MrkH, a Novel c-di-GMP-Dependent Transcriptional Activator, Controls Klebsiella pneumoniae Biofilm Formation by Regulating Type 3 Fimbriae Expression

Klebsiella pneumoniae causes significant morbidity and mortality worldwide, particularly amongst hospitalized individuals. The principle mechanism for pathogenesis in hospital environments involves the formation of biofilms, primarily on implanted medical devices. In this study, we constructed a transposon mutant library in a clinical isolate, K. pneumoniae AJ218, to identify the genes and pathways implicated in biofilm formation. Three mutants severely defective in biofilm formation contained insertions within the mrkABCDF genes encoding the main structural subunit and assembly machinery for type 3 fimbriae. Two other mutants carried insertions within the yfiN and mrkJ genes, which encode GGDEF domain- and EAL domain-containing c-di-GMP turnover enzymes, respectively. The remaining two isolates contained insertions that inactivated the mrkH and mrkI genes, which encode for novel proteins with a c-di-GMP-binding PilZ domain and a LuxR-type transcriptional regulator, respectively. Biochemical and functional assays indicated that the effects of these factors on biofilm formation accompany concomitant changes in type 3 fimbriae expression. We mapped the transcriptional start site of mrkA, demonstrated that MrkH directly activates transcription of the mrkA promoter and showed that MrkH binds strongly to the mrkA regulatory region only in the presence of c-di-GMP. Furthermore, a point mutation in the putative c-di-GMP-binding domain of MrkH completely abolished its function as a transcriptional activator. In vivo analysis of the yfiN and mrkJ genes strongly indicated their c-di-GMP-specific function as diguanylate cyclase and phosphodiesterase, respectively. In addition, in vitro assays showed that purified MrkJ protein has strong c-di-GMP phosphodiesterase activity. These results demonstrate for the first time that c-di-GMP can function as an effector to stimulate the activity of a transcriptional activator, and explain how type 3 fimbriae expression is coordinated with other gene expression programs in K. pneumoniae to promote biofilm formation to implanted medical devices

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Superpixel-Based Regional-Scale Grassland Community Classification Using Genetic Programming with Sentinel-1 SAR and Sentinel-2 Multispectral Images

Grasslands are one of the most important terrestrial ecosystems on the planet and have significant economic and ecological value. Accurate and rapid discrimination of grassland communities is critical to the conservation and utilization of grassland resources. Previous studies that explored grassland communities were mainly based on field surveys or airborne hyperspectral and high-resolution imagery. Limited by workload and cost, these methods are typically suitable for small areas. Spaceborne mid-resolution RS images (e.g., Sentinel, Landsat) have been widely used for large-scale vegetation observations owing to their large swath width. However, there still keep challenges in accurately distinguishing between different grassland communities using these images because of the strong spectral similarity of different communities and the suboptimal performance of models used for classification. To address this issue, this paper proposed a superpixel-based grassland community classification method using Genetic Programming (GP)-optimized classification model with Sentinel-2 multispectral bands, their derived vegetation indices (VIs) and textural features, and Sentinel-1 Synthetic Aperture Radar (SAR) bands and the derived textural features. The proposed method was evaluated in the Siziwang grassland of China. Our results showed that the addition of VIs and textures, as well as the use of GP-optimized classification models, can significantly contribute to distinguishing grassland communities, and the proposed approach classified the seven communities in Siziwang grassland with an overall accuracy of 84.21% and a kappa coefficient of 0.81. We concluded that the classification method proposed in this paper is capable of distinguishing grassland communities with high accuracy at a regional scale

Fusion of GF and MODIS Data for Regional-Scale Grassland Community Classification with EVI2 Time-Series and Phenological Features

Satellite-borne multispectral data are suitable for regional-scale grassland community classification owing to comprehensive coverage. However, the spectral similarity of different communities makes it challenging to distinguish them based on a single multispectral data. To address this issue, we proposed a support vector machine (SVM)–based method integrating multispectral data, two-band enhanced vegetation index (EVI2) time-series, and phenological features extracted from Chinese GaoFen (GF)-1/6 satellite with (16 m) spatial and (2 d) temporal resolution. To obtain cloud-free images, the Enhanced Spatial and Temporal Adaptive Reflectance Fusion Model (ESTARFM) algorithm was employed in this study. By using the algorithm on the coarse cloudless images at the same or similar time as the fine images with cloud cover, the cloudless fine images were obtained, and the cloudless EVI2 time-series and phenological features were generated. The developed method was applied to identify grassland communities in Ordos, China. The results show that the Caragana pumila Pojark, Caragana davazamcii Sanchir and Salix schwerinii E. L. Wolf grassland, the Potaninia mongolica Maxim, Ammopiptanthus mongolicus S. H. Cheng and Tetraena mongolica Maxim grassland, the Caryopteris mongholica Bunge and Artemisia ordosica Krasch grassland, the Calligonum mongolicum Turcz grassland, and the Stipa breviflora Griseb and Stipa bungeana Trin grassland are distinguished with an overall accuracy of 87.25%. The results highlight that, compared to multispectral data only, the addition of EVI2 time-series and phenological features improves the classification accuracy by 9.63% and 14.7%, respectively, and even by 27.36% when these two features are combined together, and indicate the advantage of the fine images in this study, compared to 500 m moderate-resolution imaging spectroradiometer (MODIS) data, which are commonly used for grassland classification at regional scale, while using 16 m GF data suggests a 23.96% increase in classification accuracy with the same extracted features. This study indicates that the proposed method is suitable for regional-scale grassland community classification

