Gut microbiota is associated with a variety of diseases, but its relationship with severe pneumonia remains to be explored. This study primarily analyzed the intestinal microbiota of patients with severe pneumonia and examined its association with clinical data. We collected clinical data from 96 patients with severe pneumonia for differential analysis and identified prognostic factors using logistic regression. Fecal samples from patients with severe pneumonia and healthy controls were collected and analyzed using 16S rRNA sequencing. We applied three machine learning algorithms (LASSO, Random Forest, and SVM) to identify microbial markers associated with severe pneumonia. The patients were grouped by "discharge status". Significant differences were observed in age (p = 0.025), total length of hospital stay (p < 0.001), and C-reactive protein (CRP) (p < 0.001). Logistic regression analysis identified age (p = 0.024) and total hospital stay (p < 0.001) as factors influencing the likelihood of improvement and discharge. Diversity analysis of collected stool samples revealed differences between the two groups. LDA Effect Size (LEfSe) analysis highlighted significant microbial differences at various taxonomic levels between the two populations. Three machine learning algorithms identified 9 microbial markers for severe pneumonia. A diagnostic prediction model was constructed, with an area under the Receiver Operating Characteristic (ROC) curve of 0.969 (95% CI: 0.946-0.992). Patients with severe pneumonia exhibit unique intestinal microbiota characteristics, which may be regulated by age and total length of hospital stay, thereby influencing the disease's prognosis.
The gut microbiome is linked to body composition, yet most studies involve probiotic or dietary interventions. This study explored relationships between changes in body composition and the fecal microbiota under natural lifestyle conditions. A repeated-measures design involved 15 adults completing four body composition assessments at 3-month intervals. Fecal samples from each time point underwent 16S rRNA gene sequencing. Participants were stratified by body composition parameters, and microbial profiles from initial and final measurements were compared to assess longitudinal patterns. Overweight participants showed lower alpha diversity. Linear mixed models revealed fecal microbiota remained stable across all four time points, with no statistically significant continuous trends observed longitudinally. Exploratory baseline-to-endpoint comparisons across stratified groups and Spearman correlation analyses suggested potential microbiota shifts, though these associations remained statistically non-significant. Preliminary observations exhibited that the OTU identified as Parasutterella excrementihominis tended to associate with higher body fat, whereas the putative species Akkermansia muciniphila showed a potential inverse association. Representative taxa, such as Dialister invisus, appeared enriched in individuals with higher skeletal muscle percentages, whereas the OTU assigned to Bifidobacterium pseudocatenulatum showed the opposite trend. Several associations differed by sex, suggesting modulation by host factors. These preliminary findings suggest possible fecal microbiota patterns associated with body composition, even without targeted interventions. While lacking robust linear associations in this small pilot cohort, the observed directional consistency across statistical approaches highlights the potential of fecal microbes as candidate indicators of metabolic health. These exploratory results require further validation in larger, longitudinal studies with sufficient statistical power.
This study identified key intra-tumor microbial signatures distinguishing head and neck cancers from gastrointestinal cancers and explored their diagnostic and prognostic potential. Intra-tumor microbial data of five cancer types were obtained from the Cancer Microbiome Atlas, and corresponding clinical data were retrieved from the Cancer Genome Atlas. The Wilcoxon test was used to analyze differences in microbial populations. Univariate logistic regression, least absolute shrinkage and selection operator, and recursive feature elimination were sequentially applied to screen optimal microbial markers, and a support vector machine classification model was constructed. A nomogram model and Kaplan-Meier curves were used to validate the predictive and prognostic value of the optimal microbes, respectively. Overall, 463 tumor samples and 47 controls were included. Twenty-three microbes showed significant differences in distribution between head and neck and gastrointestinal tumors; among these, eight overlapping microbes were selected as optimal markers. The SVM model based on these eight microbes achieved AUCs of 0.937 and 0.856 in the training and validation datasets, respectively. The nomogram model constructed with these markers showed high predictive accuracy (C-index = 0.8944 in training, 0.8023 in validation). Kaplan-Meier analysis revealed that high abundance of Capnocytophaga, Lachnospiraceae, and Bacteroidales was significantly associated with longer overall survival in both head and neck tumors and gastrointestinal tumors (all P < 0.05). The eight intra-tumor microbial communities serve as a robust signature for distinguishing head and neck tumors from gastrointestinal tumors. Among these, Capnocytophaga, Lachnospiraceae, and Bacteroidales have potential as prognostic biomarkers to improve survival prediction in cancers.
