Day :
- Computational Methodologies | Systems Biology | Metabolomics
Location: Athens
Chair
Tao Huang
Shanghai Institutes for Biological Sciences, China
Co-Chair
Andrea Ragusa
University of Salento, Italy
Session Introduction
Abdullah Basoglu
Selcuk University, Turkey
Title: Effects of boron supplementation on peripartum dairy cows’ health: A metabolomic approach
Time : 12:15-12:45
Biography:
Abdullah Basoglu, Prof.Dr has been working at Selcuk University, as an expert on NMR based matabolomics, boron metabolism and metabolic diseases seen in animals.He coordinated some proposals related to metabolomics at University of Florence, CERM in Italy.
Abstract:
Although many different dietary studies on the prevention of negative energy balance-related diseases are often encountered, this is the first study investigating the effects of boron supplementation on peripartum dairy cows’ health in the light of an omics approach. Twenty-eight healthy cows (1 control and 3 experimental groups) were enrolled from 2 months before predicted calving until 2 months after calving. Experimental groups were assigned to receive boron at increasing doses as an oral bolus. Production parameters, biochemical profile, Nuclear magnetic resonance-based metabolomics profile, and mRNA abundance of gluconeogenic enzymes and lipid oxidation genes were determined. Pivotal knowledge was obtained on boron distribution in the body. Production parameters and mRNA abundance of the genes were not affected by the treatments. Postpartum nonesterified fatty acids, β-hydroxybutyrate, and triglyceride concentrations were significantly decreased in experimentals. The primary differences among groups were in lipid-soluble metabolites. There were significant differences in metabolites including postpartum valine, β-hydroxybutyrate, polyunsaturated fatty acid and citrate, propionate, isobutyrate, choline metabolites (betaine, phosphatidylcholine, and sphingomyelin) and some types of fatty acids and cholesterol in experimentals. Boron appears to be effective in minimizing negative energy balance and improving health of postpartum dairy cows.
Alla Karnovsky
University of Michigan, USA
Title: Tools for data-driven network analysis of metabolomics data
Time : 12:45 - 13:15
Biography:
Alla Karnovsky pursued her PhD in Cell and Developmental Biology from the Russian Academy of Sciences, Russia. She did her Postdoctoral work at the University of Colorado Boulder, USA followed by nine years of bioinformatics work in pharmaceutical industry. Currently, she is a Research Assistant Professor of Computational Medicine and Bioinformatics at the University of Michigan, USA. Her research interests involve the analysis of high throughput omics data, focusing primarily on metabolomics, and the development of computational methods and tools for the analysis and integration of metabolomics data with other types of genomic data.
Abstract:
Metabolomics has established itself as a powerful platform to interrogate cellular biochemistry, identify novel biomarkers and provide insights into biochemical mechanisms of disease. As metabolomics data sets become increasingly large and complex, there is a growing need for data analysis and visualization tools to help interpret experimentally observed changes and put them into relevant biological context. A common approach to interpreting the results of metabolomics and lipidomics experiments is to map and visualize experimentally measured metabolites in the context of known biochemical pathways. Several tools for performing this type of analysis have been developed including our own tool Metscape. Some tools have adopted Functional Enrichment Testing methods developed for gene expression data for the analysis of metabolomics data. However, the scope of their application has been limited to known compounds from large, well-annotated pathways, which are often occupied by a small portion of the experimentally measured metabolome. An alternative to knowledge-based data analysis is to infer meaningful associations between metabolites/lipids from experimental data and build data-driven metabolic networks to help generate biological insights. We developed a new Differential Network Enrichment Analysis method (DNEA) that uses joint structural sparsity estimation to build partial correlation networks from the data (for two or more experimental conditions), performs consensus clustering to identify highly connected network components (subnetworks) and uses Network-based Gene Set Analysis (NetGSA) to identify the differentially enriched subnetworks. We will present the applications of DNEA for the analysis of metabolomics and lipidomics data and demonstrate that it allows identifying alterations in both network structure and expression levels of interacting biomolecules that impact disease phenotypes.
