Dear all participants, thank you for signing up to this MOOC course on Metagenomics applied to surveillance of pathogens and antimicrobial resistance. I'm here today with my colleague, Anna Sofia, and we're going to make this introduction lecture for the course. My name is Tine Hald, I'm a professor at the Division of Genomic Epidemiology at the National Food Institute at the Technical University of Denmark. Sofia why don't you say a few words about yourself too. Yes. Hello everyone, my name is Sofia Duarte. I'm an assistant professor at the same group in division with Tine, also at the Technical University of Denmark, and I'm very glad to be presenting the first lecture of this course to you. So, welcome and now I will give the floor to Tine. Thank you Sofia. I will start by presenting the course objectives. With this course, we hope to give you the theoretical background on metagenomics sequencing and application. Also we want to show you how you can use freely available bioinformatic tools for metagenomic data. Of course we'll also want to show you how you can use metagenomics for surveillance and what the potentials are for using metagenomics in surveillance of pathogens and antimicrobial resistance. Of learner background, as you probably already read, we expect you to have some background in basic epidemiology in order to be able to follow these lectures. Also some knowledge about microbial communities and bacterial genetics and we restated equivalent to a bachelor level. Yes. This MOOC is focused on using metagenomics for surveillance. So, first maybe we want to define surveillance. Surveillance has been defined by many international organizations but basically it's all about the same. So, here I took the one from the World Health Organization how they defined surveillance. Here they wrote that the surveillance is the continuous, systematic collection, analysis and interpretation of health-related data needed for the planning, implementation, and evaluation of public health practice. A good surveillance system should be able to detect emergent trends, so it should be a kind of an early warning system. It should also be able to document any interventions, or the effect of an intervention that has been implemented. Then of course to monitor and clarify the epidemiology of health problems, so it can also be used to for instance identify risk factors and set priorities for giving guidelines or regulations for preventing public health issues. For a vision for a future effective of an efficient system to survey both pathogens and antimicrobial resistance, we really like to have real-time global data collected on the occurrence of all infectious agents. That sounds really ambitious but that is something that could potentially be the future. This of course require real-time sampling and also real-time data sharing. Such a system should also automatically detect clusters related in time and space, so we can find out if there's a potential outbreak going on of specific pathogen. Such a system should also be able to detect clusters or trends in species and also genes, that could for instance be particular violence genes that we are interesting in following or particular antimicrobial resistance genes. Then such a system should also have the ability, so we can rapidly compare results collected from different parts of the world of different regions. This of course require that we have a central and easy accessible repository or a database and that we can easily transfer data between different sectors and different levels of access in such a database. Now, we have a vision that metagenomics might actually be able to do that, maybe not tomorrow but in the future. Why is that? Well, first of all, metagenomic is a method that takes all. It's based on detecting RNA or DNA from microbial organisms. So, it's a kind of a common or universal language that we can use. Metagenomics are also culture-independent because you do direct sequencing on a sample. This means that we are skipping the culturing step making it more real-time than if you have a culture step in between. Metagenomic data can also be shared electronically in a standardized format which is also very useful for a real-time data sharing system. Metagenomics can also potentially be used to survey large population for many pathogens at the same time. For instance, by taking suite samples from urban environments. Metagenomic sequencing has actually also been shown to be superior to conventional genomic and also other genomic methods for instance for quantification of antimicrobial resistance genes, antimicrobial resistance in general, but also for detecting certain pathogens for instance Campylobacter. The vision kind of a little more filed in the future is that by combining metagenomic surveillance with global sampling and then some advanced mathematical modeling and epidemiological data, we might actually be able to predict development of infectious diseases in the future and how they will spread. We believe that this could actually be the next you could say research frontier within this area. So, why don't you just get started digging into this exciting topic by initiating this course and with this, I will give the word back to Sofia that will tell you about the content of the course and what you can expect. Thank you. Thank you Tine for this nice introduction to the topic. So, as Tine said, I will now introduce you to the content of the course. In