The composition of the intestinal microbiome has been identified as a key factor influencing the efficacy of immune checkpoint inhibitors. This study aimed to systematically evaluate the potential associations among gut microbiota, metabolic profiles, and clinical outcomes in patients with MSI-H advanced colorectal cancer (CRC) treated with immunotherapy. Twenty advanced CRC patients receiving immunotherapy were enrolled and categorized into clinical benefit response (CBR) and non-benefit (NCB) groups based on treatment efficacy. Fecal samples were analyzed using metagenomic sequencing and untargeted metabolomics. The results revealed significant enrichments of s_Clostridium unclassified and metabolites such as guanosine, 3-carboxy-4-methyl-5-propyl-2-furanpropionic acid, and quercetin 3-(6"-malonyl-glucoside) in the CBR group, suggesting their potential positive predictive value for immunotherapy response. Conversely, the NCB group showed significant enrichments of s_Roseburia hominis, s_Marseilla massiliensis, and metabolites including pyrophosphate, riboflavin, and PC(22:5(4Z,7Z,10Z,13Z,16Z)/14:0), indicating a possible association with treatment resistance. By integrating fecal metagenomics and metabolomics, this study reveals distinctive "flora-metabolite" interactions linked to therapeutic response in advanced CRC patients undergoing immunotherapy. Specific microbial and metabolic profiles were positively or negatively correlated with immunotherapy outcomes, highlighting their potential not only as predictive biomarkers but also as a theoretical foundation for developing individualized immunotherapy strategies based on microecological modulation.
The review article is a critical examination of the growing global problem of multidrug-resistant (MDR) Salmonella and Shigella, focusing on their epidemiology, molecular resistance mechanisms, and clinical effects. It compiles current information on increasing resistance to major antibiotics, such as fluoroquinolones, third-generation cephalosporins, and sulfonamides, that is caused by a variety of factors, including ESBL production and plasmid-mediated gene transfer, especially in Asia, Africa, and the Middle East. The minireview discusses the new therapeutic approaches such as bacteriophage therapy, antimicrobial peptides, antimicrobials based on nanotechnology, and a combination of antibiotic regimens and their mechanisms, efficacy, and some limitations that exist in these approaches. In addition, it discusses the issues of diagnostic challenges, infection control practices, and antibiotic stewardship as part and parcel of resistance management. It will be a focused, evidence-based review to inform research, clinical practices, and policy to turn the trend of resistance around and enhance patient outcomes. The presented multidisciplinary review shows that MDR Salmonella and Shigella infections have become a threatening problem in the world, which requires urgent measures, including multilateral cooperation, improved molecular tracking, fast diagnostics, and new therapeutic options.
To develop and validate a machine learning model integrating intra-abdominal pressure (IAP) and gut microbial characteristics for early identification of enteral nutrition intolerance (EENI) in critically ill ICU patients. This cohort study (January 2023-December 2025) included 300 ICU patients receiving early enteral nutrition. Baseline clinical characteristics, intra-abdominal pressure, laboratory indices, and quantitative gut microbial taxa were collected. Candidate predictors were selected using the least absolute shrinkage and selection operator regression, and independent predictors were incorporated into a multivariable logistic regression model, which was presented as a nomogram. Model performance was assessed using discrimination, calibration, and decision curve analyses. The incidence of EENI was 49.00% (147/300). LASSO selected 16 features: age, analgesic use, serum albumin, glucose, IAP, and the absolute counts of Enterococcus, Bacteroides, Escherichia-Shigella, Klebsiella, Bifidobacterium, and Parabacteroides. The absolute counts of Enterococcus, Bacteroides, Escherichia-Shigella, Klebsiella, Bifidobacterium, and Parabacteroides were significant independent predictors (P < 0.05). The model achieved an AUC of 0.900 (95% CI: 0.863-0.936) in the training set and 0.900 (95% CI: 0.859-0.941) in the validation set. Calibration was good (Hosmer-Lemeshow P = 0.425 and P = 0.423, respectively). DCA demonstrated clinical utility across a wide range of risk thresholds. The developed machine learning model, combining IAP and selected genus-level gut microbial markers, demonstrates strong predictive performance and clinical potential for forecasting and managing early enteral nutrition intolerance in ICU patients.
