Benjamin D. Greenbaum

Patterns of Evolution and Host Gene Mimicry in Influenza and Other RNA Viruses

It is well known that the dinucleotide CpG is under-represented in the genomic DNA of many vertebrates. This is commonly thought to be due to the methylation of cytosine residues in this dinucleotide and the corresponding high rate of deamination of 5-methycytosine, which lowers the frequency of this dinucleotide in DNA. Surprisingly, many single-stranded RNA viruses that replicate in these vertebrate hosts also have a very low presence of CpG dinucleotides in their genomes. Viruses are obligate intracellular parasites and the evolution of a virus is inexorably linked to the nature and fate of its host. One therefore expects that virus and host genomes should have common features. In this work, we compare evolutionary patterns in the genomes of ssRNA viruses and their hosts. In particular, we have analyzed dinucleotide patterns and found that the same patterns are pervasively over- or under-represented in many RNA viruses and their hosts suggesting that many RNA viruses evolve by mimicking some of the features of their hosts genes (DNA) and likely also their corresponding mRNAs. When a virus crosses a species barrier into a different host, the pressure to replicate, survive and adapt, leaves a footprint in dinucleotide frequencies. For instance, since human genes seem to be under higher pressure to eliminate CpG dinucleotide motifs than avian genes, this pressure might be reflected in the genomes of human viruses (DNA and RNA viruses) when compared to those of the same viruses replicating in avian hosts. To test this idea we have analyzed the evolution of the influenza virus since 1918. We find that the influenza A virus, which originated from an avian reservoir and has been replicating in humans over many generations, evolves in a direction strongly selected to reduce the frequency of CpG dinucleotides in its genome. Consistent with this observation, we find that the influenza B virus, which has spent much more time in the human population, has adapted to its human host and exhibits an extremely low CpG dinucleotide content. We believe that these observations directly show that the evolution of RNA viral genomes can be shaped by pressures observed in the host genome. As a possible explanation, we suggest that the strong selection pressures acting on these RNA viruses are most likely related to the innate immune response and to nucleotide motifs in the host DNA and RNAs.

Evolution and diversity in human herpes simplex virus genomes

ABSTRACT Herpes simplex virus 1 (HSV-1) causes a chronic, lifelong infection in >60% of adults. Multiple recent vaccine trials have failed, with viral diversity likely contributing to these failures. To understand HSV-1 diversity better, we comprehensively compared 20 newly sequenced viral genomes from China, Japan, Kenya, and South Korea with six previously sequenced genomes from the United States, Europe, and Japan. In this diverse collection of passaged strains, we found that one-fifth of the newly sequenced members share a gene deletion and one-third exhibit homopolymeric frameshift mutations (HFMs). Individual strains exhibit genotypic and potential phenotypic variation via HFMs, deletions, short sequence repeats, and single-nucleotide polymorphisms, although the protein sequence identity between strains exceeds 90% on average. In the first genome-scale analysis of positive selection in HSV-1, we found signs of selection in specific proteins and residues, including the fusion protein glycoprotein H. We also confirmed previous results suggesting that recombination has occurred with high frequency throughout the HSV-1 genome. Despite this, the HSV-1 strains analyzed clustered by geographic origin during whole-genome distance analysis. These data shed light on likely routes of HSV-1 adaptation to changing environments and will aid in the selection of vaccine antigens that are invariant worldwide.

Quantifying influenza virus diversity and transmission in humans.

Influenza A virus is characterized by high genetic diversity. However, most of what is known about influenza evolution has come from consensus sequences sampled at the epidemiological scale that only represent the dominant virus lineage within each infected host. Less is known about the extent of within-host virus diversity and what proportion of this diversity is transmitted between individuals. To characterize virus variants that achieve sustainable transmission in new hosts, we examined within-host virus genetic diversity in household donor-recipient pairs from the first wave of the 2009 H1N1 pandemic when seasonal H3N2 was co-circulating. Although the same variants were found in multiple members of the community, the relative frequencies of variants fluctuated, with patterns of genetic variation more similar within than between households. We estimated the effective population size of influenza A virus across donor-recipient pairs to be approximately 100–200 contributing members, which enabled the transmission of multiple lineages, including antigenic variants.

A neoantigen fitness model predicts tumour response to checkpoint blockade immunotherapy

Checkpoint blockade immunotherapies enable the host immune system to recognize and destroy tumour cells. Their clinical activity has been correlated with activated T-cell recognition of neoantigens, which are tumour-specific, mutated peptides presented on the surface of cancer cells. Here we present a fitness model for tumours based on immune interactions of neoantigens that predicts response to immunotherapy. Two main factors determine neoantigen fitness: the likelihood of neoantigen presentation by the major histocompatibility complex (MHC) and subsequent recognition by T cells. We estimate these components using the relative MHC binding affinity of each neoantigen to its wild type and a nonlinear dependence on sequence similarity of neoantigens to known antigens. To describe the evolution of a heterogeneous tumour, we evaluate its fitness as a weighted effect of dominant neoantigens in the subclones of the tumour. Our model predicts survival in anti-CTLA-4-treated patients with melanoma and anti-PD-1-treated patients with lung cancer. Importantly, low-fitness neoantigens identified by our method may be leveraged for developing novel immunotherapies. By using an immune fitness model to study immunotherapy, we reveal broad similarities between the evolution of tumours and rapidly evolving pathogens.

