Applications of ß-defensins against infectious pathogenic microorganisms.

INTRODUCTION: Antimicrobial peptides (AMPs) are polypeptides with potent antimicrobial activity against a broad range of pathogenic microorganisms. Unlike conventional antibiotics, AMPs have rapid bactericidal activity, a low capacity for inducing resistance, and compatibility with the host immune system. A large body of data supports the antimicrobial activities of a large body of data supports the antimicrobial activities of the class of AMPs known as ß-defensins. This review provides a comprehensive analysis of the effects of ß-defensins against various pathogenic microorganism: bacteria, fungi, viruses, Mycoplasmas and Chlamydiae. The primary mechanisms of ß-defensins against pathogenic microorganisms include inhibition of biofilms formations, dissolution of membranes, disruption of cell walls, and inhibition of adhesion and receptor binding. Although further study and structural modifications are needed, ß-defensins are promising candidates for antimicrobial therapy. AREAS COVERED: This review describes the inhibitory effects of ß-defensins on various pathogenic microorganisms. Additionally, we focus on elucidating the mechanisms underlying their actions to provide, providing valuable references for the further study of ß-defensins. EXPERT OPINION: The biological activities and modes of action of ß-defensins provide powerful resources for clinical microbial infection management. Addressing the salt sensitivity and toxicity of ß-defensins may further enhance their potential applications.

Honey microbiota, methods for determining the microbiological composition and the antimicrobial effect of honey - A review.

Honey is a natural product used since ancient times due to its taste, aroma, and therapeutic properties (antibacterial, antiviral, anti-inflammatory, and antioxidant activity). The purpose of this review is to present the species of microorganisms that can survive in honey and the effect they can have on bees and consumers. The techniques for identifying the microorganisms present in honey are also described in this study. Honey contains bacteria, yeasts, molds, and viruses, and some of them may present beneficial properties for humans. The antimicrobial effect of honey is due to its acidity and high viscosity, high sugar concentration, low water content, the presence of hydrogen peroxide and non-peroxidase components, particularly methylglyoxal (MGO), phenolic acids, flavonoids, proteins, peptides, and non-peroxidase glycopeptides. Honey has antibacterial action (it has effectiveness against bacteria, e.g. Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Acinetobacter, etc.), antifungal (effectiveness against Candida spp., Aspergillus spp., Fusarium spp., Rhizopus spp., and Penicillium spp.), antiviral (effectiveness against SARS-CoV-2, Herpes simplex virus type 1, Influenza virus A and B, Varicella zoster virus), and antiparasitic action (effectiveness against Plasmodium berghei, Giardia and Trichomonas, Toxoplasma gondii) demonstrated by numerous studies that are comprised and discussed in this review.

Unveiling challenging corneal infections: a comprehensive etiological diagnosis through metagenomic next-generation sequencing (mNGS) of corneal tissue samples.

PURPOSE: The objective of this study was to assess the clinical diagnostic value of metagenomic next-generation sequencing (mNGS) in cases of challenging corneal infections using corneal tissue samples. METHODS: This retrospective study involved 42 patients with corneal infections, where conventional diagnostic techniques failed to identify the causative pathogen. Corneal tissue specimens underwent mNGS, followed by microbial culture for validation. Sensitivity-guided antimicrobial therapy was administered upon identification of the pathogen. The diagnostic and therapeutic efficacy of mNGS was analyzed to evaluate its clinical utility. RESULTS: A total of 42 patients were included in this study, with mNGS detection results obtained for 38 cases (90.48%). Among them, 30 cases (71.43%) were clinically significant, eight cases (19.05%) had low clinical relevance, and four cases (9.52%) showed no detection. Following corresponding antimicrobial treatment, 30 patients exhibited significant improvement, resulting in a treatment effectiveness of 71.43%. The prognosis of mNGS-positive patients was superior to that of mNGS-negative patients, with statistically significant differences observed (P < 0.001). CONCLUSIONS: Corneal tissue mNGS facilitated the rapid identification of causative agents in challenging corneal infections with unclear clinical diagnoses. It could be seamlessly integrated with traditional diagnostic methods to guide the diagnosis and treatment of corneal diseases.

Unraveling the role of tissue colonized microbiome in ovarian cancer progression.

