Biology subjects

Bloom, J. D.

Publications and source records attributed to Bloom, J. D..

At least 109 records · Page 6Linked to original sources

bioRxiv2019

Identification of HIV-1 Envelope Mutations that Enhance Entry Using Macaque CD4 and CCR5

Although Rhesus macaques are an important animal model for HIV-1 vaccine development research, most transmitted HIV-1 strains replicate poorly in macaque cells. A major genetic determinant of this species-specific restriction is a non-synonymous mutation in macaque CD4 that results in reduced HIV-1 Envelope (Env)-mediated viral entry compared to human CD4. Recent research efforts employing either laboratory evolution or structure-guided design strategies have uncovered several mutations in Envs gp120 subunit that enhance binding of macaque CD4 by transmitted/founder HIV-1 viruses. In order to identify additional Env mutations that promote infection of macaque cells, we utilized deep mutational scanning to screen thousands of Env point mutants for those that enhance HIV-1 entry via macaque receptors. We identified many uncharacterized amino acid mutations in the N-terminal heptad repeat (NHR) and C-terminal heptad repeat (CHR) regions of gp41 that increased entry into cells bearing macaque receptors by up to 38-fold. Many of these mutations also modestly increased infection of cells bearing human CD4 and CCR5 (up to 13-fold). NHR/CHR mutations identified by deep mutational scanning that enhanced entry also increased sensitivity to neutralizing antibodies targeting the MPER epitope, and to inactivation by cold-incubation, suggesting that they promote sampling of an intermediate trimer conformation between closed and receptor bound states. Identification of this set of mutations can inform future macaque model studies, and also further our understanding of the relationship between Env structure and function. ImportanceAlthough Rhesus macaques are the favored non-human primate animal model used in HIV-1 research, most circulating HIV-1 strains poorly infect macaque cells. Studies using macaques to model HIV-1 infection often use evolved, or mutant HIV-1 variants that are able to utilize macaque CD4, but these HIV-1 variants poorly model infection by circulating strains. In this work, we sought to identity HIV-1 mutations that would allow entry into macaque cells, but that would maintain critical characteristics of circulating HIV-1 strains. We employed a powerful experimental method to simultaneously assess the effects of thousands of individual HIV-1 mutations on infection of cells bearing macaque receptors. We identified many previously uncharacterized mutations that enhance infection of circulating HIV-1 strains into cells bearing macaque receptors by up to 38-fold. Identification of these mutations may be of use in future macaque model studies.

microbiology↗

bioRxiv2019

alignparse: A Python package for parsing complex features from high-throughput long-read sequencing

Summary & PurposeAdvances in sequencing technology have made it possible to generate large numbers of long, high-accuracy sequencing reads. For instance, the new PacBio Sequel platform can generate hundreds of thousands of high-quality circular consensus sequences in a single run (Rhoads and F. 2015; Hebert et al. 2018). Good programs exist for aligning these reads for genome assembly (Chaisson and Tesler 2012; Li 2018). However, these long reads can also be used for other purposes, such as sequencing PCR amplicons that contain various features of interest. For instance, PacBio circular consensus sequences have been used to identify the mutations in influenza viruses in single cells (Russell et al. 2019), or to link barcodes to gene mutants in deep mutational scanning (Matreyek et al. 2018). For such applications, the alignment of the sequences to the targets may be fairly trivial, but it is not trivial to then parse specific features of interest (such as mutations, unique molecular identifiers, cell barcodes, and flanking sequences) from these alignments. Here we describe alignparse, a Python package for parsing complex sets of features from long sequences that map to known targets. Specifically, it allows the user to provide complex target sequences in Genbank format that contain an arbitrary number of user-defined sub-sequence features. It then aligns the sequencing reads to these targets and filters alignments based on whether the user-specified features are present with the desired identities (which can be set to different thresholds for different features). Finally, it parses out the sequences, mutations, and/or accuracy of these features as specified by the user. The flexibility of this package therefore fulfills the need for a tool to extract and analyze complex sets of features in large numbers of long sequencing reads.

