Aspergillus fumigatus challenged by human dendritic cells: metabolic and regulatory pathway responses testify a tight battle

Dendritic cells (DCs) are antigen presenting cells which serve as a passage between the innate and the acquired immunity. Aspergillosis is a major lethal condition in immunocompromised patients caused by the adaptable saprophytic fungus Aspergillus fumigatus. The healthy human immune system is capable to ward off A. fumigatus infections however immune-deficient patients are highly vulnerable to invasive aspergillosis. A. fumigatus can persist during infection due to its ability to survive the immune response of human DCs. Therefore, the study of the metabolism specific to the context of infection may allow us to gain insight into the adaptation strategies of both the pathogen and the immune cells. We established a metabolic model of A. fumigatus central metabolism during infection of DCs and calculated the metabolic pathway (elementary modes; EMs). Transcriptome data were used to identify pathways activated when A. fumigatus is challenged with DCs. In particular, amino acid metabolic pathways, alternative carbon metabolic pathways and stress regulating enzymes were found to be active. Metabolic flux modeling identified further active enzymes such as alcohol dehydrogenase, inositol oxygenase and GTP cyclohydrolase participating in different stress responses in A. fumigatus. These were further validated by qRT-PCR from RNA extracted under these different conditions. For DCs, we outlined the activation of metabolic pathways in response to the confrontation with A. fumigatus. We found the fatty acid metabolism plays a crucial role, along with other metabolic changes. The gene expression data and their analysis illuminate additional regulatory pathways activated in the DCs apart from interleukin regulation. In particular, Toll-like receptor signaling, NOD-like receptor signaling and RIG-I-like receptor signaling were active pathways. Moreover, we identified subnetworks and several novel key regulators such as UBC, EGFR, and CUL3 of DCs to be activated in response to A. fumigatus. In conclusion, we analyze the metabolic and regulatory responses of A. fumigatus and DCs when confronted with each other

Evaluation and comparison of the constitutive expression levels of Toll-like receptors 2, 3 and 7 in the peripheral blood mononuclear cells of Tharparkar and crossbred cattle

Aim: This study was undertaken to assess the differential expression levels of toll-like receptors (TLRs) 2, 3 and 7 in peripheral blood mononuclear cells (PBMCs) isolated from Tharparkar and Crossbred cattle belonging to different regions of India. Materials and Methods: PBMCs were isolated from blood samples of Tharparkar cattle from Indian Veterinary Research Institute (IVRI) farm (n=30); Suratgarh farm (n=61); Jaipur farm (n=8) and cross breed cattle from Jaipur (n=47). RNA was isolated from PBMCs and cDNA was synthesized using random hexamers. The expression profiles of TLR 2, 3 and 7 were estimated by real-time PCR and normalized to the expression of β-actin. Results: PBMCs of Tharparkar cattle from Suratgarh, exhibited a significantly higher (p<0.05) constitutive expression levels of TLR2, TLR3 and TLR7 genes as compared to Tharparkar cattle from IVRI or Jaipur as well as the crossbred cattle from Jaipur. PBMCs of crossbred cattle from Jaipur showed higher expression profiles of all the TLRs than Tharparkar cattle from Jaipur and IVRI. Conclusion: Our study indicates, expression levels of TLR2, TLR3 and TLR7 are significantly higher for Tharparkar cattle from Suratgarh than the cattle from Jaipur and IVRI and crossbred cattle from Jaipur. However, crossbred cattle from Jaipur showed higher basal expression levels of all the three TLRs than Tharparkar cattle from Jaipur and IVRI. Results also indicate that PBMCs of Tharparkar cattle show a regional variation in the expression pattern of TLRs

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Acquired resistance to oxaliplatin is not directly associated with increased resistance to DNA damage in SK-N-ASrOXALI4000, a newly established oxaliplatin-resistant sub-line of the neuroblastoma cell line SK-N-AS

The formation of acquired drug resistance is a major reason for the failure of anti-cancer therapies after initial response. Here, we introduce a novel model of acquired oxaliplatin resistance, a sub-line of the non-MYCN-amplified neuroblastoma cell line SK-N-AS that was adapted to growth in the presence of 4000 ng/mL oxaliplatin (SK-N-ASrOXALI4000). SK-N-ASrOXALI4000 cells displayed enhanced chromosomal aberrations compared to SK-N-AS, as indicated by 24-chromosome fluorescence in situ hybridisation. Moreover, SK-N-ASrOXALI4000 cells were resistant not only to oxaliplatin but also to the two other commonly used anti-cancer platinum agents cisplatin and carboplatin. SK-N-ASrOXALI4000 cells exhibited a stable resistance phenotype that was not affected by culturing the cells for 10 weeks in the absence of oxaliplatin. Interestingly, SK-N-ASrOXALI4000 cells showed no cross resistance to gemcitabine and increased sensitivity to doxorubicin and UVC radiation, alternative treatments that like platinum drugs target DNA integrity. Notably, UVC-induced DNA damage is thought to be predominantly repaired by nucleotide excision repair and nucleotide excision repair has been described as the main oxaliplatin-induced DNA damage repair system. SK-N-ASrOXALI4000 cells were also more sensitive to lysis by influenza A virus, a candidate for oncolytic therapy, than SK-N-AS cells. In conclusion, we introduce a novel oxaliplatin resistance model. The oxaliplatin resistance mechanisms in SK-N-ASrOXALI4000 cells appear to be complex and not to directly depend on enhanced DNA repair capacity. Models of oxaliplatin resistance are of particular relevance since research on platinum drugs has so far predominantly focused on cisplatin and carboplatin

