Journal of Microbiological Methods

Yarrowia lipolytica is a yeast of industrial interest exhibiting remarkable lipolytic and proteolytic capacities, with a high potential for white biotechnology applications. This yeast can be isolated from a wide range of natural, polluted or anthropogenic environments, including various food products. The present study aims to increase the data on Y. lipolytica phenotypic diversity by evaluating the growth parameters and secreted enzymatic activities of 28 wild-type Y lipolytica (and Yarrowia sp.) strains isolated from various environments across 10 countries. These data could facilitate the selection of appropriate strains for specific research purposes, particularly when wild-type strains are prioritized over genetically engineered ones, like for food-related applications. Notably, strain SWJ-1b exhibited an outstanding combination of favourable characteristics, with optimum (or near) performances for both growth and enzymatic parameters.

Yeasts ability to invade surfaces has important implications for infections and food contamination. Invasive growth in yeast is influenced by genetic and environmental factors. In this exploratory study, we investigated the effects of sodium sulfide, gene deletions, and environmental conditions on the invasive behaviour of the wine yeast strain AWRI 796. Sodium sulfide enhanced invasion in the (parent) AWRI 796 strain under nitrogen-limiting conditions, although its effect was obscured by experimental variability and pre-culture conditions. Genetic factors had a major effect on the overall invasive phenotype, with deletion of key genes suppressing invasion. Most gene-deletion mutants did not significantly affect how the colony responded to sulfide. In addition to sulfide and genotype, environmental conditions also influenced invasive behaviour. The pre-2xSLAD pre-culture condition was best for detecting sulfide-induced growth, and later plate washing time and decreased nutrient levels enhanced invasiveness. Our experimental design and findings provide a framework for understanding the determinants of yeast invasiveness, which may inform future studies on filamentous yeast behaviour.

Rock-inhabiting fungi thrive in subaerial oligotrophic environments such as desert rocks, solar panels and marble monuments where organic carbon and nitrogen are scarce. We tested whether the rock-inhabiting fungus Knufia petricola showed a preference regarding nitrogen ([Formula] or [Formula]) and carbon (glucose or sucrose) sources and whether it was sensitive towards carbon and nitrogen limitation. As this fungus produces the carbon-rich, nitrogen-free 1,8-dihydroxynaphthalene (DHN) melanin, we tested whether a melanin-deficient mutant would be less sensitive to carbon limitation. The carbon and nitrogen concentrations were the primary predictors of growth, with a broad optimum partially explained by an optimal fungal C:N ratio. Limiting carbon or nitrogen supply decreased biomass formation, CO2 production and biofilm thickness but promoted substratum penetration through filamentous growth. The nitrogen content of the biomass was flexible within limits, increasing upon increasing nitrogen supply or decreasing carbon supply. The carbon use efficiency was fairly constant, whereas melanization correlated with a higher nitrogen content of the biomass despite melanin being nitrogen-free. In conclusion, in vitro, K. petricola switches to explorative growth under nutrient limitations, like fast-growing fungi, revealing universal fungal resource-acquisition patterns. Graphical abstract text and imageCarbon and nitrogen availability affect biofilm growth and morphology of the extremotolerant fungus Knufia petricola Abolfazl Dehkohneh, Julia Schumacher, Bastiaan J. R. Cockx, Karin Keil, Tessa Camenzind, Jan-Ulrich Kreft, Anna A. Gorbushina, Ruben Gerrits Growth of the rock-inhabiting fungus Knufia petricola was studied by varying carbon and nitrogen sources and concentrations. Overall, growth was best predicted by the carbon and nitrogen concentrations. Carbon and nitrogen limitation promoted substratum penetration through filamentous growth. O_FIG O_LINKSMALLFIG WIDTH=158 HEIGHT=200 SRC="FIGDIR/small/712823v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@6d98bdorg.highwire.dtl.DTLVardef@146aac5org.highwire.dtl.DTLVardef@757fa8org.highwire.dtl.DTLVardef@ff709_HPS_FORMAT_FIGEXP M_FIG C_FIG

