalamiella piersonii is a newly identified bacterial species, first isolated from surfaces of the International Space Station (ISS). It also appears as a novel human pathogen reported to be implicated in bacteremia and kidney stone disease. Here, we report the first complete genome of a multidrug-resistant strain of K. piersonii (GABEKP28), isolated from the saliva of a patient with treatment-resistant schizophrenia (TRS), to determine the mobile genetic elements (MGEs), antibiotic resistance genes (ARGs), and virulence factors (VFs) harboured by such a strain of this novel species. Methods: Whole-genome sequencing was performed using DNABSEQ (PE150) and Nanopore MinION platforms. Hybrid assembly was conducted using Unicycler v0.5.0. Genome assembly quality was verified using QUAST v5.0.2. The assembly was annotated using PROKKA v1.14.5. ARGs and VFs were identified using Abricate v1.0.0. Results: K. piersonii strain GABEKP28 was classified as multidrug-resistant while also carrying plasmidic genetic determinants associated with a hypervirulent phenotype. The complete genome size is 3 881 479 bp and has a guanine-cytosine content of 57.76% while it encodes for 3 525 chromosome coding sequences. The strain was also identified to carry three plasmids of 513 647 bp, 261 771 bp, and 106 029 bp, respectively. Conclusions: K.piersonii GABEKP28 is the first complete genome of this species to be submitted to GenBank and only the second to be sequenced from a human host. The whole-genome sequencing data with multiple plasmids, ARGs, and VFs will aid in understanding the pathogenicity, evolution, and phylogeny of this novel opportunistic pathogen.

Abstract Background Recent studies have provided insights into the persistence and succession of microbes aboard the International Space Station (ISS), notably the dominance of Klebsiella pneumoniae. However, the interactions between the various microbes aboard the ISS and how they shape the microbiome remain to be clearly understood. In this study, we apply a computational approach to predict possible metabolic interactions in the ISS microbiome and shed further light on its organization. Results Through a combination of a systems-based graph-theoretical approach, and a constraint-based community metabolic modeling approach, we demonstrated several key interactions in the ISS microbiome. These complementary approaches provided insights into the metabolic interactions and dependencies present amongst various microbes in a community, highlighting key interactions and keystone species. Our results showed that the presence of K. pneumoniae is beneficial to many other microorganisms it coexists with, notably those from the Pantoea genus. Species belonging to the Enterobacteriaceae family were often found to be the most beneficial for the survival of other microorganisms in the ISS microbiome. However, K. pneumoniae was found to exhibit parasitic and amensalistic interactions with Aspergillus and Penicillium species, respectively. To prove this metabolic prediction, K. pneumoniae and Aspergillus fumigatus were co-cultured under normal and simulated microgravity, where K. pneumoniae cells showed parasitic characteristics to the fungus. The electron micrography revealed that the presence of K. pneumoniae compromised the morphology of fungal conidia and degenerated its biofilm-forming structures. Conclusion Our study underscores the importance of K. pneumoniae in the ISS, and its potential positive and negative interactions with other microbes, including potential pathogens. This integrated modeling approach, combined with experiments, demonstrates the potential for understanding the organization of other such microbiomes, unravelling key organisms and their interdependencies. Video Abstract

This paper aims to enhance the capacitance of electroactive polymer (EAP)-based strain sensors. The enhancement in capacitance was achieved by using a free-standing stretchable polymer film while introducing conducting polymer to fabricate a hybrid dielectric film with controlled conductivity. In this work, styrene-ethylene-butylene-styrene (SEBS) rubber was used as the base material, and dodecyl benzene sulfonate anion (DBSA)-doped polyaniline (PANI) was used as filler to fabricate a hybrid composite conducting film. The maleic anhydride group of the SEBS Rubber and DBSA, the anion of the polyaniline dopant, make a very stable dispersion in Toluene and form a free-standing stretchable film by solution casting. DBSA-doped polyaniline increased the conductivity and dielectric constant of the dielectric film, resulting in a significant enhancement in the capacitance of the EAP-based strain sensor. The sensor presented in this article exhibits capacitance values ranging from 24.7 to 100 µF for strain levels ranging from 0 to 100%, and sensitivity was measured 3 at 100% strain level.

