Dynorphin B (6-9)
Formula: C26H43N11O6 (605.3398)
Chinese Name:
BioDeep ID: BioDeep_00000032774
( View LC/MS Profile)
SMILES: N[C@H](CCCNC(N)=N)C(=O)N[C@@H](CCCNC(N)=N)C(=O)N[C@H](CCC(O)=N)C(=O)N[C@@H](CC1=CC=CC=C1)C(O)=O
Found 16 Sample Hits
| m/z | Adducts | Species | Organ | Scanning | Sample | |
|---|---|---|---|---|---|---|
| 606.3427 | [M+H]+PPM:7.2 |
Homo sapiens | esophagus | DESI () |
LNTO22_1_3 - MTBLS385Resolution: 75μm, 121x68
|
|
| 623.3771 | [M+NH4]+PPM:5.6 |
Homo sapiens | esophagus | DESI () |
LNTO22_1_3 - MTBLS385Resolution: 75μm, 121x68
|
|
| 605.3659 | [M-H2O+NH4]+PPM:4.8 |
Homo sapiens | esophagus | DESI () |
LNTO22_1_4 - MTBLS385Resolution: 17μm, 82x80
|
|
| 588.3392 | [M+H-H2O]+PPM:4.6 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
|
| 605.3642 | [M-H2O+NH4]+PPM:1.9 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
|
| 623.3727 | [M+NH4]+PPM:1.4 |
Mus musculus | Liver | MALDI (CHCA) |
Salmonella_final_pos_recal - MTBLS2671Resolution: 17μm, 691x430
A more complete and holistic view on host–microbe interactions is needed to understand the physiological and cellular barriers that affect the efficacy of drug treatments and allow the discovery and development of new therapeutics. Here, we developed a multimodal imaging approach combining histopathology with mass spectrometry imaging (MSI) and same section imaging mass cytometry (IMC) to study the effects of Salmonella Typhimurium infection in the liver of a mouse model using the S. Typhimurium strains SL3261 and SL1344. This approach enables correlation of tissue morphology and specific cell phenotypes with molecular images of tissue metabolism. IMC revealed a marked increase in immune cell markers and localization in immune aggregates in infected tissues. A correlative computational method (network analysis) was deployed to find metabolic features associated with infection and revealed metabolic clusters of acetyl carnitines, as well as phosphatidylcholine and phosphatidylethanolamine plasmalogen species, which could be associated with pro-inflammatory immune cell types. By developing an IMC marker for the detection of Salmonella LPS, we were further able to identify and characterize those cell types which contained S. Typhimurium.
[dataset] Nicole Strittmatter. Holistic Characterization of a Salmonella Typhimurium Infection Model Using Integrated Molecular Imaging, metabolights_dataset, V1; 2022. https://www.ebi.ac.uk/metabolights/MTBLS2671. |
|
| 588.3426 | [M+H-H2O]+PPM:10.4 |
Mytilus edulis | gill | MALDI (DHB) |
20190202_MS38_Crassostrea_Gill_350-1500_DHB_pos_A25_11um_305x210 - MTBLS2960Resolution: 11μm, 305x210
single cell layer |
|
| 606.353 | [M+H]+PPM:9.8 |
Mytilus edulis | gill | MALDI (DHB) |
20190202_MS38_Crassostrea_Gill_350-1500_DHB_pos_A25_11um_305x210 - MTBLS2960Resolution: 11μm, 305x210
single cell layer |
|
| 606.3426 | [M+H]+PPM:7.3 |
Homo sapiens | esophagus | DESI () |
LNTO26_7_1 - MTBLS385Resolution: 17μm, 75x74
|
|
| 606.3434 | [M+H]+PPM:6 |
Homo sapiens | esophagus | DESI () |
LNTO26_7_2 - MTBLS385Resolution: 17μm, 135x101
|
|
| 606.3424 | [M+H]+PPM:7.6 |
Homo sapiens | esophagus | DESI () |
LNTO26_7_3 - MTBLS385Resolution: 75μm, 82x88
|
|
| 606.3431 | [M+H]+PPM:6.5 |
Homo sapiens | esophagus | DESI () |
LNTO22_1_5 - MTBLS385Resolution: 75μm, 135x94
|
|
| 606.3431 | [M+H]+PPM:6.5 |
Homo sapiens | esophagus | DESI () |
LNTO22_1_8 - MTBLS385Resolution: 75μm, 69x61
|
|
| 606.3425 | [M+H]+PPM:7.5 |
Homo sapiens | esophagus | DESI () |
