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opennotspecifiedJan 2017View details →

Fig. 1 in In-vitro antioxidative potential of different fractions from Prunus dulcis seeds: Vis a vis antiproliferative and antibacterial activities of active compounds

Fig. 1. Flow diagram of extraction of P. dulcis seeds and isolation of components from ethyl acetate fraction through different chromatography.

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Antibacterial and anatomical defences in an oil contaminated, vulnerable seaduck

Oil-spills have killed thousands of birds during the last 100 years, but non-lethal effects of oil-spills on birds remain poorly studied. We measured phenotype characters in 279 eiders Somateria mollissima of which 13.6% were oiled. We tested the hypotheses that (1) the morphology of eiders does not change due to oil contamination; (2) the anatomy of organs reflects the physiological reaction to contamination e.g. increase in metabolic demand, increase in food intake and counteracting toxic effects of oil; (3) large locomotion apparatus that facilitates locomotion increase the risk of getting oiled; and (4) individual eiders with a higher production of secretions from the uropygial grand were more likely to have oil on their plumage. We tested whether 19 characters differed between oiled and non-oiled individuals, showing a consistent pattern. The final model retained seven predictor variables showing relationships between eiders contaminated with oil and food consumption, flight and diving abilities. We tested whether these effects were due to differences in body condition, liver mass, empty gizzard mass or other characters that could have been affected by impaired flight and diving ability. There was no evidence of such negative impact of oiling on eiders. We found that significant exposure to oil was associated with increased diversity of antibacterial defence. Oiled eiders did not constitute a random sample, and superior diving ability as reflected by large foot area were at a selective disadvantage during oil spills. Thus, specific characteristics predispose eiders to oiling, with an adaptation to swimming, diving and flying being traded against the costs of oiling. In contrast, individuals with a high degree of physiological plasticity may experience an advantage because their uropygial secretions counteract the effects of oil contamination. --

opencc-zeroFeb 2023View details →

opencc-by-4.0Apr 2023View details →

Clinically used broad-spectrum antibiotics compromise inflammatory monocyte-dependent antibacterial defense in the lung

Code and data for the preprint "Clinically used broad-spectrum antibiotics compromise inflammatory monocyte-dependent antibacterial defense in the lung".  Metagenomic analysis  - uses `<a href="https://github.com/ropensci/targets">targets</a>` (workflow manager) and `<a href="https://github.com/rstudio/renv">renv</a>` (environment manager) R packages.  - calling `targets::tar_make()`, once the environment is configured using renv and a separate project has been created (with the exact file structure including the data), should run the entire pipeline, creating a _targets folder with all the .rds files  - independent objects can be explored using `targets::tar_load(obj)` or `targets::tar_read(plot)`  <a href="https://books.ropensci.org/targets/">Targets user manual </a>for more information. Preprocessing/QC scripts can be provided upon reasonable request.

Fig. 5 in Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Fig. 5. (A) Molecular docking interfaces of 41-hydroxy-macrobrevin-31-acetate (compound 3) with S. aureus peptide deformylase (SaPDF). 3D docking analysis of the titled macrobrevin analogue (ligand) and S. aureus PDF crystal structure (PDB ID: 1LQW) were conformationally structured (Swiss-Pdb Viewer, SPDBV, version 4.1.0). The primary algorithm used by AutoDock for conformational searching was the Lamarckian Genetic Algorithm (LGA) showing four hydrogen bonds each (displayed as red and bluecoloured lines) in the binding site, whereas USCF Chimera (University of California, San Francisco, ver. 1.11.2) software reinforced the visualizations of the best molecular docking positions of the compound and target protein. The contact residues were shown and labeled by type and number in the background. Compound 3 exhibited least binding energy among the titled compounds. (B) Illustrative representation of 41-hydroxy-macrobrevin-31-acetate (compound 3) forming hydrogen bond interactions with the amino acyl residues in the active site of SaPDF. Compound (3) displayed maximum number of hydrogen bond interactions (GLN141 at 3.118 Å, LYS84 at 3.789 Å and 3.388 Å, and ARG143 at 3.483 Å). (C) Drug-likeness score obtained for the compound (3) with molsoft software. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 4 in Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Fig. 4. Proposed biosynthesis of 21- membered macrocyclic lactones classified as macrobrevin analogues (1–4) in B. amyloliquefaciens through successive decarboxylative Claisen condensation between acetyl-S-KS domain and malonate-SACP units. Claisen condensation was activated by acyl carrier protein (ACP), ketoreductase (KR), ketosynthase (KS), thioesterase (TE), dehydratase (DH), methyl transferase (MT), acyl transferase (AT), enoyl reductase (ER) and S-adenosyl-methionine (SAM). The elongation process comprised of 16 modules with KS, KR and ACP domains. The initial step includes the decarboxylative Claisen condensation between 2-methylbutanethioic-S-KS and malonate-S-ACP. The final step of macrobrevin formation could occur through the cyclization of linear chain of 21-membered carbon framework by TE. Consequently, alterations of 21-membered carbon framework classified as macrobrevin scaffold could result in the formation of macrobrevin analogues 1–4.

