Malgorzata Kotulska

FISH Amyloid – a new method for finding amyloidogenic segments in proteins based on site specific co-occurence of aminoacids

BackgroundAmyloids are proteins capable of forming fibrils whose intramolecular contact sites assume densely packed zipper pattern. Their oligomers can underlie serious diseases, e.g. Alzheimer’s and Parkinson’s diseases. Recent studies show that short segments of aminoacids can be responsible for amyloidogenic properties of a protein. A few hundreds of such peptides have been experimentally found but experimental testing of all candidates is currently not feasible. Here we propose an original machine learning method for classification of aminoacid sequences, based on discovering a segment with a discriminative pattern of site-specific co-occurrences between sequence elements. The pattern is based on the positions of residues with correlated occurrence over a sliding window of a specified length. The algorithm first recognizes the most relevant training segment in each positive training instance. Then the classification is based on maximal distances between co-occurrence matrix of the relevant segments in positive training sequences and the matrix from negative training segments. The method was applied for studying sequences of aminoacids with regard to their amyloidogenic properties.ResultsOur method was first trained on available datasets of hexapeptides with the amyloidogenic classification, using 5 or 6-residue sliding windows. Depending on the choice of training and testing datasets, the area under ROC curve obtained the value up to 0.80 for experimental, and 0.95 for computationally generated (with 3D profile method) datasets. Importantly, the results on 5-residue segments were not significantly worse, although the classification required that algorithm first recognized the most relevant training segments. The dataset of long sequences, such as sup35 prion and a few other amyloid proteins, were applied to test the method and gave encouraging results. Our web tool FISH Amyloid was trained on all available experimental data 4-10 residues long, offers prediction of amyloidogenic segments in protein sequences.ConclusionsWe proposed a new original classification method which recognizes co-occurrence patterns in sequences. The method reveals characteristic classification pattern of the data and finds the segments where its scoring is the strongest, also in long training sequences. Applied to the problem of amyloidogenic segments recognition, it showed a good potential for classification problems in bioinformatics.

Ion flux through membrane channels—An enhanced algorithm for the Poisson-Nernst-Planck model

A novel algorithmic scheme for numerical solution of the 3D Poisson‐Nernst‐Planck model is proposed. The algorithmic improvements are universal and independent of the detailed physical model. They include three major steps: an adjustable gradient‐based step value, an adjustable relaxation coefficient, and an optimized segmentation of the modeled space. The enhanced algorithm significantly accelerates the speed of computation and reduces the computational demands. The theoretical model was tested on a regular artificial channel and validated on a real protein channel—α‐hemolysin, proving its efficiency.

Electroporation and lipid nanoparticles with cyanine IR-780 and flavonoids as efficient vectors to enhanced drug delivery in colon cancer

Nanocarriers and electroporation (also named electropermeabilization) are convenient methods to increase drug transport. In the current study, we present an effective support of drug delivery into cancer cells, utilizing these methods. We compare the efficiency of each of them and their combination. Multifunctional solid lipid nanoparticles (SLNs) loaded with a cyanine-type IR-780 - acting as a diagnostic agent and a photosensitizer, and a flavonoid derivative - baicalein (BAI) or fisetin (FIS) as a therapeutic cargo - were fabricated via solvent-diffusion method. A therapy supplemented with flavonoids may provide a more precise method to apply desirable lower drug doses and is more likely to result in lower toxicity and a decrease in tumor growth. The SLNs were stabilized with Phospholipon 90G at various concentrations; cetyl palmitate (CP) was applied as a solid matrix. The obtained nanosystems were characterized by dynamic light scattering (size along with size distribution), UV-vis (cargos encapsulation efficiency) and atomic force microscopy (morphology and shape). The obtained SLNs were used as drug carriers alone and in combination with electropermeabilization induced by millisecond pulsed electric fields of high intensity. Two cell lines were selected for the study: LoVo and CHO-K1. The viability was assessed after electroporation alone, the use of electroporation and nanoparticles, and nanoparticles or drugs alone. The intracellular accumulation of cyanine IR-780 and the impact on intracellular structure organization of cytoskeleton was visualized with confocal microscopy method with alpha-actin and beta-tubulin. In this study, the efficacy of nanoparticles with mixed cargo, additionally enhanced by electroporation, is demonstrated to act as an anticancer modality to eliminate cancer cells.