Gestational diabetes mellitus (GDM) affects maternal metabolism and may be associated with altered placental bacterial DNA community profiles and early neonatal gut microbiota. This prospective cohort study assesses GDM's impact on the placental-neonatal gut microbial axis and links key bacterial taxa to short-term perinatal outcomes and clinical significance. Pregnant women with GDM and healthy controls were enrolled. Placental tissue and first-pass neonatal meconium samples were collected. Bacterial community composition, diversity, and differential genera were analyzed using 5-region 16S rRNA sequencing. FEAST was used to model potential maternal-neonatal microbial sources. Associations among gestational weight gain (GWG), microbial features, and the risk of neonatal hospitalization were also assessed. The GDM and control groups showed significant differences in placental and early neonatal meconium microbial community structures, with increased α-diversity and distinct community separation in both sample types. In placental samples, Brevundimonas was decreased, whereas Lactobacillus and Sphingomonas were enriched. In neonatal meconium, potentially inflammation-related genera, including Staphylococcus, Streptococcus, and Clostridium, were enriched. GWG had limited effects on overall community structure but exerted refined regulation on specific genera. Source tracking showed a reduced placenta-attributed similarity contribution to neonatal meconium microbiota in the GDM group. The abundances of specific placental genera, including Escherichia, Curvibacter, and Pelomonas, were significantly associated with neonatal hospitalization. GDM is associated with altered placental bacterial DNA community profiles and early neonatal meconium microbiota, potentially affecting maternal-neonatal microbial continuity. Specific bacterial genera are associated with early neonatal hospitalization. The study provides a microbial perspective for understanding GDM-related perinatal risk.
The management of carbapenem-resistant Acinetobacter baumannii (CRAB) infections remains a formidable clinical challenge. This study evaluated the in vitro antimicrobial activities of sulbactam-durlobactam (SUL-DUR) and eravacycline (ERV) against CRAB isolates and elucidated the genomic landscapes of resistance and virulence determinants in SUL-DUR-resistant strains to inform therapeutic decision-making. A total of 233 clinical CRAB isolates were collected and screened for susceptibility to SUL-DUR and ERV using the Kirby-Bauer (K-B) disk diffusion assay. Isolates exhibiting resistance to SUL-DUR were further characterized via metagenomic next-generation sequencing (mNGS) to identify key resistance and virulence factors. SUL-DUR and ERV demonstrated robust in vitro activity, with susceptibility rates of 92.3% and 91.4%, respectively. Notably, no isolates exhibited concurrent non-susceptibility to both agents. Genomic analysis of 14 SUL-DUR-resistant strains revealed a complex and heterogeneous distribution of genetic determinants. The presence of bla NDM-1 was identified as a critical driver of SUL-DUR resistance. Additionally, reduced susceptibility was potentially associated with specific mutations in bla OXA-23, bla OXA-66, and bla TEM-1, while hyperactive efflux systems and altered membrane permeability further synergized to enhance the resistance phenotype. Despite the extensive-drug-resistant (XDR) nature of current CRAB isolates, they maintain high sensitivity to SUL-DUR and ERV. Our findings underscore that SUL-DUR and ERV represent highly promising therapeutic options with significant development potential and broad clinical application prospects for the management of CRAB-related infections.
