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Use of high resolution melting analysis for the study of lactic acid bacteria
Knápková, Monika ; Němcová, Andrea (referee) ; Brázda, Václav (advisor)
Currently, there is a growing interest in the use of probiotic products, and there are many of them in the market. With the growing interest, greater emphasis is placed on the identification of declared probiotic microorganisms. Precise identification of microbial composition is often a difficult task and it requires more advanced methods especially in the field of molecular diagnostics. The diploma thesis was focused on the verification of the presence od declared probiotic microorganisms in probiotic food supplements GS Laktobacily Forte 21, Biopron 9 Premium and Linex® Forte. DNA was isolated from the complex matrices by phenol extraction, commercial kit and magnetic carriers F79/L3-PLL in the quality suitable for PCR. Subsequently, the isolated DNA was amplified by real-time polymerase chain reaction using genus- and species-specific primers. The specific PCR product was subjected to agarose gel electrophoresis, whereas species identification was not always in compliance with the data declared by producers. The next part of the thesis was focused on polymerase chain reaction with high-resolution melting analysis to distinguish bacterial strains belonging to the Lactobacillus group and to identify probiotic microorganisms present in the complex matrices of the probiotic food supplements. Eight primer sets were tested (V1F HRM a V1R-HRM, CHAU-V3F a CHAU-V3R, CHAU-V6F a CHAU-V6R, LAC2 a LAC4, LAC1 a LAC2, P1V1 a P2V1, poxcDNAFw a poxPromRVC, poxcDNAFw a poxPromRVT). Three primer pairs (V1F HRM a V1R-HRM, poxcDNAFw a poxPromRVC, poxcDNAFw a poxPromRVT) were evaluated as the most suitable for distinguishing Lactobacillus bacterial strains.
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Production of pigments by yeasts
Gonová, Dominika ; Hlaváček, Viliam (referee) ; Němcová, Andrea (advisor)
Carotenoids are naturally occurring pigments synthesized by yeast, bacteria, filamentous fungi and plants. In recent years, the interest in the study of these pigments and their microbiological production is increasing mainly due to significant biological effects attributed to carotenoids. This work is conceived as comparative study of six carotenogenic yeasts: two strains of species Rhodotorula glutinis, Rhodotorula mucilaginosa, Sporobolomyces roseus, Sporobolomyces metaroseus a Sporobolomyces pararoseus. Their cultivation was carried out in various media where the oxidative stress was applied in the form of hydrogen peroxide and also waste material – egg pasta – was used as a nutrition source. All studied strains were able to use waste substrate as a source of nutrients, in case of the genus Sporobolomyces increasing production of metabolites was observed. Under the oxidative stress, the majority of the studied yeast showed overproduction of carotenoids and accompanying lipid substances. Sporobolomyces roseus CCY 19-6-4 was characterized by the highest production of carotenoids (1923.78 µg/g -carotene) at the egg pasta media, but on the other hand, it showed a significant decline in biomass. As potentially the best producer of biomass (9.85 g/l) and carotenoids (780.24 µg/g of -carotene), the yeast Rhodotorula glutinis CCY 20-2-26 was observed. Pulcherrimin, synthesized mainly by yeast but also by some spore-forming bacteria, also belongs among natural pigments. Recently, its antagonistic effect that was shown against several microorganisms has been intensively studied, as it seems to be very relevant in regard to biological control. The second part of the work deals with the regulation of pulcherrimin production and its antimicrobial activity. As the pigment-producing yeast strains were used Metschnikowia pulcherrima 145, Metschnikowia pulcherrima 147, Mestchnikowia pulcherrima 149, Metschnikowia andauensis 129, which were cultured on various media containing different concentrations of metal ions and hydrogen peroxide as exogenous stress. In the study of pulcherrimin antagonistic effect, gram-positive bacteria Lactobacillus sakei, gram-negative bacteria Escherichia coli, yeast Candida glabrata and filamentous fungi Phanrochaete chrysosporium were used as tested microorganisms. All studied yeasts were able to produce pulcherrimin, and therefore to show antagonist effect, only in media supplemented with iron, while the color intensity was proportional to the concentration of iron. Antimicrobial activity of pulcherrimin was not observed only against bacteria Escherichia coli.
