Health for Animals and the World Veterinary Association
launched the first annual
World Animal Vaccination Day on 20 April 2016.
The International Livestock Research Institute (ILRI) takes pleasure
in celebrating this day this year by offering
a ‘virtual workshop’ on the new and exciting tools
ushering in a new era in vaccine development.
20 April 2018
is
World Animal Vaccination Day
On 22 May 2016, a workshop on ‘Vaccines for Tropical Diseases’ was conducted before a meeting on New Approaches to Vaccines for Human and Veterinary Tropical Diseases was held 23–26 May 2016 in Cape Town, South Africa, organized by Keystone Symposia on Molecular and Cellular Biology.
The goal of the workshop was to provide background on content that would be presented in the four-day Keystone Symposium that followed, the intent being to bring participants up to speed on concepts presented at the symposium.
Vish Nene, one of the scientific organizers of the conference and a co-leader of the Animal and Human Health program at the International Livestock Research Institute (ILRI), headquartered in Nairobi, Kenya, gave a particularly lucid talk at the pre-meeting workshop on Novel tools and genomics approaches supporting vaccine development.
The following is a transcript of Nene’s talk, lightly edited for clarity and brevity. You can watch a high-quality video of Nene’s 32-minute presentation, made possible by the Bill & Melinda Gates Foundation, here.
Vish Nene’s pre-Keystone Symposium vaccine workshop
When setting up this session, Keystone asked me to supply them with two papers that could be sent to you for reading material before you got here.
I sent you two papers, one by Alessandro Sette and Rino Rappuoli on reverse vaccinology (Reverse vaccinology: Developing vaccines in the era of genomics, Immunity, Oct 2010] and the other by Helder Nakaya and Bali Pulendran on systems vaccinology (Vaccinology in the era of high-throughput biology, Philosophical Transactions of the Royal Society B: Biological Sciences, Jun 2015). These two papers will be the primary focus of our discussion today. I’m going to go over those two papers with you so that you can understand these technologies a little bit more. We’re fortunate in that both Rappuoli and Pulendran are speakers at this symposium.
This is an exciting time in the field of vaccine development, particularly due to three tools that allow us to do three main things. The first tool allows us to monitor responses to infection and immunization—not just infection but immunization as well. Second, we have an incredible array now of methods for identifying candidate vaccine antigens. Third, there is increasing understanding of how to improve the efficacy of many vaccines by redesigning vaccine antigens and antigen delivery systems—be they viral vectored or live attenuated bacterial—as well as the efficacy of vaccine adjuvants.
These two papers have played a key role in broadening understanding of immunity and vaccine development approaches.
It’s startling that, in principle, employing the reverse vaccinology approach requires you to have zero knowledge of immunology or immune response to infection. While this may be threatening to immunologists, the more immunology you do know, the more essential it becomes, particularly when you’re moving away from proof of concept towards vaccine development. The systems vaccinology approach is developing deeper molecular understanding of diseases and the processes that protect against them and using that information to understand what contributes to pathology, what contributes to immunity and, more importantly perhaps, why a vaccine doesn’t work as expected and using that information to guide successful vaccine development.
These two approaches are setting new paradigms in vaccine development and accelerating the rate of that development. The common features of both these approaches are that they rely on whole-genome sequence data, they rely on high-throughput methods and they’re discovery driven—you don’t know what you’re going to get in return. It can be difficult to tell somebody who wants to know what you’re going to find ‘I don’t really know’. But I hope you’ll be convinced today that these technologies are important to embrace and to take forward in this exciting new era of vaccine development.
Among the many technologies that have advanced this whole endeavor of vaccine development, clearly the leading ones are the new methodologies for sequencing DNA, RNA and protein, glycomics (which has led to huge progress in understanding carbohydrate structures), metabolomics, immunology, bioinformatics, nano-technology, computational biology, structural biology (crystallography), microbiomes, the ability to make large DNA molecules (we’ve always been able to make oligonucleotides but we can now synthesize kilobase pairs of DNA), genome editing, and a favourite technology that I’ve got involved with recently, which is high-density protein/peptide chips.
