Search results for: DNA profiling

Authors: Mona M. Marzouk, Ahmed Elkhateeb, Mona Elshabrawy, Mai M. Farid, Salwa A. Kawashty, EL-Sayed S. Abdel-Hameed, Sameh R. Hussein

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The genus Farsetia Turra belongs to the family Brassicaceae and has approximately 30 accepted species distributed worldwide. Amongst them, Farsetia aegyptia Turra and Farsetia longisiliqua Decne. are two common species characteristic to the Egyptian flora. The present study considers the first characterization of the chemical constituents of F. longisiliqua, aiming to compare with those identified from the medicinal species (F. aegyptia). Additionally, the chemosystematic relationships between the two studied species were evaluated and highlight the medicinal importance for F. longisiliqua. The chemical profiling of their aqueous methanol extracts were carried out using the LC-ESI-MS technique and afforded 54 compounds belonging to different chemical groups. Flavonoids are the major constituents and are represented by 32 compounds (two C-glycosyl flavone, four flavones, and 26 flavonols). Their structural variations and common constituents confirmed the chemosystematic significance of the two species. Moreover, the flavonoid profiles showed major common constituents between the two investigated species, which predicted the medicinal importance of F. longisiliqua.

Keywords: brassicaceae, chemosystematics, farsetia, flavonoids, glucosinolates, LC-ESI-MS

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Authors: Rani Abro, Ali Ata Moazzami, Jan Erik Lindberg, Torbjörn Lundh

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The effect of dietary starch level on liver metabolism in Arctic charr (Salvelinus alpinus) and tilapia (Oreochromis mossambicus) was studied using 1H-NMR based metabolomics. Fingerlings were fed iso-nitrogenous diets containing 0, 10 and 20 % starch for two months before liver samples were collected for metabolite analysis. Metabolite profiling was performed using 600 MHz NMR Chenomx software. In total, 48 metabolites were profiled in liver extracts from both fish species. Following the profiling, principal component analysis (PCA) and orthogonal partial least square discriminant analysis (OPLC-DA) were performed. These revealed that differences in the concentration of significant metabolites were correlated to the dietary starch level in both species. The most prominent difference in metabolic response to starch feeding between the omnivorous tilapia and the carnivorous Arctic charr was an indication of higher anaerobic metabolism in Arctic charr. The data also indicated that amino acid and pyrimidine metabolism was higher in Artic charr than in tilapia.

Keywords: arctic charr, metabolomics, starch, tilapia

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Authors: Darshan Panda, Lambodar Behera, M. J. Baig, Sudhanshu Sekhar

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Low light intensity is a significant limitation for grain yield and quality in rice. However, yield is not significantly reduced in low-light tolerant rice varieties. The work, therefore, planned for comparative transcriptome profiling under low light stress to decipher the genes involved and molecular mechanism of low light tolerance in rice. At the active tillering stage, 50% low light exposure for one day, three days, and five days were given to Swarnaprabha (low light tolerant) and IR8 (low light sensitive) rice varieties. Illumina (HiSeq) platform was used for transcriptome sequencing. A total of 6,652 and 12,042 genes were differentially expressed due to low light intensity in Swarnaprabha and IR8, respectively, as compared to control. CAB, LRP, SBPase, MT15, TF PCL1, and Photosystem I & II complex related gene expressions were mostly increased in Swarnaprabha upon the longer duration of low light exposure, which was not found in IR8 as compared to control. Their expressions were validated by qRT-PCR. The overall study suggested that the maintenance of grain yield in the tolerant variety under low light might be the result of accelerated expression of the genes, which enable the plant to keep the photosynthetic processes moving at the same pace even under low light.

Keywords: rice, low light, photosynthesis, yield

Procedia PDF Downloads 163

Authors: Anupuma Raina, Ajay P. Balayan, Prateek Pandya, Pankaj Shrivastava, Uma Kanga, Tulika Seth

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DNA fingerprinting analysis aids in personal identification for forensic purposes and has always been a driving motivation for law enforcement agencies in almost all countries since its inception. The introduction of DNA markers (Y-STR) has allowed for greater precision and higher discriminatory power in forensic testing. A criminal/ person committing crime after bone marrow transplantation is a rare situation but not an impossible one. Keeping such a situation in mind, a study was carried out to find out the best biological sample to be used for personal identification, especially in forensic situation. We choose a female patient (recipient) and a male donor. The pre transplant sample (blood) and post transplant samples (blood, buccal swab, hair roots) were collected from the recipient (patient). The same were compared with the blood sample of the donor using DNA FP technique. Post transplant samples were collected at different interval of time (15, 30, 60, and 90 days). The study was carried out using Y-STR kit at 23 loci. The results determined discusses the phenomenon of chimerism and its impact on Y-STR. Hair sample was found the most suitable sample which had no donor DNA profiling up to 90 days.

Keywords: bone marrow transplantation, chimerism, DNA profiling, Y-STR

Procedia PDF Downloads 116

Authors: Vikas Sharma, V. K. Dixit

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The roots of Anacyclus pyrethrum DC (AP) (Asteraceae) are frequently used in traditional medicine as Vajikarana Rasayana. An ethanolic extract of root of Anacyclus pyrethrum demonstrated its potential to enhance the sexual behaviour of male rats, with a dose dependent effect on sperm count and androgens concentration. Phytochemical analysis of ethanolic extract of Anacyclus pyrethrum revealed that it is rich in N-alkylamide. This study therefore sought to assess characterization of ethanolic extract of Anacyclus pyrethrum root. Root extract was performed using a gradient reversed phase high performance liquid chromatography/UV/electrospray ionization ion trap mass spectrometry (HPLC/ESI-MS) method on an embedded polar column. MS1 and MS2 fragmentation data were used for identification purposes, while UV was used for quantification. Thirteen N-alkylamides (five N-isobutylamides, three N-methyl isobutylamides, four tyramides, and one 2-phenylethylamide) were detected. Five of them identified as undeca-2E,4E-diene-8,10-diynoic acid N-methyl isobutylamide, tetradeca-2E,4E-diene-8,10-diynoic acid tyramide, deca-2E,4E-dienoic acid N-methyl isobutylamide, tetradeca-2E,4E,XE/Z-trienoic acid tyramide and tetradeca-2E,4E,8Z,10Z-tetraenoic isobutylamide are novel compounds, which have never been identified in Anacyclus pyrethrum.

