Cell-penetrating peptides (CPPs) traverse the membrane of biological cells at low micromolar concentrations and are able to take various cargo molecules along with. Despite large differences in their ...chemical structure, CPPs share the structural similarity of a high cationic charge density. This property confers to them the ability to bind electrostatically membrane constituents such as anionic lipids and glycosaminoglycans (GAGs). Controversies exist, however, about the biological response after the interaction of CPPs with such membrane constituents. Present review compares thermodynamic binding studies with conditions of the biological CPP uptake. It becomes evident that CPPs enter biological cells by different and probably competing mechanisms. For example, some amphipathic CPPs traverse pure lipid model membranes at low micromolar concentrations — at least in the absence of cargos. In contrast, no direct translocation at these conditions is observed for non-amphipathic CPPs. Finally, CPPs bind GAGs at low micromolar concentrations with potential consequences for endocytotic pathways.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Many cell-penetrating peptides (CPPs) bind to glycosaminoglycans (GAG) located on the extracellular side of biological tissues. CPP binding to the cell surface is intimately associated with ...clustering of surface molecules and is usually followed by uptake into the cell interior. We have investigated the uptake mechanism by comparing CPPs which bind, but cannot induce, GAG clustering with those which do induce GAG clustering. We have synthesized the tryptophan-labeled CPP nona-l-arginine (WR9) and its monodispersely PEGylated derivate (PEG27–WR9) and have compared them with respect to glycan binding, glycan clustering, and their uptake into living cells. Both CPPs bind to the GAG heparin with high affinity (K D ∼ 100 nM), but the PEGylation prevents the GAG clustering. Thus, it is possible to uncouple and analyze the contributions of GAG binding and GAG clustering to the biological CPP uptake. The uptake of PEG–WR9 into CH-K1 cells is confined to intracellular vesicles, where colocalization with transferrin attests to an endocytic uptake. Transfection experiments with plasmid DNA for GFP revealed poor GFP expression, suggesting that endocytic uptake of PEG–WR9 is compromised by insufficient release from endocytic vesicles. In contrast, WR9 shows two uptake routes. At low concentration (<5 μM), WR9 uptake occurs mainly through endocytosis. At higher concentration, WR9 uptake is greatly enhanced, showing a diffuse spreading over the entire cytoplasm and nucleusa phenomenon termed “transduction”. Transduction of WR9 leads to a higher GFP expression as compared to PEG–WR9 endocytosis but also damages the plasma membrane as evidenced by SYTOX Green staining. The results suggest that GAG binding without and with GAG clustering induce two different pathways of CPP uptake.
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IJS, KILJ, NUK, PNG, UL, UM
Recent observations in cell culture provide evidence that negatively charged glycosaminoglycans (GAGs) at the surface of biological cells bind cationic cell-penetrating compounds (CPCs) and cluster ...during CPC binding, thereby contributing to their endocytotic uptake. The GAG binding and clustering occur in the low-micromolar concentration range and suggest a tight interaction between GAGs and CPCs, although the relation between binding affinity and specificity of this interaction remains to be investigated. We therefore measured the GAG binding and clustering of various mono- and multivalent CPCs such as DNA transfection vectors (polyethylenimine; 1,2-dioleoyl-3-trimethylammonium-propane), amino acid homopolymers (oligoarginine; oligolysine), and cell-penetrating peptides (Penetratin; HIV-1 Tat) by means of isothermal titration calorimetry and dynamic light scattering. We find that these structurally diverse CPCs share the property of GAG binding and clustering. The binding is very tight (microscopic dissociation constants between 0.34 and 1.34
μM) and thus biologically relevant. The hydrodynamic radius of the resulting aggregates ranges from 78
nm to 586
nm, suggesting that they consist of numerous GAG chains cross-linked by CPCs. Likewise, the membrane