BACKGROUND: Ovarian cancer (OC) is found to be the third most common gynecologic malignancy over the world, having the highest mortality rate among such tumors. Emerging studies underscore the presence of microorganisms within tumor tissues, with certain pathogens intricately linked to disease onset and progression. Disruption of the microbiome frequently precipitates disturbances in host metabolic and immune pathways, thereby fostering the development of cancer. METHODS: In this study, we initiated the investigation by conducting microbial reannotation on the RNA sequencing data derived from ovarian cancer tissues. Subsequently, a comprehensive array of analyses on tissue microbes was executed. These analyses encompassed the assessment of intergroup variations in microbial diversity, differential microbiological analysis, exploration of the association between host gene expression and microbial abundance, as well as an enrichment analysis of functional pathways linked to host genes associated with microbes. RESULTS: The analysis results revealed that Proteobacteria, Actinobacteria, Firmicutes, and Bacteroidetes were the main components at phylum level in ovarian tissue. Notably, the microbial composition of ovarian cancer tissue significantly diverged from that of normal ovarian tissue e, exhibiting markedly lower alpha diversity and distinct beta diversity. Besides, pathogenic microorganisms Achromobacter xylosoxidans and Enterobacter hormaechei were enriched in cancer tissue. Host genes associated with these pathogens were enriched in key pathways including "JAK-STAT signaling pathway", "Transcriptional misregulation in cancer", and "Th1 and Th2 cell differentiation", suggesting their role in ovarian cancer progression through microbial dysbiosis and immune response interaction. CONCLUSION: Abundance of pathogenic microorganisms in ovarian cancer tissue could modulate the expression of host genes, consequently impacting cancer-related signaling pathways and fostering cancer progression.

Quantitative microbial risk assessment (QMRA) tool for modelling pathogen infection risk to wastewater treatment plant workers.

Wastewater treatment plants (WWTPs) provide vital services to the public by removing contaminants from wastewater prior to environmental discharge or reuse for beneficial purposes. WWTP workers occupationally exposed to wastewater can be at risk of respiratory or gastrointestinal diseases. The study objectives were to: (1) quantify pathogens and pathogen indicators in wastewater aerosols near different WWTP processes/unit operations, (2) develop a QMRA model for multi-pathogen and multi-exposure pathway risks, and (3) create a web-based application to perform and communicate risk calculations for wastewater workers. Case studies for seven different WWTP job tasks were performed investigating infection risk across nine different enteric and respiratory pathogens. It was observed that the ingestion risk among job tasks was highest for "walking the WWTP," which involved exposure from splashing, bioaerosols, and hand-to-mouth contact from touching contaminated surfaces. There was also a notable difference in exposure risk during peak (5:00am-9:00am) and non-peak hours (9:00am- 5:00am), with risks during the peak flow hours of the early morning assumed to be 5 times greater than non-peak hours. N95 respirator usage reduced median respiratory risks by 77 %. The developed tool performs multiple QMRA calculations to estimate WWTP workers' infection risks from accidental ingestion or inhalation of wastewater from multiple pathogens and exposure scenarios, which can inform risk management strategies to protect occupational health. However, more data are needed to reduce uncertainty in model estimates, including comparative data for pathogen concentrations in wastewater during peak and non-peak hours. QMRA tools will increase accessibility of risk models for utilization in decision-making.

High-throughput fluorescence sensing array based on tetraphenylethylene derivatives for detecting and distinguishing pathogenic microbes.

Infections induced by pathogenic microorganisms will bring negative effects such as diseases that damage health and result in heavy economic burden. Therefore, it is very important to detect and identify the pathogens in time. Moreover, traditional clinical diagnosis or food testing often faces the problem of dealing with a large number of samples. Here, we designed a high-throughput fluorescent sensor array based on the different binding ability of five tetraphenylethylene derivatives (TPEs) with various side chains to different kinds of pathogenic microbes, which is used to detect and distinguish various species, so as to realize rapid mass diagnosis, and hopefully provide guidance for further determination of microbial infections and clinical treatment.

An explicit review and proposal of an integrated framework system to mitigate the baffling complexities induced by road dust-associated contaminants.