Break: Lunch Break 13:20-14:20 @ La Place AB
Yan Ji
Shanghai Institutes for Biological Sciences, China
Title: SR splicing, splicing-ratio based splicing detection method
Time : 14:20-14:50
Biography:
Yan Ji obtained his PhD Degree in Bioinformatics from Shanghai Institutes for Biological Science of the Chinese Academy of Sciences, P R China. Before May 2015, he worked as a Translational Researcher at the Innovation Center of China, AstraZeneca (a pharmaceutical company). Since June 2015, he has been an Assistant Professor in Shanghai Institutes for Biological Science of the Chinese Academy of Sciences, P R China and studied some tumour types which are prevalent in China by using high-throughput data analysis from different perspectives including splicing and long non-coding RNAs. He has published more than 8 papers in reputed journals. In this conference, he will present a novel method detecting splicing events which has been successfully used to discover PTEN-regulated splicing events.
Abstract:
Through alternative splicing, most human genes express multiple isoforms that often differ in function. To infer isoform regulation from high-throughput sequencing of cDNA fragments (RNA-seq), a pipeline is developed to detect differential alternative splicing events between RNA-Seq samples of treatment and control conditions. It is based on a metric defined as splicing ratio (SR) which was used in some splicing-related studies (SR Splicing is flexible to handle different types of study design. Either control group or treatment group can have single or replicated/pooled samples. It can analyze all major types
of alternative splicing patterns and use RNA-Seq reads and use RNA-Seq reads mapped to splice junctions. By comparing with other commonly used software, the performance of SR Splicing is evaluated from three aspects: sensitivity, accuracy, and validation. SR Splicing has comparable sensitivity and higher accuracy. Experimental validation using qRT-PCR (quantitative real time polymerase chain reaction) confirmed a selected set of splicing events that are significantly changed in Pten knock out data of the mouse MEF cell line, demonstrating the utility of the approach applied on experimental biological data sets.SR Splicing used different statistics and less filtering to return a list of significantly changed splicing events, with associated p values and false discovery corrections. It includes detailed information on the detected splicing differences such as which exon/ junctions are involved, alternative splice type (skipped exon, mutually exclusive exons, retained intron, alternative 5' splice site, and alternative 3' splice site), magnitude of difference, and coverage.
Maroun Bou Sleiman
Swiss Federal Institute of Technology in Lausanne, Switzerland
Title: Enabling discovery through multi-omics and systems genetics
Time : 14:50-15:20
Biography:
Maroun Bou Sleiman obtained his PhD in the Laboratories of Professor Bart Deplancke and Professor Bruno Lemaitre, working on the genetic and molecular bases of infection in the Drosophila Genetic Reference Panel. He is a Scientist in the Laboratory of Integrative Systems Physiology headed by Professor Johan Auwerx at the Swiss Federal Institute of Technology (EPFL) in Lausanne (Switzerland). He works at the frontier between genetics, systems biology, and multi-omics in order to understand complex traits and diseases in different panels such as the BXD, HDP, and ITP in mice, as well as Caenorhabditis elegans RIAILs (recombinant inbred advanced intercross lines). These systems genetics approaches pave the way for a better mechanistic understanding of complex biological systems and pave the way for mechanistically-informed precision medicine.
Abstract:
Our laboratory is using systems approaches to map the signaling networks that govern mitochondrial function and as such regulate organismal metabolism in health, aging and disease. We apply a state-of-the-art biological toolkit to study a variety of model systems, ranging from the plant Arabidopsis thaliana, over the nematode Caenorhabditis elegans, to the mouse and all the way to humans. Our research has not only allowed the development of new methodologies and scientific approaches applied to population, as exemplified by the development of cross-species multi-layered genetics/omics gene mapping strategies, but also contributed to improved understanding of how signaling pathways control mitochondrial function and metabolism. Although our research addresses basic biomedical questions, we aim at translating our research into novel preventive and therapeutic strategies for common diseases, such as type 2 diabetes, frailty, and obesity, as well as rare inherited mitochondrial diseases. The translational value of our work is testified by the fact that several drugs targeting processes and pathways which we elucidated are currently used in the clinic.