Bloodstream infections cause significant morbidity and mortality, and rapid identification of the causative microorganisms, along with their antimicrobial resistance profiles, is crucial for appropriate treatment. Molecular diagnostic systems such as the BioFire FilmArray Blood Culture Identification 2 (BCID2) panel provide faster results than conventional culture-based methods. This study evaluated the performance of the BCID2 panel for rapid detection of microorganisms and antimicrobial resistance genes in 50 positive blood cultures collected at a university hospital between January 2023 and September 2025. All samples were obtained from peripheral blood cultures, and repeat or catheter-related cultures were excluded. Samples were analyzed using conventional culture methods, mass spectrometry-based identification, and automated antimicrobial susceptibility testing, in parallel with the BCID2 panel. Resistance genes detected by the panel were confirmed using polymerase chain reaction. At least one microorganism was detected in forty-seven samples (94%), showing strong agreement between molecular and culture-based methods. Complete concordance was observed for Escherichia coli and Pseudomonas aeruginosa, while Klebsiella pneumoniae showed slightly lower but acceptable agreement. Polymicrobial results were detected by BCID2 in 20 cases (40%). Detected resistance genes correlated well with phenotypic resistance results. However, the absence of clinical correlation data and repeat blood culture information limits the interpretation of these findings, particularly for coagulase-negative staphylococci. The BCID2 panel enables rapid and reliable identification of bloodstream pathogens and relevant resistance genes, serving as a valuable complement to conventional diagnostic methods when interpreted alongside clinical data.
Alterations in gut microbiota have been reported in coeliac disease (CeD). However, longitudinal evidence distinguishing disease-related effects from diet-driven changes after gluten-free diet initiation remains scarce, particularly in pediatric cohorts. The present study aimed to evaluate time-dependent changes in selected intestinal microorganisms in children with CeD before and during adherence to a gluten-free diet and to compare these findings with those of healthy controls. Microbial DNA isolates from stool samples of pediatric patients with CeD (n = 24) and healthy children (n = 24) were analyzed by quantitative real-time PCR. Samples from CeD patients were categorized into four time points: pre-diet, 6-month, 1-year, and 2-year follow-up. The healthy controls were assessed once. The prevalence and microbial load of selected microorganisms were evaluated. Bifidobacterium spp. remained highly prevalent across all time points, although their abundance varied significantly over follow-up, with the lowest levels at one year and higher levels at two years, comparable to those in controls. The prevalence of Candida tropicalis increased significantly during dietary treatment, reaching levels similar to those of healthy children after two years. Saccharomyces cerevisiae showed a gradual rise in prevalence and abundance, whereas Methanobrevibacter smithii remained infrequent with low and fluctuating microbial load. The duration of adherence to a gluten-free diet appears to influence gut microbial profiles in pediatric CeD. The selected gut microbiota microorganisms' assessment may serve as a complementary tool for understanding intestinal adaptation during dietary treatment, however, its routine clinical application requires further validation.
This study was designed to systematically evaluate the diagnostic performance of metagenomic next-generation sequencing (mNGS) using blood and bronchoalveolar lavage fluid (BALF) samples in patients with severe pneumonia complicated by bloodstream infections. A retrospective analysis of 30 patients with severe pneumonia-bloodstream infection admitted to our hospital from January 2018 to December 2022 was conducted, and the potential pathogens in both BALF and blood samples were simultaneously detected by conventional microbial examination (traditional group) and mNGS tests (mNGS group), comparing the differences in pathogen species and detection rates between the two methods. There was no significant difference in the positivity of pathogen detection in BALF and blood samples using mNGS (p = 0.492). The proportion of bacteria (p = 0.005) and fungi (p = 0.037) detected by BALF mNGS was higher than that by blood mNGS, but there was no significant difference in the proportion of viruses (p = 0.121). In addition, the positive rate of pathogen detection by mNGS in BALF and blood samples was significantly higher than that by traditional methods (p < 0.01). BALF mNGS demonstrated superior diagnostic sensitivity for bacterial and fungal pathogen detection compared to blood mNGS and conventional culture methods. Notably, blood specimens retained distinct advantages in identifying specific viral infections. Future prospective studies with larger sample sizes are warranted to validate these findings.