Road dust-associated contaminants (RD-AC) are gradually becoming a much thornier problem, as their monotonous correlations render them carcinogenic, mutagenic, and teratogenic. While many studies have examined the harmful effects of road dust on both humans and the environment, few studies have considered the co-exposure risk and gradient outcomes given the spatial extent of RD-AC. In this spirit, this paper presents in-depth elucidation into the baffling complexities induced by both major and emerging contaminants of road dust through a panorama-to-profile up-to-date review of diverse studies unified by the goal of advancing innovative methods to mitigate these contaminants. The paper thoroughly explores the correlations between RD-AC and provides insights to understand their potential in dispersing saprotrophic microorganisms. It also explores emerging challenges and proposes a novel integrated framework system aimed at thermally inactivating viruses and other pathogenic micro-organisms commingled with RD-AC. The main findings are: (i) the co-exposure risk of both major and emerging contaminants add another layer of complexity, highlighting the need for more holistic framework strategies, given the geospatial morphology of these contaminants; (ii) road dust contaminants show great potential for extended prevalence and severity of viral particles pollution; (iii) increasing trend of environmentally persistent free radicals (EPFRs) in road dust, with studies conducted solely in China thus far; and (iv) substantial hurdle exists in acquiring data concerning acute procedural distress and long-term co-exposure risk to RD-ACs. Given the baffling complexities of RD-ACs, co-exposure risk and the need for innovative mitigation strategies, the study underscore the significance of establishing robust systems for deep road dust contaminants control and future research efforts while recognizing the interconnectivity within the contaminants associated with road dust.

Remarkable enhancement of cinnamaldehyde antimicrobial activity encapsulated in capped mesoporous nanoparticles: A new "nanokiller" approach in the era of antimicrobial resistance.

Combating antimicrobial resistance is one of the biggest health challenges because of the ineffectiveness of standard biocide treatments. This challenge could be approached using natural products, which have demonstrated powerful therapeutics against multidrug-resistant microbes. In the present work, a nanodevice consisting of mesoporous silica nanoparticles loaded with an essential oil component (cinnamaldehyde) and functionalized with the polypeptide ε-poly-l-lysine is developed and used as an antimicrobial agent. In the presence of the corresponding stimuli (i.e., exogenous proteolytic enzymes from bacteria or fungi), the polypeptide is hydrolyzed, and the cinnamaldehyde delivery is enhanced. The nanodevice's release mechanism and efficacy are evaluated in vitro against the pathogenic microorganisms Escherichia coli, Staphylococcus aureus, and Candida albicans. The results demonstrate that the new device increases the delivery of the cinnamaldehyde via a biocontrolled uncapping mechanism triggered by proteolytic enzymes. Moreover, the nanodevice notably improves the antimicrobial efficacy of cinnamaldehyde when compared to the free compound, ca. 52-fold for E. coli, ca. 60-fold for S. aureus, and ca. 7-fold for C. albicans. The enhancement of the antimicrobial activity of the essential oil component is attributed to the decrease of its volatility due to its encapsulation in the porous silica matrix and the increase of its local concentration when released due to the presence of microorganisms.

Isolation and characterization of Paenibacillus peoriae JC-3jx from Dendrobium nobile.

Dendrobium is a rich source of high-value natural components. Endophytic fungi are well studied, yet bacteria research is limited. In this study, endophytic bacteria from Dendrobium nobile were isolated using an improved method, showing inhibition of pathogens and growth promotion. JC-3jx, identified as Paenibacillus peoriae, exhibited significant inhibitory activity against tested fungi and bacteria, including Escherichia coli. JC-3jx also promoted corn seed rooting and Dendrobium growth, highlighting its excellent biocontrol and growth-promoting potential.

Colonization of Raphanus sativus by human pathogenic microorganisms.