Keywords: Anacyclus pyrethrum (Asteraceae), LC-MS plant profiling, N-alkylamides, pellitorine, anacycline

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Authors: Pannaga Pavan Jutur

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Parachlorella kessleri, a marine unicellular green alga belonging to class Trebouxiophyceae, accumulates large amounts of oil, i.e., lipids under nutrient-deprived (-N, -P, and -S) conditions. Understanding their metabolic imprints is important for elucidating the physiological mechanisms of lipid accumulations in this microalga subjected to nutrient deprivation. Metabolic and lipidomic profiles were obtained respectively using gas chromatography-mass spectrometry (GC-MS) of P. kessleri under nutrient starvation (-N, -P and -S) conditions. Relative quantities of more than 100 metabolites were systematically compared in all these three starvation conditions. Our results demonstrate that in lipid metabolism, the quantities of neutral lipids increased significantly followed by the decrease in other metabolites involved in photosynthesis, nitrogen assimilation, etc. In conclusion, the metabolomics and lipidomic profiles have identified a few common metabolites such as citric acid, valine, and trehalose to play a significant role in the overproduction of oil by this microalga subjected to nutrient deprivation. Understanding the entire system through untargeted metabolome profiling will lead to identifying relevant metabolites involved in the biosynthesis and degradation of precursor molecules that may have the potential for biofuel production, aiming towards the vision of tomorrow’s bioenergy needs.

Keywords: algae, biofuels, nutrient stress, omics

Procedia PDF Downloads 241

Authors: P. S. Seboletswe, Z. Mkhize, L. M. Katata-Seru

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Protorhus longifolia is known as a medicinal plant that has been used traditionally to treat various ailments such as hemiplegic paralysis, blood clotting related diseases, diarrhoea, heartburn, etc. The study reports a High-Performance Thin Layer Chromatography (HPTLC) fingerprint profile of Protorhus longifolia methanolic extract and its qualitative analysis of gallic acid, rutin, and quercetin. HPTLC analysis was achieved using CAMAG HPTLC system equipped with CAMAG automatic TLC sampler 4, CAMAG Automatic Developing Chamber 2 (ADC2), CAMAG visualizer 2, CAMAG Thin Layer Chromatography (TLC) scanner and visionCATS CAMAG HPTLC software. Mobile phase comprising toluene, ethyl acetate, formic acid (21:15:3) was used for qualitative analysis of gallic acid and revealed eight peaks while the mobile phase containing ethyl acetate, water, glacial acetic acid, formic acid (100:26:11:11) for qualitative analysis of rutin and quercetin revealed six peaks. HPTLC sillica gel 60 F254 glass plates (10 × 10) were used as the stationary phase. Gallic acid was detected at the R_f = 0.35; while rutin and quercetin were not evident in the extract. Further studies will be performed to quantify gallic acid in Protorhus longifolia leaves and also identify other biomarkers.

Keywords: biomarkers, fingerprint profiling, gallic acid, HPTLC, Protorhus longifolia

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Authors: Seema Garcha, Sheetal Chopra, Navraj Sarao

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Plant hormones play a role in internal colonization by beneficial microbes and also systemic acquired resistance. They define qualitative and quantitative nature of root microbiome and also influence dynamics of root rhizospheric soil. The present study is an attempt to relate salicylic acid (signal molecule) content and qualitative nature of root endophytes at various stages in the growth of rice varieties of commercial value- Parmal 121 and Basmati 1121. Root seedlings of these varieties were raised using tissue culture techniques and then they were transplanted in the fields. Cultivation was done using conventional methods in agriculture. Field soil contained 0.39% N, 75.12 Kg/hectare of phosphorus and 163.0 Kg/hectare of potassium. Microfloral profiling of the root tissue was done using the selective microbiological medium. The salicylic acid content was estimated using HPLC-Agilent 1100 HPLC Series. Salicylic acid level of Basmati 1121 remained relatively low at the time of transplant and 90 days after transplant. It increased marginally at 60 days. A similar trend was observed with Parmal 121 as well. However, Parmal variety recorded 0.935 ug/g of salicylic acid at 60 days after transplant. Salicylic acid content decreased after 90 days as both the rice varieties remained disease free. The endophytic root microflora was established by 60 days after transplant in both the varieties after which their population became constant. Rhizobium spp dominated over Azotobacter spp. Genetic profiling of endophytes for nitrogen-fixing ability is underway.

Keywords: plant-microbe interaction, rice, root microbiome, salicylic acid

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Authors: M. Latha, Achintya K. Dolui, P. Vijayaraj

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Vegetable oils mainly triacylglycerol (TAG) are an essential nutrient in the human diet as well as one of the major global commodity. There is a pressing need to enhance the yield of oil production to meet the world’s growing demand. Oil content is controlled by the balance between synthesis and breakdown in the cells. Several studies have established to increase the oil content by the overexpression of oil biosynthetic enzymes. Interestingly the significant oil accumulation was observed with impaired TAG hydrolysis. Unfortunately, the structural, as well as the biochemical properties of the lipase enzymes, is widely unknown, and so far, no candidate gene was identified in seeds except sugar-dependent1 (SDP1). Evidence has shown that SDP1directly responsible for initiation of oil breakdown in the seeds during germination. The present study is the identification of seed-specific acyl-hydrolases by activity based proteome profiling (ABPP) using Arabidopsis thaliana as a model system. The ABPP reveals that around 8 to 10 proteins having the serine hydrolase domain and are expressed during germination of Arabidopsis seed. The N-term sequencing, as well as LC-MS/MS analysis, was performed for the differentially expressed protein during germination. The coding region of the identified proteins was cloned, and lipases activity was assessed with purified recombinant protein. The enzyme assay was performed against various lipid substrates, and we have observed the acylhydrolase activity towards lysophosphatidylcholine and monoacylglycerol. Further, the functional characteristic of the identified protein will reveal the physiological significance the enzyme in oil accumulation.

Keywords: lipase, lipids, vegetable oil, triacylglycerol

Procedia PDF Downloads 151

Authors: Changde Zhang, Qiang Zhang, Shilong Zheng, Jiawang Liu, Shanchun Guo, Qiu Zhong, Guangdi Wang

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Fulvestrant was approved by FDA to treat breast cancer as a selective estrogen receptor downregulator (SERD) with intramuscular injection administration. ZB716, a fulvestarnt-3 boronic acid, is an SERD with comparable anticancer effect to fulvestrant, but could produce good pharmacokinetic properties under oral administration with mice or rat models. To understand why ZB716 produced much better oral bioavailability, it was proposed that the boronic acid blocked the phase II direct biotransformation with the hydroxyl group on the 3 position of the aromatic ring on fulvestrant. In this study, ZB716 or fulvestrant was incubated with human liver microsome and oxidation cofactor NADPH in vitro. Their metabolites after oxidation were profiled with the Q-Exactive, a high-resolution mass spectrometer. The result showed that ZB716 blocked the forming of hydroxyl groups on its benzene ring except for the oxidation of C-B bond forming fulvestrant in its metabolites, and the concentration of fulvestrant with one more hydroxyl group found in the metabolites from incubation with fulvestrant was about 34 fold high as that formed from incubation with ZB716. Compared to fulvestrant, ZB716 is expected to be much difficult to be further bio-transformed into more hydrophilic compounds, to be difficult excreted out of blood system, and to have longer residence time in blood, which can lead to higher oral bioavailability. This study provided evidence to explain the high bioavailability of ZB716 after oral administration from the perspective of its difficulty of oxidation, a phase I biotransformation, on positions on its aromatic ring.