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Sensory quality of French cheese Brie de Meaux in connection with chemical and microbial composition
Májková, Monika ; Němcová, Andrea (referee) ; Vítová, Eva (advisor)
This thesis deals with the assessment of the effect of storage of French Brie de Meaux (AOC) on its volatile (aromatic) compounds, free and bound fatty acids and microbial composition, in relation to its sensory quality. The theoretical part is devoted to cheeses with white mould on the surface. In the experimental part, the influence of temperature and storage time on the sensory quality and safety of cheese is assessed. In the storage experiment, the cheeses were stored for 21 days at 5 °C (one bulk, one vacuumed) and at 20 °C. The samples were evaluated by SPME-GC-MS for volatile (aromatic) compounds. Fatty acids were identified and quantified by GC-FID after conversion to methyl esters using BF3. RT-PCR method was used for microbial profile. Fifty-nine volatile compounds were identified in the samples and contribute to the flavour characteristics of the cheese. Among the fatty acids, palmitic, oleic, myristic and stearic acids were predominant. The microbial profile confirmed Micrococcus luteus as a contaminant in cheese stored at 20°C, while the other contaminants were not detected positively. From a sensory point of view, the standard cheese (analysed immediately after purchase) together with cheese stored at 5 °C in vacuum form for 21 days was the best performing cheese.
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Study of the effect of cosmetics on the human skin microbiome using molecular techniques
Alexová, Adéla ; Kovalčík, Adriána (referee) ; Němcová, Andrea (advisor)
The theoretical part of the thesis is focused on the basic description of the physiology of the skin, human microbiome and a brief summary of where individual microorganisms occur. Furthermore, there is a list of analytical and microbiological methods that are used in this thesis. In the beginning, the practical part is focused on determination of antimicrobial effects of the chosen cosmetic products using microbial tests. Then, the inhibiton and microbial effect of the chosen cosmetic products on examined microorganisms has been measured using ELISA method. The second part of the thesis is focused on the isolation of bacterial DNA in quality that would be high enough to be used for amplification in PCR. There has been an optimalization of isolation of microbial DNA that was to be found on tested subjects’ skin. The presence of chosen microorganisms on skin before and after the usage of cosmetic products was measured using a PCR method. PCR products were then detected using gel electrophoresis. From the gathered data it is clear that the number of observed microorganisms has changed significantly after the application of cosmetic products.
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Neinvazivní stanovení glykémie z fotopletysmografických signálů nasnímaných pomocí chytrých zařízení
Vargová, Enikö ; Němcová, Andrea
Tento příspěvek se zabývá možnostmi neinvazivního stanovení glykémie z fotopletysmografických (PPG) signálů nasnímaných pomocí chytrého náramku a chytrého telefonu. Byly navrženy a implementovány dvě metody pro klasifikaci glykémie do dvou skupin (nízká a vysoká glykémie). Byly také vytvořeny modely strojového učení pro predikci konkrétní hodnoty glykémie. Reference byla získána invazivním měřením glykémie pomocí glukometru. Nejlepších výsledků klasifikace PPG záznamů do dvou skupin dosahuje metoda náhodný les (RF) a metoda podpůrných vektorů (SVM) s rbf jádrem. Zmíněné modely dosahují přesnosti na testovací sadě dat z chytrého náramku Acc = 76 % (SVM) a Acc = 75 % (RF). Ověření funkčnosti navržených modelů bylo následně provedeno na testovací sadě dat z chytrého telefonu, kde oba modely dosahují obdobných výsledků: Acc = 74 % (SVM) a Acc = 75 % (RF). Konkrétní hodnotu glykémie nejlépe predikoval RF pro regresi, který dosahuje průměrné absolutní chyby MAE = 1,25 mmol/l na testovací sadě dat z chytrého náramku a MAE = 1,37 mmol/l na testovací sadě dat z chytrého telefonu.