Chapter two - Voltage- and Current-Clamp Methods for Determination of Planar Lipid Bilayer Properties

Biological membranes, the barriers that envelope the cell and its inner organelles, play a crucial role in the normal functioning of cells. The simplest model of these biological membranes is the planar lipid bilayer. Because its geometry allows chemical and electrical access to both sides of the bilayer, the physical properties of this model membrane can be easily measured. Usually, a thin bimolecular film composed of specified phospholipids and organic solvent is formed on a small aperture in a hydrophobic partition separating two compartments containing aqueous solutions. From the electrical point of view, a planar lipid bilayer can be considered as an imperfect capacitor; therefore, two electrical properties, capacitance (C) and resistance (R), determine most of its behavior. Electrodes placed in the aqueous compartments on each side of the planar lipid bilayer permit the measurement of current and voltage across the model membrane. The two measuring techniques most commonly used to measure the properties of planar lipid bilayers are voltage-clamp methods and current-clamp methods. The focus of this chapter is to review measurement systems and methods for the determination of the physical properties of planar lipid bilayers.

AmyLoad: website dedicated to amyloidogenic protein fragments

UNLABELLED Analyses of amyloidogenic sequence fragments are essential in studies of neurodegenerative diseases. However, there is no one internet dataset that collects all the sequences that have been investigated for their amyloidogenicity. Therefore, we have created the AmyLoad website which collects the amyloidogenic sequences from all major sources. The website allows for filtration of the fragments and provides detailed information about each of them. Registered users can both personalize their work with the website and submit their own sequences into the database. To maintain database reliability, submitted sequences are reviewed before making them available to the public. Finally, we re-implemented several amyloidogenic sequence predictors, thus the AmyLoad website can be used as a sequence analysis tool. We encourage researchers working on amyloid proteins to contribute to our service. AVAILABILITY AND IMPLEMENTATION The AmyLoad website is freely available at http://comprec-lin.iiar.pwr.edu.pl/amyload/. CONTACT malgorzata.kotulska@pwr.edu.pl.

Metastable Pores at the Onset of Constant-Current Electroporation

Single metastable nanopores, appearing before the actual electroporation under constant-current conditions, are used to characterize the onset of electroporation. Unlike the long-lived electropores typical of the current controlled methods, these pores survive for milliseconds and observing them is possible due to slow development of electroporation, provided by the gradual accumulation of charges on a planar membrane. Analysis of the metastable pore appearance frequency and lifetime shows the first introductory stage of electroporation. During this stage two species of metastable pores open, the majority of very low conductance that seem not fully developed as hydrophilic electropores. The experiments reveal that voltage value defines the electroporation onset while the current value affects the rate of electroporation. Membrane capacitance has a great impact on the membrane susceptibility to the pore appearance, related to its thickness and integrity. Pores of nonperfect membranes appear more easily, but they do not live any longer than others.

Doxorubicin delivery enhanced by electroporation to gastrointestinal adenocarcinoma cells with P-gp overexpression.