The baseline data for all of this is whole-genome sequence information, be that of the pathogens, of the vector (e.g. mosquito, tick, snail) or of their hosts (human, mouse or other animal). These have all depended on cheaper computational power—you can now do things on your laptop computer that once required a whole computer server. And we have access to amazing connections and information through the World Wide Web. We have particularly good access to data on model organisms—mouse, yeast, bacteria—or C. elegans if you’re in the worm field.
So there’s rich information out there that you can use, but that also raises a common problem. We tend to believe computer data, so if we see something on the World Wide Web or if our computer program predicts something, we tend to believe it. My advice is, don’t. Don’t believe information until you experimentally verify it yourself or somebody else has done that or a really well-defined model system was used to garner it. I see this problem particularly in students who undertake bioinformatics courses and come up with a variety of fantastic new findings that turn out to be artefacts of the system.
Reverse vaccinology
As you know, the fashionable area of reverse vaccinology is generating big hype. But what has been the success? Well, this is one success. This is a vaccine called Bexsero. It’s a first vaccine to be produced using reverse vaccinology. It’s a vaccine that’s been developed for meningococcal group B disease. The vaccine depends on priming an antibody response that’s surprisingly efficient.
It’s been very difficult to develop a meningococcal group B vaccine because most of the antibody response goes towards carbohydrates. Think about what’s been done in the past in vaccine development work—let’s call this the ‘forward approach’. You take the immune responses, whether from your animal model or from humans who’ve experienced that infection, and you ask the question, ‘What antigens do they identify?, and you work on the assumption that those antigens play a role in immunity and you take that forward. Well, that didn’t work in the case of meningococcal group B.
With the forward approach, you identify only a few antigens rather than looking at the whole range of potential antigens. Look at the genome sequence of a bacterium—E. coli, for example, encodes 4,000 proteins. That’s a lot! But while pathogens express a lot of proteins, you find very few using the conventional forward approach. Using reverse vaccinology, the developers of the meningococcal group B vaccine started with the genome sequence of the pathogen that causes the disease, used bioinformatics to identify candidate antigens, used high-throughput methods to express about 600 genes, immunized mice, made antibodies in mice to those antigens and asked the question ‘Did those antibodies play a role in killing the bacteria?’ That work reduced the number of genes of interest down to about 90 and they finally homed in on about four or five genes, which went forward to make up the vaccine. The advantage of using reverse vaccinology is that you can screen so many of the pathogen’s antigens. In this particular case, that meant only protein antigens—missing all the meningococcal-specific carbohydrates. So while this approach is very good, it did have its limitations in this case. But this approach is now being used to tackle a whole series of other bacterial infections.
Schematic diagram summarizing the pathway of vaccine development starting from reverse vaccinology, from a paper by Sette and Rappuoli, Reverse vaccinology: Developing vaccines in the era of genomics, published in Immunity, Oct 2010.
In addition to the antibody work, the reverse vaccinology paper also discussed T-cell work. Here I’ve pulled out some T-cell work that we’ve been involved with at ILRI in developing a pipeline for identifying pathogen antigens recognized by the CD8 T cells of the host animal. We’re particularly interested in CD8 T cells at ILRI because they play a role in immunity against a deadly disease of cattle called East Coast fever. We developed this pipeline for identifying these antigens, again starting out with whole-genome sequence information, predicting candidate antigens, cloning these, then going into a cell-mediated assay that allowed us to identify candidate antigens, and then making synthetic peptides, because as you well know, T cells see peptides rather than whole antigen and recognize the peptides in association either with class I or class II major histocompatibility (MHC) molecules.
The reverse vaccinology paper looked at whether the approach could be used to simplify the identification of CD8 T cells. The answer is ‘yes’. Each MHC molecule will bind a range of peptides that exhibit a motif. So as soon as the peptides conform to a motif, you can develop algorithms to predict them in a computational manner. We’ve been developing a whole bunch of new types of immunological assays at ILRI, including peptide-tetramers, because they didn’t exist for the bovine. Part of the problem in working to develop livestock vaccines is that we have to develop our own reagents. Nobody does them for you. You can’t go to a company and buy these reagents. This affects our ability to develop livestock vaccines but we are working to catch up to the human and mouse communities.