Ryohei Eguchi
Nara Institute of Science and Technology, Japan
Title: Classification of biosynthesis pathways of alkaloids using graph convolutional neural networks
Time : 15:20-15:50
Biography:
Ryohei Eguchi obtained his Doctor’s Degree in Engineering at the Graduate School of Information Science of Nara Institute of Science and Technology, Japan
(2018) and in the same year joined the institute as a Doctoral Researcher at the Data Driven Science Creation Center. He is involved in the research on gene expression analysis and metabolic pathway prediction of secondary metabolites by applying multivariate analysis and machine learning techniques, mainly in the
field of bioinformatics and chemoinformatics.
Abstract:
Secondary metabolites are defined as a group of natural compounds that are not directly involved in growth, development or reproduction of organisms. The term ‘secondary’ in the context of metabolic pathways, was introduced in 1891. The functions of secondary metabolites are related to their prevalent potent biomolecular activity acquired in evolution process involving pest and pathogen defense, UV-B-sunscreens etc. The classification of secondary metabolites taking chemical structure and metabolic pathway into consideration could provide important clues to activities of metabolites which lead to interpretation of function acquisition mechanisms of secondary metabolites in evolutional process. And, various chemical descriptors such like molecular fingerprints have been long discussed to represent biochemical features, in order to embed molecular structures into a numerical space and quantify their activities. However, it is still difficult to predict bioactivities from molecular structures since it depends on the choices of those chemical descriptors. Recently, machine learning methods based on Graph Convolutional Neural Networks (GCNN) have been proposed that can automatically optimize a model for molecular feature extraction from the given training sets. This study introduces an application of GCNN to predict metabolic pathways of alkaloids, namely, one of the largest family of secondary metabolites in plants. The author trained and tested GCNN model on 578 alkaloid compounds and the mean accuracy of 20 runs with random sampling is about 94% (Number of epoch: 200). It is greatly expected that it will lead to an understanding of the evolution of metabolic system unique to organisms.
Break: Networking & Refreshments 15:50-16:10 @ Europa Foyer
- Metabolomics in Drug Discovery | Cancer Metabolomics | Transcriptomics and Proteomics
Location: Athens
Chair
Philip J Jackson
University of Sheffield, UK
Co-Chair
Eloiza H Tajara
University of São Paulo, Brazil
Session Introduction
William Hidalgo
Industrial University of Santander, Colombia
Title: Transcriptomic and metabolic analysis of the plant hormones signalling pathways in the resistant “Calcutta 4†and susceptible “Williams†banana genotypes during the interaction with the pathogenic fungus Pseudocercospora fijiensis
Time : 12:35-13:05
Biography:
William Hidalgo pursued Master of Science Degree in Biotechnology from National University of Colombia (Colombia). He is a Chemist from University of Nariño (Colombia); Doctor in Natural Science from Friedrich Schiller University Jena (Germany). Since March 2017, he joined the Industrial University of Santander (Bucaramanga, Colombia) as an Assistant Lecturer and Researcher in the Chemistry School. His scientific background is focused on the study of plant chemical defenses especially in the biological system “Musa-Mycosphaerella fijiensis” (causing the Black Sigatoka Disease in Banana plants), biosynthesis of natural products (by using 13C-tracer) and metabolomics studies by using NMR and MS spectrometry techniques. He has participated in several international conferences organized mainly by the International Society of Chemical Ecology and Latin American Association of Chemical Ecology, with a scientific contribution of ten international publications.
Abstract:
Statement of the Problem: Bananas (Musa spp.) represent one of the most important crops throughout the world. Black Sigatoka disease (BSD), caused by the ascomycete fungus Pseudocercospora fijiensis, is still one of the main phytosanitary problems facing the crop.