Keywords: biotransformation, fulvestrant, metabolite profiling, ZB716

Procedia PDF Downloads 228

Authors: Wanchalerm Patanacharoenwong, Panaya Sudta, Prachya Bumrungkun

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The paper focuses on the development of a system that combines Internet of Things (IoT) technologies and deep learning algorithms for anomaly detection in residential Electric Vehicle (EV) charging in smart cities. With the increasing number of EVs, ensuring efficient and reliable charging systems has become crucial. The aim of this research is to develop an integrated IoT and deep learning system for detecting anomalies in residential EV charging and enhancing EV load profiling and event detection in smart cities. This approach utilizes IoT devices equipped with infrared cameras to collect thermal images and household EV charging profiles from the database of Thailand utility, subsequently transmitting this data to a cloud database for comprehensive analysis. The methodology includes the use of advanced deep learning techniques such as Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) algorithms. IoT devices equipped with infrared cameras are used to collect thermal images and EV charging profiles. The data is transmitted to a cloud database for comprehensive analysis. The researchers also utilize feature-based Gaussian mixture models for EV load profiling and event detection. Moreover, the research findings demonstrate the effectiveness of the developed system in detecting anomalies and critical profiles in EV charging behavior. The system provides timely alarms to users regarding potential issues and categorizes the severity of detected problems based on a health index for each charging device. The system also outperforms existing models in event detection accuracy. This research contributes to the field by showcasing the potential of integrating IoT and deep learning techniques in managing residential EV charging in smart cities. The system ensures operational safety and efficiency while also promoting sustainable energy management. The data is collected using IoT devices equipped with infrared cameras and is stored in a cloud database for analysis. The collected data is then analyzed using RNN, LSTM, and feature-based Gaussian mixture models. The approach includes both EV load profiling and event detection, utilizing a feature-based Gaussian mixture model. This comprehensive method aids in identifying unique power consumption patterns among EV owners and outperforms existing models in event detection accuracy. In summary, the research concludes that integrating IoT and deep learning techniques can effectively detect anomalies in residential EV charging and enhance EV load profiling and event detection accuracy. The developed system ensures operational safety and efficiency, contributing to sustainable energy management in smart cities.

Keywords: cloud computing framework, recurrent neural networks, long short-term memory, Iot, EV charging, smart grids

Procedia PDF Downloads 26

Authors: O. O. Sufyani, M. E. Oraiby, S. A. Qumaiy, A. I. Alaamri, Z. M. Eisa, A. M. Hakami, M. A. Attafi, O. M. Alhassan, W. M. Elsideeg, E. M. Noureldin, Y. A. Hobani, Y. Q. Majrabi, I. A. Khardali, A. B. Maashi, A. A. Al Mane, A. H. Hakami, I. M. Alkhyat, A. A. Sahly, I. M. Attafi

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According to the Food and Agriculture Organization (FAO) Pesticides Use Database, pesticide use in agriculture in Saudi Arabia has more than doubled from 4539 tons in 2009 to 10496 tons in 2019. Among pesticides, pyrethroids is commonly used in Saudi Arabia. Pesticides may increase susceptibility to a variety of diseases, particularly among pesticide workers, due to their extensive use, indiscriminate use, and long-term exposure. Therefore, analyzing blood chemo-profiles and evaluating the detected substances as biomarkers for pyrethroid pesticide exposure may assist to identify and predicting adverse effects of exposure, which may be used for both preventative and risk assessment purposes. The purpose of this study was to (a) analyze chemo-profiling by Gas Chromatography-Mass Spectrometry (GC-MS) analysis, (b) identify the most commonly detected chemicals in a time-exposure-dependent manner using a Venn diagram, and (c) identify their associated disease among pesticide workers using analyzer tools on the Comparative Toxicogenomics Database (CTD) website, (250 healthy male volunteers (20-60 years old) who deal with pesticides in the Jazan region of Saudi Arabia (exposure intervals: 1-2, 4-6, 6-8, more than 8 years) were included in the study. A questionnaire was used to collect demographic information, the duration of pesticide exposure, and the existence of chronic conditions. Blood samples were collected for biochemistry analysis and extracted by solid-phase extraction for gas chromatography-mass spectrometry (GC-MS) analysis. Biochemistry analysis reveals no significant changes in response to the exposure period; however, an inverse association between the albumin level and the exposure interval was observed. The blood chemo-profiling was differentially expressed in an exposure time-dependent manner. This analysis identified the common chemical set associated with each group and their associated significant occupational diseases. While some of these chemicals are associated with a variety of diseases, the distinguishing feature of these chemically associated disorders is their applicability for prevention measures. The most interesting finding was the identification of several chemicals; erucic acid, pelargonic acid, alpha-linolenic acid, dibutyl phthalate, diisobutyl phthalate, dodecanol, myristic Acid, pyrene, and 8,11,14-eicosatrienoic acid, associated with pneumoconiosis, asbestosis, asthma, silicosis and berylliosis. Chemical-disease association study also found that cancer, digestive system disease, nervous system disease, and metabolic disease were the most often recognized disease categories in the common chemical set. The hierarchical clustering approach was used to compare the expression patterns and exposure intervals of the chemicals found commonly. More study is needed to validate these chemicals as early markers of pyrethroid insecticide-related occupational disease, which might assist evaluate and reducing risk. The current study contributes valuable data and recommendations to public health.

Keywords: occupational, toxicology, chemo-profiling, pesticide, pyrethroid, GC-MS

Procedia PDF Downloads 62

Authors: Francesca Carta, Giovanna Linfante, Laura Agneni, Debora Radicchia, Camilla Micheletta, Angelo Del Cimmuto

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Overtaking competence mismatches and fostering career pathways congruent with the individual skills profile would significantly contribute to fighting unemployment. The aim of this paper is to examine the usefulness and efficiency of qualitative tools in supporting and improving the quality of caseworkers’ activities during the jobseekers’ profile analysis and career guidance process. The selected target groups are long-term and middle term unemployed, job seekers, young people at the end of the vocational training pathway and unemployed woman with social disadvantages. The experimentation is conducted in Italy at public employment services in 2017. In the framework of Italian labour market reform, the experimentation represents the first step to develop a customized qualitative model profiling; the final general object is to improve the public employment services quality. The experimentation tests the transferability of an OECD self-assessment competences tool in the Italian public employment services. On one hand, the first analysis results will indicate the user’s perception concerning the tool’s application and their different competence levels (literacy, numeracy, problem solving, career interest, subjective well-being and health, behavioural competencies) with reference to the specific target. On the other hand, the experimentation outcomes will show caseworkers understanding regarding the tool’s usability and efficiency for career guidance and reskilling and upskilling programs.