This paper aims to develop a machine-learning model based on a gradient-boosting algorithm to predict the energy-saving awareness of households using a questionnaire survey and 11-month energy data collected from more than 200 smart houses in Kitakyushu, Japan. We utilize the LightGBM (light gradient boosting machine) classifier to perform feature selection for the prediction. By using this approach, we demonstrate that the key features are the standard deviations of electricity purchased between 8 a.m. and 9 a.m. and electricity consumed between 7 p.m. and 9 p.m. Next, by using k-means clustering we split the households based on the obtained features into three groups. Finally, by using statistical hypothesis testing, we prove that these three groups have statistically distinct levels of energy-saving awareness. This model enables us to detect eco-friendly households from their energy data, which may support energy policymaking.

Ensuring biological cleanliness while assembling and launching spacecraft is critical for robotic exploration of the solar system. To date, when preventing forward contamination of other celestial bodies, NASA Planetary Protection policies have focused on endospore-forming bacteria while fungi were neglected. In this study, for the first time the mycobiome of two spacecraft assembly facilities at Jet Propulsion Laboratory (JPL) and Kennedy Space Center (KSC) was assessed using both cultivation and sequencing techniques. To facilitate enumeration of viable fungal populations and downstream molecular analyses, collected samples were first treated with chloramphenicol for 24 h and then with propidium monoazide (PMA). Among cultivable fungi, 28 distinct species were observed, 16 at JPL and 16 at KSC facilities, while 13 isolates were potentially novel species. Only four isolated species Aureobasidium melanogenum, Penicillium fuscoglaucum, Penicillium decumbens, and Zalaria obscura were present in both cleanroom facilities, which suggests that mycobiomes differ significantly between distant locations. To better visualize the biogeography of all isolated strains the network analysis was undertaken and confirmed higher abundance of Malassezia globosa and Cyberlindnera jadinii. When amplicon sequencing was performed, JPL-SAF and KSC-PHSF showed differing mycobiomes. Metagenomic fungal reads were dominated by Ascomycota (91%) and Basidiomycota (7.15%). Similar to amplicon sequencing, the number of fungal reads changed following antibiotic treatment in both cleanrooms; however, the opposite trends were observed. Alas, treatment with the antibiotic did not allow for definitive ascribing changes observed in fungal populations between treated and untreated samples in both cleanrooms. Rather, these substantial differences in fungal abundance might be attributed to several factors, including the geographical location, climate and the in-house cleaning procedures used to maintain the cleanrooms. This study is a first step in characterizing cultivable and viable fungal populations in cleanrooms to assess fungal potential as biocontaminants during interplanetary explorations. The outcomes of this and future studies could be implemented in other cleanrooms that require to reduce microbial burden, like intensive care units, operating rooms, or cleanrooms in the semiconducting and pharmaceutical industries.

The field of human space travel is in the midst of a dramatic revolution. Upcoming missions are looking to push the boundaries of space travel, with plans to travel for longer distances and durations than ever before. Both the National Aeronautics and Space Administration (NASA) and several commercial space companies (e.g., Blue Origin, SpaceX, Virgin Galactic) have already started the process of preparing for long-distance, long-duration space exploration and currently plan to explore inner solar planets (e.g., Mars) by the 2030s. With the emergence of space tourism, space travel has materialized as a potential new, exciting frontier of business, hospitality, medicine, and technology in the coming years. However, current evidence regarding human health in space is very limited, particularly pertaining to short-term and long-term space travel. This review synthesizes developments across the continuum of space health including prior studies and unpublished data from NASA related to each individual organ system, and medical screening prior to space travel. We categorized the extraterrestrial environment into exogenous (e.g., space radiation and microgravity) and endogenous processes (e.g., alteration of humans’ natural circadian rhythm and mental health due to confinement, isolation, immobilization, and lack of social interaction) and their various effects on human health. The aim of this review is to explore the potential health challenges associated with space travel and how they may be overcome in order to enable new paradigms for space health, as well as the use of emerging Artificial Intelligence based (AI) technology to propel future space health research.