Methodology: In order to understand the physiological mechanism behind the plant defences in Musa during the interaction with P. fijiensis, a transcriptomic and metabolomic analysis were led with two Musa genotypes differing in their resistance to the BSD development: The susceptible genotype “Williams” and the resistant genotype “Calcutta 4”. RNA-seq with Illumina technology, Nuclear Magnetic Resonance and Mass Spectrometry were the analytical techniques used for sample analysis.
Findings: The results clearly showed a fast and early plant response in the resistant genotype “Calcutta 4”, mainly with the induction of a group of genes and metabolites involved in pathogen recognition, hormonal signal transduction and pathogenesis-related proteins whereas a poor induction of those physiological responses were detected in the susceptible genotype “Williams”.
Conclusion & Significance: Our results support new insights about the role of JA-Et signalling pathways play in the response of
the resistant banana genotype Calcutta 4 during the pathogen attack. Furthermore, it opens the possibility to explore whether
these defence mechanism reported here are similar for other resistant Musa genotypes.
Philip J Jackson
University of Sheffield, UK
Title: Proteomic adaptation in high and low light ecotypes of the marine picocyanobacterium Prochlorococcus marinus, an important global primary producer
Time : 13:05-13:35
Biography:
Philip J Jackson obtained his PhD in Biochemistry from the University of Leeds, UK where his research is centered on the control of ATP synthesis in mitochondria.His subsequent postdoctoral positions, also in Leeds, involved the characterization of potential glycoprotein tumour biomarkers and the structural analysis of several membrane-intrinsic proteins including a proton-translocating ATPase. He then joined an instrumentation manufacturer as a product application specialist in proteomics and lipidomics. In 2010, he returned to Postdoctoral research to work in the Laboratories of Professors Neil Hunter, FRS and Mark Dickman at the University of Sheffield (UK). He specializes in biological mass spectrometry, applying this technology to (1) quantitative proteomics of complexes involved in light harvesting and energy transfer in photosynthesis, (2) analysis of protein-protein interactions within complexes that direct photosystem assembly and (3) structural characterization of the enzyme systems responsible for chlorophyll biosynthesis.
Abstract:
Prochlorococcus marinus, an oceanic phototrophic picocyanobacterium, is probably the most abundant organism on earth with an estimated population of 2.9±0.1 x 1027 cells. Consequently it is an important global primary producer responsible for the fixation of 4.0 x 106 tonnes of carbon per annum. In terms of habitat, Prochlorococcus has been recovered from diverse locations at depths down to 200 m. Given the wide distribution of Prochlorococcus within the euphotic zone, genetically distinct ecotypes have evolved in response to the level of sunlight penetration and nutrient availability. The four examples used for this study were: (1) MED4 (Mediterranean 5 m), (2) NATL2A (N. Atlantic 10 m), (3) SS120 (Sargasso 120 m) and (4) MIT9313 (Gulf Stream 135 m). Cells were grown under very low intensity illumination, similar to that experienced by the deep water ecotypes. After isolating thylakoid membranes, proteins were extracted, digested with endoproteinase Lys-C and trypsin, then analyzed by nanoLC-MS/MS. Identified proteins were quantified by the label-free iBAQ method which was validated by the expected PSI:PSII ratio of 3-4 for Synechocystis as determined by spectroscopy. The Prochlorococcus ecotypes showed markedly different PSI:PSII ratios to Synechocystis: near to 1:1 in MED4 and MIT9313, and 0.5 in NATL2A and SS120. Therefore there appears not to be a simple relationship between PSI:PSII ratio and illumination. On the other hand, amounts of high light inducible proteins (HLIPs), associated with photoprotection, and the relative amounts of light dependent and independent POR enzymes, occurring in the chlorophyll biosynthesis pathway did reflect the expected habitat illumination levels in the Prochlorococcus ecotypes and Synechocystis. As the Prochlorococcus ecotypes were grown under the same low light intensity, the expression patterns observed in this study appear to be an inherent feature of ecotypic adaptation to light intensity within their specific habitats.