Phytophthora species are globally significant soilborne oomycetes responsible for widespread ecosystem decline. Standard soil sampling protocols, originally developed for qualitative baiting assays, typically require collecting substantial soil volumes in order to capture viable propagules. While effective for culture-based detection, these protocols are labour-intensive and can damage the shallow root systems of sensitive host species such as New Zealand kauri (Agathis australis). Phytophthora agathidicida (PA), the pathogen associated with kauri dieback disease, is routinely surveyed using these methods. However, quantitative data describing the vertical distribution of PA in natural forest soils are lacking. Consequently, it remains unclear whether extensive depth sampling is necessary to ensure consistent molecular detection. In this study, we applied a quantitative oospore DNA (oDNA) qPCR assay to characterise the fine-scale vertical distribution of PA across four soil depth increments (0-5, 5-10, 10-15, 15-20 cm) from 12 kauri trees representing a range of disease stages. Results revealed distinct vertical stratification, with PA DNA concentrations peaking within the upper 0-10 cm of soil in non-symptomatic and possibly symptomatic trees. In symptomatic trees, the absolute peak occasionally reached 10-15 cm, while pathogen signals remained consistently detectable within the top 10 cm. Field validation from an additional eight trees confirmed that targeted 0-10 cm "shallow" sampling yielded higher PA concentrations than deeper sampling protocols. These findings provide a data-driven basis for refining soil sampling strategies, enabling more sensitive molecular detection while minimising disturbance and logistical effort in fragile ecosystems. IMPORTANCEPhytophthora species are among the most destructive soilborne pathogens globally, requiring robust diagnostic protocols for both agricultural and conservation settings. Traditional sampling frameworks were established to meet the biological requirements of baiting assays, which often necessitate collecting large soil volumes from broad depth profiles to ensure the capture of viable, infectious propagules. However, these extensive requirements are labour-intensive and can cause significant soil disturbance in sensitive forest ecosystems. Using P. agathidicida as a model, this study provides a high-resolution quantitative assessment of how pathogen DNA is distributed vertically across different disease stages. We demonstrate that while absolute peak abundance can shift within the 0-15 cm range as infection progresses, the pathogen signal remains consistently detectable within the top 10 cm. This evidence-based approach suggests that targeted, shallow sampling enhances sensitivity by reducing signal dilution, offering a lower-impact path for monitoring soilborne oomycetes worldwide.

As human space exploration expands to the Moon, Mars, and beyond, there is a growing need to study the effects of altered gravity on the microbial systems that we will bring with us for life support. Because spaceflight experiment opportunities are rare and resource-intensive, most space biology experiments are conducted using ground-based simulators. The most common microgravity simulator for microbial experiments, the rotating wall vessel, can approximate the low-shear and low-turbulence conditions that characterize microgravity. However, current designs do not allow for real-time measurement of growth or metabolic activity during rotation: experiments require destructive sampling or disruption of the microgravity simulation conditions. Here, we describe the development of an in situ spectroscopy system compatible with the Cell Spinpod rotating wall vessel, which enables measurement of both optical absorbance and fluorescence with high temporal resolution, producing growth curves similar to those from an off-the-shelf plate reader. These results are validated using two common microbial hosts: Escherichia coli and Saccharomyces cerevisiae. The Spinpod Optical System has the potential to diversify the types of microbiology experiments possible in simulated microgravity, allowing the measurement of not only growth curve parameters but also metabolic activity, gene expression, or community dynamics. It thus has the potential to improve the quality of experiments seeking to characterize microbial responses to spaceflight conditions.

