-
-
- Interplay of Immunity and Viral
- Evolution
+
+
+
+ {{ aim.title }}
-
-
-
- We study immunity and viral evolution at both the population and single-cell
- levels.
-
-
-
- At the population level, differences in exposure history and immune imprinting lead
- human individuals to make antibody responses that target different regions
- of rapidly evolving viruses like influenza and SARS-CoV-2.
- This population heterogeneity has profound implications for viral evolution and disease
- susceptibility, as
- it causes viral mutations to impact the immunity of different individuals
- differently. We are characterizing this population heterogeneity using both
- deep
- mutational scanning
- and a sequencing based-neutralization
- assay
- we developed that increases the throughput of traditional neutralization assays by several
- orders of magnitude (see schematic at left).
-
-
-
- At the single-cell level, we developed approaches to
- sequence viruses in single
- cells
- and quantify how many progeny each
- infected cell produces.
- We use these approaches to understand how viral variation impacts the
- outcome of infection in individual cells.
-
-
-
-
-
-
-
-
-
-
- Big Datasets and Viral Evolution
-
-
-
-
-
+
+.sky {
+ @apply decoration-sky-500;
+}
+
+.pink {
+ @apply decoration-pink-500;
+}
+
+.indigo {
+ @apply decoration-indigo-500;
+}
+
\ No newline at end of file
diff --git a/.vitepress/theme/research.data.js b/.vitepress/theme/research.data.js
new file mode 100644
index 0000000..dd55665
--- /dev/null
+++ b/.vitepress/theme/research.data.js
@@ -0,0 +1,13 @@
+import { createContentLoader } from "vitepress";
+
+export default createContentLoader("research/*.md", {
+ render: true,
+ transform: (raw) => {
+ return raw.map((page) => ({
+ title: page.frontmatter.title,
+ color: page.frontmatter.color,
+ order: page.frontmatter.order,
+ html: page.html,
+ }));
+ },
+});
diff --git a/README.md b/README.md
index a1d6447..aa3e921 100644
--- a/README.md
+++ b/README.md
@@ -223,8 +223,21 @@ An interactive web tool for visualizing site-level data on a protein structure w
```
### Editing the home page and section home pages
+
While the individual posts can be edited by just editing the Markdown, to edit the homepage and the top text for each section (*Blog*, *Team*, *Papers*, *Software*) you will need to edit the corresponding `*.vue` file at [.vitepress/theme](.vitepress/theme) (eg, [.vitepress/theme/Home.vue](.vitepress/theme/Home.vue) for the home page).
+However, you can edit the research aims that appear on the Home Page ([.vitepress/theme/Home.vue](.vitepress/theme/Home.vue)) using markdown files located in [research/*.md](/research/). These research aims will automatically populate the Home Page.
+
+```md
+---
+title: Big Datasets and Viral Evolution # Title of the aim
+color: pink # Color of the underline
+order: 3 # Order of the research aim
+---
+```
+
+The frontmatter above specifies the title of the aim, the color of the title's underline, and the order of the aim.
+
## Deployment
The deployment is handled by GitHub Actions. A workflow script located at [`.github/workflows/deploy.yml`](.github/workflows/deploy.yml) is run on **pushes** or **pull requests** to the `main` branch. The workflow script builds the website using `npm run build` and copies the contents of the resulting `.dist/` directory to a branch called `gh-pages`. The website is automatically deployed from the root of this branch by GitHub Pages.
diff --git a/research/big-data-and-viruses.md b/research/big-data-and-viruses.md
new file mode 100644
index 0000000..520a29a
--- /dev/null
+++ b/research/big-data-and-viruses.md
@@ -0,0 +1,13 @@
+---
+title: Big Datasets and Viral Evolution
+color: pink
+order: 3
+---
+
+We also develop new ways to leverage large datasets to better understand viral evolution.
+
+We have come up with a way to leverage the millions of publicly available SARS-CoV-2 sequences to estimate the effect of individual mutations on viral fitness (see [this paper](https://academic.oup.com/ve/article/9/2/vead055/7265011) and [these slides](https://slides.com/jbloom/sars2-mut-fitness/)). We've also created a platform to [visualize the mutational effects](https://jbloomlab.github.io/SARS2-mut-fitness/) to aid in interpretation of viral evolution.