Keywords: career guidance, evaluation competences, reskilling pathway, unemployment

Procedia PDF Downloads 276

Authors: Tahani Aljohani, Jialin Yu, Alexandra. I. Cristea

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The more an educational system knows about a learner, the more personalised interaction it can provide, which leads to better learning. However, asking a learner directly is potentially disruptive, and often ignored by learners. Especially in the booming realm of MOOC Massive Online Learning platforms, only a very low percentage of users disclose demographic information about themselves. Thus, in this paper, we aim to predict learners’ demographic characteristics, by proposing an approach using linguistically motivated Deep Learning Architectures for Learner Profiling, particularly targeting gender prediction on a FutureLearn MOOC platform. Additionally, we tackle here the difficult problem of predicting the gender of learners based on their comments only – which are often available across MOOCs. The most common current approaches to text classification use the Long Short-Term Memory (LSTM) model, considering sentences as sequences. However, human language also has structures. In this research, rather than considering sentences as plain sequences, we hypothesise that higher semantic - and syntactic level sentence processing based on linguistics will render a richer representation. We thus evaluate, the traditional LSTM versus other bleeding edge models, which take into account syntactic structure, such as tree-structured LSTM, Stack-augmented Parser-Interpreter Neural Network (SPINN) and the Structure-Aware Tag Augmented model (SATA). Additionally, we explore using different word-level encoding functions. We have implemented these methods on Our MOOC dataset, which is the most performant one comparing with a public dataset on sentiment analysis that is further used as a cross-examining for the models' results.

Keywords: deep learning, data mining, gender predication, MOOCs

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Authors: Mark Ashton Newman, Richard Blagrove, Jonathan Folland

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The force-velocity profile of an individual has been shown to influence success in ballistic movements, independent of the individuals' maximal power output; therefore, effective and accurate evaluation of an individual’s F-V characteristics and not solely maximal power output is important. The relatively narrow range of loads typically utilised during force-velocity profiling protocols due to the difficulty in obtaining force data at high velocities may bring into question the accuracy of the F-V slope along with predictions pertaining to the maximum force that the system can produce at a velocity of null (F₀) and the theoretical maximum velocity against no load (V₀). As such, the reliability of the slope of the force-velocity profile, as well as V₀, has been shown to be relatively poor in comparison to F₀ and maximal power, and it has been recommended to assess velocity at loads closer to both F₀ and V₀. The aim of the present study was to assess the relative and absolute reliability of an instrumented novel leg press machine which enables the assessment of force and velocity data at loads equivalent to ≤ 10% of one repetition maximum (1RM) through to 1RM during a ballistic leg press movement. The reliability of maximal and mean force, velocity, and power, as well as the respective force-velocity and power-velocity relationships and the linearity of the force-velocity relationship, were evaluated. Sixteen male strength-trained individuals (23.6 ± 4.1 years; 177.1 ± 7.0 cm; 80.0 ± 10.8 kg) attended four sessions; during the initial visit, participants were familiarised with the leg press, modified to include a mounted force plate (Type SP3949, Force Logic, Berkshire, UK) and a Micro-Epsilon WDS-2500-P96 linear positional transducer (LPT) (Micro-Epsilon, Merseyside, UK). Peak isometric force (IsoMax) and a dynamic 1RM, both from a starting position of 81% leg length, were recorded for the dominant leg. Visits two to four saw the participants carry out the leg press movement at loads equivalent to ≤ 10%, 30%, 50%, 70%, and 90% 1RM. IsoMax was recorded during each testing visit prior to dynamic F-V profiling repetitions. The novel leg press machine used in the present study appears to be a reliable tool for measuring F and V-related variables across a range of loads, including velocities closer to V₀ when compared to some of the findings within the published literature. Both linear and polynomial models demonstrated good to excellent levels of reliability for SFV and F₀ respectively, with reliability for V₀ being good using a linear model but poor using a 2nd order polynomial model. As such, a polynomial regression model may be most appropriate when using a similar unilateral leg press setup to predict maximal force production capabilities due to only a 5% difference between F₀ and obtained IsoMax values with a linear model being best suited to predict V₀.

Keywords: force-velocity, leg-press, power-velocity, profiling, reliability

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Authors: Maja Martinovic, Valentina Zarkovic, Hrvoje Maljak

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Europe is one of the most popular tourist destinations in the world, in which tourism occupies a significant place among the most relevant economic activities, and this applies to the Republic of Croatia as well. Based on this study, the authors intended to encourage and support the creation of an effective tourism policy in Croatia that would be based on the profiling of certain target groups. Another objective was to compare the results obtained from the customer analysis with the market analysis of the tourism industry in Croatia. The objective is to adapt the current tourist offer according to the identified needs and expectations of a particular tourist group in order to increase the attractiveness of Croatia as a tourist destination and motivate greater attendance of the targeted tourist groups. The current research was oriented towards the Russian market as the target group. Therefore, the authors wanted to encourage a discussion on how to attract more Russian guests. Consequently, the intention of the research was a detailed analysis of Russian tourists, in order to gain a better understanding of their travelling motives and tendencies. Furthermore, attention was paid to the expectations of Russian customers and to compare them with the Croatian tourist offer, and to determine whether there is a possibility for an overlap. The method used to obtain the information required was a survey conducted among Russian citizens about their travelling habits. The research was carried out on the basis of 166 participants of different age, gender, profession and income group. The sampling and distribution of the survey took place between May and July 2016. The results provided from the research indicate that Croatian tourism has certain unrealized potential considering the popularization of Croatia as a tourist destination, and there is a capacity for increasing the revenues within the group of Russian tourists. Such a conclusion is based on the fact that the Croatian tourist offer and the preferences of the Russian guests are compatible, i.e. they overlap in many aspects. The results demonstrate that beautiful nature, cultural and historical heritage as well as the sun and sea, play a leading role in attracting more Russian tourists. It is precisely these elements that form the three pillars of the Croatian tourist offer. On the other hand, the profiling revealed that the most desirable destinations for the Russian guests are Italy and Spain, both of which provide the same main tourist attractions as Croatia. Therefore, the focus of the strategic ideas given in the paper shifted to other tourism segments, such as type of accommodation, sales channels, travel motives, additional offer and seasonality etc., in order to gain advantage in the Russian market, the Mediterranean region and tourism in general. The purpose of the research is to serve as a foundation for analysing the attractiveness of the other tourist destinations in the Russian market, as well as to be a general basis for a more detailed profiling of the various specific target groups of the Russian and other tourist groups.

