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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.

Summary: Microbial research in space is being conducted for almost 50 years now. The closed system of the International Space Station (ISS) has acted as a microbial observatory for the past 10 years, conducting research on adaptation and survivability of microorganisms exposed to space conditions. This adaptation can be either beneficial or detrimental to crew members and spacecraft. Therefore, it becomes crucial to identify the impact of two primary stress conditions, namely, radiation and microgravity, on microbial life aboard the ISS. Elucidating the mechanistic basis of microbial adaptation to space conditions aids in the development of countermeasures against their potentially detrimental effects and allows us to harness their biotechnologically important properties. Several microbial processes have been studied, either in spaceflight or using devices that can simulate space conditions. However, at present, research is limited to only a few microorganisms, and extensive research on biotechnologically important microorganisms is required to make long-term space missions self-sustainable.

BackgroundWith increasing numbers of interplanetary missions, there is a need to establish robust protocols to ensure the protection of extraterrestrial planets being visited from contamination by terrestrial life forms. The current study is the first report comparing the commercial resupply vehicle (CRV) microbiome with the International Space Station (ISS) microbiome to understand the risks of contamination, thus serving as a model system for future planetary missions.ResultsSamples obtained from the internal surfaces and ground support equipment of three CRV missions were subjected to various molecular techniques for microbial diversity analysis. In total, 25 samples were collected with eight defined locations from each CRV mission prior to launch. In general, the internal surfaces of vehicles were clean, with an order of magnitude fewer microbes compared to ground support equipment. The first CRV mission had a larger microbial population than subsequent CRV missions, which were clean as compared to the initial CRV locations sampled. Cultivation assays showed the presence of Actinobacteria, Proteobacteria, Firmicutes, and Bacteroidetes and members of Ascomycota and Basidiomycota. As expected, shotgun metagenome analyses revealed the presence of more microbial taxa compared to cultivation-based assays. The internal locations of the CRV microbiome reportedly showed the presence of microorganisms capable of tolerating ultraviolet radiation (e.g., Bacillus firmus) and clustered separately from the ISS microbiome.ConclusionsThe metagenome sequence comparison of the CRV microbiome with the ISS microbiome revealed significant differences showing that CRV microbiomes were a negligible part of the ISS environmental microbiome. These findings suggest that the maintenance protocols in cleaning CRV surfaces are highly effective in controlling the contaminating microbial population during cargo transfer to the ISS via the CRV route.

Abstract Background The International Space Station (ISS) is an ideal test bed for studying the effects of microbial persistence and succession on a closed system during long space flight. Culture-based analyses, targeted gene-based amplicon sequencing (bacteriome, mycobiome, and resistome), and shotgun metagenomics approaches have previously been performed on ISS environmental sample sets using whole genome amplification (WGA). However, this is the first study reporting on the metagenomes sampled from ISS environmental surfaces without the use of WGA. Metagenome sequences generated from eight defined ISS environmental locations in three consecutive flights were analyzed to assess the succession and persistence of microbial communities, their antimicrobial resistance (AMR) profiles, and virulence properties. Metagenomic sequences were produced from the samples treated with propidium monoazide (PMA) to measure intact microorganisms. Results The intact microbial communities detected in Flight 1 and Flight 2 samples were significantly more similar to each other than to Flight 3 samples. Among 318 microbial species detected, 46 species constituting 18 genera were common in all flight samples. Risk group or biosafety level 2 microorganisms that persisted among all three flights were Acinetobacter baumannii, Haemophilus influenzae, Klebsiella pneumoniae, Salmonella enterica, Shigella sonnei, Staphylococcus aureus, Yersinia frederiksenii, and Aspergillus lentulus. Even though Rhodotorula and Pantoea dominated the ISS microbiome, Pantoea exhibited succession and persistence. K. pneumoniae persisted in one location (US Node 1) of all three flights and might have spread to six out of the eight locations sampled on Flight 3. The AMR signatures associated with β-lactam, cationic antimicrobial peptide, and vancomycin were detected. Prominent virulence factors were cobalt-zinc-cadmium resistance and multidrug-resistance efflux pumps. Conclusions There was an increase in AMR and virulence gene factors detected over the period sampled, and metagenome sequences of human pathogens persisted over time. Comparative analysis of the microbial compositions of ISS with Earth analogs revealed that the ISS environmental surfaces were different in microbial composition. Metagenomics coupled with PMA treatment would help future space missions to estimate problematic risk group microbial pathogens. Cataloging AMR/virulence characteristics, succession, accumulation, and persistence of microorganisms would facilitate the development of suitable countermeasures to reduce their presence in the closed built environment.