This figure shows you the generation of peptide tetramers that allows us to do peptide binding assays and also to screen antigen-specific T cell responses. And this shows one example of where the algorithm told us that the epitope sequence we were working with was wrong, although it worked in the ELISpot data, it didn’t work in the peptide binding assay. The algorithm predicted that we needed to be working with a shorter peptide. That shorter peptide bound to the MHC and that also now is reflected when we stain CD8 T cells with tetramers—you can see that the shorter peptide works whereas the longer one doesn’t.
So, algorithms do have value. They can help guide your research but, again, you have to experimentally verify them.
The last slide that I want to show you regarding antigen discovery is in the area of contagious bovine pleuropneumonia (CBPP),an infectious disease of cattle caused by Mycoplasma mycoides mycoides bacteria. While genetics is extremely powerful—if you can genetically modify something, you can learn a lot in return—there is no genetics for the bacterium that causes CBPP. But some of my previous colleagues have been working up synthetic genomics approaches towards synthesizing whole bacterial genomes. They started with Mycoplasma because it has the smallest known genome size. You can resynthesize this bacterial genome. And what’s quite remarkable is that if you put a yeast origin of replication in that genome you can actually maintain that in yeast. If you do that, you can now use yeast genetics to manipulate the bacterial genome. You can recover the mutated bacterial genome, transplant it into a recipient cell, use a selection mechanism that kicks out the resident bacterial genome and the incoming genome now reprograms that cell, and you reconstitute your mutant.
This kind of mind-blowing stuff is now becoming routine. You can keep your bacterial mutants in yeast and you can reconstitute your bacteria when you want to by transforming those bacterial genomes back into the bacterial cell. Unfortunately, this has only been worked out so far for Mycoplasma. Eventually, obviously, it would be great to be able to do this with other bacterial species as well.
What we’ve done here—this is work done by the Mycoplasma group at ILRI led by Joerg Jores, one of my ILRI colleagues—is to knock out the gene that codes for the carbohydrate envelop of the Mycobacterium. As shown in this assay, when you knock out the carbohydrate structure, the cells become a lot leakier, as you can see by the diffuse staining. When we put this mutant Mycoplasma into goat, the strain is apathogenic. We haven’t yet tested to see whether this might work as a vaccine but that is clearly our next step. Sanjay Vashee, from the J. Craig Venter Institute, is going to be giving a talk on this subject. This Venter team is now making not only synthetic bacterial genomes but also synthetic viral genomes, so you can now mix and match viral genomes for use in viral-vectored vaccines. They’ve been working with herpes viruses and CMV (Cytomegalovirus) in particular.
Systems vaccinology
Switching now to the systems vaccinology approach, as this figure from the paper shows, this approach starts out by considering the humans that you’re vaccinating. High-resolution mass spectrometry is used to see what happens to individuals, including mass cytometry (CyTOF), metabolomics (what happens to metabolites in these humans), proteomics (what happens to the protein population), high-throughput sequencing (RNA-seq, expression-linked to the RNA-seq, and then getting down to the single-cell level). While we have been able to view activities either at the tissue or the cell population level, we want to know what individual cells are doing. For example, we’ve got many different kinds of immune cells: Are they all doing the same job or something different? Can we identify what that difference is at the level of the single cell and then integrate all that information back together.
Systems vaccinology framework revisited. eQTL, expression quantitative trait loci; RNA-seq, whole transcriptome shotgun sequencing; siRNA, small interfering RNA; CRISPR, clustered regularly interspaced short palindromic repeats. From a paper by Nakaya and Pulendran, Vaccinology in the era of high-throughput biology, published in the Philosophical Transactions of the Royal Society B: Biological Sciences, Jun 2015.
