GuiTope: an application for mapping random-sequence peptides to protein sequences

BACKGROUND: Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. RESULTS: GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. CONCLUSIONS: GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net

Blood transcriptomic discrimination of bacterial and viral infections in the emergency department: a multi-cohort observational validation study

Background: There is an urgent need to develop biomarkers that stratify risk of bacterial infection in order to support antimicrobial stewardship in emergency hospital admissions. / Methods: We used computational machine learning to derive a rule-out blood transcriptomic signature of bacterial infection (SeptiCyte™ TRIAGE) from eight published case-control studies. We then validated this signature by itself in independent case-control data from more than 1500 samples in total, and in combination with our previously published signature for viral infections (SeptiCyte™ VIRUS) using pooled data from a further 1088 samples. Finally, we tested the performance of these signatures in a prospective observational cohort of emergency department (ED) patients with fever, and we used the combined SeptiCyte™ signature in a mixture modelling approach to estimate the prevalence of bacterial and viral infections in febrile ED patients without microbiological diagnoses. / Results: The combination of SeptiCyte™ TRIAGE with our published signature for viral infections (SeptiCyte™ VIRUS) discriminated bacterial and viral infections in febrile ED patients, with a receiver operating characteristic area under the curve of 0.95 (95% confidence interval 0.90–1), compared to 0.79 (0.68–0.91) for WCC and 0.73 (0.61–0.86) for CRP. At pre-test probabilities 0.35 and 0.72, the combined SeptiCyte™ score achieved a negative predictive value for bacterial infection of 0.97 (0.90–0.99) and 0.86 (0.64–0.96), compared to 0.90 (0.80–0.94) and 0.66 (0.48–0.79) for WCC and 0.88 (0.69–0.95) and 0.60 (0.31–0.72) for CRP. In a mixture modelling approach, the combined SeptiCyte™ score estimated that 24% of febrile ED cases receiving antibacterials without a microbiological diagnosis were due to viral infections. Our analysis also suggested that a proportion of patients with bacterial infection recovered without antibacterials. / Conclusions: Blood transcriptional biomarkers offer exciting opportunities to support precision antibacterial prescribing in ED and improve diagnostic classification of patients without microbiologically confirmed infections

Succession of the Mangrove Vegetation of Bombay and Salsette Islands

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GuiTope: an application for mapping random-sequence peptides to protein sequences

Abstract Background Random-sequence peptide libraries are a commonly used tool to identify novel ligands for binding antibodies, other proteins, and small molecules. It is often of interest to compare the selected peptide sequences to the natural protein binding partners to infer the exact binding site or the importance of particular residues. The ability to search a set of sequences for similarity to a set of peptides may sometimes enable the prediction of an antibody epitope or a novel binding partner. We have developed a software application designed specifically for this task. Results GuiTope provides a graphical user interface for aligning peptide sequences to protein sequences. All alignment parameters are accessible to the user including the ability to specify the amino acid frequency in the peptide library; these frequencies often differ significantly from those assumed by popular alignment programs. It also includes a novel feature to align di-peptide inversions, which we have found improves the accuracy of antibody epitope prediction from peptide microarray data and shows utility in analyzing phage display datasets. Finally, GuiTope can randomly select peptides from a given library to estimate a null distribution of scores and calculate statistical significance. Conclusions GuiTope provides a convenient method for comparing selected peptide sequences to protein sequences, including flexible alignment parameters, novel alignment features, ability to search a database, and statistical significance of results. The software is available as an executable (for PC) at http://www.immunosignature.com/software and ongoing updates and source code will be available at sourceforge.net.</p

Sensitivity of the seismic response of monopile-supported offshore wind turbines to soil variability