Abstract A comparison of the linear and non-linear regression method in selecting the optimum isotherm among three most commonly used adsorption isotherms (Langmuir, Freundlich, and Redlich–Peterson) was made to the experimental data of fluoride (F) sorption onto Bio-F at a solution temperature of 30 ± 1 °C. The coefficient of correlation ( $$r^{2}$$ r 2 ) was used to select the best theoretical isotherm among the investigated ones. A total of four Langmuir linear equations were discussed and out of which linear form of most popular Langmuir-1 and Langmuir-2 showed the higher coefficient of determination (0.976 and 0.989) as compared to other Langmuir linear equations. Freundlich and Redlich–Peterson isotherms showed a better fit to the experimental data in linear least-square method, while in non-linear method Redlich–Peterson isotherm equations showed the best fit to the tested data set. The present study showed that the non-linear method could be a better way to obtain the isotherm parameters and represent the most suitable isotherm. Redlich–Peterson isotherm was found to be the best representative ( $$r^{2}$$ r 2 = 0.999) for this sorption system. It is also observed that the values of $$\beta$$ β are not close to unity, which means the isotherms are approaching the Freundlich but not the Langmuir isotherm.

The genus Acinetobacter consists of 31 validly published species ubiquitously distributed in nature and primarily associated with nosocomial infection. We report the 4.4 Mb genome of Acinetobacter gerneri strain MTCC 9824T. The genome has a G + C content of 38.0% and includes 3 rRNA genes (5S, 23S16S) and 64 aminoacyl-tRNA synthetase genes.

The genus Acinetobacter consists of 31 validly published species ubiquitously distributed in nature and primarily associated with nosocomial infection. We report the 3.4 Mb genome of Acinetobacter haemolyticus strain MTCC 9819T. The genome has a G + C content of 40.0% and includes 3 rRNA genes (5S, 23S, 16S) and 65 aminoacyl-tRNA synthetase genes.

The genus Acinetobacter consists of 31 validly published species ubiquitously distributed in nature and primarily associated with nosocomial infection. We report 4.3 Mb genome of the Acinetobacter gyllenbergii strain MTCC 11365T. The draft genome of A. gyllenbergii has a G + C content of 41.0% and includes 3 rRNA genes (5S, 23S, 16S) and 67 aminoacyl-tRNA synthetase genes.

The genus Acinetobacter consists of 31 validly published species ubiquitously distributed in nature and primarily associated with nosocomial infection. We report the 4.8 Mb genome of Acinetobacter guillouiae MSP 4-18, isolated from a mangrove soil sample from Parangipettai (11°30′N, 79°47′E), Tamil Nadu, India. The draft genome of A. guillouiae MSP 4-18 has a G + C content of 38.0% and includes 3 rRNA genes (5S, 23S, 16S) and 69 aminoacyl-tRNA synthetase genes.

The genus Acinetobacter consists of 31 validly published species ubiquitously distributed in nature and primarily associated with nosocomial infection. We report the 3.5 Mb draft genome of the Acinetobacter junii strain MTCC 11364. The genome has a G + C content of 38.0% and includes 3 rRNA genes (5S, 23S, 16S) and 64 aminoacyl-tRNA synthetase genes.