The Chenier Islands are depositional areas within intertidal zones, characterized by unique soil textures and distinctive environmental conditions that shape specific vegetation distribution patterns. However, the adaptive mechanisms of Phragmites australis (common reed) and Suaeda salsa (L.) Pall. (common seepweed) two prevalent plant species in this region—in saline stress environments, as well as the composition and functional characteristics of their rhizosphere bacterial communities, remain largely unclear. In this study, rhizosphere soil samples were collected from common reed and common seepweed. DNA was extracted and subjected to high-throughput sequencing to analyze the composition and predictive functional profiles of the rhizosphere microbial communities. The results indicated that no significant differences were observed in the alpha diversity indices (Chao1, ACE, Simpson, and Shannon), indicating similar microbial species richness and evenness in the rhizospheres of common reed and common seepweed. Taxonomic analysis at the phylum level showed that the dominant bacterial phyla shared by both plants were Proteobacteria, Bacteroidota, Chloroflexota, and Actinomycetota. Notably, Acidobacteriota and Cyanobacteria were uniquely enriched in the common reed and common seepweed rhizospheres, respectively. At the genus level, the microbial communities of both plants were largely composed of unclassified taxa and minor groups, with Zeaxanthinibacter being the only cultivable dominant genus identified. Principal Coordinates Analysis (PCoA) explained 75.02% of the total β-diversity variance, and the clear separation of samples along the first coordinate axis revealed visually distinct community structures between the two plants. PERMANOVA further confirmed that plant species significantly influenced microbial community assembly, with a moderate explanatory strength (R2 = 0.205, p = 0.008). Integrated results from LEfSe, PICRUSt2, and FAPROTAX analyses demonstrated that common seepweed rhizospheres were enriched with 19 photosynthesis-related biomarkers, suggesting a stronger photoautotrophic potential compared to common reed. In contrast, the common reed rhizosphere retained only two oligotrophic degraders Acidobacteriota and Chloroflexota. Although PICRUSt2 predictions indicated high overlap in core metabolic pathways between the two plants, FAPROTAX profiling revealed markedly divergent energy-acquisition strategies. Specifically, the common seepweed microbiome exhibited a “photoautotrophy nitrogen fixation” coupling strategy, whereas common reed relied predominantly on a “chemoheterotrophy nitrate reduction” pathway, reflecting niche partitioning in the saline environment. It should be noted that functional predictions derived from PICRUSt2 and FAPROTAX are computational inferences rather than empirical measurements, and thus mechanistic interpretations should be treated with caution. This study identifies a rhizosphere bacterial community assembly pattern characterized by “structural differentiation but functional convergence” offering valuable insights into microbial-mediated plant adaptation to saline stress.
Treatment of infectious diseases uses antibiotics to kill or inhibit the growth of pathogenic bacteria. Inappropriate antibiotic use triggers resistance, which in turn affects patient clinical outcomes, length of hospital stays, and treatment costs. This study aimed to analyze trends in the quantity and quality of antibiotics used in surgical and medical wards. This study was conducted at the Dr. Soetomo General Academic Hospital, Surabaya, Indonesia. This retrospective observational study analyzed trends in the quantity and quality of antibiotics in surgical and medical wards by collecting medical records of patients from January to May 2019. Quantity analysis was performed using DDD per 100 patient-days or DDD per 100 bed-days (DDD/100-BD), and quality analysis was performed using the Gyssens category method. The antibiotics most consumed in the surgical wards were ceftriaxone (41.67 DDD/100-BD), levofloxacin (22.82 DDD/100-BD), and cefazoline (17.75 DDD/100-BD). The most consumed in medical wards were ceftriaxone (106.22 DDD/100-BD), levofloxacin (34.95 DDD/100-BD), and metronidazole (26.25 DDD/100-BD). The quality of antibiotics used in surgical wards showed 53.2% appropriate use, 16.9% without indication, and 13.9% inappropriate choice, while in medical wards, they were 66.5%, 29.7%, and 2.1%, respectively. Third-generation cephalosporins and fluoroquinolones were the most consumed antibiotics in surgical and medical wards. The quality of antibiotic use was appropriate, with 53.2-66.5% of antibiotic use appropriate. Establishing an antimicrobial stewardship program would help control antibiotic consumption and optimize antibiotic use in hospitals.
During the post COVID-19 pandemic, monkeypox (mpox) has returned and become a significant concern for health. The epicenter of clade I mpox is within the Democratic Republic of Congo (DRC) where two subclade consists of Ia and Ib are now in circulation and maintain their transmission from human to human. As of late 2024, worldwide mpox cases had surpassed 100,000 across 127 nations, with the World Health Organization reporting over 260 fatalities. CDC recently reported that the spread of clade I is no longer limited to Africa, highlighting its growing potential to become a pandemic. The World Health Organization (WHO) declared the disease an international public health emergency on August 14, 2024. This undoubtedly raises the question of whether global outbreaks of mpox represent the onset of another full-blown pandemic. Although Monkeypox can lead to other public health issues (especially in areas where it is not usually endemic), it is unlikely to become a pandemic on the same scale as COVID-19. Moreover, it is more containable due to vaccine availability, its transmission dynamics, and lessons learned from COVID-19. Nonetheless, it is still important to remain vigilant to prevent outbreaks from spreading, particularly in vulnerable populations and regions with limited healthcare resources.