To make effective antimicrobial toothpastes, you need to optimize many parts that work together. Creating new formulations the old-fashioned way takes a lot of time and money. This research formulates and substantiates a methodological framework that combines systematic antimicrobial susceptibility testing with Particle Swarm Optimization (PSO) to enhance toothpaste formulations against clinically significant oral pathogens. Using a D-optimal mixture design, we made 24 different toothpaste formulations by changing the type of fluoride (NaF, MFP, SnF2), the concentration of fluoride (1000-1500 ppm), the concentration of SLS (0.5-2.5%), the type of abrasive (silica, calcium carbonate, dicalcium phosphate), and the concentration of abrasive (10-30%). We used agar well diffusion and minimum inhibitory concentration (MIC) tests to see how well the drugs worked against Streptococcus mutans ATCC 25175, Porphyromonas gingivalis ATCC 33277, and Lactobacillus acidophilus ATCC 4356. A Random Forest surrogate model was trained on 120 experimental data points (24 formulations x 5 concentrations) and validated through 10-fold cross-validation. Multi-objective PSO was used to improve the effectiveness of antimicrobials, the availability of fluoride, and the cost of the formulation. Chosen PSO-predicted formulations underwent experimental validation. The antimicrobial activity changed a lot (p < 0.001) depending on the formulation parameters. The optimized formulation (sodium fluoride 1120 ppm, SLS 2.3%, hydrated silica 18%, pH 7.2) showed 28.4 {+/-} 1.2 mm of inhibition against S. mutans, 26.8 {+/-} 1.4 mm against P. gingivalis, and 24.2 {+/-} 1.1 mm against L. acidophilus. These were improvements of 18.5%, 22.3%, and 19.8%, respectively, over the best commercial comparator. Experimental validation corroborated PSO predictions with a mean absolute error of 5.2%. Multi-objective Optimization found Pareto-optimal formulations that let you choose based on trade-offs between effectiveness, safety, and cost. Combining systematic experimental design with PSO gives a tested framework for making rational toothpaste formulations. This method significantly lowers the amount of work needed for experiments while also allowing for the Optimization of multiple competing formulation goals.

Leaf diseases pose a serious threat to faba bean production. Leaf blotch of faba bean, caused by Alternaria spp., has become increasingly widespread and destructive in several countries. Leaf diseases pose a serious threat to faba bean production. The infection of plant by pathogens can be influenced by various factors associated with the host plant, environmental conditions and presence of other microorganisms. The phyllosphere and endosphere play a critical role in plant health and disease development. This study aimed to evaluate the factors shaping the structure and diversity of fungal communities associated with faba beans. Plant samples were collected in 2004 from two intensively managed faba bean production fields in the central region of Latvia. Fungal assemblages were characterized using an ITS region metabarcoding approach based on Illumina MiSeq sequencing. Among the assigned amplicon sequence variant (AVS), 65% belonged to the phylum Ascomycota, while approximately 4% were classified as Basidiomycota. Alternaria and Cladosporium were the dominant genera across samples. The alfa and beta diversities of fungal communities was higher during flowering of faba beans to compare with ripening. The higher abundance of Basidiomycota yeasts were observed during flowering, in contrast, Cladosporium genus was significantly more abundant during ripening. Alternaria DNA was found on leaves that showed no symptoms of the disease. The diversity and composition of fungal communities were significantly influenced by sampling time and presence of leaf blotch, caused by Alternaria spp.

Antimicrobial resistance (AMR) is a significant and growing threat to human, plant and animal health, the global economy, and food security. The One Health approach to AMR recognises the role of the environment in the evolution, emergence, and dissemination of AMR. In part, this is due to anthropogenic pollution that releases AMR organisms alongside cocktails of compounds that may select for AMR in situ, which then pose an exposure risk to humans and animals. This has spurred growing interest from cross-sectoral stakeholders in environmental risk assessment (ERA) of antibiotics, with regards to their selective potential. Many different experimental and modelling approaches have been used to determine the lowest concentration of an antibiotic that may select for AMR. Debates continue regarding which individual approach, if any, may be best for determining concentrations of antibiotics that may select for AMR, for ERA purposes. This paper contributes to this ongoing discourse by refining and using a previously published method SELECT (SELection Endpoints in Communities of bacTeria) to rapidly generate predicted no effect concentrations for resistance (PNECRs) for 32 antibiotics on the premise that reduction in growth of complex community of bacteria correlates with selection for AMR resistance genes. The database of PNECRs of antibiotics presented here is the largest generated using a single experimental, empirical approach that will aid future efforts towards creating a standardised test. PNECR data were used to conduct ERAs using measured environmental concentrations of antibiotics to rank antibiotics by potential selection risk in different environments. The experimental approach and statistical code have been made open access, with online tutorials available to facilitate other laboratories using the SELECT 2.0 method. Finally, we discuss the limitations of this approach and how these could be addressed in future studies.

