Researchers believe that pathogens are evolving to evade detection from the human immune system. I recently co-published a paper that discussed research into the ongoing evolutionary struggle between the immune system and pathogens. In this study, we sought to identify possible commonalities in HLA (opens in new tab) (human leukocyte antigen) binding preferences that would reveal patterns of optimization of this component of the immune system in response to the variation in pathogens.
I worked with post-doctoral student Tomer Hertz (now with Fred Hutchinson Cancer Research Lab) and a distinguished group of colleagues from the Institute for Immunology and Infectious Diseases, Royal Perth Hospital, and Murdoch University (Western Australia); the School of Anatomy and Human Biology, Centre for Forensic Science, University of Western Australia (Western Australia); and Fundacion Ciencia para la Vida (Chile).
Microsoft Research Blog
Microsoft Research Forum Episode 3: Globally inclusive and equitable AI, new use cases for AI, and more
In the latest episode of Microsoft Research Forum, researchers explored the importance of globally inclusive and equitable AI, shared updates on AutoGen and MatterGen, presented novel use cases for AI, including industrial applications and the potential of multimodal models to improve assistive technologies.
Our paper, “Mapping the Landscape of Host-Pathogen Coevolution: HLA Class I Binding and Its Relationship with Evolutionary Conservation in Human and Viral Proteins,” appeared in the American Society for Microbiology’s Journal of Virology (opens in new tab) in February 2011. I’d like to share some highlights from the study with you.
Identifying Possible Commonalities in HLA Binding Preference
The majority of the cells in our bodies express something called HLA molecules, whose role is to sample cellular proteins and present them on the cellular surface for external surveillance by the specialized cells of our immune systems. This action forces all cells to reveal imprints of their inner workings.
When something out of the ordinary is detected—for example, the presence of an unusual mutation or a gene expression—the type and quality of the presented samples can spur the immune system’s specialized killer cells into action. By sending kill signals to “odd” cells, the immune system can stop diseases such as cancer or viral infections. (Viruses bring their own genetic material to the cell and use the cellular resources to propagate.)
However, this scrutiny of the immune system creates evolutionary pressure on viruses, which often mutate to evade detection. Since the system of HLA molecules is highly selective in its sampling of protein segments, the mutational patterns in viruses are not entirely random: mutations tend to occur within the segments that HLA molecules are most likely to present.
On the other hand, over many generations, the distribution of thousands of HLA variants present in human populations may change. Additionally, in different geographic regions, we find significant variation in frequencies of different HLA molecules. This sets up an evolutionary game between the viruses on the one side and our immune systems on the other.
Targeting Efficiency
In order to analyze the results of the evolutionary processes that are driven by the interaction of HLA molecules with a wide diversity of viral intruders, we quantified the HLA binding preferences by using a novel measure called “targeting efficiency.”
Targeting efficiency entails capturing the correlation between HLA-peptide binding affinities with the genetic conservation in the targeted proteomic regions. If HLA molecules possessed such targeting efficiency, this would (presumably) prove beneficial to humans. In theory, HLA molecules would draw attention to protein segments that are shared across related viral species as functionally important and thus immutable sections of their proteins. Individual invading viruses would find it more difficult to evade surveillance by mutating, because mutation within these segments would ruin the protein function. Targeting efficiency could even allow the immune system to generalize across related viral species.
Our analysis of targeting efficiencies for 95 HLA Class I alleles (opens in new tab) over thousands of human proteins and 52 human viruses indicate that HLA molecules do indeed prefer to target conserved regions in these proteomes! However, the arboviral Flaviviridae (for example, Dengue virus) proved a notable exception in which non-conserved regions were the preferred target of most alleles.
HLA molecules are encoded in three separate parts of the human genome: A, B, and C. During our study, we discovered that the oldest versions of our HLA molecules—namely the HLA-A alleles and several HLA-B alleles that had maintained a close sequence identity with chimpanzee homologues—were targeting conserved human proteins and DNA viruses (for example, Herpesviridae and Adenoviridae) most efficiently.
By contrast, the HLA-B alleles were targeting RNA viruses (opens in new tab) efficiently. This is reminiscent of predator-prey patterns that have been identified in evolutionary theory. For example, we know the following factors to be true:
- The different HLA families can evolve separately because they are encoded separately.
- The different HLA families can act on the same targets in the same cells.
Based on this information, we can extrapolate that evolution is going to drive their binding properties in different directions, thus splitting their targets, as in the established Lotka-Volterra (opens in new tab) (predator-prey) model of different types of foxes and rabbits inhabiting the same forest. In addition, we identified various patterns of host/pathogen specialization that are consistent with co-evolutionary selection and were also functionally relevant in specific cases. For example, preferential HLA targeting of conserved proteomic regions is associated with improved outcomes in HIV infections as well as protection against Dengue Hemorrhagic Fever.
I have just scratched the surface of the study in this blog. For complete study details, including a complete presentation of our methodology and findings, please follow the links below.
Learn More
- Study abstract (opens in new tab)
- Complete published paper (PDF format) (opens in new tab)
- Supplemental material (opens in new tab)
- Microsoft Research Connections (opens in new tab)
—Nebojsa Jojic, Principal Researcher, Microsoft Research eScience Group