Carbapenem-resistant and hypervirulent Klebsiella pneumoniae have been identified worldwide, posing a significant threat to public health. This study aimed to characterize a novel KPC-harboring plasmid in a carbapenem-resistant and hypervirulent ST111 K63 Klebsiella pneumoniae (CR-HvKp), designated AZJ065, and to analyze the evolutionary pathway of multidrug-resistant and hypervirulent clinical ST111 K63 strains using genomic data. Antimicrobial susceptibility testing, the string test, the Galleria mellonella infection model, and the mouse intraperitoneal challenge infection model were employed to determine the drug resistance and virulence of the clinical strains. Next-generation sequencing and phylogenetic analysis were conducted to investigate the genetic characteristics of AZJ065 and the evolutionary pathway of ST111 K63. Phenotypic tests indicated that AZJ065 exhibited carbapenem resistance and hypervirulence. Next-generation sequencing analysis revealed that AZJ065 harbored two plasmids: a KPC-harboring plasmid, pAZJ065-KPC, and a virulence plasmid, pAZJ065-Hv. The pAZJ065-KPC conferred carbapenem resistance and displayed a unique structure in the resistance region, with a complete Tn2680 insertion. Phylogenetic analysis suggested that AZJ065 evolved from an ST111 K63 HvKp through the acquisition of a CR plasmid. This study reports a new genotype of HvKp, ST111 K63, and highlights the importance of monitoring plasmid-mediated resistance in hypervirulent strains.
This study aimed to investigate the changes in the microbiome on the inner surface of clear aligners following the consumption of Coca-Cola. The pH value and bacterial composition on the inner surface of clear aligners were assessed over five wearing cycles in three groups of subjects: those with a normal diet (Group A), those who drank Coca-Cola while wearing the aligners (Group C), and those who drank Coca-Cola after removing the aligners (Group B). Microbial analysis was performed using 16S rRNA gene sequencing and operational taxonomic unit (OTU) abundance profiling. The pH of the fluid inside the aligners significantly decreased immediately after Coca-Cola consumption (0 hour) in Groups B and C (p < 0.05). Group B exhibited the most pronounced decline in pH and alpha diversity at 12 hours, along with the highest beta diversity among the groups (p < 0.05). In Group A, the relative abundances of the phylum Actinobacteria was highest at 0 hour, Bacteroidetes at 12 hours, and class Actinobacteria, Gammaproteobacteria, and species Haemophilus influenzae peaked at 24 hours; conversely, Neisseria subflava showed the lowest abundance compared to Groups B and C (p < 0.05). Compared to Group C, Group B demonstrated higher levels of phylum Fusobacteria at 4 hours and 12 hours, and lower Actinobacteria abundance at 8 hours (p < 0.05). Consumption of Coca-Cola induces unfavorable changes in the microbiome on the inner surface of clear aligners. Notably, drinking Coca-Cola without wearing the aligners resulted in a lower pH and greater microbial imbalance, especially at 12 hours post-consumption.
Streptococcus mutans and Lactobacillus casei are the two bacterial species that cause tooth decay and affect orthodontically treated teeth. In orthodontic treatment, zinc oxide (ZnO) is incorporated into the cement, providing antibacterial properties. The objective of the study was to evaluate the antimicrobial activity of zinc oxide nanoparticles containing cement for the management of orthodontic teeth. ZnO nanoparticles were prepared using ZnCl2 and then incorporated into the Orthodontic Portland Cement (OPC) with a grade of 43. It was evaluated for physicochemical parameters like colour, odour, appearance, and pH. Flexural strength, split tensile strength, and setting time were also determined with standard ASTM C496 methods. The antibacterial activity of the ZnO nanoparticles was determined by crystal violet staining. It was found that biomass growth was lower in the cement containing zinc oxide nanoparticles than in the control samples. There was inhibition of biofilm formation in the presence of zinc oxide nanoparticles incorporated into the cement material, thereby enhancing the antimicrobial effect. The incorporation of ZnO nanoparticles into orthodontic cement demonstrates enhanced antimicrobial properties, making it beneficial for managing oral bacterial colonization during orthodontic treatment.