bioinformatics↗

bioRxiv2019

Linking influenza virus evolution within and between human hosts

Influenza viruses rapidly diversify within individual human infections. Several recent studies have deep-sequenced clinical influenza infections to identify viral variation within hosts, but it remains unclear how within-host mutations fare in the global viral population. Here, we compare viral variation within and between hosts to link influenzas evolutionary dynamics across scales. Synonymous sites evolve at similar rates at both scales, indicating that global evolution at these putatively neutral sites results from the accumulation of within-host variation. However, nonsynonymous mutations are depleted in global viral populations compared to within hosts, suggesting that selection purges many of the protein-altering changes that arise within hosts. The exception is at antigenic sites, where selection detectably favors nonsynonymous mutations at the global scale, but not within hosts. These results suggest that selection against deleterious mutations and selection for antigenic change are the main forces that transform influenzas within-host genetic variation into global evolution.

evolutionary biology↗

bioRxiv2019

When Two are Better than One: Modeling the Mechanisms of Antibody Mixtures

It is difficult to predict how antibodies will behave when mixed together, even after each has been independently characterized. Here, we present a statistical mechanical model for the activity of antibody mixtures that accounts for whether pairs of antibodies bind to distinct or overlapping epitopes. This model requires measuring n individual antibodies and their [Formula] pairwise interactions to predict the 2n potential combinations. We apply this model to epidermal growth factor receptor (EGFR) antibodies and find that the activity of antibody mixtures can be predicted without positing synergy at the molecular level. In addition, we demonstrate how the model can be used in reverse, where straightforward experiments measuring the activity of antibody mixtures can be used to infer the molecular interactions between antibodies. Lastly, we generalize this model to analyze engineered multidomain antibodies, where components of different antibodies are tethered together to form novel amalgams, and characterize how well it predicts recently designed influenza antibodies. Author summaryWith the rise of new antibody combinations in therapeutic regimens, it is important to understand how antibodies work together as well as individually. Here, we investigate the specific case of monoclonal antibodies targeting a cancer-causing receptor or the influenza virus and develop a statistical mechanical framework that predicts the effectiveness of a mixture of antibodies. The power of this model lies in its ability to make a large number of predictions based on a limited amount of data. For example, once 10 antibodies have been individually characterized and their epitopes have been mapped, our model can predict how any of the 210 = 1024 combinations will behave. This predictive power can aid therapeutic efforts by assessing which combinations of antibodies will elicit the most effective response.

biophysics↗

bioRxiv2019

Deep mutational scanning comprehensively maps how Zika envelope protein mutations affect viral growth and antibody escape

Functional constraints on viral proteins are often assessed by examining sequence conservation among natural strains, but this approach is relatively ineffective for Zika virus because all known sequences are highly similar. Here we take an alternative approach to map functional constraints on Zika viruss envelope (E) protein by using deep mutational scanning to measure how all amino-acid mutations to the protein affect viral growth in cell culture. The resulting sequence-function map is consistent with existing knowledge about E protein structure and function, but also provides insight into mutation-level constraints in many regions of the protein that have not been well characterized in prior functional work. In addition, we extend our approach to completely map how mutations affect viral neutralization by two monoclonal antibodies, thereby precisely defining their functional epitopes. Overall, our study provides a valuable resource for understanding the effects of mutations to this important viral protein, and also offers a roadmap for future work to map functional and antigenic selection to Zika virus at high resolution.\n\nImportanceZika virus has recently been shown to be associated with severe birth defects. The viruss E protein mediates its ability to infect cells, and is also the primary target of the antibodies that are elicited by natural infection and vaccines that are being developed against the virus. Therefore, determining the effects of mutations to this protein is important for understanding its function, its susceptibility to vaccine-mediated immunity, and its potential for future evolution. We completely mapped how amino-acid mutations to E protein affected the viruss ability to grow in cells in the lab and escape from several antibodies. The resulting maps relate changes in the E proteins sequence to changes in viral function, and therefore provide a valuable complement to existing maps of the physical structure of the protein.