Keywords: Croatia, Russian market, target groups, tourism, tourist destination

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Authors: Victor S. Klimin, Alexey A. Rezvan, Maxim S. Solodovnik, Oleg A. Ageev

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In this paper, the problems of existing methods of profiling and surface modification of nanoscale arsenide-gallium structures are analyzed. The use of a combination of methods of local anodic oxidation and plasma chemical etching to solve this problem is considered. The main features that make this technology one of the promising areas of modification and profiling of near-surface layers of solids are demonstrated. In this paper, we studied the effect of formation stress and etching time on the geometrical parameters of the etched layer and the roughness of the etched surface. Experimental dependences of the thickness of the etched layer on the time and stress of formation were obtained. The surface analysis was carried out using atomic force microscopy methods, the corresponding profilograms were constructed from the obtained images, and the roughness of the etched surface was studied accordingly. It was shown that at high formation voltage, the depth of the etched surface increased, this is due to an increase in the number of active particles (oxygen ions and hydroxyl groups) formed as a result of the decomposition of water molecules in an electric field, during the formation of oxide nanostructures on the surface of gallium arsenide. Oxide layers were used as negative masks for subsequent plasma chemical etching by the STE ICPe68 unit. BCl₃ was chosen as the chlorine-containing gas, which differs from analogs in some parameters for the effect of etching of nanostructures based on gallium arsenide in the low-temperature plasma. The gas mixture of reaction chamber consisted of a buffer gas NAr = 100 cm³/min and a chlorine-containing gas NBCl₃ = 15 cm³/min at a pressure P = 2 Pa. The influence of these methods modes, which are formation voltage and etching time, on the roughness and geometric parameters, and corresponding dependences are demonstrated. Probe nanotechnology was used for surface analysis.

Keywords: nanostructures, GaAs, plasma chemical etching, modification structures

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Authors: Hanan Khojah, RuAngelie Edrada-Ebel

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Neurodegenerative disease including Alzheimer’s disease is a major cause of long-term disability. Oxidative stress is frequently implicated as one of the key contributing factors to neurodegenerative diseases. Protection against neuronal damage remains a great challenge for researchers. Ficus carica (commonly known as fig) is a species of great antioxidant nutritional value comprising a protective mechanism against innumerable health disorders related to oxidative stress as well as Alzheimer’s disease. The purpose of this work was to characterize the non-polar active metabolites in Ficus carica endocarp, mesocarp, and exocarp. Crude extracts were prepared using several extraction solvents, which included 1:1 water: ethylacetate, acetone and methanol. The dried extracts were then solvent partitioned between equivalent amounts of water and ethylacetate. Purification and fractionation were accomplished by high-throughput chromatography. The isolated metabolites were tested on their effect on human neuroblastoma cell line by cell viability test and cell cytotoxicity assay with acrolein. Molecular weights of the active metabolites were determined via LC–HRESIMS and GC-EIMS. Metabolomic profiling was performed to identify the active metabolites by using differential expression analysis software (Mzmine) and SIMCA for multivariate analysis. Structural elucidation and identification of the interested active metabolites were studied by 1-D and 2-D NMR. Significant differences in bioactivity against a concentration-dependent assay on acrolein radicals were observed between the three fruit parts. However, metabolites obtained from mesocarp and the endocarp demonstrated bioactivity to scavenge ROS radical. NMR profiling demonstrated that aliphatic compounds such as γ-sitosterol tend to induce neuronal bioactivity and exhibited bioactivity on the cell viability assay. γ-Sitosterol was found in higher concentrations in the mesocarp and was considered as one of the major phytosterol in Ficus carica.

Keywords: alzheimer, Ficus carica, γ-Sitosterol, metabolomics

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Authors: Shagufta Jabeen, Faez Jesse Firdaus Abdullah, Zunita Zakaria, Nurulfiza Mat Isa, Yung Chie Tan, Wai Yan Yee, Abdul Rahman Omar

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Pasteurella multocida is associated with acute, as well as, chronic infections in avian and bovine such as pasteurellosis and hemorrhagic septicemia (HS) in cattle and buffaloes. Iron is one of the most important nutrients for pathogenic bacteria including Pasteurella and acts as a cofactor or prosthetic group in several essential enzymes and is needed for amino acid, pyrimidine, and DNA biosynthesis. In our recent study, we showed that 2% of Pasteurella multocida serotype A strain PMTB2.1 encode for iron regulating genes (Accession number CP007205.1). Genome sequencing of other Pasteurella multocida serotypes namely PM70 and HB01 also indicated up to 2.5% of the respective genome encode for iron regulating genes, suggesting that Pasteurella multocida genome comprises of multiple systems for iron uptake. Since P. multocida PMTB2.1 has more than 40 CDs out of 2097 CDs (approximately 2%), encode for iron-regulated. The gene expression profiling of four iron-regulating genes namely fbpb, yfea, fece and fur were characterized under iron-restricted environment. The P. multocida strain PMTB2.1 was grown in broth with and without iron chelating agent and samples were collected at different time points. Relative mRNA expression profile of these genes was determined using Taqman probe based real-time PCR assay. The data analysis, normalization with two house-keeping genes and the quantification of fold changes were carried out using Bio-Rad CFX manager software version 3.1. Results of this study reflect that iron reduced environment has significant effect on expression profile of iron regulating genes (p < 0.05) when compared to control (normal broth) and all evaluated genes act differently with response to iron reduction in media. The highest relative fold change of fece gene was observed at early stage of treatment indicating that PMTB2.1 may utilize its periplasmic protein at early stage to acquire iron. Furthermore, down-regulation expression of fece with the elevated expression of other genes at later time points suggests that PMTB2.1 control their iron requirements in response to iron availability by down-regulating the expression of iron proteins. Moreover, significantly high relative fold change (p ≤ 0.05) of fbpb gene is probably associated with the ability of P. multocida to directly use host iron complex such as hem, hemoglobin. In addition, the significant increase (p ≤ 0.05) in fbpb and yfea expressions also reflects the utilization of multiple iron systems in P. multocida strain PMTB2.1. The findings of this study are very much important as relative scarcity of free iron within hosts creates a major barrier to microbial growth inside host and utilization of outer-membrane proteins system in iron acquisition probably occurred at early stage of infection with P. multocida. In conclusion, the presence and utilization of multiple iron system in P. multocida strain PMTB2.1 revealed the importance of iron in the survival of P. multocida.