The γ-proteobacterium Xanthomonas campestris pv. campestris B100 is the causal agent of black rot disease in a wide range of economically important crops. In addition, X. campestris pv. campestris is commercially relevant due to the synthesis of the exopolysaccharide xanthan. In this work, we first introduce a novel transcriptional regulator, termed Crt1, and present the effect that the deletion of the crt1 gene exerts on growth, xanthan production, virulence, and transcriptome and proteome profiles. Differential transcriptome analysis of the deletion mutant X. campestris pv. campestris B100 Δcrt1 compared to the wild type revealed the up-regulation of the pilP, pilM and pilE genes, which are relevant for the type 4 pilus assembly. Furthermore, increased xanthan production and upregulated transcription of genes within the gum cluster, which are critical for xanthan biosynthesis, were observed. Profiling of the cytosolic proteome identified increased expression of the glucosyltransferase GtrB, which is involved in LPS biosynthesis, and of a type III effector with phytase activity. Moreover, the presence of the fructose import and utilization proteins FruAB and FruK was reduced in the deletion mutant. The plant-pathogenicity assay demonstrated that the severity of the infection of the host plant tissue was higher in the case of the deletion mutant than in the wildtype strain. The regulator Crt1 modulates multiple virulence factors as well as LPS and xanthan production. In conclusion, Crt1 influences a diverse network of genes that contribute to the pathogenic lifestyle of X. campestris pv. campestris.
Catheter-associated urinary tract infections (CAUTIs) represent a substantial clinical burden, particularly in diabetes Mellitus (DM) patients, with extended duration of catheterization. Escherichia coli remains most prevalent uropathogen, often exhibiting virulence factors, robust biofilm formation, and multidrug resistance (MDR). This study investigates antimicrobial resistance patterns, virulence gene profiles, and biofilm production of E. coli isolates from CAUTI patients with and without diabetes mellitus. A total of 260 CAUTI patients were enrolled in this study, comprising 130 diabetic (HbA1c > 6.5%) and 130 non-diabetic (HbA1c < 5.7%) individuals admitted to various wards of DHQ Hospital, Jhang, between January 2023 and January 2024. From 183 urine culture-positive urine samples 123 E. coli isolates were analyzed. Antimicrobial susceptibility testing was performed by disk diffusion, Molecular profiling and virulence genes were conducted via polymerase chain reaction (PCR), and biofilm quantification was assessed by microtiter plate method. MDR (89.7%) and XDR (19.2%) phenotypes were significantly more common in diabetic isolates with increased resistance to ß-lactams, fluoroquinolones, carbapenems, and sulfonamides. The most prevalent genes were blaCTX-M, blaNDM and blaOXA-48. Virulence genes (fimH (78%), PapC (50%), FyuA (45%), and KpsMTII (33%) associated with enhanced biofilm formation. Diabetes mellitus (DM) substantially exacerbates CAUTIs caused by E. coli through increased multidrug resistance, virulence genes prevalence and biofilm production emphasizing the need for targeted antimicrobial stewardship and stringent infection control strategies in diabetic populations.
This study aimed to analyze the clinical features and infection status of COVID-19 patients with bacterial infections in Shaanxi Province. A retrospective analysis was conducted on 2,000 hospitalized patients from December 2022 to February 2023, categorized into mild, moderate, and severe COVID-19 groups. Among these, 300 patients had bacterial coinfections, with Klebsiella pneumoniae and Acinetobacter baumannii identified as the main pathogens. The study found a higher male prevalence and a higher median age, with severe cases mostly affecting individuals aged 70–90 years. The drug resistance rates of patients with mild and severe COVID-19 were low. Patients with severe COVID-19 were mainly infected with carbapenem-resistant Enterobacterales (CRE), carbapenem-resistant A. baumannii (CR-Ab) and extended-spectrum β-lactamase producing bacteria (ESBLs (+)). The findings highlight the importance of rational antibiotic use for severe COVID-19 patients to prevent the development of multidrug resistance caused by empirical medication and to provide a basis for clinical medication.