About why the microbiome should be of interest in vaccine development, consider the number of microbes that live in an individual—apparently, we’re outnumbered 10 to 1 (so are you a human or are you a microbe?) Our immune system has to learn to live with all these microbes and vice versa. It’s therefore inevitable that our microbial composition is going to influence us, in terms of both our health and disease. There is newer appreciation of the microbiome today and new technologies that are allowing us to investigate how our microbes influence our pre-immunization status and vaccine intake and efficacy.
All of this information gets integrated into databases. You need clever people with computer algorithms to do data modelling to integrate all of that information and come up with biomarkers either of protection or of immunogenicity. This is a figure taken out of one of the earlier papers of Bali Pulendran’s lab. At both individual and population levels, the idea is to assess what is common to many vaccines, even vaccines against different pathogens, and what is different among them. With this information, you can start developing signatures, in terms of B or T cells or innate immunity. These signatures then can serve as markers indicating whether a person will prove immune to a pathogen or be susceptible to disease. You can see that we’re moving away from a concept of ‘one size fits all’—that is, if you have a headache, you just take Panadol. The cause of your headache may be different from that of other’s. There is no one solution.
Let’s drill down a bit into the B cells and T cells. B cells make antibodies, T cells target intracellular pathogens. The beauty about this now is that we know that the specificity of these are dependent on the B-cell receptors and T-cell receptors. And we can sequence those. We can make a database of these receptor gene sequences, match sequence to function and identify correlates of immunity. These receptors can also be used as diagnostic assays. In the cancer field now, for example, the T-cell receptor repertoire is being used as diagnostic markers of whether cancer therapies are working or not in patients. Some patients get an overwhelming representation of one type of clonal response in either their B or T cells and you can follow those diagnostically post-treatment. This is now being used in clinical studies.
At ILRI, we’re going down this road as well. As I said, sequencing at the level of the single cell as well as population is becoming important. Various laboratories as well as companies are now beginning to offer this as a service. So even if you don’t do this work yourself, you can contract it out. And note that if you’re working in a clinic or a lab, you’re the person with the interesting samples! Sequencing is now becoming a commodity. You can send this stuff away and get sequences in return. There’s a company that’s developed sequencing of both antibody pairs and PCR T-cell receptor genes from humans and mice. This allows you, at the other end, to do all the interesting work. You can do clustering analysis to discover what are the major responses, shown here in green, and what are the minor responses, shown in blue, and then match function to these sequences. We’re now working with this company on single cell bovine work. We’ve had a few hitches—we work in Africa where we have foot-and-mouth disease and so we can’t send samples to the US, where this work is being done—and so we’re trying to find ways to resolve that.
This basically is the way things are going: Once you have sequenced data, you can make recombinant antibodies and answer the question, ‘What is their function?’
Let’s go back to the Nakaya and Pulendran figure. When you have your biomarkers for protection or immunogenicity, you can now start to test or validate that in your human or animal population. If you’re fortunate in having a mouse model, you have incredible resources available to you because you can manipulate the mouse genome in a variety of ways—there are ‘knock-ins’ and ‘knock-outs’, you can do ‘interference RNA’ experiments. And then there’s the big business of ‘genome editing’, which is really taking off (I wouldn’t be surprised if these guys get a Nobel Prize). Genome editing allows you to do site-specific manipulation, and not just at one site but at multiple sites in an individual organism, be it in protozoa or mammals. This technology has utterly transformed our ability to manipulate genomes.
Systems vaccinology is forcing us away from the narrow view of vaccinology we used to have; it is making us look at vaccinology holistically. Systems vaccinology is extremely multidisciplinary, as you can see. You need to have loads (and loads and loads) of different types of expertise coming together to undertake these approaches. (A lot of engineering, for example, has gone into developing these methods.)
I encourage you during your three days here to make contacts with people, to build up your networks, to explore these types of approaches. If in your work you don’t have a hypothesis or you don’t know what the next step is or you don’t understand what is going on, these types of approaches will often allow you to determine what your next steps should be.
We’ve said the business of vaccines and genomics is multidisciplinary and ‘large’ data driven. But there’s nothing wrong with the conventional approaches to vaccine development. They’ve worked fine and they still work and there’s a lot to be said for empirical approaches. If you use empirical approaches and you learn from them, fantastic. And when empirical approaches fail, you can integrate all sorts of other methods to understand why.