Microbial communities play a central role in compost-bedded pack (CBP) systems by driving organic matter decomposition and nutrient cycling. The objective of this study was to characterize and compare the bacterial community structure of CBP from two dairy farms in Cordoba, Argentina, using 16S rRNA gene sequencing. Two CBP systems were evaluated: Martin Bono (MB; 30 months in operation) and Angela Teresa (AT; 20 months). The MB system was established on natural soil without bedding addition and included concrete feed alleys, whereas AT was initiated with peanut shell bedding and lacked concrete alleys. In both systems, compost was tilled twice daily. Two samples per farm were collected at a depth of 30 cm during winter 2019. Raw Illumina reads were processed using the DADA2 pipeline, including quality filtering, error modeling, denoising, and chimera removal. A total of four samples yielded 2,503 amplicon sequence variants (ASVs), with approximately 76% of reads retained after filtering and chimera removal, indicating high-quality sequencing data. Taxonomic analysis revealed that bacterial communities in both systems were dominated by phyla typically associated with compost environments, including Actinobacteriota, Proteobacteria, and Firmicutes. Differences in relative abundance between systems suggested shifts in community composition associated with management conditions.

Gastrointestinal disorder caused by the ingestion of (oo)cysts of Cryptosporidium and Giardia is one of the major health problems in developing countries. Fruits and vegetables that are usually consumed unpeeled, poorly washed and or cooked and are the major modes of transmission. Frequent large-scale screening of the food samples is necessary to prevent outbreaks but screening of vegetables for such microbes is limited in Nepal. In this study, we used a smartphone microscopy system to study prevalence and quantification of (oo)cysts of Cryptosporidium and Giardia in 651 vegetable samples collected from nine major vegetable collection sites across Nepal. The overall prevalence rate of vegetable samples was 37.5% with at least with one of the parasites. We found that 23.2% samples were contaminated with Giardia and 33.3% samples were contaminated with Cryptosporidium. Among eight vegetable types, the prevalence rate was lowest in carrot (20%) and highest in spinach (48%). The prevalence rate of vegetable samples at different sites ranged from 13% in Dhading to 61% in Dhangadi. The contamination rate was 28% for winter, 43% for summer and 33% for monsoon seasons in samples collected from Kathmandu. These vegetables should be considered as a potential source of parasitic contamination in people. These vegetables can cause infection if consumed poorly washed and or cooked, posing a potential source of parasitic contamination in people.

Multiplexing samples in long-read sequencing with Oxford Nanopore Next Generation Sequencing Technology (ONT) by ligating specific native barcodes to individual DNA samples enables significant increases of high throughput sequencing combined with a significant reduction of sequencing costs. However, this advantage carries the risk of barcode misassignment / crosstalk. Employing ONT multiplex sequencing with samples, we observed misassigned barcodes so called barcode crosstalk, after ONT library preparation according to the standard protocol, particularly in samples with low input DNA concentrations. We assumed that these barcode misassignments are largely due to misligation of remaining native barcodes during subsequent the subsequent sequencing adapter ligation. To systematically investigate and quantify barcode crosstalk, genomic DNA (gDNA) from four bacterial type strains with different DNA input concentrations was prepared using three protocols for library preparation: the Nanopore standard protocol (protocol A: version valid until July 2, 2025) the new Nanopore protocol (protocol B: version from July 2, 2025), and an in house protocol with pooling of the barcoded samples only after the sequencing adapter ligation step (protocol C: in house). All samples were sequenced on a Nanopore PromethIon device. The results clearly showed that the use of protocol A resulted in a pronounced barcode crosstalk especially detectable in samples with low DNA input concentrations (up to 2.4% misassigned reads). The ONT adjustment in protocol B (altered washing buffer vs. protocol A) significantly alleviated the barcode crosstalk to below 0.01%, whereas protocol C eliminated barcode crosstalk virtually completely. These observations emphasize that sequencing results obtained with older ONT native barcoding protocol variants should be critically reviewed. The newer ONT barcoding protocol is preferable for sequencing, but it does not completely eliminate the barcode crosstalk effect. In conclusion, for low DNA input and high accuracy sequencing, protocol C is recommended.