Break: Lunch Break 13:35-14:35 @ La Place AB
Masahiro Onuma
Trisguide CO.,LTD, Japan
Title: Electronic water can reduce oxidative stress in cancer and diabetes patients for 3 weeks drinking
Time : 14:35-15:05
Biography:
Masahiro Onuma pursued his Bachelors in Biochemistry from Tokyo University of Agriculture and Technology. He is the President of TriSGuide Ltd. He has expertise in oxidative disease prevention to use non-medical product based on GSK’s experience of allopurinol which is the strongest anti-oxidant in this world.
Abstract:
Oxidative stress means a state where there is an imbalance between the oxidizing action and the reducing action due to reactive oxygen species (ROS) in a living body, resulting in the oxidizing action becoming dominant. Oxidative stress arises as the balance between production and removal is disrupted through excessive production of ROS and impairment of the antioxidant system. Oxidative stress has been reported to be involved in the onset and progress of various diseases. Characteristics of Type 2 diabetes are insulin secretion failure and insulin resistance, but it seems that oxidative stress is greatly involved in insulin secretion failure. In the insulin secretion-inducing β cells of Langerhans islets in the pancreas, the amount of superoxide dismutase (SOD), which is representative of the ROS elimination system, is small and resistance to oxidative stress is considered to be weak. Regarding cancer, it is well known that chronic inflammatory conditions increase the risk of carcinogenesis. Cells
such as neutrophils and macrophages are activated in the inflammation area leading to increase in production of active oxygen and nitric oxide. These free radicals cause DNA mutation and cell proliferation thereby promoting cancer development. When chronic inflammation is present, cancer develops more easily. Electronic water, which was developed to generate electron in water, was consumed for three weeks, after meals, between meals and before sleeping 6 times a day, and according to the test subjects' possible time periods. The amount of drinking water was 750-1000 mL, and BAP and d-ROMs checks for all cases were carried out at 4:30 pm. The results of cancer patients and diabetes patients were seen as attached. As a result, the d-ROMs value in the degree of oxidative stress has reduced, and the BAP value, which is an indicator of plasma antioxidant capacity, has improved
significantly.
Halina Malina
Axanton Technology GmbH, Switzerland
Title: Elimination the chemically modified proteins from the cell membranes prevents the cell degeneration
Time : 15:05-15:35
Biography:
Halina Malina pursued her PhD in antibiotic biosynthesis working at the Medical School of Lodz (Poland). She is a Chemical Engineer from Polytechnic of Lodz, Lodz. Since 1984, she worked at the Institute of Chemistry of Natural Substances (CNRS), with collaboration with Pasteur Institute of Paris (France). In 1990 she worked as project leader in CNRS University in Zurich. She discovered the IDO in the eye and the role of xanthurenic acid in the cataract development. She followed the research on xanthurenic acid-induced cell pathology at universities in Lausanne, and Bern and ETH. Her research on the chemical mechanism of the diseases with aging met a strong opposition of the academia healing the transgenic mice. All support for research was rejected in 2004. She continued on her own and established the technology curing the infection and the aging-associated pathology.
Abstract:
Statement of the Problem: Most young people are healthy, and with aging, they develop the degenerative diseases. In the last thirty years, it was thought that the disorders in aging are genetic and cannot be prevented. We present here the proof of concept that the aging-associated diseases are not genetic, but develops because of the chemically modified proteins. The discovery leads to effective prevention of the cell degeneration in aging and infection permitting to keep people healthy longer and improving the quality of life.
Methodology & Theoretical Orientation: The peptides corresponding to the intrinsically disordered sequences were synthesized in vitro and incubated with xanthurenic acid to obtain the covalently modified polymers observed on the SDSPAGE (patents). The polymers were injected into rabbits. The IgG's were isolated and tested in the primary cell cultures, in vivo in mice (outsourcing) and human, directly used by the investigator for her dermatitis and the metabolic disorder.