microbiology↗

bioRxiv2019

Identification of antibodies targeting the H3N2 hemagglutinin receptor binding site following vaccination of humans

Antibodies targeting the receptor binding site (RBS) of the influenza virus hemagglutinin (HA) protein are usually not broadly-reactive because their footprints are typically large and extend to nearby variable HA residues. Here, we identified several human H3N2 HA RBS-targeting monoclonal antibodies (mAbs) that were sensitive to substitutions in conventional antigenic sites and were not broadly-reactive. However, we also identified one H3N2 HA RBS-targeting mAb that was exceptionally broadly reactive despite being sensitive to substitutions in residues outside of the RBS. We determined that similar antibodies are present at measurable levels in the sera of some individuals but that they are inefficiently elicited by conventional vaccines. Our data indicate that some HA RBS-targeting antibodies can be surprisingly effective against variable viral strains even if they are somewhat sensitive to substitutions in HA residues adjacent to the RBS.

microbiology↗

bioRxiv2019

Mapping person-to-person variation in viral mutations that escape polyclonal serum targeting influenza hemagglutinin

A longstanding question is how influenza evolves to escape human immunity, which is polyclonal and can target many distinct epitopes on the virus. Here we map how all amino-acid mutations to influenzas major surface protein affect viral neutralization by polyclonal human sera. The serum of some individuals is so focused that it selects single mutations that reduce viral neutralization by over an order of magnitude. However, different viral mutations escape the sera of different individuals. This individual-to-individual variation in viral escape mutations is not present among ferrets, which are frequently used as a model in influenza studies. Our results show how different single mutations help influenza escape the immunity of different members of the human population, a phenomenon that could shape viral evolution and disease susceptibility.

microbiology↗

bioRxiv2019

Comprehensive mapping of avian influenza polymerase adaptation to the human host

Viruses like influenza are infamous for their ability to adapt to new hosts. Retrospective studies of natural zoonoses and passaging in the lab have identified a modest number of host-adaptive mutations. However, it is unclear if these mutations represent all ways that influenza can adapt to a new host. Here we take a prospective approach to this question by completely mapping amino-acid mutations to the avian influenza virus polymerase protein PB2 that enhance growth in human cells. We identify numerous previously uncharacterized human-adaptive mutations. These mutations cluster on PB2s surface, highlighting potential interfaces with host factors. Some previously uncharacterized adaptive mutations occur in avian-to-human transmission of H7N9 influenza, showing their importance for natural virus evolution. But other adaptive mutations do not occur in nature because they are inaccessible via single-nucleotide mutations. Overall, our work shows how selection at key molecular surfaces combines with evolutionary accessibility to shape viral host adaptation.

microbiology↗

bioRxiv2018

Massively parallel profiling of HIV-1 resistance to the fusion inhibitor enfuvirtide

Resistance to enfuvirtide, the only clinically approved HIV-1 entry inhibitor, has primarily been mapped to the binding site in the N-terminal heptad repeat (NHR) of the Env transmembrane domain and a limited number of allosteric sites. To better delineate the genotypic determinants of resistance, we used deep mutational scanning to quantify how all mutations to HIV-1 Env affect enfuvirtide sensitivity. We identified numerous additional resistance mutations in the NHR and other regions of Env, including the co-receptor binding site. This complete map of resistance sheds light on the diverse mechanisms of enfuvirtide resistance and can inform clinical monitoring of patients.

microbiology↗

bioRxiv2018

Single-cell virus sequencing of influenza infections that trigger innate immunity

The outcome of viral infection is extremely heterogeneous, with infected cells only sometimes activating innate immunity. Here we develop a new approach to assess how the genetic variation inherent in viral populations contributes to this heterogeneity. We do this by determining both the transcriptome and full-length sequences of all viral genes in single influenza-infected cells. Most cells are infected by virions with defects such as amino-acid mutations, internal deletions, or failure to express a gene. We identify instances of each type of defect that increase the likelihood that a cell activates an innate-immune response. However, immune activation remains stochastic in cells infected by virions with these defects, and sometimes occurs even when a cell is infected by a virion that expresses unmutated copies of all genes. Our work shows that viral genetic variation substantially contributes to but does not fully explain the heterogeneity in single influenza-infected cells.