Keywords: iron-related genes, real-time PCR, gene expression profiling, fold changes

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Authors: Hanan Begali, Shahi Dost, Annett Ziegler, Markus Cornberg, Maria-Esther Vidal, Anke R. M. Kraft

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Chronic hepatitis B virus (HBV) infection can be treated with nucleot(s)ide analog (NA), for example, which inhibits HBV replication. However, they have hardly any influence on the functional cure of HBV, which is defined by hepatitis B surface antigen (HBsAg) loss. NA needs to be taken life-long, which is not available for all patients worldwide. Additionally, NA-treated patients are still at risk of developing cirrhosis, liver failure, or hepatocellular carcinoma (HCC). Although each patient has the same components of the immune system, immune responses vary between patients. Therefore, a deeper understanding of the immune response against HBV in different patients is necessary to understand the parameters leading to HBV cure and to use this knowledge to optimize HBV therapies. This requires seamless integration of an enormous amount of diverse and fine-grained data from viral markers, e.g., hepatitis B core-related antigen (HBcrAg) and hepatitis B surface antigen (HBsAg). The data integration system relies on the assumption that profiling human immune systems requires the analysis of various variables (e.g., demographic data, treatments, pre-existing conditions, immune cell response, or HLA-typing) rather than only one. However, the values of these variables are collected independently. They are presented in a myriad of formats, e.g., excel files, textual descriptions, lab book notes, and images of flow cytometry dot plots. Additionally, patients can be identified differently in these analyses. This heterogeneity complicates the integration of variables, as data management techniques are needed to create a unified view in which individual formats and identifiers are transparent when profiling the human immune systems. The proposed study (HBsRE) aims at integrating heterogeneous data sets of 87 chronically HBV-infected patients, e.g., clinical data, immune cell response, and HLA-typing, with knowledge encoded in biomedical ontologies and open-source databases into a knowledge-driven framework. This new technique enables us to harmonize and standardize heterogeneous datasets in the defined modeling of the data integration system, which will be evaluated in the knowledge graph (KG). KGs are data structures that represent the knowledge and data as factual statements using a graph data model. Finally, the analytic data model will be applied on top of KG in order to develop a deeper understanding of the immune profiles among various patients and to evaluate factors playing a role in a holistic profile of patients with HBsAg level loss. Additionally, our objective is to utilize this unified approach to stratify patients for new effective treatments. This study is developed in the context of the project “Transforming big data into knowledge: for deep immune profiling in vaccination, infectious diseases, and transplantation (ImProVIT)”, which is a multidisciplinary team composed of computer scientists, infection biologists, and immunologists.

Keywords: chronic hepatitis B infection, immune response, knowledge graphs, ontology

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Authors: Mohammad Nazri Abdul Bahari, Nurshafika Mohd Sakeh, Siti Nor Akmar Abdullah

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Basal stem rot (BSR) is the most devastating disease in oil palm. Among the oil palm pathogenic fungi, the most prevalent and virulent species associated with BSR is Ganoderma boninense. Early detection of G. boninense attack in oil palm wherein physical symptoms has not yet appeared can offer opportunities to prevent the spread of the necrotrophic fungus. However, poor understanding of molecular defense responses and roles of antifungal metabolites in oil palm against G. boninense has complicated the resolving measures. Hence, characterization of defense-related molecular responses and production of antifungal compounds during early interaction with G. boninense is of utmost important. Four month-old oil palm (Elaeis guineensis) seedlings were artificially infected with G. boninense-inoculated rubber wood block via sitting technique. RNA of samples were extracted from roots and leaves tissues at 0, 3, 7 and 11 days post inoculation (d.p.i) followed with sequencing using RNA-Seq method. Differentially-expressed genes (DEGs) of oil palm-G. boninense interaction were identified, while changes in metabolite profile will be scrutinized related to the DEGs. The RNA-Seq data generated a total of 113,829,376 and 313,293,229 paired-end clean reads from untreated (0 d.p.i) and treated (3, 7, 11 d.p.i) samples respectively, each with two biological replicates. The paired-end reads were mapped to Elaeis guineensis reference genome to screen out non-oil palm genes and subsequently generated 74,794 coding sequences. DEG analysis of phytohormone biosynthetic genes in oil palm roots revealed that at p-value ≤ 0.01, ethylene and jasmonic acid may act in antagonistic manner with salicylic acid to coordinate defense response at early interaction with G. boninense. Findings on metabolite profiling of G. boninense-infected oil palm roots and leaves are hoped to explain the defense-related compounds elicited by Elaeis guineensis in response to G. boninense colonization. The study aims to shed light on molecular defense response of oil palm at early interaction with G. boninense and promote prevention measures against Ganoderma infection.

Keywords: Ganoderma boninense, metabolites, phytohormones, RNA-Seq

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Authors: Harika Atmaca, Emir Bozkurt, Latife Merve Oktay, Selim Uzunoglu, Ruchan Uslu, Burçak Karaca

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Microarrays have been developed for highly parallel enzyme-linked immunosorbent assay (ELISA) applications. The most common protein arrays are produced by using multiple monoclonal antibodies, since they are robust molecules which can be easily handled and immobilized by standard procedures without loss of activity. Protein expression profiling with protein array technology allows simultaneous analysis of the protein expression pattern of a large number of proteins. Trabectedin, a tetrahydroisoquinoline alkaloid derived from a Caribbean tunicate, Ecteinascidia turbinata, has been shown to have antitumor effects. Here, we used a novel proteomic approach to explore the mechanism of action of trabectedin in prostate cancer cell line PC-3 by apoptosis antibody microarray. XTT cell proliferation kit and Cell Death Detection Elisa Plus Kit (Roche) was used for measuring cytotoxicity and apoptosis. Human Apoptosis Protein Array (R&D Systems) which consists of 35 apoptosis related proteins was used to assess the omic protein expression pattern. Trabectedin induced cytotoxicity and apoptosis in prostate cancer cells in a time and concentration-dependent manner. The expression levels of the death receptor pathway molecules, TRAIL-R1/DR4, TRAIL R2/DR5, TNF R1/TNFRSF1A, FADD were significantly increased by 4.0-, 21.0-, 4.20- and 11.5-fold by trabectedin treatment in PC-3 cells. Moreover, mitochondrial pathway related pro-apoptotic proteins Bax, Bad, Cytochrome c, and Cleaved Caspase-3 expressions were induced by 2.68-, 2.07-, 2.8-, and 4.5-fold and the expression levels of anti-apoptotic proteins Bcl-2 and Bcl-XL were reduced by 3.5- and 5.2-fold in PC-3 cells. Proteomic (antibody microarray) analysis suggests that the mechanism of action of trabectedin may be exerted via the induction of both intrinsic and extrinsic apoptotic pathways. The antibody microarray platform can be utilised to explore the molecular mechanism of action of novel anticancer agents.