The Bacillus genus comprises physiologically versatile, endospore-forming bacteria widely distributed in natural environments. In this study, we report the isolation and genomic characterization of strain Bva_UNVM-123, recovered from agricultural soil in Pergamino, Argentina. Whole-genome sequencing using Illumina technology yielded a 5.1 Mbp draft genome assembled in 67 contigs with a GC content of 36%. Comparative genomic analyses using the TYGS server and digital DNADNA hybridization (dDDH) values supported its classification as a potentially novel species within the Bacillus sensu lato (s.l.) group. Genome annotation revealed 4,866 protein-coding genes, including multiple determinants conferring resistance to antibiotics (e.g., fosfomycin, tetracycline, beta-lactams) and toxic heavy metals (e.g., arsenic, cadmium, mercury), supporting its potential application in bioremediation. Additionally, PathogenFinder predicted a low probability of human pathogenicity (0.207), reinforcing its safety for environmental use. Functional classification based on Swiss-Prot further supported a metabolically versatile profile and revealed the presence of resistance-related categories associated with environmental adaptation. This study adds to the growing knowledge of environmental Bacillus species and their biotechnological potential

This study was aimed at characterizing the physicochemical analysis of stingless bees honey (SBH) in the Wonchi district, Southwest Shewa Zone, Ethiopia. In this study, a total of 30 stingless bees honey samples were collected from Damu Dagele, Fite Wato, and Warabu Messe sites from underground soils through an excavation of natural nests. Physicochemical characterization of properties and proximate analysis of the honey were performed. The result showed a total mean of 20.12{+/-}1.14% moisture content, 8.62{+/-}2.73 meq./kg free acidity, 1.8{+/-}0.52 mS/cm electrical conductivity, 3.39{+/-}0.32 pH, 40.52{+/-}6.61 mg/kg HMF, 0.83{+/-}0.33% ash, 0.56{+/-}0.25% protein, 0.56{+/-}0.24% fat, and 0.59{+/-}0.23% WISC for physicochemical properties of stingless bees honey. Among sugar profiles of SBH, fructose constituted the highest proportion at 18.87 g per 100 g (53.87%), while sucrose exhibited the lowest concentration at 5 g per 100 g (14.33%). The result showed that the highest constituted mean of mineral composition was observed with potassium (K) of 16.64{+/-}0.257 mg/kg, while magnesium (Mg) showed the lowest concentration of 3.48{+/-}0.17 mg/kg. A substantial correlation was observed between K and Mg, with a correlation coefficient of 0.72 and 0.72, and similarly between K and Calcium (Ca); the correlation was highly significant, exhibiting a correlation coefficient of 0.65. Furthermore, the correlation between fatty and other physicochemical and proximate analyses showed very insignificant correlations. In general, this study showed that the SBH produced in the current study area has good physicochemical properties and moisture and contains high-quality honey, which may help its traditional medicinal uses. The findings of the study further suggests the potentiality of the area for quality honey, and to easily locate priority areas for stingless bee conservation, further detailed studies of other stingless species honey medicinal values are recommended.