-permeant monovalent cation acridine orange leads to GAG binding and clustering, in contrast to its membrane-impermeant structural analogs propidium iodide and ethidium bromide. Because the binding and clustering of GAGs were found to be a common denominator of all CPCs tested, these properties might be helpful to identify further CPCs.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Objectives Biotin >20.0 ng/mL (81.8 nmol/L) can reduce Elecsys® Troponin T Gen 5 (TnT Gen 5; Roche Diagnostics) assay recovery, potentially leading to false-negative results in patients with ...suspected acute myocardial infarction (AMI). We aimed to determine the prevalence of elevated biotin and AMI misclassification risk from biotin interference with the TnT Gen 5 assay. Methods Biotin was measured using an Elecsys assay in two cohorts: (i) 797 0-h and 646 3-h samples from 850 US emergency department patients with suspected acute coronary syndrome (ACS); (ii) 2023 random samples from a US laboratory network, in which biotin distributions were extrapolated for higher values using pharmacokinetic modeling. Biotin >20.0 ng/mL (81.8 nmol/L) prevalence and biotin 99th percentile values were calculated. AMI misclassification risk due to biotin interference with the TnT Gen 5 assay was modeled using different assay cutoffs and test timepoints. Results ACS cohort: 1/797 (0.13%) 0-h and 1/646 (0.15%) 3-h samples had biotin >20.0 ng/mL (81.8 nmol/L); 99th percentile biotin was 2.62 ng/mL (10.7 nmol/L; 0-h) and 2.38 ng/mL (9.74 nmol/L; 3-h). Using conservative assumptions, the likelihood of false-negative AMI prediction due to biotin interference was 0.026% (0-h result; 19 ng/L TnT Gen 5 assay cutoff). US laboratory cohort: 15/2023 (0.74%) samples had biotin >20.0 ng/mL (81.8 nmol/L); 99th percentile biotin was 16.6 ng/mL (68.0 nmol/L). Misclassification risk due to biotin interference (19 ng/L TnT Gen 5 assay cutoff) was 0.025% (0-h), 0.0064% (1-h), 0.00048% (3-h), and <0.00001% (6-h). Conclusions Biotin interference has minimal impact on the TnT Gen 5 assay's clinical utility, and the likelihood of false-negative AMI prediction is extremely low.
The positively charged protein transduction domain of the HIV-1 TAT protein (TAT-PTD; residues 47–57 of TAT) rapidly translocates across the plasma membrane of living cells. This property is ...exploited for the delivery of proteins, drugs, and genes into cells. The mechanism of this translocation is, however, not yet understood. Recent theories for translocation suggest binding of the protein transduction domain (PTD) to extracellular glycosaminoglycans as a possible mechanism. We have studied the binding equilibrium between TAT-PTD and three different glycosaminoglycans with high sensitivity isothermal titration calorimetry and provide the first quantitative thermodynamic description. The polysulfonated macromolecules were found to exhibit multiple identical binding sites for TAT-PTD with only small differences between the three species as far as the thermodynamic parameters are concerned. Heparan sulfate (HS, molecular weight, 14.2
±
2 kDa) has 6.3
±
1.0 independent binding sites for TAT-PTD which are characterized by a binding constant
K
0
=
(6.0
±
0.6)
×
10
5 M
−1 and a reaction enthalpy
Δ
H
pep
0
=
−
4.6
±
1.0
kcal/mol at 28°C. The binding affinity,
Δ
G
pep
0
, is determined to equal extent by enthalpic and entropic contributions. The HS-TAT-PTD complex formation entails a positive heat capacity change of
Δ
C
p
0
=
+
135
cal/mol peptide, which is characteristic of a charge neutralization reaction. This is in contrast to hydrophobic binding reactions which display a large negative heat capacity change. The stoichiometry of 6–7 TAT-PTD molecules per HS corresponds to an electric charge neutralization. Light scattering data demonstrate a maximum scattering intensity at this stoichiometric ratio, the intensity of which depends on the order of mixing of the two components. The data suggest cross-linking and/or aggregation of HS-TAT-PTD complexes. Two other glycosaminoglycans, namely heparin and chondroitin sulfate B, were also studied with isothermal titration calorimetry. The thermodynamic parameters are
K
0
=
(6.0
±
0.8)
×
10
5 M
−1 and
Δ
H
pep
0
=
−
5.1
±
0.7
kcal/mol for heparin and
K
0
=
(2.5
±
0.5)
×
10
5 M
−1 and
Δ
H
pep
0
=
−
3.2
±