microbiology↗

bioRxiv2018

An antigenic atlas of HIV-1 escape from broadly neutralizing antibodies

Anti-HIV broadly neutralizing antibodies (bnAbs) have revealed vaccine targets on the viruss Env protein and are themselves promising immunotherapeutics. The efficacy of bnAb-based therapies and vaccines depends in part on how readily the virus can escape neutralization. While structural studies can define contacts between bnAbs and Env, only functional studies can define mutations that confer escape. Here we map how all single amino-acid mutations to Env affect neutralization of HIV by nine bnAbs targeting five epitopes. For most bnAbs, mutations at only a small fraction of structurally defined contact sites mediated escape, and most escape occurred at sites that are near but do not directly contact the antibody. The mutations selected by two pooled bnAbs were similar to those expected from the combination of the bnAbs independent action. Overall, our mutation-level antigenic atlas provides a comprehensive dataset for understanding viral immune escape and refining therapies and vaccines.

immunology↗

bioRxiv2018

Reconciling disparate estimates of viral genetic diversity during human influenza infections

Deep sequencing can measure viral genetic diversity within human influenza infections, but published studies disagree in their estimates of how much genetic diversity is typically present. One large-scale deep-sequencing study of human influenza reported high levels of shared viral genetic diversity among infected individuals in Hong Kong, but subsequent studies of other cohorts have reported little shared viral diversity. We re-analyze sequencing data from four studies of within-host genetic diversity encompassing more than 500 acute human influenza infections. We identify an anomaly in the Hong Kong data that provides a technical explanation for these discrepancies: read pairs from this study are often split between different biological samples, indicating that some reads are incorrectly assigned. These technical abnormalities explain the high levels of within-host variation and loose transmission bottlenecks reported by this study. Studies without these anomalies consistently report low levels of genetic diversity in acute human influenza infections.

evolutionary biology↗

bioRxiv2018

Characterization of influenza B virus variants with reduced neuraminidase inhibitor susceptibility

Treatment options for influenza B virus infections are limited to neuraminidase inhibitors (NAIs) which block the neuraminidase (NA) glycoprotein on the virion surface. The development of NAI resistance would therefore result in a loss of antiviral treatment options for influenza B infections. This study characterized two contemporary influenza B viruses with known resistance-conferring NA amino acid substitutions, D197N and H273Y, detected during routine surveillance. The D197N and H273Y variants were characterized in vitro by assessing NA enzyme activity and affinity, as well as replication in cell culture compared to NAI-sensitive wild-type viruses. In vivo studies were also performed in ferrets to assess the replication and transmissibility of each variant. Mathematical models were used to analyse within-host and between-host fitness of variants relative to wild-type viruses. The data revealed that the H273Y variant had similar NA enzyme function relative to its wild-type but had slightly reduced replication and transmission efficiency in vivo. The D197N variant had impaired NA enzyme function but there was no evidence of reduction in replication or transmission efficiency in ferrets. Our data suggest that the influenza B variant with H273Y NA substitution had a more notable reduction in fitness compared to wild-type viruses than the influenza B variant with the D197N NA substitution. Although a D197N variant is yet to become widespread, it is the most commonly detected NAI-resistant influenza B virus in surveillance studies. Our results highlight the need to carefully monitor circulating viruses for the spread of influenza B viruses with the D197N NA substitution.

microbiology↗

bioRxiv2018

Comprehensive profiling of translation initiation in influenza virus infected cells