Antimicrobial resistance (AMR) presents a pressing need to ensure that the right antimicrobials are used to target the right microbes at the right time. Ideally, the appropriate antimicrobial is selected after patient samples have been cultured and assessed with antimicrobial sensitivity testing (AST). However, the time needed for culture-based diagnosis leads to immediate empirical treatment, often with broad-spectrum and/or high-tier antimicrobials. Direct nanopore metagenomic whole genome sequencing to identify pathogens and predict their antimicrobial resistance is a rapid and patient-side alternative. A limitation of this approach is potential inconsistencies in in silico predicted AMR phenotypes. Here, we benchmarked the current performance of in silico AMR prediction strategies for nanopore-generated long read data. Using nanopore data paired with AST phenotyping for 201 samples, we assessed the impact of basecalling mode, data volume, and assembly strategy, and compared the performance of eight in silico AMR prediction tools with seven AMR databases. We found that basecalling accuracy mode does not affect the overall accuracy of in silico AMR predictions, but assembly strategy and data volume both do. Prediction tools using the ResFinder database scored best for balanced accuracy (0.80 {+/-} 0.02 for both ResFinder and ABRicate), whilst DeepARG scored best for sensitivity (0.65 {+/-} 0.03). However, even the best performing in silico AMR prediction strategy missed some resistance identified by lab-based AST. In silico AMR prediction can therefore supplement lab-based AST, but cannot yet replace it. Impact statementAntimicrobial resistance (AMR) is threatening modern standards of human and veterinary healthcare. Rapid and patient-side diagnostic tests are needed to diagnose bacterial infections and allow clinicians to select effective antibiotics. Current tests based on bacterial cultures take several days, which may delay diagnosis and treatment, or lead to inappropriate "just in case" treatment while waiting for the results. In contrast, nanopore metagenomic whole genome sequencing can identify bacterial infections and predict which antibiotics will be effective in minutes to hours. However, the accuracy of these tests is uncertain. We therefore compared the performance of eight AMR prediction tools and seven databases of AMR determinants, using 201 bacterial samples with known antibiotic susceptibility and resistance. We found that the sensitivity (i.e. false negative rate), specificity (i.e. false positive rare) and overall accuracy of the tools and databases varied. In particular, even the best performing AMR prediction methods missed some AMR. Therefore, while these tools are useful for rapid and patient-side diagnosis and treatment decisions, they still have limitations and should be used alongside bacterial cultures and antibiotic sensitivity testing. Data summarySequencing data for the samples sequenced for this study are available at the NCBI under BioProject ID PRJNA1292816 (SRA accessions for all datasets used here are available in Supplementary Table S1). All commands and code used can be found at: https://github.com/nataliering/nanopore_AMR_tools/ The authors confirm all supporting data, code and protocols have been provided within the article or through supplementary data files.

Endocavity ultrasound transducers, particularly transvaginal ultrasound (TVUS) probes, contain intricate structures such as notches, grooves, lens surfaces, and handle edges that are highly susceptible to microbial contamination yet difficult to disinfect using conventional high-level disinfection (HLD) methods. This study evaluated the efficacy of a novel ultraviolet-C light-emitting diode (UV-C LED) HLD system in eliminating microbial contamination from these complex probe surfaces. Two TVUS probes were sampled from predefined high-risk regions before and after disinfection following clinical use. Probe A was sampled at the top and bottom notches and both sides of the handle, while Probe B was assessed at the lens, edges, and bent groove regions. Microbial contamination was quantified using swab sampling, culture on agar plates, and identification via MALDI-TOF. Environmental sampling of examination and disinfection rooms was also performed. To assess this system robustness, probe sites were repeatedly inoculated with Bacillus subtilis spores and evaluated following UV-C treatment. Before UV-C treatment, contamination rates ranged from 25% to 57% across sampled regions, with microbial loads reaching up to 3.9 log CFU. Identified organisms included Staphylococcus epidermidis, Pseudomonas koreensis, Bacillus cereus, and Propionibacterium spp. Probe sheaths were also predominantly contaminated with Staphylococcus epidermidis., with counts reaching up to 4.3 log CFU, Environmental sampling revealed diverse microbiota, with higher contamination levels in examination rooms compared to disinfection areas. Following 90 seconds of UV-C exposure, no microbial growth was detected on any sampled site, indicating 100% decontamination. Additionally, UV-C treatment achieved >6.7 log reduction of B. subtilis spores across all tested regions. These findings demonstrate that UV-C LED technology provides rapid, effective, and consistent high-level disinfection of complex TVUS probe surfaces, supporting its potential as a rapid and reliable disinfection modality in clinical setting.