Findings: In a primary cell culture Xan led to the cell death caused by the covalently modified proteins. The regulatory sequences of the proteins, called intrinsically disordered sequences (IDSeqs) are preferentially modified. Any cell system cannot remove the chemically modified and polymerized IDSeqs. They alter the cell membranes leading to the caspases activation and cell degeneration.The author established a new technology targeting the chemically modified proteins. In mice, the molecule establishing membranes (MEMS) healed the Staphylococcus aureus and restored immunity in cyclophosphamide-treated mice using MEMS A-144 at five micrograms, weekly, on the mouth mucosa cured skin infection and cardiovascular disorder.
Conclusion & Significance: The chemically modified proteins must be eliminated to restore the cell homeostasis. MEMS stops the upstream cause of the pathology in infection or aging.
Vivek Kamath
Heal The World, India
Title: Case study of insulin dependent diabetes: Healing without medicines
Time : 15:35-16:05
Biography:
Vivek Kamath is the founder of heal the world organization is a Reiki Master, Mexican Healer, Melchizedek Healer, Crystal Healer, and Past Life Regression Therapy Expert. He has healed many diabetic patients (Type1, Type2, Type 3/1.5/LADA) without any medicines. He has also healed Cancer (stage 4) blood pressure (both high and low blood pressure), heart disease (removed the heart blockages), removed kidney stones, ovarian cysts, fibrosis of the breast, fatty liver, lungs disease, cured sinusitis, severe joint pain, lumbar L5 spinal disk pain, Sciatica pain, neck pain, constipation, rheumatoid arthritis, glaucoma, migraines, headaches, insomnia, stomach related problem, IBS, diabetic gum problems, skin problems( dry skin, eczema) and chronic nasal allergies, nasal blockages without any medicines. Some of the above treatments have been completed within a week to maximum 1-month duration.
Abstract:
As most of us are aware Type 2 diabetes can be controlled and cured completely with the diet, workouts (yoga), effective stress management and other healing methods. Testimonial of one of my patient aged 70 years, male suffering from diabetes from more than 12 years and took 3 insulin doses per day. He has completed Reiki Master Degree through some Reiki Master in India. He came to be with the problem that he is not able to feel the energy while doing his self healing. Moreover, he was suffering major health problems like (Insulin dependent diabetes for nearly 12 years, insomnia, constipation, stomach heaviness, etc.). I gave him Reiki Level 1 attunement a month back. On 25th July he has taken his random glucose reading. The random glucose level was 575 mg/dl. On July 27th I have given him Usui Reiki Level 2, 3 Attunement, Karuna Reiki Attunement and Mexican Healing attunement (Guru Poornima Day). Immediately after the attunement we checked his random glucose level it came down to 383 mg/Dl. After 1 Mexican Healing: On 28th July evening, I conducted Mexican healing training class to my patient along with others. I took his random glucose level before giving him Mexican healing and it was 344 mg/Dl. After 1 Mexican healing his glucose came down to 260 mg/Dl. All the people who attended the training class were astonished with the power of Mexican healing. To summarize in 3 days, using attunement (Reiki and Mexican attunement) and with 1 Mexican healing, his glucose level came down from 575 mg/dL to 260 mg/DL. What is the percentage in drop down? 54.8%. Is possible to bring this much of level down in 3 days without taking insulin? Please note that there is no change in his food/diet or workouts. Also note the difference between the readings after attunement and after healing. We are all made up of energy and it flows though the energy centers (chakra). We can’t necessarily see energy, but we can feel the energy. When our energy centers becomes weak, diseases related to corresponding energy centers will pop up. For Diabetes, there is energy center called “Solar Plexus” (Also called as Manipura Chakra). All diabetic patients will have low energy in their solar plexus energy. If you energize this energy center you will see the drastic reduction in your glucose level. You do not need to go for a pancreas transplant or tablets/insulin to treat your diabetes. It is all in the energy. Learn from your Reiki master or healers to energize all your weaker organs or energy centers.
Break: Networking & Refreshments 16:05-16:25 @ Europa Foyer