The expansion of the offshore wind industry in areas with high seismicity has led to engineering challenges related to the design of the offshore wind turbines (OWTs). Monopiles, i.e., tubular steel piles of large outer diameter, low aspect ratio (penetration depth over outer diameter), and relatively thin pile wall, are traditionally the preferred foundation type for OWT due to fabrication, transportation, and installation standardization. For all bottom-founded systems, soil–structure interaction (SSI) plays a crucial role in the system's response. Additional challenges arise in the case of seismic SSI as, not only the system's response, but also the seismic ground motion itself are affected by the soil characteristics. Furthermore, uncertainties related to soil properties, as derived from the soil testing campaign and interpretation, need to be thoroughly considered for OWT load calculations and the design of the support structure. The uncertainty in soil interpretation may have a large impact on the characteristics of the input seismic motion. Subsequently, SSI will affect the seismic loads acting on the support structure and the OWT. This knock-on effect of the interpretation of the soil parameters is unknown, but may be significant to account for. In fact, when a “best estimate” soil parameter set is used, the resulting seismic load may not necessarily correspond to the most probable load for the assumed seismic event. This paper investigates the influence of the uncertainty in soil parameters, as they may result from the soil interpretation, on the seismic loads. It demonstrates the skewed distribution of OWT seismic loads using a realistic design case study on a commercial OWT. Results are presented in the form of transfer functions, response spectra at mudline and normalized bending moments along the support structure. Three distinct structural components of interest are selected to evaluate the results. It is concluded that, for the analysis of OWT under seismic loading conditions in particular, it cannot be decided a priori which soil properties would result in conservative or progressive design. Based on the obtained results, recommendations are given which aim to de-risk and enhance the current design practice.Offshore EngineeringAerospace EngineeringTeam Jan-Willem van Wingerde

Complexation of NAC-Derived Peptide Ligands with the C-Terminus of alpha-Synuclein Accelerates Its Aggregation

Aggregation of alpha-synuclein (alpha-Syn) into neurotoxic oligomers and amyloid fibrils is suggested to be the pathogenic mechanism for Parkinson's disease (PD). Recent studies'have indicated that oligomeric species of alpha-Syn are more cytotoxic than their mature fibrillar counterparts, which are responsible for dopaminergic neuronal cell death in PD. Therefore, the effective therapeutic strategies for tackling aggregation-associated diseases would be either to prevent aggregation or to modulate the aggregation process to minimize the formation of toxic oligomers during aggregation. In this work, we showed that arginine-substituted alpha-Syn ligands, based on the most aggregation-prone sequence of alpha-Syn, accelerate the protein aggregation in a concentration-dependent manner. To elucidate the mechanism by which Arg-substituted peptides could modulate alpha-Syn aggregation kinetics, we performed surface plasmon resonance (SPR) spectroscopy, nuclear magnetic resonance (NMR) studies, and all-atom molecular dynamics (MD) simulation. The SPR analysis showed a high binding potency of these peptides with alpha-Syn but one that was nonspecific in nature. The two-dimensional NMR studies suggest that a large stretch within the C-terminus of alpha-Syn displays a chemical shift perturbation upon interacting with Arg-substituted peptides, indicating C-terminal residues of alpha-Syn might be responsible for this class of peptide binding. This is further supported by MD simulation studies in which the Arg-substituted peptide showed the strongest interaction with the C-terminus of alpha-Syn. Overall, our results suggest that the binding of Arg-substituted ligands to the highly acidic C-terminus of alpha-Syn leads to reduced charge density and flexibility, resulting in accelerated aggregation kinetics. This may be a potentially useful strategy while designing peptides, which act as alpha-Syn aggregation modulators

The Familial alpha-Synuclein A53E Mutation Enhances Cell Death in Response to Environmental Toxins Due to a Larger Population of Oligomers

Amyloid formation of alpha-synuclein (alpha-Syn) and its familial mutations are directly linked with Parkinson's disease (PD) pathogenesis. Recently, a new familial alpha-Syn mutation (A53E) was discovered, associated with an early onset aggressive form of PD, which delays alpha-Syn aggregation. When we overexpressed wild-type (WT) and AS3E proteins in cells, showed neither toxicity nor aggregate formation, suggesting merely overexpression may not recapitulate the PD phenotype in cell models. We hypothesized that cells expressing the A53E mutant might possess enhanced susceptibility to PD-associated toxicants compared to that of the WT. When cells were treated with PD toxicants (dopamine and rotenone), cells expressing A53E showed more susceptibility to cell death along with compromised mitochondrial potential and an increased production of reactive oxygen species. The higher toxicity of A53E could be due to more oligomers being formed in cells as confirmed by a dot blot assay using amyloid specific OC and All antibody and using an in vitro aggregation study. The cellular model presented here suggests that along with familial mutation, environmental and other cellular factors might play a crucial role in dictating PD pathogenesis