Contamination of vegetables with human pathogenic microorganisms (HPMOs) is considered one of the most important problems in the food industry, as current nutritional guidelines include increased consumption of raw or minimally processed organic vegetables due to healthy lifestyle promotion. Vegetables are known to be potential vehicles for HPMOs and sources of disease outbreaks. In this study, we tested the susceptibility of radish (Raphanus sativus) to colonization by different HPMOs, including Escherichia coli PCM 2561, Salmonella enterica subsp. enterica PCM 2565, Listeria monocytogenes PCM 2191 and Bacillus cereus PCM 1948. We hypothesized that host plant roots containing bactericidal compounds are less prone to HPMO colonization than shoots and leaves. We also determined the effect of selected pathogens on radish growth to check host plant-microbe interactions. We found that one-week-old radish is susceptible to colonization by selected HPMOs, as the presence of the tested HPMOs was demonstrated in all organs of R. sativus. The differences were noticed 2 weeks after inoculation because B. cereus was most abundant in roots (log10 CFU - 2.54), S. enterica was observed exclusively in stems (log10 CFU - 3.15), and L. monocytogenes and E. coli were most abundant in leaves (log10 CFU - 4.80 and 3.23, respectively). The results suggest that E. coli and L. monocytogenes show a higher ability to colonize and move across the plant than B. cereus and S. enterica. Based on fluorescence in situ hybridization (FISH) and confocal laser scanning microscopy (CLSM) approach HPMOs were detected in extracellular matrix and in some individual cells of all analyzed organs. The presence of pathogens adversely affected the growth parameters of one-week-old R. sativus, especially leaf and stem fresh weight (decreased by 47-66 and 17-57%, respectively). In two-week-old plants, no reduction in plant biomass development was noted. This observation may result from plant adaptation to biotic stress caused by the presence of HPMOs, but confirmation of this assumption is needed. Among the investigated HPMOs, L. monocytogenes turned out to be the pathogen that most intensively colonized the aboveground part of R. sativus and at the same time negatively affected the largest number of radish growth parameters.

Metabolites of pathogenic microorganisms database (MPMdb) and its seed metabolite applications.

Seed metabolites are the combination of essential compounds required by an organism across various potential environmental conditions. The seed metabolites screening framework based on the network topology approach can capture important biological information of species. This study aims to identify comprehensively the relationship between seed metabolites and pathogenic bacteria. A large-scale data set was compiled, describing the seed metabolite sets and metabolite sets of 124,192 pathogenic strains from 34 genera, by constructing genome-scale metabolic models. The enrichment analysis method was used to screen the specific seed metabolites of each species/genus of pathogenic bacteria. The metabolites of pathogenic microorganisms database (MPMdb) (http://qyzhanglab.hzau.edu.cn/MPMdb/) was established for browsing, searching, predicting, or downloading metabolites and seed metabolites of pathogenic microorganisms. Based on the MPMdb, taxonomic and phylogenetic analyses of pathogenic bacteria were performed according to the function of seed metabolites and metabolites. The results showed that the seed metabolites could be used as a feature for microorganism chemotaxonomy, and they could mirror the phylogeny of pathogenic bacteria. In addition, our screened specific seed metabolites of pathogenic bacteria can be used not only for further tapping the nutritional resources and identifying auxotrophies of pathogenic bacteria but also for designing targeted bactericidal compounds by combining with existing antimicrobial agents.IMPORTANCEMetabolites serve as key communication links between pathogenic microorganisms and hosts, with seed metabolites being crucial for microbial growth, reproduction, external communication, and host infection. However, the large-scale screening of metabolites and the identification of seed metabolites have always been the main technical bottleneck due to the low throughput and costly analysis. Genome-scale metabolic models have become a recognized research paradigm to investigate the metabolic characteristics of species. The developed metabolites of pathogenic microorganisms database in this study is committed to systematically predicting and identifying the metabolites and seed metabolites of pathogenic microorganisms, which could provide a powerful resource platform for pathogenic bacteria research.

First report of Anaplasma spp., Ehrlichia spp., and Rickettsia spp. in Amblyomma gervaisi ticks infesting monitor lizards (Varanus begalensis) of Pakistan.