0.4
kcal/mol for chondroitin sulfate B at 28°C. The close thermodynamic similarity of the three binding molecules also implies a close structural relationship. The ubiquitous occurrence of glycosaminoglycans on the cell surface together with their tight and rapid interaction with the TAT protein transduction domain makes complex formation a strong candidate as the primary step of protein translocation.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Early detection of atrial fibrillation (AF) enables initiation of anticoagulation and early rhythm control therapy to reduce stroke, cardiovascular death, and heart failure. In a cross-sectional, ...observational study, we aimed to identify a combination of circulating biomolecules reflecting different biological processes to detect prevalent AF in patients with cardiovascular conditions presenting to hospital. Twelve biomarkers identified by reviewing literature and patents were quantified on a high-precision, high-throughput platform in 1485 consecutive patients with cardiovascular conditions (median age 69 years Q1, Q3 60, 78; 60% male). Patients had either known AF (45%) or AF ruled out by 7-day ECG-monitoring. Logistic regression with backward elimination and a neural network approach considering 7 key clinical characteristics and 12 biomarker concentrations were applied to a randomly sampled discovery cohort (n = 933) and validated in the remaining patients (n = 552). In addition to age, sex, and body mass index (BMI), BMP10, ANGPT2, and FGF23 identified patients with prevalent AF (AUC 0.743 95% CI 0.712, 0.775). These circulating biomolecules represent distinct pathways associated with atrial cardiomyopathy and AF. Neural networks identified the same variables as the regression-based approach. The validation using regression yielded an AUC of 0.719 (95% CI 0.677, 0.762), corroborated using deep neural networks (AUC 0.784 95% CI 0.745, 0.822). Age, sex, BMI and three circulating biomolecules (BMP10, ANGPT2, FGF23) are associated with prevalent AF in unselected patients presenting to hospital. Findings should be externally validated. Results suggest that age and different disease processes approximated by these three biomolecules contribute to AF in patients. Our findings have the potential to improve screening programs for AF after external validation.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Background Patients with atrial fibrillation (AF) face an increased risk of death and major adverse cardiovascular events (MACE). We aimed to assess the predictive value of the novel atrial-specific ...biomarker BMP10 (bone morphogenetic protein 10) for death and MACE in patients with AF in comparison with NT-proBNP (N-terminal prohormone of B-type natriuretic peptide). Methods and Results BMP10 and NT-proBNP were measured in patients with AF enrolled in Swiss-AF (Swiss Atrial Fibrillation Study), a prospective multicenter cohort study. A total of 2219 patients were included (median follow-up 4.3 years interquartile range 3.9, 5.1, mean age 73±9 years, 73% male). In multivariable Cox proportional hazard models, the adjusted hazard ratio (aHR) associated with 1 ng/mL increase of BMP10 was 1.60 (95% CI, 1.37-1.87) for all-cause death, and 1.54 (95% CI, 1.35-1.76) for MACE. For all-cause death, the concordance index was 0.783 (95% CI, 0.763-0.809) for BMP10, 0.784 (95% CI, 0.765-0.810) for NT-proBNP, and 0.789 (95% CI, 0.771-0.815) for both biomarkers combined. For MACE, the concordance index was 0.732 (95% CI, 0.715-0.754) for BMP10, 0.747 (95% CI, 0.731-0.768) for NT-proBNP, and 0.750 (95% CI, 0.734-0.771) for both biomarkers combined. When grouping patients according to NT-proBNP categories (<300, 300-900, >900 ng/L), higher aHRs were observed in patients with high BMP10 in the categories of low NT-proBNP (all-cause death aHR, 2.28 95% CI, 1.15-4.52, MACE aHR, 1.88 95% CI, 1.07-3.28) and high NT-proBNP (all-cause death aHR, 1.61 95% CI, 1.14-2.26, MACE aHR, 1.38 95% CI, 1.07-1.80). Conclusions BMP10 strongly predicted all-cause death and MACE in patients with AF. BMP10 provided additional prognostic information in low- and high-risk patients according to NT-proBNP stratification. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT02105844.
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