+
+We have also integrated thousands of deep mutational scanning measurements into an [antibody-escape calculator](https://jbloomlab.github.io/SARS2-RBD-escape-calc/) that was [widely used](https://slides.com/jbloom/sars2-rbd-escape-calc#/12) during the SARS-CoV-2 pandemic to understand the antigenic effects of viral mutations.
+
+We also have projects that involve analyzing the evolution of viruses [within individual infected humans](https://elifesciences.org/articles/26875), and developing models to [understand epistasis among viral mutations](https://academic.oup.com/ve/article/8/2/veac110/6889254).
diff --git a/research/deep-mutational-scanning.md b/research/deep-mutational-scanning.md
new file mode 100644
index 0000000..1bcb42d
--- /dev/null
+++ b/research/deep-mutational-scanning.md
@@ -0,0 +1,13 @@
+---
+title: Deep Mutational Scanning
+color: sky
+order: 1
+---
+
+Our lab uses deep mutational scanning to experimentally measure how tens-of-thousands of mutations to viral proteins affect key properties including function, immune escape, and receptor binding.
+
+!["Pseudovirus neutralization system"](/assets/research/dms.png)
+
+We primarily perform these experiments using a [pseudovirus system](https://www.sciencedirect.com/science/article/pii/S0092867423001034) that allows us to safely characterize mutants of entry proteins from a wide range of viruses, including [SARS-CoV-2 spike](https://www.nature.com/articles/s41586-024-07636-1), [influenza hemagglutinin](https://doi.org/10.1101/2024.05.23.595634), [Lassa virus GPC](https://www.sciencedirect.com/science/article/pii/S1074761324003194), [HIV envelope](https://www.sciencedirect.com/science/article/pii/S1931312823002184), and [Nipah virus RBP](https://doi.org/10.1101/2024.04.17.589977).
+
+Deep mutational scanning can inform efforts to [forecast the evolution of human seasonal viruses](https://www.nature.com/articles/s41586-024-07636-1) and [surveil the evolution of potential pandemic viruses](https://doi.org/10.1101/2024.05.23.595634). To facilitate the use of deep mutational scanning for these important goals, we develop [interactive visualization tools](https://dms-viz.github.io/) and [data analysis pipelines](https://github.com/dms-vep/dms-vep-pipeline-3). See [here](https://dms-vep.org/Flu_H5_American-Wigeon_South-Carolina_2021-H5N1_DMS/) for an example of how we analyze and visualize large datasets to inform the study of viral evolution.
diff --git a/research/immunity-and-evolution.md b/research/immunity-and-evolution.md
new file mode 100644
index 0000000..e4e4c2a
--- /dev/null
+++ b/research/immunity-and-evolution.md
@@ -0,0 +1,13 @@
+---
+title: Interplay of Immunity and Viral Evolution
+color: indigo
+order: 2
+---
+
+We study immunity and viral evolution at both the population and single-cell levels.
+
+!["Sequencing-based neutralization assay"](/assets/research/seqneut.jpg)
+
+At the population level, differences in exposure history and immune imprinting lead human individuals to make antibody responses that target different regions of rapidly evolving viruses like influenza and SARS-CoV-2. This population heterogeneity has profound implications for viral evolution and disease susceptibility, as it causes viral mutations to impact the immunity of different individuals differently. We are characterizing this population heterogeneity using both [deep mutational scanning](https://www.sciencedirect.com/science/article/pii/S1931312824002336) and a [sequencing based-neutralization assay](https://doi.org/10.1101/2024.03.08.584176) we developed that increases the throughput of traditional neutralization assays by several orders of magnitude (see schematic at left).
+
+At the single-cell level, we developed approaches to [sequence viruses in single cells](https://journals.asm.org/doi/10.1128/jvi.00500-19) and [quantify how many progeny each infected cell produces](https://elifesciences.org/articles/86852). We use these approaches to understand how viral variation impacts the outcome of infection in individual cells.