The genomics approaches we’re discussing here are thus additional ways to tackle vaccine development. There’s an overlap between the conventional and genomics approaches. Neither are exclusive. But particularly for the most difficult vaccine problems—we still don’t have a vaccine for HIV 30 years down the road, or for malaria or other devastating animal as well as human diseases—these new technologies are giving us hope that we will be able to tackle these, too.
Both the new reverse and systems vaccinology approaches identify antigens and delivery systems that I think can be taken forward. What we’ve talked about here—discovery-driven early-stage research—gets us as far as proof of concept in human and veterinary vaccine development. What’s still left, of course, is the important work of commercializing vaccines. This can be even more complex in nature than the experimental work because the commercial work is largely in the hands of people who had nothing to do with the science of developing the experimental vaccine, and these people have to address a wealth of regulatory issues, of ‘what if’ issues. I was working at The Institute for Genomic Research (TIGR), in the USA, about 16 years ago when the Bexsero vaccine researchers identified the antigens needed to go into the vaccine. It took them another 10 years just to go through the regulatory hoops before they could get the product out onto the market.
So while the early phase of vaccine development work is critical, we have to pay equal attention to what comes after proof of concept—and that’s a very different ballgame. It’s much easier for veterinary research than for medical because you develop all your data in the animal of interest: you’re not having to apply things you learned from a mouse or monkey model to humans.
A main objective of this workshop and symposium is to further build the African continent’s capacity to take on discovery-driven vaccine research. There’s been a lot of clinical research on the continent, but not many products have come out of Africa that were developed in Africa and that have gone into clinical trials.
We hope this symposium stimulates you, as developing-country scientists working in Africa, to develop these discovery-driven vaccine programs yourselves. We want to build a broad base of vaccine-related research on this continent—able to move research from knowledge discovery to experimental products to commercial vaccines.
For more information, please contact Vish Nene at v.nene [at] cigar.org or visit ILRI’s Animal and Human Health program: https://www.ilri.org/ahh
About the Keystone meeting
Keystone Symposia on Molecular and Cellular Biology is a non-profit organization convening open, peer-reviewed conferences that connect the scientific community and accelerate life science discovery. The May 2016 vaccine symposium in Cape Town was part of the Keystone Symposia Global Health Series, which is supported by the Bill & Melinda Gates Foundation and Robert Bosch Stiftung GmbH.
Human and livestock vaccines contribute greatly to improving human health, welfare and incomes in developing countries. This Keystone Symposia meeting aimed to stimulate crosstalk between Africa’s human and veterinary vaccine communities by highlighting cross-cutting technical advances and new science and knowledge from laboratory and field research. The meeting provided a rare opportunity for scientists from North and South to pool resources and knowledge in the common fight against tropical diseases.
Excerpts (excluding references) from one of the two main papers cited:
From Alessandro Sette and Rino Rappuoli, Reverse vaccinology: Developing vaccines in the era of genomics, Immunity, Oct 2010
Abstract
‘The sequence of microbial genomes made all potential antigens of each pathogen available for vaccine development. This increased by orders of magnitude potential vaccine targets in bacteria, parasites, and large viruses and revealed virtually all their CD4+ and CD8+ T cell epitopes. The genomic information was first used for the development of a vaccine against serogroup B meningococcus, and it is now being used for several other bacterial vaccines. In this review, we will first summarize the impact that genome sequencing has had on vaccine development, and then we will analyze how the genomic information can help further our understanding of immunity to infection or vaccination and lead to the design of better vaccines by diving into the world of T cell immunity.