Translation can initiate at alternate, non-canonical start codons in response to stressful stimuli in mammalian cells. Recent studies suggest that viral infection and anti-viral responses alter sites of translation initiation, and in some cases, lead to production of novel immune epitopes. Here we systematically investigate the extent and impact of alternate translation initiation in cells infected with influenza virus. We perform evolutionary analyses that suggest selection against non-canonical initiation at CUG codons in influenza virus lineages that have adapted to mammalian hosts. We then use ribosome profiling with the initiation inhibitor lactidomycin to experimentally delineate translation initiation sites in a human lung epithelial cell line infected with influenza virus. We identify several candidate sites of alternate initiation in influenza mRNAs, all of which occur at AUG codons that are downstream of canonical initiation codons. One of these candidate downstream start sites truncates 14 amino acids from the N-terminus of the N1 neuraminidase protein, resulting in loss of its cytoplasmic tail and a portion of the transmembrane domain. This truncated neuraminidase protein is expressed on the cell surface during influenza virus infection, is enzymatically active, and is conserved in most N1 viral lineages. Host transcripts induced by the anti-viral response are enriched for translation initiation at non-canonical start sites and non-AUG start codons. Together, our results systematically map the landscape of translation initiation during influenza virus infection, and shed light on the evolutionary forces shaping this landscape.

microbiology↗

bioRxiv2018

Sera from individuals with narrowly focused influenza virus antibodies rapidly select viral escape mutations in ovo

Influenza viruses use distinct antibody escape mechanisms depending on the overall complexity of the antibody response that is encountered. When grown in the presence of a hemagglutinin (HA) monoclonal antibody, influenza viruses typically acquire a single HA mutation that reduces the binding of that specific monoclonal antibody. In contrast, when confronted with mixtures of HA monoclonal antibodies or polyclonal sera that have antibodies that bind several HA epitopes, influenza viruses acquire mutations that increase HA binding to host cells. Recent data from our laboratory and others suggest that some humans possess antibodies that are narrowly focused on HA epitopes that were present in influenza virus strains that they were likely exposed to in childhood. Here, we completed a series of experiments to determine if humans with narrowly focused HA antibody responses are able to select for influenza virus antigenic escape variants in ovo. We identified three human donors that possessed HA antibody responses that were heavily focused on a single HA antigenic site. Remarkably, sera from all three of these donors selected single HA escape mutations during in ovo passage experiments, similar to what has been previously reported for single monoclonal antibodies. These single HA mutations directly reduced binding of serum antibodies used for selection. We propose that new antigenic variants of influenza viruses might originate in individuals that produce antibodies that are narrowly focused on HA epitopes that were present in viral strains that they encountered in childhood.\n\nImportanceInfluenza vaccine strains must be updated frequently since circulating viral strains continuously change in antigenically important epitopes. Our previous studies have demonstrated that some individuals possess antibody responses that are narrowly focused on epitopes that were present in viral strains that they encountered during childhood. Here, we show that influenza viruses rapidly escape this type of polyclonal antibody response when grown in ovo by acquiring single mutations that directly prevent antibody binding. These studies improve our understanding of how influenza viruses evolve when confronted with narrowly focused polyclonal human antibodies.

microbiology↗

bioRxiv2018

Complete functional mapping of infection- and vaccine-elicited antibodies against the fusion peptide of HIV

Eliciting broadly neutralizing antibodies (bnAbs) targeting envelope (Env) is a major goal of HIV vaccine development, but cross-clade breadth from immunization has only sporadically been observed. Recently, Xu et al (2018) elicited cross-reactive neutralizing antibody responses in a variety of animal models using immunogens based on the epitope of bnAb VRC34.01. The VRC34.01 antibody, which was elicited by natural human infection, targets the N terminus of the Env fusion peptide, a critical component of the virus entry machinery. Here we precisely characterize the functional epitopes of VRC34.01 and two vaccine-elicited murine antibodies by mapping all single amino-acid mutations to the BG505 Env that affect viral neutralization. While escape from VRC34.01 occurred via mutations in both fusion peptide and distal interacting sites of the Env trimer, escape from the vaccine-elicited antibodies was mediated predominantly by mutations in the fusion peptide. Cryo-electron microscopy of four vaccine-elicited antibodies in complex with Env trimer revealed focused recognition of the fusion peptide and provided a structural basis for development of neutralization breadth. Together, these functional and structural data suggest that the breadth of vaccine-elicited antibodies targeting the fusion peptide can be enhanced by specific interactions with additional portions of Env. Thus, our complete maps of viral escape provide a template to improve the breadth or potency of future vaccine-induced antibodies against Envs fusion peptide.\n\nAuthor summaryA major goal of HIV-1 vaccine design is to elicit antibodies that neutralize diverse strains of HIV-1. Recently, some of us elicited such antibodies in animal models using immunogens based on the epitope of a broad antibody (VRC34.01) isolated from an infected individual. Further improving these vaccine-elicited antibody responses will require a detailed understanding of how the resulting antibodies target HIVs envelope protein (Env). Here, we used mutational antigenic profiling to precisely map the epitope of two vaccine-elicited antibodies and the template VRC34.01 antibody. We did this by quantifying the effect of all possible amino acid mutations to Env on antibody neutralization. Although all antibodies target a similar region of Env, we found clear differences in the functional interaction of Env with the vaccine- and infection-elicited antibodies. We combined these functional data with structural analyses to identify antibody-Env interactions that could improve the breadth of vaccine-elicited antibodies, and thereby help to refine vaccination schemes to achieve broader responses.