Patterns of Oligonucleotide Sequences in Viral and Host Cell RNA Identify Mediators of the Host Innate Immune System

The innate immune response provides a first line of defense against pathogens by targeting generic differential features that are present in foreign organisms but not in the host. These innate responses generate selection forces acting both in pathogens and hosts that further determine their co-evolution. Here we analyze the nucleic acid sequence fingerprints of these selection forces acting in parallel on both host innate immune genes and ssRNA viral genomes. We do this by identifying dinucleotide biases in the coding regions of innate immune response genes in plasmacytoid dendritic cells, and then use this signal to identify other significant host innate immune genes. The persistence of these biases in the orthologous groups of genes in humans and chickens is also examined. We then compare the significant motifs in highly expressed genes of the innate immune system to those in ssRNA viruses and study the evolution of these motifs in the H1N1 influenza genome. We argue that the significant under-represented motif pattern of CpG in an AU context - which is found in both the ssRNA viruses and innate genes, and has decreased throughout the history of H1N1 influenza replication in humans - is immunostimulatory and has been selected against during the co-evolution of viruses and host innate immune genes. This shows how differences in host immune biology can drive the evolution of viruses that jump into species with different immune priorities than the original host.

Viral reassortment as an information exchange between viral segments

Viruses have an extraordinary ability to diversify and evolve. For segmented viruses, reassortment can introduce drastic genomic and phenotypic changes by allowing a direct exchange of genetic material between coinfecting strains. For instance, multiple influenza pandemics were caused by reassortments of viruses typically found in separate hosts. What is unclear, however, are the underlying mechanisms driving these events and the level of intrinsic bias in the diversity of strains that emerge from coinfection. To address this problem, previous experiments looked for correlations between segments of strains that coinfect cells in vitro. Here, we present an information theory approach as the natural mathematical framework for this question. We study, for influenza and other segmented viruses, the extent to which a virus’s segments can communicate strain information across an infection and among one another. Our approach goes beyond previous association studies and quantifies how much the diversity of emerging strains is altered by patterns in reassortment, whether biases are consistent across multiple strains and cell types, and if significant information is shared among more than two segments. We apply our approach to a new experiment that examines reassortment patterns between the 2009 H1N1 pandemic and seasonal H1N1 strains, contextualizing its segmental information sharing by comparison with previously reported strain reassortments. We find evolutionary patterns across classes of experiments and previously unobserved higher-level structures. Finally, we show how this approach can be combined with virulence potentials to assess pandemic threats.

Oligonucleotide Motifs That Disappear during the Evolution of Influenza Virus in Humans Increase Alpha Interferon Secretion by Plasmacytoid Dendritic Cells

ABSTRACT CpG motifs in an A/U context have been preferentially eliminated from classical H1N1 influenza virus genomes during virus evolution in humans. The hypothesis of the current work is that CpG motifs in a uracil context represent sequence patterns with the capacity to induce an immune response, and the avoidance of this immunostimulatory signal is the reason for the observed preferential decline. To analyze the immunogenicity of these domains, we used plasmacytoid dendritic cells (pDCs). pDCs express pattern recognition receptors, including Toll-like receptor 7 (TLR7), which recognizes guanosine- and uridine-rich viral single-stranded RNA (ssRNA), including influenza virus ssRNA. The signaling through TLR7 results in the induction of inflammatory cytokines and type I interferon (IFN-I), an essential process for the induction of specific adaptive immune responses and for mounting a robust antiviral response mediated by IFN-α. Secretion of IFN-α is also linked to the activation of other immune cells, potentially amplifying the effect of an initial IFN-α secretion. We therefore also examined the role of IFN-α-driven activation of NK cells as another source of selective pressure on the viral genome. We found direct evidence that CpG RNA motifs in a U-rich context control pDC activation and IFN-α-driven activation of NK cells, likely through TLR7. These data provide a potential explanation for the loss of CpG motifs from avian influenza viruses as they adapt to mammalian hosts. The selective decrease of CpG motifs surrounded by U/A may be a viral strategy to avoid immune recognition, a strategy likely shared by highly expressed human immune genes.

Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy

HLA genotype affects response Immunotherapy works by activating the patients own immune system to fight cancer. For effective tumor killing, CD8+ T cells recognize tumor peptides presented by human leukocyte antigen class I (HLA-I) molecules. In humans, there are three major HLA-I genes (HLA-A, HLA-B, and HLA-C). Chowell et al. asked whether germline HLA-I genotype influences how T cells recognize tumor peptides and respond to checkpoint inhibitor immunotherapies (see the Perspective by Kvistborg and Yewdell). They examined more than 1500 patients and found that heterozygosity at HLA-I loci was associated with better survival than homozygosity for one or more HLA-I genes. Thus, specific HLA-I mutations could have implications for immune recognition and for the design of epitopes for cancer vaccines and immunotherapies. Science, this issue p. 582; see also p. 516 Human leukocyte antigen superfamilies predict immunotherapy response. CD8+ T cell–dependent killing of cancer cells requires efficient presentation of tumor antigens by human leukocyte antigen class I (HLA-I) molecules. However, the extent to which patient-specific HLA-I genotype influences response to anti–programmed cell death protein 1 or anti–cytotoxic T lymphocyte–associated protein 4 is currently unknown. We determined the HLA-I genotype of 1535 advanced cancer patients treated with immune checkpoint blockade (ICB). Maximal heterozygosity at HLA-I loci (“A,” “B,” and “C”) improved overall survival after ICB compared with patients who were homozygous for at least one HLA locus. In two independent melanoma cohorts, patients with the HLA-B44 supertype had extended survival, whereas the HLA-B62 supertype (including HLA-B*15:01) or somatic loss of heterozygosity at HLA-I was associated with poor outcome. Molecular dynamics simulations of HLA-B*15:01 revealed different elements that may impair CD8+ T cell recognition of neoantigens. Our results have important implications for predicting response to ICB and for the design of neoantigen-based therapeutic vaccines.

Dengue virus NS2B protein targets cGAS for degradation and prevents mitochondrial DNA sensing during infection

During the last few decades, the global incidence of dengue virus (DENV) has increased dramatically, and it is now endemic in more than 100 countries. To establish a productive infection in humans, DENV uses different strategies to inhibit or avoid the host innate immune system. Several DENV proteins have been shown to strategically target crucial components of the type I interferon system. Here, we report that the DENV NS2B protease cofactor targets the DNA sensor cyclic GMP-AMP synthase (cGAS) for lysosomal degradation to avoid the detection of mitochondrial DNA during infection. Such degradation subsequently results in the inhibition of type I interferon production in the infected cell. Our data demonstrate a mechanism by which cGAS senses cellular damage upon DENV infection.

Intrahost Dynamics of Antiviral Resistance in Influenza A Virus Reflect Complex Patterns of Segment Linkage, Reassortment, and Natural Selection

ABSTRACT Resistance following antiviral therapy is commonly observed in human influenza viruses. Although this evolutionary process is initiated within individual hosts, little is known about the pattern, dynamics, and drivers of antiviral resistance at this scale, including the role played by reassortment. In addition, the short duration of human influenza virus infections limits the available time window in which to examine intrahost evolution. Using single-molecule sequencing, we mapped, in detail, the mutational spectrum of an H3N2 influenza A virus population sampled from an immunocompromised patient who shed virus over a 21-month period. In this unique natural experiment, we were able to document the complex dynamics underlying the evolution of antiviral resistance. Individual resistance mutations appeared weeks before they became dominant, evolved independently on cocirculating lineages, led to a genome-wide reduction in genetic diversity through a selective sweep, and were placed into new combinations by reassortment. Notably, despite frequent reassortment, phylogenetic analysis also provided evidence for specific patterns of segment linkage, with a strong association between the hemagglutinin (HA)- and matrix (M)-encoding segments that matches that previously observed at the epidemiological scale. In sum, we were able to reveal, for the first time, the complex interaction between multiple evolutionary processes as they occur within an individual host. IMPORTANCE Understanding the evolutionary forces that shape the genetic diversity of influenza virus is crucial for predicting the emergence of drug-resistant strains but remains challenging because multiple processes occur concurrently. We characterized the evolution of antiviral resistance in a single persistent influenza virus infection, representing the first case in which reassortment and the complex patterns of drug resistance emergence and evolution have been determined within an individual host. Deep-sequence data from multiple time points revealed that the evolution of antiviral resistance reflects a combination of frequent mutation, natural selection, and a complex pattern of segment linkage and reassortment. In sum, these data show how immunocompromised hosts may help reveal the drivers of strain emergence. Understanding the evolutionary forces that shape the genetic diversity of influenza virus is crucial for predicting the emergence of drug-resistant strains but remains challenging because multiple processes occur concurrently. We characterized the evolution of antiviral resistance in a single persistent influenza virus infection, representing the first case in which reassortment and the complex patterns of drug resistance emergence and evolution have been determined within an individual host. Deep-sequence data from multiple time points revealed that the evolution of antiviral resistance reflects a combination of frequent mutation, natural selection, and a complex pattern of segment linkage and reassortment. In sum, these data show how immunocompromised hosts may help reveal the drivers of strain emergence.