Keywords: trabectedin, prostate cancer, omic protein expression profile, apoptosis

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Authors: Suzana Leitão Russo, Mayara Laysa de Oliveira Silva, José Augusto Andrade Filho, Vitor Hugo Simon

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Currently, seismic methods and prospecting methods are commonly applied in the oil industry and, according to the information reported every day; oil is a source of non-renewable energy. It is easier to understand why the ownership of areas of oil extraction is coveted by many nations. It is necessary to think about ways that will enable the maximization of oil production. The technique of spectral analysis can be used to analyze the behavior of the variables already defined in oil well the profile. The main objective is to verify the series dependence of variables, and to model the variables using the frequency domain to observe the model residuals.

Keywords: oil, well, spectral analysis, oil extraction

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Authors: Priyanka Jain, Ashish K. Sharma, Esha Shukla, K. J. Mukherjee

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We propose a paradigm shift in our approach to design improved platforms for recombinant protein production, by addressing system level issues rather than the individual steps associated with recombinant protein synthesis like transcription, translation, etc. We demonstrate that by controlling and modulating the cellular stress response (CSR), which is responsible for feedback control of protein synthesis, we can generate hyper-producing strains. We did transcriptomic profiling of post-induction cultures, expressing different types of protein, to analyze the nature of this cellular stress response. We found significant down-regulation of substrate utilization, translation, and energy metabolism genes due to generation CSR inside the host cell. However, transcription profiling has also shown that many genes are up-regulated post induction and their role in modulating the CSR is unclear. We hypothesized that these up-regulated genes trigger signaling pathways, generating the CSR and concomitantly reduce the recombinant protein yield. To test this hypothesis, we knocked out the up-regulated genes, which did not have any downstream regulatees, and analyzed their impact on cellular health and recombinant protein expression. Two model proteins i.e., GFP and L-Asparaginase were chosen for this analysis. We observed a significant improvement in expression levels, with some knock-outs showing more than 7-fold higher expression compared to control. The 10 best single knock-outs were chosen to make 45 combinations of all possible double knock-outs. A further increase in expression was observed in some of these double knock- outs with GFP levels being highest in a double knock-out ΔyhbC + ΔelaA. However, for L-Asparaginase which is a secretory protein, the best results were obtained using a combination of ΔelaA+ΔcysW knock-outs. We then tested all the knock outs for their ability to enhance the expression of a 'difficult-to-express' protein. The Rubella virus E1 protein was chosen and tagged with sfGFP at the C-terminal using a linker peptide for easy online monitoring of expression of this fusion protein. Interestingly, the highest increase in Rubella-sGFP levels was obtained in the same double knock-out ΔelaA + ΔcysW (5.6 fold increase in expression yield compared to the control) which gave the highest expression for L-Asparaginase. However, for sfGFP alone, the ΔyhbC+ΔmarR knock-out gave the highest level of expression. These results indicate that there is a fair degree of commonality in the nature of the CSR generated by the induction of different proteins. Transcriptomic profiling of the double knock out showed that many genes associated with the translational machinery and energy biosynthesis did not get down-regulated post induction, unlike the control where these genes were significantly down-regulated. This confirmed our hypothesis of these genes playing an important role in the generation of the CSR and allowed us to design a strategy for making better expression hosts by simply knocking out key genes. This strategy is radically superior to the previous approach of individually up-regulating critical genes since it blocks the mounting of the CSR thus preventing the down-regulation of a very large number of genes responsible for sustaining the flux through the recombinant protein production pathway.

Keywords: cellular stress response, GFP, knock-outs, up-regulated genes

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Authors: Mwafaq Ibdah, Mossab, Yahyaa, Dor Rachmany, Yoram Gerchman, Doron Holland, Liora Shaltiel-Harpaz

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Pear Psylla is the most important pest of pear in all pear-growing regions, in Asian, European, and the USA. Pear psylla damages pears in several ways: high-density populations of these insects can cause premature leaf and fruit drop, diminish plant growth, and reduce fruit size. In addition, their honeydew promotes sooty mold on leaves and russeting on fruit. Pear psyllas are also considered vectors of pear pathogens such as Candidatus Phytoplasma pyri causing pear decline that can lead to loss of crop and tree vigor, and sometimes loss of trees. Psylla control is a major obstacle to efficient integrated pest management. Recently we have identified two naturally resistance pear accessions (Py.760-261 and Py.701-202) in the Newe Ya’ar live collection. GC-MS volatile metabolic profiling identified several volatile compounds common in these accessions but lacking, or much less common, in a sensitive accession, the commercial Spadona variety. Among these volatiles were styrene and its derivatives. When the resistant accessions were used as inter-stock, the volatile compounds appear in commercial Spadona scion leaves, and it showed reduced susceptibility to pear psylla. Laboratory experiments and applications of some of these volatile compounds were very effective against psylla eggs, nymphs, and adults. The genes and enzymes involved in the specific reactions that lead to the biosynthesis of styrene in plant are unknown. We have identified a phenolic acid decarboxylase that catalyzes the formation of p-hydroxystyrene, which occurs as a styrene analog in resistant pear genotypes. The His-tagged and affinity chromatography purified E. coli-expressed pear PyPAD1 protein could decarboxylate p-coumaric acid and ferulic acid to p-hydroxystyrene and 3-methoxy-4-hydroxystyrene. In addition, PyPAD1 had the highest activity toward p-coumaric acid. Expression analysis of the PyPAD gene revealed that its expressed as expected, i.e., high when styrene levels and psylla resistance were high.

Keywords: pear Psylla, volatile, GC-MS, resistance

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Authors: Mark Gavriel, Ariel J. Jaffa, Dan Grisaru, David Elad

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The human endometrium-myometrium interface (EMI) is the uterine inner barrier without a separatig layer. It is composed of endometrial epithelial cells (EEC) and endometrial stromal cells (ESC) in the endometrium and myometrial smooth muscle cells (MSMC) in the myometrium. The EMI undergoes structural remodeling during the menstruation cycle which are essential for human reproduction. Recently, we co-cultured a layer-by-layer in vitro model of EEC, ESC and MSMC on a synthetic membrane for mechanobiology experiments. We also treated the model with progesterone and β-estradiol in order to mimic the in vivo receptive uterus In the present study we analyzed the cytokines profile in a single layer of EEC the hormonal treated in vitro model of the EMI. The methodologies of this research include simple tissue-engineering . First, we cultured commercial EEC (RL95-2, ATCC® CRL-1671™) in 24-wellplate. Then, we applied an hormonal stimuli protocol with 17-β-estradiol and progesterone in time dependent concentration according to the human physiology that mimics the menstrual cycle. We collected cell supernatant samples of control, pre-ovulation, ovulation and post-ovulaton periods for analysis of the secreted proteins and cytokines. The cytokine profiling was performed using the Proteome Profiler Human XL Cytokine Array Kit (R&D Systems, Inc., USA) that can detect105 human soluble cytokines. The relative quantification of all the cytokines will be analyzed using xMAP – LUMINEX. We conducted a fishing expedition with the 4 membranes Proteome Profiler. We processed the images, quantified the spots intensity and normalized these values by the negative control and reference spots at the membrane. Analyses of the relative quantities that reflected change higher than 5% of the control points of the kit revealed the The results clearly showed that there are significant changes in the cytokine level for inflammation and angiogenesis pathways. Analysis of tissue-engineered models of the uterine wall will enable deeper investigation of molecular and biomechanical aspects of early reproductive stages (e.g. the window of implantation) or developments of pathologies.