From Pasteur to Reverse Vaccinology
‘Vaccination is a medical practice of ancient origin that possibly started somewhere in Asia using materials from smallpox lesions to transmit a mild infection and thereby protect against more serious disease. The practice was formally introduced into Western medicine in 1796 by Edward Jenner, who used infected materials isolated from cows (vacca in Latin) to immunize against smallpox and introduced the terminology “vaccine”. A century later, when it was discovered that infections are caused by microbes, Louis Pasteur started the rational development of vaccines and established the basic rules of vaccinology. Pasteur proposed that in order to make a vaccine, one should “isolate, inactivate and inject the microorganism” that causes the disease. Pasteur’s rules were followed for a century by vaccine developers . . . . The vaccines developed using Pasteur’s rules became powerful tools in the history of medicine and, in less than a century, led to the elimination of some of the most devastating infectious diseases globally.
‘At the end of the 20th century, most of the vaccines that could be developed by these traditional technologies had been developed, and new technologies were required to conquer the remaining pathogens. Remarkable progress was made during this period by the introduction of new technologies such as recombinant DNA and chemical conjugation of proteins to polysaccharides, as well as advances in the use of novel adjuvants.
Additionally, a powerful tool came from the ability to access the genomes of microorganisms, a new technology that become available in 1995 when Craig Venter published the genome of the first free living organism. This technological revolution allowed for the first time the capacity to move beyond the rules of Pasteur, using the computer to rationally design vaccines starting with information present in the genome, without the need to grow the specific microorganisms. This new approach was denominated “reverse vaccinology”.
‘The first pathogen addressed by the reverse vaccinology approach was Meningococcus B (MenB), a pathogen that causes 50% of the meningococcal meningitis worldwide. . . . Reverse vaccinology has [now] been applied to many other bacterial pathogens. . . .
In conclusion, reverse vaccinology uses the entire protein repertoire of each pathogen to select the best candidate vaccine antigens. This allows the development of vaccines that were previously difficult or impossible to make and can lead to the discovery of unique antigens that may improve existing vaccines. . . .
Reverse Vaccinology and Cellular Immunity
‘As discussed above, reverse vaccinology relies on the combined use of immunological and genomic information to identify relevant protein antigens for diagnostic or vaccine purposes. In this context, the identification of the epitopes recognized by CD4+ T cell or CD8+ T cells can be utilized in “reverse” as a tool to identify new antigens. . . .
Future Trends: Further Technology Development and Integration with Bioinformatics, Genomics, Proteomics, and Systems Biology
‘The outlook for reverse vaccinology is bright. A growing number of studies demonstrate that the technical and conceptual advances of recent years have enabled tackling large and complex pathogens . . . .
‘An important development is the growing availability of bioinformatic resources that store and organize both immune reactivity data and pathogen data. This is particularly key as the amount of data escalate, both regarding immune recognition and genomic transcriptomic and proteomic information for various pathogens. . . .
‘In conclusion, it is easy to predict in the following years an ever-growing widespread application of reverse vaccinology to infectious diseases in an integrated fashion. . . . The lessons learned, and the technologies developed, will also be applicable to other diseases where strategies to either induce or control cellular immune responses are of potential clinical benefit, such as in autoimmunity and cancer.’
Excerpts (excluding references) from one of the two main papers cited:
From Helder Nakaya and Bali Pulendran, Vaccinology in the era of high-throughput biology, Philosophical Transactions of the Royal Society B, Jun 2015.
‘Vaccination has been tremendously successful saving lives and preventing infections. However, the development of vaccines against global pandemics such as HIV, malaria and tuberculosis has been obstructed by several challenges. A major challenge is the lack of knowledge about the correlates and mechanisms of protective immunity. Recent advances in the application of systems biological approaches to analyse immune responses to vaccination in humans are beginning to yield new insights about mechanisms of vaccine immunity, and to define molecular signatures, induced rapidly after vaccination, that correlate with and predict vaccine induced immunity. Here, we review these advances and discuss the potential of this systems vaccinology approach in defining novel correlates of protection in clinical trials, and in infection-induced “experimental challenge models” in humans.
