Biology subjects

Whitehead, T. A.

Publications and source records attributed to Whitehead, T. A..

23 records · Page 2Linked to original sources

bioRxiv2021

One-shot identification of SARS-CoV-2 S RBD escape mutants using yeast screening

The potential emergence of SARS-CoV-2 Spike (S) escape mutants is a threat to reduce the efficacy of existing vaccines and neutralizing antibody (nAb) therapies. An understanding of the antibody/S escape mutations landscape is urgently needed to preemptively address this threat. Here we describe a rapid method to identify escape mutants for nAbs targeting the S receptor binding site. We identified escape mutants for five nAbs, including three from the public germline class VH3-53 elicited by natural COVID-19 infection. Escape mutations predominantly mapped to the periphery of the ACE2 recognition site on the RBD with K417, D420, Y421, F486, and Q493 as notable hotspots. We provide libraries, methods, and software as an openly available community resource to accelerate new therapeutic strategies against SARS-CoV-2. One Sentence SummaryWe present a facile method to identify antibody escape mutants on SARS-CoV-2 S RBD.

biochemistry↗

bioRxiv2021

Paired heavy and light chain signatures contribute to potent SARS-CoV-2 neutralization in public antibody responses

Understanding protective mechanisms of antibody recognition can inform vaccine and therapeutic strategies against SARS-CoV-2. We discovered a new antibody, 910-30, that targets the SARS-CoV-2 ACE2 receptor binding site as a member of a public antibody response encoded by IGHV3-53/IGHV3-66 genes. We performed sequence and structural analyses to explore how antibody features correlate with SARS-CoV-2 neutralization. Cryo-EM structures of 910-30 bound to the SARS-CoV-2 spike trimer revealed its binding interactions and ability to disassemble spike. Despite heavy chain sequence similarity, biophysical analyses of IGHV3-53/3-66 antibodies highlighted the importance of native heavy:light pairings for ACE2 binding competition and for SARS-CoV-2 neutralization. We defined paired heavy:light sequence signatures and determined antibody precursor prevalence to be ~1 in 44,000 human B cells, consistent with public antibody identification in several convalescent COVID-19 patients. These data reveal key structural and functional neutralization features in the IGHV3-53/3-66 public antibody class to accelerate antibody-based medical interventions against SARS-CoV-2. HighlightsO_LIA molecular study of IGHV3-53/3-66 public antibody responses reveals critical heavy and light chain features for potent neutralization C_LIO_LICryo-EM analyses detail the structure of a novel public antibody class member, antibody 910-30, in complex with SARS-CoV-2 spike trimer C_LIO_LICryo-EM data reveal that 910-30 can both bind assembled trimer and can disassemble the SARS-CoV-2 spike C_LIO_LISequence-structure-function signatures defined for IGHV3-53/3-66 class antibodies including both heavy and light chains C_LIO_LIIGHV3-53/3-66 class precursors have a prevalence of 1:44,000 B cells in healthy human antibody repertoires C_LI

immunology↗

bioRxiv2019

Saturation mutagenesis genome engineering of infective {Phi}X174 bacteriophage via unamplified oligo pools and golden gate assembly

Here we present a novel protocol for the construction of saturation single-site--and massive multi-site--mutant libraries of a bacteriophage. We segmented the {Phi}X174 genome into 14 non-toxic and non-replicative fragments compatible with golden gate assembly. We next used nicking mutagenesis with oligonucleotides prepared from unamplified oligo pools with individual segments as templates to prepare near-comprehensive single-site mutagenesis libraries of genes encoding the F capsid protein (421 amino acids scanned) and G spike protein (172 amino acids scanned). Libraries possessed greater than 99% of all 11,860 programmed mutations. Golden Gate cloning was then used to assemble the complete {Phi}X174 mutant genome and generate libraries of infective viruses. This protocol will enable reverse genetics experiments for studying viral evolution and, with some modifications, can be applied for engineering of therapeutically relevant bacteriophages with larger genomes.

genomics↗

bioRxiv2019

Impact of initial protein stability on local fitness landscapes

It is incompletely understood how biophysical properties like protein stability impact molecular evolution and epistasis. Epistasis is defined as specific when a mutation exclusively influences the phenotypic effect of another mutation, often at physically interacting residues. By contrast, nonspecific epistasis results when a mutation is influenced by a large number of non-local mutations. As most mutations are pleiotropic, the in vivo folding probability - governed by basal protein stability - is thought to determine activity-enhancing mutational tolerance, which implies that nonspecific epistasis is dominant. However, evidence exists for both specific and nonspecific epistasis as the prevalent factor, with limited comprehensive datasets to validate either claim. Using deep mutational scanning we probe how in vivo enzyme folding probability impacts local fitness landscapes. We computationally designed two different variants of the amidase AmiE in which catalytic efficiencies are statistically indistinguishable but the enzyme variants have lower probabilities of folding in vivo. Local fitness landscapes show only slight alterations among variants, with essentially the same global distribution of fitness effects. However, specific epistasis was predominant for the subset of mutations exhibiting positive sign epistasis. These mutations mapped to spatially distinct locations on AmiE near the initial mutation or proximal to the active site. Intriguingly, the majority of specific epistatic mutations were codon-dependent, with different synonymous codons resulting in fitness sign reversals. Together, these results offer a nuanced view of how protein folding probability impacts local fitness landscapes, and suggest that transcriptional-translational effects are an equally important determinant as stability in determining evolutionary outcomes.

evolutionary biology↗

bioRxiv2016

Interpreting deep mutational scanning data resulting from selections on solid media

Deep mutational scanning is now used in directed evolution experiments to quantify the change in frequency of a cellular variant in a mixed population. A key concern is the extent to which the enrichment of a variant in a population corresponds to a fitness metric like relative growth rate or survival percentage. We present here analytical equations converting the enrichment of a variant to fitness metrics for plate-based selections. Using isogenic and mixed cultures we show that growth rates and survival percentages correlate for antibiotic plate-based selections. These results are important for proper interpretation of data resulting from deep sequencing.

biochemistry↗