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Sugarcane smut is the most damaging disease that is present almost across the globe, causing mild to severe yield losses depending upon the cultivar types, pathogen races and climatic conditions. Cultivation of smut-resistant cultivars is the most feasible and economical option to mitigate its damages. Previous investigations revealed that there is a scarcity of information on early detection and effective strategies to suppress etiological agents of smut disease due to the characteristics overlapping within species complexes. In this study, 104 sugarcane cultivars were screened by artificial inoculation with homogenate of all possible pathogen races of Sporisorium scitamineum during two consecutive growing seasons. The logistic smut growth pattern and the disease intrinsic rate were recorded by disease growth curve. Variable levels of disease incidence i.e., ranging from 0 to 54.10% were observed among these sugarcane cultivars. Besides, pathogen DNA in plant shoots of all the cultivars was successfully amplified by PCR method using smut-specific primers except 26 cultivars which showed an immune reaction in the field trial. Furthermore, the plant germination and tillering of susceptible sugarcane cultivars were greatly influenced by pathogen inoculation. In susceptible cultivars, S. scitamineum caused a significant reduction in setts germination, coupled with profuse tillering, resulting in fewer millable canes. Correlation analysis demonstrated that there was a positive relationship between reduction in setts germination and increase in the number of tillers. The present study would be helpful for the evaluation of smut resistance in a wide range of sugarcane germplasm, especially from the aspects of setts germination and tillers formation, and it also screened out several excellent germplasm for potential application in sugarcane breeding.

BACKGROUND: Infectious meningitis/encephalitis (IM) is a severe neurological disease that can be caused by bacterial, viral, and fungal pathogens. IM suffers high morbidity, mortality, and sequelae in childhood. Metagenomic next-generation sequencing (mNGS) can potentially improve IM outcomes by sequencing both pathogen and host responses and increasing the diagnosis accuracy.
METHODS: Here we developed an optimized mNGS pipeline named comprehensive mNGS (c-mNGS) to monitor DNA/RNA pathogens and host responses simultaneously and applied it to 142 cerebrospinal fluid samples. According to retrospective diagnosis, these samples were classified into three categories: confirmed infectious meningitis/encephalitis (CIM), suspected infectious meningitis/encephalitis (SIM), and noninfectious controls (CTRL).
RESULTS: Our pipeline outperformed conventional methods and identified RNA viruses such as Echovirus E30 and etiologic pathogens such as HHV-7, which would not be clinically identified via conventional methods. Based on the results of the c-mNGS pipeline, we successfully detected antibiotic resistance genes related to common antibiotics for treating Escherichia coli, Acinetobacter baumannii, and Group B Streptococcus. Further, we identified differentially expressed genes in hosts of bacterial meningitis (BM) and viral meningitis/encephalitis (VM). We used these genes to build a machine-learning model to pinpoint sample contaminations. Similarly, we also built a model to predict poor prognosis in BM.
CONCLUSIONS: This study developed an mNGS-based pipeline for IM which measures both DNA/RNA pathogens and host gene expression in a single assay. The pipeline allows detecting more viruses, predicting antibiotic resistance, pinpointing contaminations, and evaluating prognosis. Given the comparable cost to conventional mNGS, our pipeline can become a routine test for IM.

Tannerella forsythia, a member of the \"red complex\" bacteria implicated in severe periodontitis, employs various survival strategies and virulence factors to interact with the host. It thrives as a late colonizer in the oral biofilm, relying on its unique adaptation mechanisms for persistence. Essential to its survival are the type 9 protein secretion system and O-glycosylation of proteins, crucial for host interaction and immune evasion. Virulence factors of T. forsythia, including sialidase and proteases, facilitate its pathogenicity by degrading host glycoproteins and proteins, respectively. Moreover, cell surface glycoproteins like the S-layer and BspA modulate host responses and bacterial adherence, influencing colonization and tissue invasion. Outer membrane vesicles and lipopolysaccharides further induce inflammatory responses, contributing to periodontal tissue destruction. Interactions with specific host cell types, including epithelial cells, polymorphonuclear leukocytes macrophages, and mesenchymal stromal cells, highlight the multifaceted nature of T. forsythia\'s pathogenicity. Notably, it can invade epithelial cells and impair PMN function, promoting dysregulated inflammation and bacterial survival. Comparative studies with periodontitis-associated Porphyromonas gingivalis reveal differences in protease activity and immune modulation, suggesting distinct roles in disease progression. T. forsythia\'s potential to influence oral antimicrobial defense through protease-mediated degradation and interactions with other bacteria underscores its significance in periodontal disease pathogenesis. However, understanding T. forsythia\'s precise role in host-microbiome interactions and its classification as a keystone pathogen requires further investigation. Challenges in translating research data stem from the complexity of the oral microbiome and biofilm dynamics, necessitating comprehensive studies to elucidate its clinical relevance and therapeutic implications in periodontitis management.