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Photoplethysmography using a smartphone
Dräxler, Vladislav ; Němcová, Andrea (referee) ; Janoušek, Oto (advisor)
The diploma thesis deals with the use of digital photoplethysmography (PPG) technology. The thesis describes the process of acquisition of the photoplethysmographic curve using a smartphone, preprocessing of the PPG signal, calculation of parameters and evaluation of the quality of the obtained data. The practical part includes a measurement protocol for different experimental conditions, describes an algorithm for obtaining a photoplethysmographic curve from video recordings and deals with determining the parameters of the PPG curve and evaluating the quality of the obtained PPG signal. The output of the work is an optimal acquisition protocol for digital scanning of the PPG curve.
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Estimation of blood glucose level based on PPG signals measured by smart devices
Vargová, Enikö ; Němcová, Andrea
This paper deals with the possibilities of non-invasivedetermination of blood glucose from photoplethysmographic signals.Monitoring blood sugar is the most important part of managingdiabetes. Diabetes is one of the world’s major chronic diseases.Untreated diabetes is often a cause of death.Two datasets have been created by recording thephotoplethysmographic signals of 16 people using two smart devices(a smart wristband and a smartphone), along with their bloodglucose levels measured in an invasive way. Thephotoplethysmographic signals were preprocessed, and suitablefeatures were extracted from them. The aim of the work is to proposemethods for glycemic classification and prediction.Various machine-learning models were created. The best modelfor classifying blood glucose into two groups (low blood glucose andhigh blood glucose) is random forest, which achieves an F1 score of84% and 80% on two different test sets obtained from two smartdevices. The best blood glucose level prediction model is also basedon random forest and achieves an MAE of 1.02 mmol/l and 1.17mmol/l on both testing datasets.
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Blood pressure estimation using smartphone
Šíma, Jan ; Němcová, Andrea
This paper presents an experimental cuff-less measurementof systolic (SBP) and diastolic blood pressure (DBP)using smartphone. A photoplethysmographic signal (PPG) measuredby a smartphone camera is used to estimate blood pressure(BP). This paper contains comparison of several machinelearning (ML) methods for BP estimation. Filtering the PPGsignal with a band-pass filter (0.5-12 Hz) followed by featureextraction and using Random Forest (RF) methods separatelyor as a weak regressor in adaptive boosting (AdaBoost) or bootstrapaggregating (Boosting) reached the best results accordingto Association for the Advancement of Medical Instrumentation(AAMI) and British Hypertension Society (BHS) standardsamong all regression ML models. The mean absolute error(MAE) and standard deviation (SD) of Bagging model were4.532±3.760 mmHg for SBP and 2.738±3.032 mmHg for DBP(AAMI). This result meets the criteria of the AAMI standard.
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Influence of selected types of food on changes in the composition of the intestinal microbiome
Šantavý, Tomáš ; Němcová, Andrea (referee) ; Ryšávka, Petr (advisor)
The master's thesis focuses on determining the influence of selected types of food on changes in the intestinal microbiome composition. Dietary composition plays an important role in controlling intestinal microbial populations, including the prevention and treatment of certain diseases. In order to evaluate the effect of daily consumption of fruit-vegetable smoothie on the human intestinal microbiome, changes in the intestinal microbiome at the beginning and after 14 days of intervention were compared. The experimental part was attended by 10 men and 10 women aged 35-45 years, who were evenly divided into 2 groups. The first group of participants consumed a combination of orange, dried turmeric and ginger. The second group consumed a combination of apple, carrot and lemon juice. DNA isolation from stool samples followed by a quantitative PCR method was used to detect differences in the intestinal microbiome. After 14 days of consumption of the fruit-vegetable smoothie, specific changes in the phylum Firmicutes, Bacteroidetes and the genus Lactobacillus, Bifidobacterium were observed. After statistical evaluation of the obtained results, the differences were not detectable at a statistically significant level (p-value > 0.05).
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