Bacterial interactions-whether positive or negative - are crucial for the functioning of microbial communities. Though bacterial interactions are mainly expected to be negative, the sign and strength of interactions are predicted to be context dependent, with interactions typically being more positive in more stressful and nutrient-poor conditions. However, systematic studies investigating how the environment affects interactions between multiple taxa are lacking. Here, we determine if interactions between a panel of natural soil isolates change in response to the environment in which they are grown, with two different artificial media used (one simple and one complex) and a more ecologically relevant soil wash. To maximise natural variation in interactions, we collected multiple isolates from multiple sites: co-occurring (sympatric) isolates were predicted to show more negative interactions than allopatric isolates because of greater overlap in resource use. Pairwise interactions were in general negative, but more negative when grown in a complex lab-derived medium (Tryptic Soy Broth). Mutually beneficial interactions were most common in a simple resource medium (M9 minimal media) and exploitative interactions were most frequent in a soil broth. These patterns were independent of whether species originated from the same or a different site. The study supports the prediction that nutrient rich environments promote more negative interactions, and that measuring interactions of soil isolates in standard lab media is likely to misrepresent interactions occurring in natural environments.

The tobacco hornworm moth (Manduca sexta) is evaluated as a model of bacterial virulence and host-pathogen dynamics. Infections of Pseudomonas aeruginosa were established by injection of 5th-instar larvae, and multiple assays of virulence were evaluated. Infected larvae exhibited dose-dependent mortality, reduced growth, melanization, behavioral changes, and altered frass constitution. Even low-dose infections that were not fatal exhibited impaired growth, but individual growth trajectories revealed considerable heterogeneity among worms given the same dose. Twice-daily antibiotic treatment with gentamicin or cefepime improved survival four- to five-fold but did not rescue 100%. Heat-killed cells and filtered culture supernatant alone induced significant morbidity and mortality, suggesting secreted bacterial products are important to pathogenesis. Bacterial burden analysis revealed a shifting bacterial distribution over time, with decreasing hemolymph titers and increasing localization in fat body, gut, and carcass. Hornworms thus offer a more sensitive analysis of bacterial infection dynamics and consequences than do larvae of the more commonly used wax moth.

Industrial waste containing hydrophobic pollutants, like oils and hydrocarbons, is toxic and difficult to degrade, posing both ecological and human health risks. Biosurfactants are eco-friendly surface-active compounds produced by microorganisms, known for their ability to lower surface and interfacial tension, enhancing the solubility and bioavailability of hydrophobic compounds, facilitating their breakdown. The current study focuses on isolating biosurfactant-producing bacteria from industrial waste sources near Dhaka, Bangladesh, and characterizing their properties, determining potential usage. Using diesel-enriched nutrient agar, bacterial strains were isolated and screened for biosurfactant production by oil displacement, emulsification index (E24%), and drop collapse assay. The most promising isolates were characterized according to their biochemical activities and 16S rRNA amplicon-based sequencing. Isolation and characterization of the surfactants have been carried out using chromatographic techniques. The identified bacteria passed the drop collapse and oil displacement tests. CTAB agar assay, indicates their anionic nature, showing an emulsification index ranging 10-41%. The potential biosurfactant producers belong to Bacillus, Pseudomonas, Acinetobacter, and Enterobacterium genera. The surfactants showed antibacterial, antifungal, and plant growth promotion activity and have been characterized in terms of pH stability, salinity, adhesion, and temperature tolerance. The study successfully identified and characterized potential biosurfactant-producing bacteria from industrial waste, highlighting their efficiency in breaking down hydrophobic pollutants and hydrocarbons. These microorganisms provide a green and economical substitute for synthetic surfactants due to their biodegradability and lower toxicity. Upon further research and scaling, these bacteria can be a good source of biosurfactants for potential applications in industrial, agricultural, and biomedical fields. IMPORTANCEThe study carries high significance as it creates multi-disciplinary scopes for utilizing these environmentally adapted biosurfactant-producing bacteria in industry, agriculture, and medicine. Since the bacterial isolates have hydrocarbon degradation ability, upon optimization for higher production, industrial usage in oil refinery and other industries can be adopted. Due to their biodegradable nature, usage in wound healing bandages and as antimicrobial agents in medicine will be noteworthy. The isolates have plant growth promotion ability and utilizing them as biofertilizer will reduce the dependency on chemical fertilizers. This is the first detailed report on biosurfactant-producing bacteria from this industrial waste-polluted Turag River of Dhaka City. Moreover, it compiles detailed screening protocols and methods for analyzing such environmentally friendly microbes. Such characterization also opens the scope for optimizing the production of the surfactant compounds on a large scale and utilizing them commercially.