In recent years, combining hydrogels with nanozymes has shown promise as a platform for sensing applications. Nanozymes are simple, affordable, and stable alternatives that use enzyme-like capabilities. Conversely, hydrogels provide hydrated, biocompatible environments, which enhance the stability and activity of nanozymes. The most recent advancements in nanozyme-hydrogel hybrid sensing systems are examined in this study, with a focus on their enzymatic activities—peroxidase and oxidase mimetics—and how they can be used to detect a variety of analytes, such as glucose, pesticide, and many more.In addition to simulating the biological environment, the synergistic combination of hydrogels and nanozyme improves the biosensor's sensitivity, specificity, and fast reaction times. These hybrid systems also provide an extensible framework for integrating multiple sensory modalities into a single functional device. This review highlights the groundbreaking potential and uses of hydrogel sensors based on nanozymes in environmental and medical diagnostics and potential future developments.

High soil salinity has an unfavorable consequence on the growth and productivity of rice crop. However, some salt-tolerant plant growth-promoting bacteria (ST-PGPB) regulate specific physiological, biochemical, and molecular properties to promote crop growth while minimizing the detrimental effects of salt stress. In this regard, we isolated ST-PGPB from rhizospheric soil and examined it to mitigate the salinity stress in rice seedlings. The growth of the bacterium at 3 M NaCl demonstrated its halotolerance, and 16S rRNA sequencing identified it as Bacillus siamensis, and the isolated strain was named BW. Further study indicated that biopriming with BW strain helps plant growth promotion-related phenotype and significantly mitigates salinity stress in rice seedlings. Treatment of rice seeds with BW resulted in significantly improved germination of seedlings at 75 mM to 150 mM NaCl, along with better physiology and biochemical parameters than the untreated ones. Furthermore, Bacillus sp. BW efficiently colonizes rice roots and produces auxin and siderophore, via forming biofilm under different salt concentrations. Under 100–200 mM NaCl treatment conditions, the extracellular metabolite profile from BW showed a substantial abundance in specific metabolites, such as osmoprotective chemicals, suggesting the likely protective mechanism against salinity stress damage. This study demonstrates the role and potential of a halotolerant- BW strain in supporting the growth of rice plants under salinity conditions.

Sepsis is a critical disease caused by the abrupt increase of bacteria in human blood, which subsequently causes a cytokine storm. Early identification of bacteria is critical to treating a patient with proper antibiotics to avoid sepsis. However, conventional culture-based identification takes a long time. Polymerase chain reaction (PCR) is not so successful because of the complexity and similarity in the genome sequence of some bacterial species, making it difficult to design primers and thus less suitable for rapid bacterial identification. To address these issues, several new technologies have been developed. Recent advances in nanotechnology have shown great potential for fast and accurate bacterial identification. The most promising strategy in nanotechnology involves the use of nanoparticles, which has led to the advancement of highly specific and sensitive biosensors capable of detecting and identifying bacteria even at low concentrations in very little time. The primary drawback of conventional antibiotics is the potential for antimicrobial resistance, which can lead to the development of superbacteria, making them difficult to treat. The incorporation of diverse nanomaterials and designs of nanomaterials has been utilized to kill bacteria efficiently. Nanomaterials with distinct physicochemical properties, such as optical and magnetic properties, including plasmonic and magnetic nanoparticles, have been extensively studied for their potential to efficiently kill bacteria. In this review, we are emphasizing the recent advances in nano-biotechnologies for bacterial identification and anti-bacterial properties. The basic principles of new technologies, as well as their future challenges, have been discussed.