Electroporation (EP) can effectively support the penetration of macromolecules from the extracellular space into cells. Electropores induced by the influence of electromagnetic field generate additional paths of transport for macromolecules. The aim of this study was evaluation of the electroporation effect on doxorubicin transport efficiency to human colon (LoVo and LoVo/DX) and gastric (EPG85-257/P and EPG85-257/RDB) adenocarcinoma cells with overexpression of P-glycoprotein and murine macrophage cell line (P388/D1). In our EP experiments cells were placed into a cuvette with aluminum electrodes and pulsed with five square electric pulses of 1300 V/cm and duration of 50 μs each. Cells were also treated with low doxorubicin concentration ([DOX]=1.7 μM). The ultrastructure (TEM) and changes of P-glycoprotein expression of tumor cells subjected to electric field were monitored. The mitochondrial cell function and trypan blue staining were evaluated after 24h. Our results indicate the most pronounced effect of EP with DOX and disturbed ultrastructure in resistant gastric and colon cells with decrease of P-gp expression. Electroporation may be an attractive delivery method of cytostatic drugs in chemotherapy, enabling reduction of drug dose, exposure time and side effects.

Advances in photodynamic therapy assisted by electroporation.

Low invasive therapies of cancer are directed toward the methods that target selectively on carcinoma cells. Photodynamic therapy (PDT) is a therapeutic modality in which combination of a photosensitizer, light, and oxygen renders reactive oxygen species (ROS) which cause damage to a tumor tissue. Each of these factors is not toxic in itself and the effect of therapy results from high uptake of a photosensitizer by carcinoma cells and directed tumor irradiation by light. Realization of the therapy depends on efficient transport of the photosensitizer across the membrane and intracellular accumulation of the drug. Depending on the treatment conditions and the uptake mechanism, sensitizers can potentially reach different intracellular concentrations and different cellular effects can be triggered. Transport efficacy can be significantly augmented by applying electric pulses to plasma membrane, which opens transient non-selective hydrophilic nanopores as additional pathways across lipid membranes. Electroporation (EP) has been utilized to facilitate drug uptake in electrochemotherapy (ECT) and has been tested in combination with PDT. In the review, we described effects of PDT and electrophotodynamic therapy (EPDT) on carcinoma and healthy cells, studied in vitro and vivo. The comparison of different drugs has been applied to tests considering the enhancement of their cytotoxicity, selectivity, and additional effects caused by electroporation.

Combination of therapy with 5-fluorouracil and cisplatin with electroporation in human ovarian carcinoma model in vitro

High electric field, applied to plasma membrane, affects organization of the lipid molecules, generating transient hydrophilic electropores. The application of the cell membrane electroporation in combination with cytotoxic drugs could increase the drug transport into cells. This approach is known as electrochemotherapy (ECT). Our work shows new data concerning the influence of electrochemical reaction with cisplatin or with 5-fluorouracil (5-FU) on cancer ovarian cells resistant to standard therapy with cisplatin, in comparison to ECT effect on human primary fibroblasts. We investigated the effect of electroporation and electrochemotherapy with 5-FU and cisplatin on human ovarian clear-cell carcinoma cell line (OvBH-1) and epithelial ovarian carcinoma cell line (SKOV-3) - both resistant to cisplatin typically used in ovarian cancers. As control cells, human gingival fibroblasts (HGFs) from primary culture were used. Electropermeabilization efficiency was determined by FACS analysis with iodide propidium. Efficiency of electrochemotherapy was evaluated with viability assay. The cytotoxic effect was dependent on the electroporation parameters and on drug concentration. Electroporation alone only insignificantly decreased cells proliferation in OvBH-1 line; SKOV-3 line was more sensitive to the electrical field. Electrochemotherapy with cisplatin and 5-FU showed promising effects on both ovarian cell lines with recovery of normal cells revealed after 72 hours.

Machine learning methods can replace 3D profile method in classification of amyloidogenic hexapeptides

BackgroundAmyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods.ResultsWe generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning).ConclusionsWe showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset proved representative enough to use simple statistical methods for testing the amylogenicity based only on six letter sequences. Statistical machine learning methods such as Alternating Decision Tree and Multilayer Perceptron can replace the energy based classifier, with advantage of very significantly reduced computational time and simplicity to perform the analysis. Additionally, a decision tree provides a set of very easily interpretable rules.