immunology↗

bioRxiv2018

Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral divergence

Molecular phylogenetics is often used to estimate the time since the divergence of modern gene sequences. For highly diverged sequences, such phylogenetic techniques sometimes estimate surprisingly recent divergence times. In the case of viruses, independent evidence indicates that the estimates of deep divergence times from molecular phylogenetics are sometimes too recent. This discrepancy is caused in part by inadequate models of purifying selection leading to branch-length underestimation. Here we examine the effect on branch-length estimation of using models that incorporate experimental measurements of purifying selection. We find that models informed by experimentally measured site-specific amino-acid preferences estimate longer deep branches on phylogenies of influenza virus hemagglutinin. This lengthening of branches is due to more realistic stationary states of the models, and is mostly independent of the branch-length-extension from modeling site-to-site variation in amino-acid substitution rate. The branch-length extension from experimentally informed site-specific models is similar to that achieved by other approaches that allow the stationary state to vary across sites. However, the improvements from all of these site-specific but time-homogeneous and site-independent models are limited by the fact that a proteins amino-acid preferences gradually shift as it evolves. Overall, our work underscores the importance of modeling site-specific amino-acid preferences when estimating deep divergence times--but also shows the inherent limitations of approaches that fail to account for how these preferences shift over time.

evolutionary biology↗

bioRxiv2018

Deep mutational scanning of hemagglutinin helps predict evolutionary fates of human H3N2 influenza variants

Human influenza virus rapidly accumulates mutations in its major surface protein hemagglutinin (HA). The evolutionary success of influenza virus lineages depends on how these mutations affect HAs functionality and antigenicity. Here we experimentally measure the effects on viral growth in cell culture of all single amino-acid mutations to the HA from a recent human H3N2 influenza virus strain. We show that mutations that are measured to be more favorable for viral growth are enriched in evolutionarily successful H3N2 viral lineages relative to mutations that are measured to be less favorable for viral growth. Therefore, despite the well-known caveats about cell-culture measurements of viral fitness, such measurements can still be informative for understanding evolution in nature. We also compare our measurements for H3 HA to similar data previously generated for a distantly related H1 HA, and find substantial differences in which amino acids are preferred at many sites. For instance, the H3 HA has less disparity in mutational tolerance between the head and stalk domains than the H1 HA. Overall, our work suggests that experimental measurements of mutational effects can be leveraged to help understand the evolutionary fates of viral lineages in nature -- but only when the measurements are made on a viral strain similar to the ones being studied in nature.\n\nSignificance StatementA key goal in the study of influenza virus evolution is to forecast which viral strains will persist and which ones will die out. Here we experimentally measure the effects of all amino-acid mutations to the hemagglutinin protein from a human H3N2 influenza strain on viral growth in cell culture. We show that these measurements have utility for distinguishing among viral strains that do and do not succeed in nature. Overall, our work suggests that new high-throughput experimental approaches may be useful for understanding virus evolution in nature.

evolutionary biology↗