Ticks pose significant health risks to both wildlife and humans due to their role as vectors for various pathogens. In this study, we investigated tick infestation patterns, tick-associated pathogens, and genetic relationships within the tick species Amblyomma gervaisi, focusing on its prevalence in monitor lizards (Varanus bengalensis) across different districts in Pakistan. We examined 85 monitor lizards and identified an overall mean intensity of 19.59 ticks per infested lizard and an overall mean abundance of 11.98 ticks per examined lizard. All collected ticks (n = 1019) were morphologically identified as A. gervaisi, including 387 males, 258 females, 353 nymphs, and 21 larvae. The highest tick prevalence was observed in the Buner district, followed by Torghar and Shangla, with the lowest prevalence in Chitral. Lizard captures primarily occurred from May to October, correlating with the period of higher tick infestations. Molecular analysis was conducted on tick DNA, revealing genetic similarities among A. gervaisi ticks based on 16S rDNA and ITS2 sequences. Notably, we found the absence of A. gervaisi ITS2 sequences in the NCBI GenBank, highlighting a gap in existing genetic data. Moreover, our study identified the presence of pathogenic microorganisms, including Ehrlichia sp., Candidatus Ehrlichia dumleri, Anaplasma sp., Francisella sp., Rickettsia sp., and Coxiella sp., in these ticks. BLAST analysis revealed significant similarities between these pathogenic sequences and known strains, emphasizing the potential role of these ticks as vectors for zoonotic diseases. Phylogenetic analyses based on nuclear ITS2 and mitochondrial 16S rDNA genes illustrated the genetic relationships of A. gervaisi ticks from Pakistan with other Amblyomma species, providing insights into their evolutionary history. These findings contribute to our understanding of tick infestation patterns, and tick-borne pathogens in monitor lizards, which has implications for wildlife health, zoonotic disease transmission, and future conservation efforts. Further research in this area is crucial for a comprehensive assessment of the risks associated with tick-borne diseases in both wildlife and humans.

Bioaerosolization behaviour of potential pathogenic microorganisms from wastewater treatment plants: Occurrence profile, social function and health risks.

Wastewater treatment plants (WWTPs) are the leading sources of potential pathogenic bioaerosol that cause non-negligible health risks. However, bioaerosolization behaviour of potential pathogenic microorganisms (PPMs) migrating from wastewater to the atmosphere is still unclear. This study investigated the occurrence profile of PPMs in wastewater, sludge and bioaerosol, then analyzed bioaerosolization level, impact factors and social function. Staphylococcus aureus was selected as the target due to its pathogenicity, and the health risks of workers, engineers and researchers wearing various masks (N90, N95 and medical masks) were evaluated. The results showed that there were 38 and 64 PPMs in bioaerosol from plant A and B. Streptomyces in plant A (average bioaerosolization index, BI= 237.71) and Acinetobacter in plant B (average BI = 505.88) were more likely to migrate from wastewater to the atmosphere forming bioaerosol. Environmental factors (relative humidity, wind speed and temperature) affected both BI and microbial species of PPMs in different ways. PPMs related to fermentation, aerobic chemoheterotrophy, and chemoheterotrophy are the most abundant. Meanwhile microbial networks from plants A and B showed that PPMs were well-connected. Emission level of Staphylococcus aureus bioaerosol can reach 980 ± 309.19 CFU/m3 in plant A and 715.55 ± 44.17 CFU/m3 in plant B. For three exposure population, disease burden (DB) and annual probability infection (Py) of Staphylococcus aureus bioaerosol in two plants were both higher than the U.S.EPA benchmark (10-4 DALYs pppy). All three masks (N90,N95 and medical masks) can decrease Py and DB by at least one order of magnitude. This study illustrated the bioaerosolization behaviour of PPMs comprehensively, which provides a scientific basis for exposure risk prevention and control.

Hazards reported on food of plant origin in the Rapid Alert System for Foodand Feed (RASFF) from 1997 to 2021 and their occurrence, prevention and reduction.

Between 1997 and 2021 notifications for foods of plant origin covered 44.6% of all notifications in the EU Rapid Alert System for Food and Feed (RASFF). A two-way joining cluster analysis for notifications on plants reported in the RASFF in 1997-2021 was carried out. The following variables were considered: hazard, product category and country of origin in relation to year of notification. In the period studied mainly mycotoxins, pesticide residues and pathogenic micro-organisms were reported. The most frequently notified product categories were nuts and seeds, fruit and vegetables and herbs and spices. The submitted products originated from Asian, African and South-American countries. The study findings were followed by a literature analysis outlining the occurrence and prevention and reduction possibilities of the mentioned hazards, which can be used in these countries. Attention was drawn to the need to carry out controls at EU border inspection posts, monitor and update hazard limits and improve the rapid exchange of information and response to detected hazards.