Fig. 3 in Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Fig. 3. (A) Biosynthetic gene cluster coding for biosynthesis of macrobrevin analogues in B. amyloliquefaciens showing 46% similarity with macrobrevin biosynthetic gene cluster BGC0001470 (as elucidated by Known-Cluster-Blast prediction, the gene cluster also had 32% similarity with aurantinine and bacillaene with 100% similarity), (B) organization of genes in macrobrevin biosynthetic gene cluster of Brevibacillus sp. (C) Domain organization of the modules of trans-AT PKS gene cluster coding for bacillaene, which is 46% similar to macrobrevin biosynthetic gene cluster is shown. (D) The proposed functions of genes (1–16) contained in the biosynthetic gene cluster has been listed out, and are described as: (1) Biosynthetic additional (smcogs) SMCOG1170: metallo-β-lactamase family protein (score: 203; E-value: 5.4e-62); (2) biosynthetic trans-AT-PKS:PKS_AT biosynthetic additional SMCOG1021: malonyl CoA-acyl carrier protein transacylase (score: 400.8; E-value: 1.8e-121); (3) biosynthetic trans AT-PKS:PKS_AT biosynthetic additional SMCOG1021: malonyl CoA-acyl carrier protein transacylase (score: 232.8; E-value: 1.5e-70); (4) biosynthetic trans-AT-PKS:PKS_AT biosynthetic additional SMCOG1021:malonyl CoA-acyl carrier protein transacylase (score: 481.1; E-value: 9e-146); (5) biosynthetic additional PP-binding; (6) biosynthetic T3PKS:Chal_sti_synt_N biosynthetic additional SMCOG1043:hydroxymethylglutaryl-CoA synthase (score: 496.9; E-value: 6.5e-151); (7) biosynthetic additional SMCOG1023: enoyl-CoA hydratase (score: 228.4; E-value: 1.3e-69); (8) biosynthetic trans-AT-PKS:PP-binding biosynthetic trans-AT-PKS:tra_KS-biosynthetic trans AT-PKS:ATd-biosynthetic NRPS:AMP-binding biosynthetic-NRPS: condensation biosynthetic additional adh_short biosynthetic additional SMCOG1127: condensation domain-containing protein (score: 295.3; E-value: 1.6e-89); (9) biosynthetic additional-tra_KS biosyntheticadditional SMCOG1022: β-ketoacyl synthase (score: 160.9; E-value: 8.3e-49); (10) biosynthetic-trans-AT-PKS:PP-binding-biosynthetic-trans-AT-PKS:tra_KS-biosynthetic-trans-AT-KS:ATd-biosynthetic-additional-adh_short-biosynthetic-additional-SMCOG1001:short-chain-dehydrogenase/reductase SDR (score: 48.7; E-value: 1.2e-14); (11) biosynthetic-trans-AT-PKS:PP-binding-biosynthetic-trans-AT-PKS:tra_KS-biosynthetic-trans-AT-PKS:ATd-biosynthetic-additional-adh_short-biosynthetic-additional SMCOG1093: β-ketoacyl synthase (score: 73.2; E-value: 2.8e-22); (12) biosynthetic trans AT-PKS: PP-binding-biosynthetic-trans-AT-PKS:tra_KSbiosynthetic-trans-AT-PKS:ATd-biosynthetic-additional-adh biosynthetic-additional SMCOG1022: β-ketoacyl synthase (score: 222.6; E-value: 1.5e-67); (13) biosynthetic-additional-condensation biosynthetic-additional SMCOG1127:condensation domain-containing protein (score: 196.8; E-value: 1.3e-59); (14) biosynthetic-trans-AT-PKS:PP-binding-biosynthetic-trans-AT-PKS:tra_KS-biosynthetic-trans-AT-PKS:ATd-biosynthetic-NRPS-like:AMP-binding-biosynthetic-NRPS-like:PPbinding-biosynthetic-additional adh_short-biosynthetic-additional SMCOG1002: AMP-dependent synthetase and ligase (score: 373.7; E-value: 1.9e-113); (15) biosynthetic-additional-PP-binding-biosynthetic-additional-tra_KS-biosynthetic-additional MCOG1022: β-ketoacyl (score: 73.2; E-value: 2.8e-22); (16) biosynthetictrans-AT-PKS-like:tra_KS-biosynthetic-trans-AT-PKS-like:ATd-biosynthetic-additional-PP-binding-biosynthetic-additional SMCOG1022: β-ketoacyl synthase (score: 207.7; E-value: 5.1e-63).

