Raman
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB59025 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Primary outcome(s): Identification of enteric nerve system in the gastrointestinal wall using Raman spectroscopy
| 103701 | ecrin-mdr-crc
Project description:With the global increase in the use of carbapenems, several gram-negative bacteria have acquired carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is one of such notorious pathogen that is being widely studied to find novel resistance mechanisms and drug targets. These antibiotic-resistant clinical isolates generally harbor many genetic alterations, and identification of causal mutations will provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance, in which mutated genes that also show significant expression changes among their functionally coupled genes become more likely candidates. For network-based analyses, we developed a genome-scale co-functional network of K. pneumoniae genes, KlebNet (www.inetbio.org/klebnet). Using KlebNet, we could reconstruct functional modules for antibiotic-resistance, and virulence, and retrieved functional association between them. With complementation assays with top candidate genes, we could validate a gene for negative regulation of meropenem resistance and four genes for positive regulation of virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antimicrobial resistance and virulence of human pathogenic bacteria with genomic and transcriptomic profiles from antibiotic-resistant clinical isolates.
2018-06-10 | GSE115539 | GEO
Project description:Multi-excitation Raman Spectroscopy Complements Whole Genome Sequencing for Rapid Detection of Bacterial Infection and Resistance in WHO Priority Pathogens
| PRJEB59061 | ENA
Project description:Alteration in metabolic repertoire is commonly associated with resistance phenotype. Although it’s a common phenotype, not much efforts have been undertaken to design effective strategies to target the metabolic drift in such cancerous cells and especially with drug resistant properties. In our study, we identified that drug resistant AML cell line HL-60/MX2 do not follow classical Warburg effect, instead these cells exhibit drastically low levels of aerobic glycolysis. Biochemical analysis confirms reduced glucose consumption and lactic acid production by resistant population with no differences in glutamine consumption. Raman spectroscopy revealed increased lipid and cytochrome content in resistant cells which were also visualized in the form of lipid droplets by Raman mapping, electron microscopy and lipid specific staining. Gene set enrichment analysis data from both the cell lines revealed significant enrichment of lipid metabolic pathways in HL-60/MX2 cells. Further drug resistant cells possess higher mitochondrial activity and increased OXPHOS suggested the role of fatty acid metabolism as energy source which was confirmed by increased rate of fatty acid oxidation. Pharmacological inhibition of fatty acid oxidation using Etomoxir affected the colony formation ability of resistant cells and inhibition of OXPHOS using Antimycin-A increased the sensitivity of resistant cells to chemotherapeutic drug, demonstrating requirement of fatty acid metabolism and increased dependency on OXPHOS by resistant leukemic cells for tumorigenicity.
2021-01-01 | E-MTAB-8981 | biostudies-arrayexpress
Project description:Polyprenol phosphate mannose (PPM) is a lipid linked sugar donor used by extra-cytoplasmic glycosyl tranferases in bacteria. PPM is synthesised by polyprenol phosphate mannose synthase, Ppm1, and in most Actinobacteria is used as the sugar donor for protein O-mannosyl transferase, Pmt, in protein glycosylation. Ppm1 and Pmt have homologues in yeasts and humans, where they are required for protein O-mannosylation. Actinobacteria also use PPM for lipoglycan biosynthesis. Here we show that ppm1 mutants of Streptomyces coelicolor have increased susceptibility to a number of antibiotics that target cell wall biosynthesis. The pmt mutants also have mildly increased antibiotic susceptibilities, in particular to -lactams and vancomycin. Despite normal induction of the vancomycin gene cluster, vanSRJKHAX, the pmt and ppm1 mutants remained highly vancomycin sensitive indicating that the mechanism of resistance is blocked post-transcriptionally. Differential RNA expression analysis indicated that catabolic pathways were downregulated and anabolic ones upregulated in the ppm1 mutant compared to the parent or complemented strains. Of note was the increase in expression of fatty acid biosynthetic genes in the ppm1- mutant. A change in lipid composition was confirmed using Raman spectroscopy, which showed that the ppm1- mutant had a greater relative proportion of unsaturated fatty acids compared to the parent or the complemented mutant. Taken together these data suggest that an inability to synthesise PPM (ppm1-) and loss of the glycoproteome (pmt- mutant) can detrimentally affect membrane or cell envelope functions leading to loss of intrinsic and, in the case of vancomycin, acquired antibiotic resistance.
2018-01-11 | GSE107982 | GEO
Project description:Emerging known and unknown pathogens create profound threats to public health. Platforms for rapid detection and characterization of microbial agents are critically needed to prevent and respond to disease outbreaks. Available detection technologies cannot provide broad functional information about known and novel organisms. As a step toward developing such a system, we have produced and tested a series of high-density functional gene arrays to detect elements of virulence and antibiotic resistance mechanisms. Our first generation array targets genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for gene family detection and discrimination. When tested with organisms at varying phylogenetic distances from the four target strains, the array detected orthologs for the majority of targeted gene families present in bacteria belonging to the same taxonomic family. In combination with whole-genome amplification, the array detects femtogram concentrations of purified DNA, either spiked in to an aerosol sample background, or in combinations from one or more of the four target organisms. This is the first report of a high density NimbleGen microarray system targeting microbial antibiotic resistance and virulence mechanisms. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. Keywords: detection, pathogen, virulence mechanism In this report, we describe the process used to design our first generation functional array for highly sensitive detection of virulence and antibiotic resistance gene families. We discuss the probe design algorithms, including virulence gene sequence selection, and our protocols for sample preparation, amplification, labeling, hybridization, and data analysis. We present the results from experiments designed to assess whether the array can detect virulence gene orthologs from organisms without perfect match probes on the array, using both targeted mismatch probes and hybridizations to DNA from other organisms. Also, we report the results from limit of detection studies, using known amounts of bacterial DNA spiked into aerosol samples to measure the minimal concentration required for detection of virulence elements against a complex background.