Keywords: tissue-engineering, hormonal stimuli, reproduction, multi-layer uterine model, progesterone, β-estradiol, receptive uterine model, fertility

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Authors: Sofia Barbosa, Mariana Pinto, José António Almeida, Edgar Carvalho, Catarina Diamantino

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The aim of this work was to test a methodology able to generate spatial-temporal maps that can synthesize simultaneously the trends of distinct hydrochemical indicators in an old radium-uranium tailings dam deposit. Multidimensionality reduction derived from principal component analysis and subsequent data aggregation derived from clustering analysis allow to identify distinct hydrochemical behavioural profiles and to generate synthetic evolutionary hydrochemical maps.

Keywords: Contamination plume migration, K-means of PCA scores, groundwater and mine water monitoring, spatial-temporal hydrochemical trends

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Authors: Dorcas Ropo Abejide, Olamide Ahmed Falusi, Oladipupo Abdulazeez Yusuf Daudu, Bolaji Zuluqurineen Salihu, Muhammad Liman Muhammad

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This study evaluated the morpho-agronomic response of twenty-four (24) Nigerian Bambara groundnut landraces to water stress and genetic diversity of some selected accessions using SSR markers. The studies were carried out in the botanical garden of the Department of Plant Biology, Federal University of Technology, Minna, Niger State, Nigeria in a randomized complete block design using three replicates. Molecular analysis using SSR primers was carried out at the International Institute of Tropical Agriculture (IITA) Ibadan in order to characterize ten selected accessions comprising the seven most drought tolerant and three most susceptible accessions from the 24 accessions evaluated. Results revealed that water stress decreased morpho-agronomic traits such as plant height, leaf area, number of leaves per plant, seed yield, etc. A total of 22 alleles were detected by the SSR markers used with a mean number of 4 allelles. SSR markers MBamCO₃₃, Primer 65, and G358B2-D15 each detected 4 allelles, while Primer 3FR and 4FR detected 5 allelles each. The study revealed significantly high polymorphisms in 10 Loci. The mean value of polymorpic information content was 0.6997, implying the usefulness of the primers used in identifying genetic similarities and differences among the Bambara groundnut genotypes. The SSR analysis revealed a comparable pattern between genetic diversity and drought tolerance of the genotypes. The UPGMA dendrogram showed that at a genetic distance of 0.1, the accessions were grouped into three groups according to their level of tolerance to drought. The two most drought-tolerant accessions were grouped together, and the 5th and 6th most drought-tolerant accessions were also grouped together. This suggests that the genotypes grouped together may be genetically close, may possess similar genes, or have a common origin. The degree of genetic variants obtained from this profiling could be useful in Bambara groundnut breeding for drought tolerance. The identified drought tolerant Bambara groundnut landraces are important genetic resources for drought stress tolerance breeding programme of Bambara groundnut. The genotypes are also useful for germplasm conservation and global implications.

Keywords: Bambara groundnut, genetic diversity, germplasm, SSR markers, water stress

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Authors: Oshma Chakoory, Sophie Comtet-Marre, Pierre Peyret

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Metagenomic classifiers are widely used for the taxonomic profiling of metagenomic data and estimation of taxa relative abundance. Small subunit rRNA genes are nowadays a gold standard for the phylogenetic resolution of complex microbial communities, although the power of this marker comes down to its use as full-length. We benchmarked the performance and accuracy of rRNA-specialized versus general-purpose read mappers, reference-targeted assemblers and taxonomic classifiers. We then built a pipeline called RiboTaxa to generate a highly sensitive and specific metataxonomic approach. Using metagenomics data, RiboTaxa gave the best results compared to other tools (Kraken2, Centrifuge (1), METAXA2 (2), PhyloFlash (3)) with precise taxonomic identification and relative abundance description, giving no false positive detection. Using real datasets from various environments (ocean, soil, human gut) and from different approaches (metagenomics and gene capture by hybridization), RiboTaxa revealed microbial novelties not seen by current bioinformatics analysis opening new biological perspectives in human and environmental health. In a study focused on corals’ health involving 20 metagenomic samples (4), an affiliation of prokaryotes was limited to the family level with Endozoicomonadaceae characterising healthy octocoral tissue. RiboTaxa highlighted 2 species of uncultured Endozoicomonas which were dominant in the healthy tissue. Both species belonged to a genus not yet described, opening new research perspectives on corals’ health. Applied to metagenomics data from a study on human gut and extreme longevity (5), RiboTaxa detected the presence of an uncultured archaeon in semi-supercentenarians (aged 105 to 109 years) highlighting an archaeal genus, not yet described, and 3 uncultured species belonging to the Enorma genus that could be species of interest participating in the longevity process. RiboTaxa is user-friendly, rapid, allowing microbiota structure description from any environment and the results can be easily interpreted. This software is freely available at https://github.com/oschakoory/RiboTaxa under the GNU Affero General Public License 3.0.

Keywords: metagenomics profiling, microbial diversity, SSU rRNA genes, full-length phylogenetic marker

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Authors: Aïcha Ben Salem, Faouzi Boufares, Sebastiao Correia

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The subject covered in this paper aims at assisting the user in its quality approach. The goal is to better extract, mix, interpret and reuse data. It deals with the semantic schema recognition of a data source. This enables the extraction of data semantics from all the available information, inculding the data and the metadata. Firstly, it consists of categorizing the data by assigning it to a category and possibly a sub-category, and secondly, of establishing relations between columns and possibly discovering the semantics of the manipulated data source. These links detected between columns offer a better understanding of the source and the alternatives for correcting data. This approach allows automatic detection of a large number of syntactic and semantic anomalies.

Keywords: schema recognition, semantic data profiling, meta-categorisation, semantic dependencies inter columns

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