1. Introduction
‘Vaccination has saved hundreds of millions of lives, and has had spectacular success in eliminating smallpox and in greatly reducing the burden of infections such as yellow fever, diphtheria, meningitis and measles. Despite this impressive record, the development of vaccines against global pandemics such as HIV, TB, malaria and dengue is faced with major challenges. Among the major scientific challenges are the difficulties in identifying the relevant antigens that can be incorporated into a vaccine. A second major challenge is in defining the quality of the immune response that confers protection against infection, and in determining the mechanisms by which the immune system mounts the protective response. The latter is crucial for evaluating which immunological parameters are stimulated by vaccination (i.e. correlates of immunogenicity), or are associated with protection against subsequent infection, as determined in clinical trials (i.e. correlates of protection). The final challenge is to devise strategies to induce protective immunity that is long lasting.
Recent developments in the field of systems biology offer the tools to analyse the dynamics and interactions of all components of a biological system during vaccination. These systems-level analyses are beginning to define the molecular correlates (“signatures”) of immunity and protection, and are yielding new insights into the mechanisms by which vaccines induce protective immunity. Here, we review these advances and their promise in enabling the development of vaccines against unmet medical needs.
2. Assessing the complexity of immune responses through systems vaccinology
‘The human immune system consists of an intricate network of specialized cells and organs. Vaccination or infection triggers a complex cascade of biological events, which if successful, culminates in the establishment of protective immunity and immunological memory against the pathogen. A powerful way to comprehensively dissect this complexity of immune responses is through the systems vaccinology approach. This approach possesses the same essential elements of systems biology, which are (i) monitoring all components of the system in response to perturbations, (ii) integration of data from multiple types and (iii) creation of mathematical models to predict the structure and behaviour of the informational system. Moreover, it requires the testing and validation of novel hypotheses and insights that may arise from it.
‘The first step in the systems vaccinology approach is to perturb the immune system, and vaccines offer an excellent means to perturb the human immune system. . . . The next step is to use large-scale techniques for molecular profiling of tissues and cells from human vaccinees. . . . The third step is to generate mathematical models from the molecular snapshots of cells and tissues that explain or predict the structure and behaviour of the system being perturbed. . . .
‘[W]e and others have been using these iterative cycles of perturbations and high-throughput biology to investigate the molecular signatures induced by a broad range of vaccines (including yellow fever, influenza, meningococcal, adenovirus, shingles, pneumococcal, malaria, tularaemia, rotavirus), with a view to identifying signatures of protective immunity and delineating the molecular mechanisms of vaccine immunity. . . .
‘Although the analysis of multi-omics experiments holds great promises for achieving higher biological knowledge, it also poses a tremendous challenge for computational biologists. . . . With the concomitant decrease in costs and the increase in power, sensitivity and specificity of “omics” technologies, combined with new approaches and genome editing, relatively small laboratories will soon be able to generate massive amount of data. Several databases and tools are already available to, respectively, store and analyse “single omics” data, but very few computational programs and models exist to truly integrate more than one type of “omics” data. More importantly, bioinformaticians will need to work very closely with immunology experts in order to transform high-throughput analyses into concrete knowledge, and ultimately, understanding.
3. Recent tools and developments
‘Biological processes are carried out in a modular manner, where sets of molecules (e.g. RNA transcripts and proteins) work together to achieve specific functions. These molecules interact with each other functionally or physically and are often coordinately expressed within the cell. Therefore, systems analyses should focus on subtle changes in the networks formed by these interacting molecules rather than on small numbers of highly differentially expressed genes. . . .
Dedicated databases and user-friendly web tools will soon become essential for immunologists and computational biologists to manage, integrate and analyse high-throughput data. . . .
4. Biological insights emerging from systems vaccinology
‘An integral part of systems vaccinology is the development and testing of new insights and the generation of data-driven hypotheses. To achieve this, computational scientists must work closely with immunologists, and both teams should be able to comprehend and to communicate with each other effectively. . . .
5. Ongoing studies and future directions
‘. . . [E]xciting advances highlight the potential of systems biology to transform vaccine design and development. Using systems approaches to identify molecular signatures that can be used to predict vaccine efficacy in clinical trials will greatly accelerate the testing of vaccines. Furthermore, the novel biological insights provided by such studies will greatly enhance our understanding of the mechanisms underlying vaccine immunity and, immune regulation in general.’
ILRI news 