LNTO22_2_1 - MTBLS385Resolution: 75μm, 89x88
|
|
| 606.3431 | [M+H]+PPM:6.5 |
Homo sapiens | esophagus | DESI () |
LNTO22_2_2 - MTBLS385Resolution: 75μm, 135x94
|
|
| 606.3426 | [M+H]+PPM:7.3 |
Homo sapiens | esophagus | DESI () |
LNTO26_16_1 - MTBLS385Resolution: 75μm, 95x88
|
|
Dynorphin B (6-9) is fraction of Dynorphin B with only Arg-Arg-Gln-Phe peptide chain. Dynorphin B is an agonist of nuclear opioid receptors coupling nuclear protein Kinase C activation to the transcription of cardiogenic genes in GTR1 embryonic stem cells. Dynorphin B is a form of dynorphin.Dynorphins are a class of opioid peptides that arise from the precursor protein prodynorphin. When prodynorphin is cleaved during processing by proprotein convertase 2 (PC2), multiple active peptides are released: dynorphin A, dynorphin B, and a/b-neo-endorphin. Depolarization of a neuron containing prodynorphin stimulates PC2 processing, which occurs within synaptic vesicles in the presynaptic terminal. Occasionally, prodynorphin is not fully processed, leading to the release of "big dynorphin."This 32-amino acid molecule consists of both dynorphin A and dynorphin B.Dynorphin A, dynorphin B, and big dynorphin all contain a high proportion of basic amino acid residues, in particular lysine and arginine (29.4\\%, 23.1\\%, and 31.2\\% basic residues, respectively), as well as many hydrophobic residues (41.2\\%, 30.8\\%, and 34.4\\% hydrophobic residues, respectively). Although dynorphins are found widely distributed in the CNS, they have the highest concentrations in the hypothalamus, medulla, pons, midbrain, and spinal cord. Dynorphins are stored in large (80-120 nm diameter) dense-core vesicles that are considerably larger than vesicles storing neurotransmitters. These large dense-core vesicles differ from small synaptic vesicles in that a more intense and prolonged stimulus is needed to cause the large vesicles to release their contents into the synaptic cleft. Dense-core vesicle storage is characteristic of opioid peptides storage. The first clues to the functionality of dynorphins came from Goldstein et al. in their work with opioid peptides. The group discovered an endogenous opioid peptide in the porcine pituitary that proved difficult to isolate. By sequencing the first 13 amino acids of the peptide, they created a synthetic version of the peptide with a similar potency to the natural peptide. Goldstein et al. applied the synthetic peptide to the guinea ileum longitudinal muscle and found it to be an extraordinarily potent opioid peptide. The peptide was called dynorphin (from the Greek dynamis=power) to describe its potency. Dynorphins exert their effects primarily through the κ-opioid receptor (KOR), a G-protein-coupled receptor. Two subtypes of KORs have been identified: K1 and K2. Although KOR is the primary receptor for all dynorphins, the peptides do have some affinity for the μ-opioid receptor (MOR), d-opioid receptor (DOR), N-methyl-D-aspartic acid (NMDA)-type glutamate receptor. Different dynorphins show different receptor selectivities and potencies at receptors. Big dynorphin and dynorphin A have the same selectivity for human KOR, but dynorphin A is more selective for KOR over MOR and DOR than is big dynorphin. Big dynorphin is more potent at KORs than is dynorphin A. Both big dynorphin and dynorphin A are more potent and more selective than dynorphin B (Wikipedia). Dynorphin B (6-9) is fraction of Dynorphin B with only Arg-Arg-Gln-Phe peptide chain.