The global expansion of highly pathogenic avian influenza (HPAI) virus A(H5N1) underscores the need for rapid surveillance at high-risk wildlife interfaces. Taiaroa Head (45.7828{degrees} S, 170.7333{degrees} E) in the South Island of Aotearoa New Zealand hosts a plethora of aquatic wildlife including a large red-billed gull (Chroicocephalus novaehollandiae scopulinus) colony as well as the only mainland breeding colony of northern royal albatross (Diomedea sanfordi). The Royal Albatross Centre is also a major nature tourism destination, attracting tens of thousands of visitors annually, thereby creating a dense ecological and human-wildlife interface vulnerable to viral incursion. We evaluated the GeneXpert II platform using the Xpert(R) Xpress Flu/RSV cartridge as a field-deployable tool for avian influenza virus detection in environmental and wildlife-associated samples. The assay detected synthetic influenza A viral RNA and multiple endemic low pathogenic avian influenza virus subtypes (A(H3N8), A(H1N9), A(H5N2) and A(H7N7)) circulating in New Zealand birds. Influenza A virus was reliably identified in spiked environmental water samples with no consistent PCR inhibition as well as naturally occurring avian influenza virus in duck pond water. Field deployment demonstrated that the system could be operated by non-laboratory personnel with minimal training in a non-clinical setting. This study establishes the feasibility of near-real-time environmental monitoring. Repurposing clinical cartridge-based point-of-care diagnostics offers a practical early warning approach for avian influenza virus surveillance at ecologically and economically significant locations.

The auxin-inducible degron (AID) technology is a convenient and powerful tool for protein functional characterization in a broad array of eukaryotic species. We recently demonstrated that the original AID and improved AID2 systems are very effective at rapid protein depletion in Candida albicans and described a limited set of reagents for their use in certain auxotrophic lab strains. With an eye towards broader applicability with improved flexibility, we report here a new series of template vectors suitable for employing AID2 technology in prototrophic C. albicans strains, including clinical isolates. We adapted a common recyclable antibiotic marker system for the required genome editing steps and developed a strategy for simultaneous CRISPR/Cas9-mediated tagging of both target alleles. We also developed a composite all-in-one tagging cassette that combines the degron tag and the OsTIR1F74A gene for single step strain engineering. We added a fluorescent protein tag option and designed and validated an approach for N-terminal tagging that retains natural promoter control. We also compared effectiveness of the two commonly used synthetic auxins, 5-Ph-IAA and 5-Ad-IAA and the two common OsTIR1 variants, F74A and F74G, and provide guidelines for using the new AID2 system. Finally, using the novel all-in-one cassette, we demonstrate that the AID2 system also works in Candida auris. The new reagents should enhance the convenience and accessibility of the AID2 system for the Candida research community. IMPORTANCEInvasive fungal infections, including those caused by Candida species, are a persistent global health problem, and their treatment is hindered by limited antifungal options and the emergence of drug resistance. There is an urgent need for tools and methods to accelerate discovery of novel therapeutic targets. The expanded and optimized auxin-inducible degron system described herein provides a versatile platform for characterizing protein function and dissecting pathways governing important traits like virulence, stress tolerance, and antifungal resistance. The new reagents make AID technology applicable to any strain. Ultimately, this enhanced toolkit has the potential to help identify and validate new high-value drug targets and deepen our understanding of molecular mechanisms that drive pathogenicity of Candida and other fungal pathogen species.