Fig. 1 in Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Fig. 1. Structural representation of (A) trihydroxy-decahydro-37-methyl-macrobrevin (compound 1), (B) hexahydro-macrobrevin (compound 2), (C) hexahydro-41- hydroxy-macrobrevin-31-acetate (compound 3), and (D) hexahydro-28-nor-methyl-5-methoxy-macrobrevin (compound 4) isolated from marine macroalgaassociated B. amyloliquefaciens MTCC 12713. (E) The zone of inhibition (34 mm) observed with hexahydro-41-hydroxy-macrobrevin-31-acetate (compound 3) against VREfs as visualized on Mueller Hinton agar plates by disc diffusion assay was illustrated. The amounts of compound 3 and chloramphenicol were 30 μg per disc. Chloramphenicol and ethyl acetate, which were used as the positive and negative control, were denoted with (+) and (), respectively.

Fig. 2. 1H–1H in Polyketide-derived macrobrevins from marine macroalga-associated Bacillus amyloliquefaciens as promising antibacterial agents against pathogens causing nosocomial infections

Fig. 2. 1H–1H COSY/HMBC (A-D) correlations of macrobrevin analogues (1–4). Key 1H–1H COSY correlations and HMBC pairings were characterized by bold-faced bonds and double-barbed arrows, respectively.

opennotspecifiedMar 2022View details →

Fig. 3. 4 in Undescribed polyether ionophores from Streptomyces cacaoi and their antibacterial and antiproliferative activities

Fig. 3. 4 treatment results in proteasome inhibition and ER stress. A) Proteasomal activity was determined via Suc-Leu-Leu-Val-Tyr AMC. 1 μM Mg132 was used as a proteasome inhibitor. Reported values were normalized to cells treated with vehicle. Error bars represent standard deviation. p-values were calculated with respect to the vehicle-treated cells (****p <0.0001). B) The level of K48-linked ubiquitinated proteins was determined by IB. C) After cells were treated with 4 or vehicle for 24 h, soluble and insoluble protein fractions were prepared, then the levels of K48-linked ubiquitinated proteins were investigated. D) Following A549 cells were treated with 10 and 20 μM 4 or vehicle for 24 h, CHOP and BIP protein levels were determined via IB. E) ROS production was determined via 2′,7′-Dichlorodihydrofluorescein diacetate (DCFH). 200 mM H2O2 was used as a positive control (1 h). Error bars represent standard deviation and p-values were calculated with respect to vehicle-treated cells. (**p = 0.009, ***p = 0.0002, ****p <0.0001).

opennotspecifiedMar 2022View details →

Fig. 2. 4 in Undescribed polyether ionophores from Streptomyces cacaoi and their antibacterial and antiproliferative activities

Fig. 2. 4 triggers apoptosis and inhibits autophagic flux similar to K41-A. (A–D) A549 cells were treated with 4 (10 and 20 μM), K41-A (7 and 14 μM), or vehicle for 24 h. A) Expression level of cleaved and full length of PARP-1 was analyzed via immunoblotting (IB). (* indicate overexposure of full-length PARP-1.) B) Conversion of LC3-I to LC3-II, C) p62 level, and D) Atg-7 levels were determined via IB. (E-F) A549 cells which stably express mCherry-GFP-LC3 probe were treated with 20 μM 4, 14 μM K41-A or vehicle. Additionally, 100 ng/mL Bafilomycin was used as positive control which blocks autophagic flux. E) The mCherry-GFP-LC3 expression was visualized by fluorescence microscopy and the representative data are shown. F) Percentage of autophagosomes (mCherry+/GFP+, yellow puncta) and autolysosomes (mCherry+/GFP, red puncta) number were quantified by counting at least 40 cells. Error bars represent standard deviation and p-values were calculated with respect to vehicle-treated cells.

opennotspecifiedJun 2021View details →

Fig. 3 in Chemical constituents of Psidium guajava leaves and their antibacterial activity

Fig. 3. Experimental CD spectra of (+)/()-1, (+)/()-2, and (+)/()-3, and calculated ECD spectra of R-3 and S-3.

Fig. 2 in Induction of promising antibacterial prenylated isoflavonoids from different subclasses by sequential elicitation of soybean

Fig. 2. Timeline of (H2O2 + AgNO3)-treatment with or without subsequent microbial elicitation of soybean seedlings. Microbial elicitation was performed with a live preparation of either a phytopathogenic fungus, Rhizopus spp. or a symbiotic bacterium, Bacillus subtilis. "Early" and "Late" refer to the time point of application of the (H2O2 + AgNO3)-treatment to 2d- and 4d-germinated seedlings, respectively.