2008-04-02 | E-GEOD-11010 | biostudies-arrayexpress
Project description:Emerging known and unknown pathogens create profound threats to public health. Platforms for rapid detection and characterization of microbial agents are critically needed to prevent and respond to disease outbreaks. Available detection technologies cannot provide broad functional information about known and novel organisms. As a step toward developing such a system, we have produced and tested a series of high-density functional gene arrays to detect elements of virulence and antibiotic resistance mechanisms. Our first generation array targets genes from Escherichia coli strains K12 and CFT073, Enterococcus faecalis and Staphylococcus aureus. We determined optimal probe design parameters for gene family detection and discrimination. When tested with organisms at varying phylogenetic distances from the four target strains, the array detected orthologs for the majority of targeted gene families present in bacteria belonging to the same taxonomic family. In combination with whole-genome amplification, the array detects femtogram concentrations of purified DNA, either spiked in to an aerosol sample background, or in combinations from one or more of the four target organisms. This is the first report of a high density NimbleGen microarray system targeting microbial antibiotic resistance and virulence mechanisms. By targeting virulence gene families as well as genes unique to specific biothreat agents, these arrays will provide important data about the pathogenic potential and drug resistance profiles of unknown organisms in environmental samples. Keywords: detection, pathogen, virulence mechanism
2008-04-02 | GSE11010 | GEO
Project description:Early detection and treatment of gastric premalignant lesion and early gastric cancer (EGC) have been proposed to improve outcomes of gastric cancer. Gastric dysplasia is a premalignant lesion and the penultimate stage in gastric carcinogenesis. On white light endoscopy (WLE), it is difficult to distinguish gastric dysplasia and EGC from benign pathology such as gastric intestinal metaplasia (GIM). Image enhanced endoscopy such as narrow-band imaging (NBI) is recommended to improve characterization of suspicious gastric lesions detected on WLE. Magnified-endoscopy with NBI (ME-NBI) have been shown to be superior to HD-WLE for diagnosis of GIM and EGC. Data on gastric dysplasia is less robust. Ultimately, biopsy is required to confirm diagnosis of gastric dysplasia/EGC. Gastric dysplasia can be classified into low-grade dysplasia (LGD) or high-grade dysplasia (HGD). Biopsy sampling may not be representative of the final histopathological grade of resected specimens and may under-stage dysplasia. Thus, endoscopic resection (ER) is recommended for gastric dysplasia and EGC on biopsy for diagnostic and therapeutic purpose. The current gap is to improve concordance of endoscopic and histologic findings of gastric dysplasia and early gastric cancer. Raman spectroscopy based artificial intelligence system (SPECTRA IMDx) was developed to provide an objective method to identify patients with gastric premalignant lesions and EGC. SPECTRA IMDx interrogate tissues at the cellular level and utilizes molecular information to provide actionable information to endoscopist during gastroscopy. Studies on diagnostic performance using Raman spectroscopy analysis devices have shown high sensitivity and specificity in detection of gastric cancer and precancerous lesions compared to WLE. However, these studies included few GIM, gastric dysplasia and gastric carcinoma. It is still unclear if Raman spectroscopy outperforms WLE in diagnosis of gastric HGD and EGC. In addition, the Raman spectroscopy algorithm is only able to characterize lesions into high risk (HGD/EGC) versus low risk (GIM/LGD/Gastritis/Normal). It is also uncertain if this technology is able to differentiate GIM and LGD. We plan to conduct a prospective trial to validate the diagnostic accuracy of SPECTRA for prediction of gastric HGD and EGC prior to gastric ER. Hypothesis: SPECTRA IMDx is able to differentiate higher risk lesions (HGD/EGC) from lower risk tissue/lesion (GIM/LGD/Gastritis/Normal)
| 2376206 | ecrin-mdr-crc
Project description:Bloodstream infections (BSIs), the presence of microorganisms in blood, are potentially serious conditions that can quickly develop into sepsis and life-threatening situations. When assessing proper treatment, rapid diagnosis is the key; besides clinical judgement performed by attending physicians, supporting microbiological tests typically are performed, often requiring microbial isolation and culturing steps, which increases the time required for confirming positive cases of BSI. The additional waiting time forces physicians to prescribe broad-spectrum antibiotics and empiric treatment, before determining the precise cause of the disease. Thus, alternative and more rapid cultivation-independent methods are needed to improve clinical diagnostics, supporting prompt and accurate treatment and reducing the development of antibiotic resistance. In this study, a culture-independent workflow for pathogen detection and identification in blood samples was developed, using peptide biomarkers and applying bottom-up proteomics analyses, i.e., so-called ”proteotyping”. To demonstrate the feasibility of detection of blood infectious pathogens using proteotyping, Escherichia coli and Staphylococcus aureus were included in the study, as the most prominent bacterial causes of bacteremia and sepsis, as well as Candida albicans, one of the most prominent causes of fungemia. Model systems including spiked negative blood samples, as well as positive blood cultures, without further culturing steps, were investigated. Furthermore, an experiment designed to study the incubation time needed for correct identification of the infectious pathogens in blood cultures was performed. Compared to the MALDI-TOF MS-based approaches, shotgun proteotyping demonstrated higher sensitivity and accuracy, and required shorter incubation time before detection and identification of the correct pathogen could be accomplished.
2021-07-20 | PXD023033 | Pride