Following publication of the original article [1], the authors reported a typographic error in scientific notation in the number of reads, the text should read as:

Growing numbers of studies employ cell line-based systematic short interfering RNA (siRNA) screens to study gene functions and to identify drug targets. As multiple sources of variations that are unique to siRNA screens exist, there is a growing demand for a computational tool that generates normalized values and standardized scores. However, only a few tools have been available so far with limited usability. Here, we present siMacro, a fast and easy-to-use Microsoft Office Excel-based tool with a graphic user interface, designed to process single-condition or two-condition synthetic screen datasets. siMacro normalizes position and batch effects, censors outlier samples, and calculates Z-scores and robust Z-scores, with a spreadsheet output of >120,000 samples in under 1 minute.

BACKGROUND: The ectoparasitic mite, Varroa destructor, is considered to be one of the most significant threats to apiculture around the world. Chemical cues are known to play a significant role in the host-finding behavior of Varroa. The mites distinguish between bees from different task groups, and prefer nurses over foragers. We examined the possibility of disrupting the Varroa--honey bee interaction by targeting the mite's olfactory system. In particular, we examined the effect of volatile compounds, ethers of cis 5-(2'-hydroxyethyl) cyclopent-2-en-1-ol or of dihydroquinone, resorcinol or catechol. We tested the effect of these compounds on the Varroa chemosensory organ by electrophysiology and on behavior in a choice bioassay. The electrophysiological studies were conducted on the isolated foreleg. In the behavioral bioassay, the mite's preference between a nurse and a forager bee was evaluated. PRINCIPAL FINDINGS: We found that in the presence of some compounds, the response of the Varroa chemosensory organ to honey bee headspace volatiles significantly decreased. This effect was dose dependent and, for some of the compounds, long lasting (>1 min). Furthermore, disruption of the Varroa volatile detection was accompanied by a reversal of the mite's preference from a nurse to a forager bee. Long-term inhibition of the electrophysiological responses of mites to the tested compounds was a good predictor for an alteration in the mite's host preference. CONCLUSIONS: These data indicate the potential of the selected compounds to disrupt the Varroa--honey bee associations, thus opening new avenues for Varroa control.

A Gram-positive, yellowish bacterium strain AK-1T was isolated from soil sample collected from peanut (Arachis hypogaea) crop field and studied by using a polyphasic approach. The organism had morphological and chemotaxonomic properties consistent with its classification in the genus Agromyces. Phylogenetic analysis of the 16S rRNA gene sequence showed that strain AK-1T was closely related to Agromyces aurantiacus (98.6%) followed by Agromyces soli (98.3%), Agromyces tropicus (97.6%), Agromyces ulmi (97.3%), Agromyces flavus (97.2%), and Agromyces italicus (97.0%), whereas the sequence similarity values with respect to the other Agromyces species with validly published names were between 95.3 and 96.7 %. However, the DNA-DNA hybridization values obtained between strain AK-1T and other related strains were well below the threshold that is required for the proposal of a novel species. The DNA G+C content of the strain is 71.8 mol%. The above data in combination with the phenotypic distinctiveness of AK-1T clearly indicate that the strain represents a novel species, for which the name Agromyces arachidis sp. nov. is proposed. The type strain is AK-1T (=MTCC 10524T = JCM 19251T).

Silkworm, Bombyx mori, vitellogenin (Vg) was isolated from perivisceral fat body of day 3 of pupa. Both Vg subunits were co-purified as verified by mass spectrometry and immunoblot. Purified Vg responded to specific tests for major posttranslational modifications on native gels indicating its nature as lipo-glyco-phosphoprotein. The Vg fraction had strong antibacterial activity against Gram negative bacterium Escherichia coli and Gram positive bacterium Bacillus subtilis. Microscopic images showed binding of Vg to bacterial cells and their destruction. When infected silkworm larvae were treated with purified Vg they survived the full life cycle in contrast to untreated animals. This result showed that Vg has the ability to inhibit the proliferation of bacteria in the silkworm fluid system without disturbing the regular metabolism of the host.