Quantitative risk assessments of Salmonella spp. in domestic pork in China.

Pork is one of the most commonly consumed meats, and its safety has always been a concern. Recently, safety incidents caused by chemical or biological contamination such as drug residues, heavy metals, and pathogenic microorganisms in pork have been reported, and the safety of pork is a cause for concern. Salmonella spp. is one of the important foodborne pathogens that threaten human health. Pork is a high-risk vector food for Salmonella spp. infection. The assessment of the safety risk of Salmonella spp. in pork is conducive to the prevention of related foodborne diseases. In this paper, risk assessment models for Salmonella spp. in meat were developed. The quantitative risk assessment model for Salmonella spp. based on the pork supply chain showed that the annual number of cases of salmonellosis due to pork consumption in China is approximately 27 per 10,000 males and 24 per 10,000 females. Sensitivity analysis showed that the main factors affecting the risk of Salmonella spp. in pork were the display temperature, display time, and Salmonella spp. contamination concentration in pork at the sale.

Recent advances in electrochemical aptasensors and genosensors for the detection of pathogens.

In recent years, pathogenic microorganisms have caused significant mortality rates and antibiotic resistance and triggered exorbitant healthcare costs. These pathogens often have high transmission rates within human populations. Rapid diagnosis is crucial in controlling and reducing the spread of pathogenic infections. The diagnostic methods currently used against individuals infected with these pathogens include relying on outward symptoms, immunological-based and, some biomolecular ones, which mainly have limitations such as diagnostic errors, time-consuming processes, and high-cost platforms. Electrochemical aptasensors and genosensors have emerged as promising diagnostic tools for rapid, accurate, and cost-effective pathogen detection. These bio-electrochemical platforms have been optimized for diagnostic purposes by incorporating advanced materials (mainly nanomaterials), biomolecular technologies, and innovative designs. This review classifies electrochemical aptasensors and genosensors developed between 2021 and 2023 based on their use of different nanomaterials, such as gold-based, carbon-based, and others that employed other innovative assemblies without the use of nanomaterials. Inspecting the diagnostic features of various sensing platforms against pathogenic analytes can identify research gaps and open new avenues for exploration.

Foodborne Pathogen and Microbial Community Differences in Fresh Processing Tomatoes in Xinjiang, China.

The microbes on fresh processing tomatoes correlate closely with diseases, preservation, and quality control. Investigation of the microbial communities on processing tomatoes from different production regions may help define microbial specificity, inform disease prevention methods, and improve quality. In this study, surface microbes on processing tomatoes from 10 samples in two primary production areas of southern and northern Xinjiang were investigated by sequencing fungal internal transcribed spacer and bacterial 16S rRNA hypervariable sequences. A total of 133 different fungal and bacterial taxonomies were obtained from processing tomatoes in the two regions, of which 63 genera were predominant. Bacterial and fungal communities differed significantly between southern and northern Xinjiang, and fungal diversity was higher in southern Xinjiang. Alternaria and Cladosporium on processing tomatoes in southern Xinjiang were associated with plant pathogenic risk. The plant pathogenic fungi of processing tomatoes in northern Xinjiang were more abundant in Alternaria and Fusarium. The abundance of Alternaria on processing tomatoes was higher in four regions of northern Xinjiang, indicating that there is a greater risk of plant pathogenicity in these areas. Processing tomatoes in northern and southern Xinjiang contained bacterial genera identified as gut microbes, such as Pantoea, Erwinia, Enterobacter, Enterococcus, and Serratia, indicating the potential risk of contamination of processing tomatoes with foodborne pathogens. This study highlighted the microbial specificity of processing tomatoes in two tomato production regions, providing a basis for further investigation and screening for foodborne pathogenic microorganisms.

Discovering targeted inhibitors for Escherichia coli efflux pump fusion proteins using computational and structure-guided approaches.