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SUMMARYA significant increase in the incidence of Candida-mediated infections has been observed in the last decade, mainly due to rising numbers of susceptible individuals. Recently, the World Health Organization published its first fungal pathogen priority list, with Candida species listed in medium, high, and critical priority categories. This review is a synthesis of information and recent advances in our understanding of two of these species-Candida albicans and Candida glabrata. Of these, C. albicans is the most common cause of candidemia around the world and is categorized as a critical priority pathogen. C. glabrata is considered a high-priority pathogen and has become an increasingly important cause of candidemia in recent years. It is now the second most common causative agent of candidemia in many geographical regions. Despite their differences and phylogenetic divergence, they are successful as pathogens and commensals of humans. Both species can cause a broad variety of infections, ranging from superficial to potentially lethal systemic infections. While they share similarities in certain infection strategies, including tissue adhesion and invasion, they differ significantly in key aspects of their biology, interaction with immune cells, host damage strategies, and metabolic adaptations. Here we provide insights on key aspects of their biology, epidemiology, commensal and pathogenic lifestyles, interactions with the immune system, and antifungal resistance.

Improved phenotyping in pneumonia is necessary to strengthen risk assessment. Via a feasible and multidimensional approach with basic parameters, we aimed to evaluate the effect of host response at admission on severity stratification in COVID-19 and community-acquired pneumonia (CAP). Three COVID-19 and one CAP multicenter cohorts including hospitalized patients were recruited. Three easily available variables reflecting different pathophysiologic mechanisms-immune, inflammation, and respiratory-were selected (absolute lymphocyte count [ALC], C-reactive protein [CRP] and, SpO2/FiO2). In-hospital mortality and intensive care unit (ICU) admission were analyzed as outcomes. A multivariable, penalized maximum likelihood logistic regression was performed with ALC (< 724 lymphocytes/mm3), CRP (> 60 mg/L), and, SpO2/FiO2 (< 450). A total of 1452, 1222 and 462 patients were included in the three COVID-19 and 1292 in the CAP cohort for the analysis. Mortality ranged between 4 and 32% (0 to 3 abnormal biomarkers) and 0-9% in SARS-CoV-2 pneumonia and CAP, respectively. In the first COVID-19 cohort, adjusted for age and sex, we observed an increased odds ratio for in-hospital mortality in COVID-19 with elevated biomarkers altered (OR 1.8, 3, and 6.3 with 1, 2, and 3 abnormal biomarkers, respectively). The model had an AUROC of 0.83. Comparable findings were found for ICU admission, with an AUROC of 0.76. These results were confirmed in the other COVID-19 cohorts Similar OR trends were reported in the CAP cohort; however, results were not statistically significant. Assessing the host response via accessible biomarkers is a simple and rapidly applicable approach for pneumonia.

MicroRNAs (miRNAs) contribute to post-transcriptional modulation of the host response during influenza A virus (IAV) infection and may be involved in shaping disease severity. Differential disease severity was achieved in two groups of pigs by immunization of one group with a commercial swine IAV vaccine prior to heterologous IAV (H1N2) challenge of both groups. Lung tissue was harvested 1, 3, and 14 days after challenge and miRNA expression was quantified. Gene Ontology term enrichment analysis was employed to examine the functional relevance of genes potentially regulated by differentially expressed miRNAs in pigs with varying degrees of disease severity following IAV infection. Results suggested that the miRNA response associated with less severe disease may modulate host mechanisms essential for viral life cycle, e.g. transcription, translation, and protein trafficking. During more severe disease, miRNA-mediated regulation may focus on dampening virus-specific processes e.g. virion assembly and viral protein processing, and controlling host metabolism.

Dysregulation of innate immunity is deeply involved in infectious and autoimmune diseases. For a better understanding of pathogenesis and improved management of these diseases, it is of vital importance to implement convenient monitoring of systemic innate immunity. Built upon our previous works on the host transcriptional response to infection in peripheral blood, we proposed a 2D gene model for the simultaneous assessment of two major components of systemic innate immunity, including VirSig as the signature of the host response to viral infection and BacSig as the signature of the host response to bacterial infection. The revelation of dysregulation in innate immunity by this 2D gene model was demonstrated with a wide variety of transcriptome datasets. In acute infection, distinctive patterns of VirSig and BacSig activation were observed in viral and bacterial infection. In comparison, both signatures were restricted to a defined range in the vast majority of healthy adults, regardless of age. In addition, BacSig showed significant elevation during pregnancy and an upward trend during development. In tuberculosis (TB), elevation of BacSig and VirSig was observed in a significant portion of active TB patients, and abnormal BacSig was also associated with a longer treatment course. In cystic fibrosis (CF), abnormal BacSig was observed in a subset of patients, and no overall change in BacSig abnormality was observed after the drug treatment. In systemic sclerosis-associated interstitial lung disease (SSc-ILD), significant elevation of VirSig and BacSig was observed in some patients, and treatment with a drug led to the further deviation of BacSig from the control level. In systemic lupus erythematosus (SLE), positivity for the anti-Ro autoantibody was associated with significant elevation of VirSig in SLE patients, and the additive effect of VirSig/BacSig activation was also observed in SLE patients during pregnancy. Overall, these data demonstrated that the 2D gene model can be used to assess systemic innate immunity in health and disease, with the potential clinical applications including patient stratification, prescription of antibiotics, understanding of pathogenesis, and longitudinal monitoring of treatment response.

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