2-(2-Benzofuranyl)-2-imidazoline treatment within 5 hours after cerebral ischemia/reperfusion protects the brain

We previously demonstrated that administering 2-(2-benzofuranyl)-2-imidazolin (2-BFI), an imidazoline I2 receptor agonist, immediately after ischemia onset can protect the brain from ischemic insult. However, immediate administration after stroke is difficult to realize in the clinic. Thus, the therapeutic time window of 2-BFI should be determined. Sprague-Dawley rats provided by Wenzhou Medical University in China received right middle cerebral artery occlusion for 120 minutes, and were treated with 2-BFI (3 mg/kg) through the caudal vein at 0, 1, 3, 5, 7, and 9 hours after reperfusion. Neurological function was assessed using the Longa's method. Infarct volume was measured by 2,3,5-triphenyltetrazolium chloride assay. Morphological changes in the cortical penumbra were observed by hematoxylin-eosin staining under transmission electron microscopy . The apoptosis levels in the ipsilateral cortex were examined with terminal deoxynucleotidyl transferase-mediated dUTP nick end-labeling (TUNEL) assay. The protein expression of Bcl-2 and BAX was detected using immunohistochemistry. We found the following: Treatment with 2-BFI within 5 hours after reperfusion obviously improved neurological function. Administering 2-BFI within 9 hours after ischemia/reperfusion decreased infarct volume and alleviated apoptosis. 2-BFI administration at different time points after reperfusion alleviated the pathological damage of the ischemic penumbra and reduced the number of apoptotic neurons, but the protective effect was more obvious when administered within 5 hours. Administration of 2-BFI within 5 hours after reperfusion remarkably increased Bcl-2 expression and decreased BAX expression. To conclude, 2-BFI shows potent neuroprotective effects when administered within 5 hours after reperfusion, seemingly by up-regulating Bcl-2 and down-regulating BAX expression. The time window provided clinical potential for ischemic stroke by 2-BFI

KLK10/LIPH/PARD6B/SLC52A3 are promising molecular biomarkers for the prognosis of pancreatic cancer through a ceRNA network

Pancreatic adenocarcinoma (PAAD) remains challenging to diagnose and treat clinically due to its difficult early diagnosis, low surgical resection rate, and high risk of postoperative recurrence and metastasis. SMAD4 is a classical mutated gene in pancreatic cancer and is lost in up to 60%–90 % of PAAD patients, and its mutation often predicts a poor prognosis and treatment resistance. In this study, based on the expression profile data in The Cancer Genome Atlas database, we identified a ceRNA network composed of 2 lncRNAs, 1 miRNA, and 4 mRNAs through differential expression analysis and survival prognosis analysis. Among them, high expression of KLK10/LIPH/PARD6B/SLC52A3 influenced the prognosis and overall survival of PAAD patients. We confirmed the high expression of these target genes in pancreatic tissue of pancreatic-specific SMAD4-deficient mice. In addition, immune infiltration analysis showed that the high expression of these target genes affects the tumor immune environment and contributes to the progression of PAAD. Abnormal overexpression of these target genes may be caused by hypermethylation. In conclusion, we found that KLK10/LIPH/PARD6B/SLC52A3 is a potential prognostic marker for PAAD based on a competing endogenous RNA-mediated mechanism and revealed the potential pathogenic mechanism by which deficient expression of SMAD4 promotes pancreatic cancer progression, which provides a new pathway and theoretical basis for targeted therapy or improved prognosis of pancreatic cancer. These data will help reveal potential therapeutic targets for pancreatic cancer and improve the prognosis of pancreatic cancer patients

Identification and validation of functional roles for three MYC-associated genes in hepatocellular carcinoma

Background: Aberrations in MYC underlie a large proportion of liver hepatocellular carcinoma (LIHC) cases; however, MYC is difficult to target because of its undruggable structure. We aimed to uncover MYC-associated molecular targets to provide new strategies for LIHC treatment. Methods: LIHC transcriptome datasets and clinical information were obtained from The Cancer Genome Atlas. A series of bioinformatics analyses were performed for 370 patients who were stratified based on the median MYC expression level (high-MYC group and low-MYC group). Correlation analysis was performed to determine relationships between the expression of key MYC-associated genes and prognosis, DNA promotor methylation, and immune cell infiltration. Gene ontology and Kyoto Encyclopedia of Genes and Genomes Pathway enrichment analyses were performed to elucidate the functions of these genes in LIHC. Their expression and functions in LIHC were further verified using transgenic mice overexpressing c-Myc under control of the hepatocyte-specific promoter (Alb-Cre). Results: AURKB, CCNB2, and CDKN3 were overexpressed in LIHC patients with high MYC expression and were associated with poor prognosis. Upregulation of these 3 genes was significantly correlated with hypomethylated promoter status, advanced T stage, metastasis, and immune cell infiltration in LIHC patients. Functional enrichment analyses indicated that these genes participate in the “p53 signaling pathway” and “cell cycle”. Furthermore, RT-PCR and IHC analysis revealed that their mRNA and protein expression levels were upregulated in an Alb-Cre;cMYClsl/- mouse model. Drugs that target these 3 MYC-related genes were identified. Conclusion: Taken together, our results identify biomarkers of potential utility for managing liver cancer therapy owing to their significance in tumorigenesis, proliferation, and tumor immunity