Alveolar Regeneration in COVID-19 Patients: A Network Perspective

A viral infection involves entry and replication of viral nucleic acid in a host organism, subsequently leading to biochemical and structural alterations in the host cell. In the case of SARS-CoV-2 viral infection, over-activation of the host immune system may lead to lung damage. Albeit the regeneration and fibrotic repair processes being the two protective host responses, prolonged injury may lead to excessive fibrosis, a pathological state that can result in lung collapse. In this review, we discuss regeneration and fibrosis processes in response to SARS-CoV-2 and provide our viewpoint on the triggering of alveolar regeneration in coronavirus disease 2019 (COVID-19) patients

Review: Role of the plant-specific calcium-binding C2-DOMAIN ABSCISIC ACID-RELATED (CAR) protein family in environmental signaling

Many signaling processes rely on information decoding at the plasma membrane, and membrane-associated proteins and their complexes are fundamental for regulating this process. Still many questions exist as to how protein complexes are assembled and function at membrane sites to change identity and dynamics of membrane systems. Peripheral membrane proteins containing a calcium and phospholipid-binding C2-domain can act in membrane-related signaling by providing a tethering function so that protein complexes form. C2 domain proteins termed C2-DOMAIN ABSCISIC ACID-RELATED (CAR) proteins are plant-specific, and the functional relevance of this C2 domain protein subgroup is just emerging. The ten Arabidopsis CAR proteins CAR1 to CAR10 have a single C2 domain with a plant-specific insertion, the so-called “CAR-extra-signature” or also termed “sig domain”. Via this “sig domain” CAR proteins can bind signaling protein complexes of different kinds and act in biotic and abiotic stress, blue light and iron nutrition. Interestingly, CAR proteins can oligomerize in membrane microdomains, and their presence in the nucleus can be linked with nuclear protein regulation. This shows that CAR proteins may play unprecedented roles in coordinating environmental responses and assembling required protein complexes to transmit information cues between plasma membrane and nucleus. The aim of this review is to summarize structure-function characteristics of the CAR protein family and assemble findings from CAR protein interactions and physiological functions. From this comparative investigation we extract common principles about the molecular operations that CAR proteins may fulfill in the cell. We also deduce functional properties of the CAR protein family based on its evolution and gene expression profiles. We highlight open questions and suggest novel avenues to prove and understand the functional networks and roles played by this protein family in plants

Efficient Statistical Clustering Techniques for Optimizing Cluster Size in Wireless Sensor Network

AbstractMobility of sensor node in Wireless Sensor Network (WSN) is one of the key advantages of wireless over fixed communication system. In heterogeneous system, generally power consumption is more then homogeneous system. The information or data message passing process must be well architecture to save the limited energy resources of the sensors. Clustering of sensors into different groups, so that sensors communicate information to the other cluster and then the cluster communicate the true information to the processing center which may save energy. So the coordination in distributed sensor network the implementation of clustering is an important technique and clusters of bounded size which is the total number of nodes in a specific cluster, is an important parameter in clustering algorithms which are very much effective in reducing energy consumption by minimizing the neighborhood of a node. Communication cost is also an important parameter for computation in a large area. Clustering techniques is Wireless Sensor Networks (WSNs) compare to random selection techniques is less costly due to the saving of time in journeys, reduction in number of transmissions and receptions at each node, identification, contacts etc. Which are valuable for increasing the overall network life, scalability of WSNs. Clustering sensor nodes is an effective and efficient technique for achieving all the requirement. In this paper, we propose a distributed, randomized clustering techniques to find optimum cluster size and cost to organize the sensors in a wireless sensor network within clusters

Genome-wide inference of the Camponotus floridanus protein-protein interaction network using homologous mapping and interacting domain profile pairs

Apart from some model organisms, the interactome of most organisms is largely unidentified. High-throughput experimental techniques to determine protein-protein interactions (PPIs) are resource intensive and highly susceptible to noise. Computational methods of PPI determination can accelerate biological discovery by identifying the most promising interacting pairs of proteins and by assessing the reliability of identified PPIs. Here we present a first in-depth study describing a global view of the ant Camponotus floridanus interactome. Although several ant genomes have been sequenced in the last eight years, studies exploring and investigating PPIs in ants are lacking. Our study attempts to fill this gap and the presented interactome will also serve as a template for determining PPIs in other ants in future. Our C. floridanus interactome covers 51,866 non-redundant PPIs among 6,274 proteins, including 20,544 interactions supported by domain-domain interactions (DDIs), 13,640 interactions supported by DDIs and subcellular localization, and 10,834 high confidence interactions mediated by 3,289 proteins. These interactions involve and cover 30.6% of the entire C. floridanus proteome

Identification of antifungal targets based on computer modeling

Aspergillus fumigatus is a saprophytic, cosmopolitan fungus that attacks patients with a weak immune system. A rational solution against fungal infection aims to manipulate fungal metabolism or to block enzymes essential for Aspergillus survival. Here we discuss and compare different bioinformatics approaches to analyze possible targeting strategies on fungal-unique pathways. For instance, phylogenetic analysis reveals fungal targets, while domain analysis allows us to spot minor differences in protein composition between the host and fungi. Moreover, protein networks between host and fungi can be systematically compared by looking at orthologs and exploiting information from host–pathogen interaction databases. Further data—such as knowledge of a three-dimensional structure, gene expression data, or information from calculated metabolic fluxes—refine the search and rapidly put a focus on the best targets for antimycotics. We analyzed several of the best targets for application to structure-based drug design. Finally, we discuss general advantages and limitations in identification of unique fungal pathways and protein targets when applying bioinformatics tools