this course, we try to follow the workflow of a metagenomics project. Of course you could add some steps in between. You could make it more or less detailed. We chose to follow this one. We tried to cover with our program. Each and every step of this workflow. We organize the course in three modules. The first module is mostly theoretical and it's called from sampling to sequencing, but actually it covers from the very first step of the study design until you obtain your sequences. Then module B is called from reads to results, and it covers the bioinformatics analysis of you read to your sequences. Finally, module C is the one more targeted at its subject of surveillance because it deals with the interpretation of your reads and epidemiological analysis of your reads together with explanatory variables. A little bit about assessment. Just a side note. You will notice that there are, in almost every lecture, in-video quizzes. Keep in mind these are not for assessment. So, they are not graded. They are just for the sake of keeping you engaged in the lecture but also to consolidate some of the messages, the most important messages in the video that we want to convey. Now, the real assessment is organized in module quizzes and one overall final quiz. The module quizzes there's one or more for each module, and they follow a case study that we defined in module A. We present to you a case study with the background of a surveillance problem, and then some of the questions will be based on that case study. Other questions are just theoretical about which you have just learned in the lectures. The case study questions will be based on you interpreting certain reports that we will provide to you in this specific module. This can be reports of the bioinformatics analysis of the data, the quality control of your reads, or the count matrix analysis, for example. Then in the final quiz, we consider that during the module quizzes, you will practice to do the work that is done throughout the workflow of such a project, and then in final quiz, you'll have the extra challenge of having actually hands-on work on a similar case study, a different one but similarly structured. Then you do the work yourself. So, you produce the reports that you will need to interpret in order to reply to the questions of this final quiz. Don't worry, we will guide you through every step you will need, for example, for the final quiz to install what is called the virtual machine. We will give a detailed tutorial on how to do this. You need to install it and set it up. This virtual machine works like a separate independent computer working inside of your own computer. This is because some of the tools you need to use might be challenging to install and set up. So we've done all that for you, and you have everything inside of this virtual machine ready to use. So after installing the virtual machine, you will need to set up a shared folder between your own computer and this virtual machine. It is a folder where all your reports, all your results from your exercises will be stored inside of the virtual machine, but they will be shared with your own computer. So, once you close the virtual machine and you're not working in it anymore, you still have access to all your reports, your results in your own computer in this shared folder. All the exercises in the final quiz can be run from within the virtual machine with the tools that we provide you there, and we will give you, as I said, detailed instructions on which tools you need to use and where to find them. Then, as I already said, your results will be available in the shared folder which is called "Vboxshare." So if you have any questions at all, if you have any feedback about the course, about the quizzes, about two lectures, anything at all, it is very welcome from our side. So, please communicate it. Use the discussion forums with other learners with the tutors and explore Coursera's possibilities to communicate with us into say what you think. We will try to be on track and reply as soon as possible to questions you might have, but also use the learners community to help each other. This is how many MOOCS work, and it has been demonstrated that it's actually a good system. Finally, I would like to say a few words about two projects that have made this course possible. The course was developed under the umbrella of European project called EFFORT. EFFORT stands for Ecology from Farm to Fork Of microbial drug Resistance and Transmission. You can learn more about it in the project's website. Here you will find all the members of the consortium. We are distributed among ten different European countries, and it's a project that is mostly focused on evaluating the occurrence in transmission of antimicrobial resistance genes from animals to humans using metagenomics data. Even though this was the project under which we developed the course, it has the participation of many participants or members of the Compare Project which is also a large consortium project. International, it is broader than EFFORT. It is also focused on metagenomics data and surveillance, in general, how to establish real-time global surveillance using sequencing data in an open access environment. If you want to learn more about Compare, you can also visit the project's website. So this was all from me for now in this initial lecture. Both Tine, and I, and all the tutors in this course hope you will enjoy it. So, welcome.