Multidrug resistance pathogens causing infections and illness remain largely untreated clinically. Efflux pumps are one of the primary processes through which bacteria develop resistance by transferring antibiotics from the interior of their cells to the outside environment. Inhibiting these pumps by developing efficient derivatives appears to be a promising strategy for restoring antibiotic potency. This investigation explores literature-reported inhibitors of E. coli efflux pump fusion proteins AcrB-AcrA and identify potential chemical derivatives of these inhibitors to overcome the limitations. Using computational and structure-guided approaches, a study was conducted with the selected inhibitors (AcrA:25-AcrB:59) obtained by data mining and their derivatives (AcrA:857-AcrB:3891) to identify their inhibitory effect on efflux pump using virtual screening, molecular docking and density functional theory (DFT) calculations. The finding indicates that Compound 2 (ZINC000072136376) has shown better binding and a significant inhibitory effect on AcrA, while Compound 3 (ZINC000072266819) has shown stronger binding and substantial inhibition effect on both non-mutant and mutated AcrB subunits. The identified derivatives could exhibit a better inhibitor and provide a potential approach for restoring the actions of resistant antibiotics.

Constructing an Interactive and Integrated Analysis and Identification Platform for Pathogenic Microorganisms to Support Surveillance Capacity.

INTRODUCTION: Whole genome sequencing (WGS) holds significant promise for epidemiological inquiries, as it enables the identification and tracking of pathogenic origins and dissemination through comprehensive genome analysis. This method is widely preferred for investigating outbreaks and monitoring pathogen activity. However, the effective utilization of microbiome sequencing data remains a challenge for clinical and public health experts. Through the National Pathogen Resource Center, we have constructed a dynamic and interactive online analysis platform to facilitate the in-depth analysis and use of pathogen genomic data, by public health and associated professionals, to support infectious disease surveillance framework building and capacity warnings. METHOD: The platform was implemented using the Java programming language, and the front-end pages were developed using the VUE framework, following the MVC (Model-View-Controller) pattern to enable interactive service functionalities for front-end data collection and back-end data computation. Cloud computing services were employed to integrate biological information analysis tools for conducting fundamental analysis on sequencing data. RESULT: The platform achieved the goal of non-programming analysis, providing an interactive visual interface that allows users to visually obtain results by setting parameters in web pages. Moreover, the platform allows users to export results in various formats to further support their research. DISCUSSION: We have established a dynamic and interactive online platform for bioinformatics analysis. By encapsulating the complex background experiments and analysis processes in a cloud-based service platform, the complex background experiments and analysis processes are presented to the end-user in a simple and interactive manner. It facilitates real-time data mining and analysis by allowing users to independently select parameters and generate analysis results at the click of a button, based on their needs, without the need for a programming foundation.

Application of Host-Depleted Nanopore Metagenomic Sequencing in the Clinical Detection of Pathogens in Pigs and Cats.

Metagenomic sequencing is a valuable tool for non-specifically detecting various microorganisms in samples, offering unique advantages for detecting emerging pathogens, fastidious or uncultivable pathogens, and mixed infections. It has recently been applied to clinically detect pathogenic microorganisms in animals; however, the high proportion of host genes, expensive sequencing equipment, and the complexity of sequencing and data analysis methods have limited its clinical utility. In this study, a combination of tissue homogenization and nuclease digestion was employed to remove host genes from pig and cat samples; DNA and RNA were then extracted and subjected to nonselective PCR amplification to simultaneously detect DNA and RNA pathogen genomes using R9.4.1 or R10.4.1 flow cells on the MinION platform. Real-time pathogen detection was conducted using EPI2M WIMP, and viral genome assembly was performed using NanoFilt, minimap2, samtools, and ivar. Pathogens in five clinical samples (serum, nasopharyngeal swab, feces, or ascites) from cats and four clinical samples (lung or small intestine tissue) from pigs were examined by metagenomic sequencing, and the results were consistent with those obtained by PCR and bacterial culture. Additionally, we detected four viruses and three bacteria that may be associated with diseases. A comparison of results before and after host gene removal in three samples showed a 9-50% reduction in host genes. We also compared the assembly efficiency of six virus genomes and found that data volumes ranging from 3.3 to 98.3 MB were sufficient to assemble >90% of the viral genomes. In summary, this study utilized optimized nanopore metagenomic sequencing and analysis methods to reduce host genes, decrease the required data volume for sequencing analysis, and enable real-time detection to determine when to stop sequencing. The streamlined sequencing and analysis process overcomes barriers to the veterinary clinical application of metagenomic sequencing and provides a reference for clinical implementation.