Fig. 4 in Induction of promising antibacterial prenylated isoflavonoids from different subclasses by sequential elicitation of soybean

Fig. 4. Isoflavonoid content (μmol/g DW) of "early" and "late" (H2O2 + AgNO3)-elicited (A) and (H2O2 + AgNO3)-elicited prior to R- or B- elicited (B) soybean seedlings over five days. Isoflavonoids are classified into four main families (from top to bottom); ie. glycosylated isoflavonoids (white), non-prenylated aglycones (patterned), glyceollins (light grey) and prenylated isoflavones (dark grey). Phaseol contents (black) are also depicted for sequential elicitation treatments (B). Error bars indicate the standard deviation of three biological replicates. Quantification of the individual isoflavonoids over time per treatment can be found in Tables S2–S4. Statistical analysis (Tukey's test, p <0.05) of the over-time differences in each isoflavonoid subclass within the same treatment can be found in Table S5.

Fig. 3 in Induction of promising antibacterial prenylated isoflavonoids from different subclasses by sequential elicitation of soybean

Fig. 3. RP-UHPLC-PDA (280 nm) profiles of 96% (v/v) EtOH extracts of germinated (without any treatment application), ROS-primed and subsequently Rhizopus spp. (R)-elicited (Kalli et al., 2020), (H2O2 + AgNO3)-treated and (H2O2 + AgNO3)-treated and subsequently R-elicited soybean seedlings. Extracts correspond to 7d-old seedlings, where treatments (if any) were applied on the 4th day of germination. Peak numbers refer to compounds in Table S1.

Fig. 5 in Induction of promising antibacterial prenylated isoflavonoids from different subclasses by sequential elicitation of soybean

Fig. 5. Content (μmol/g DW) of prenylated isoflavonoids in (H2O2 + AgNO3)- elicited (and subsequently B. subtilis (B)- or Rhizopus spp. (R)- elicited) soybean seedlings in comparison to the recently proposed priming and elicitation treatment, ROS + R published by Kalli et al., 2020. Prenylated isoflavonoids were classified into (from right to left): C4-glyceollins (light grey), C2-glyceollins (light grey striped), prenylated isoflavones (grey), and phaseol (dark grey). Treatments are shown at their optimum day (4d for (H2O2 + AgNO3)-elicited and 3d for the sequentially elicited or ROS + R treatments) after "late" application with respect to maximum prenylated isoflavonoid accumulation. Error bars indicate the standard deviation of three biological replicates. Asterisks signify a statistically higher accumulation of a specific prenylated isoflavonoid subclass compared to the rest of the treatments (p <0.05).

Fig. 1 in Induction of promising antibacterial prenylated isoflavonoids from different subclasses by sequential elicitation of soybean

Fig. 1. Simplified biosynthetic pathway of the main prenylated isoflavonoids and their corresponding subclasses encountered in stressed soybeans (Glycine max). The prenyl group in its different configurations is highlighted in red. The different prenyltransferases involved in the biosynthesis of the two main subclasses of prenylated isoflavonoids (ie. glyceollins and prenylated isoflavones) are demonstrated. Both possible prenylation positions (C2 and C4) on the glycinol backbone for the synthesis of glyceollins are also depicted. Based on Suzuki et al., 2006, Yoneyama et al., 2016 and Dewick et al., 1970. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 7 in Lichen-associated bacteria transform antibacterial usnic acid to products of lower antibiotic activity

Fig. 7. Molecular networking results from GNPS visualized with Cytoscape. Inset: cluster of UA and derivatives with close fragmentation pathway (m/z 357.12: compound K, m/z 389.104: compound L) and self-loop of compound H (at m/z 386.139).

Fig. 4 in Lichen-associated bacteria transform antibacterial usnic acid to products of lower antibiotic activity

Fig. 4. HPLC chromatograms of S. cyaneofuscatus cultures with or without UA: A) At the beginning of the stationary phase of bacterial growth; B) After 7 days of stationary phase. Circled in blue: compounds inhibited in the presence of UA, circled in orange: compounds more concentrated in the presence of UA, circled in red: UA. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Lichen-associated bacteria transform antibacterial usnic acid to products of lower antibiotic activity

Fig. 1. Monitoring of the bacterial growth over 15 days (D0 to D15) by measuring optical density (log OD (optical density), gray curve) and cell viability (%) using MTT assay (blue curve) compared to untreated culture (orange curve). A) Nocardia sp., B) S. cyaneofuscatus, C) M. ruber. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Lichen-associated bacteria transform antibacterial usnic acid to products of lower antibiotic activity

Fig. 3. HPLC chromatograms of Nocardia sp. culture with or without UA. A) At the beginning of the stationary phase of the bacterial growth; B) After 7 days of stationary phase. Compounds circled in red appear only in the culture with UA. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)