# Pooled and dual-guided CRISPRi, a genome-wide tool for genetic interaction mapping in high-throughput

> **NIH NIH R21** · BOSTON COLLEGE · 2021 · $234,750

## Abstract

Project Summary
No single gene acts by itself, instead the genome is organized into an intricate network of interacting components
to ensure the organism mounts an appropriate response to its environment. A genetic interaction network (GIN)
represents a global view of these relationships and, for instance, can depict a cell as a functional wiring diagram.
Thereby GINs are key to develop an integrated understanding of all processes in a cell or organism. A genetic
interaction is defined as a combination of mutations that have an unexpected phenotype with respect to the effect
of the individual perturbations. For instance, two mutations that have little effect by themselves when combined
may be lethal (a negative interaction) or two mutations that have a negative effect individually may have no effect
when combined (a positive interaction). For model systems including yeast, tools such as synthetic genetic array
analyses exist that allows for sampling of double gene knockouts on a genome-wide scale. This approach has
enabled sampling of >23 million interactions and has resulted in the most detailed genetic interaction network to
date consisting of ~900,000 genetic interactions. In contrast, an easily implementable approach for bacteria that
can map genome-wide genetic interactions in high-throughput is lacking. In this proposal we solve this
challenge by developing pooled and dual-guided CRISPRi (p&dgCRISPRi) in the bacterial pathogen
Streptococcus pneumoniae. As a proof-of-principle we developed a relatively small version of p&dgCRISPRi.
To enable this, we designed a cloning strategy aimed at combining two single guide RNAs (gRNAs) into a single
genome targeting all pairwise combinations of a set of 105 genes in S. pneumoniae. Thereby ~5000 pairwise
interactions were screened in a pool, resulting in ~500 negative interactions and ~200 positive interactions. In
Aim 1, we scale-up the approach and generate saturated libraries totaling ~1.2 million interactions. We first
evaluate 10 gRNAs for each open reading frame (ORF) in the genome, and select two efficient ones. These
gRNAs are than used to generate over 1.2 million pooled S. pneumoniae CRISPRi strains where each bacterium
expresses 2 gRNAs. Each gRNA-pair is linked to two random barcodes, and the change in frequency of these
barcodes in the population, which is determined by Illumina sequencing, is used to calculate their effect on
fitness. In Aim 2, we build
the first genome-wide genetic interaction network for S. pneumoniae by screening the
p&dgCRISPRi libraries in rich and minimal media, and in rich media supplemented with an antibiotic from one of
the four major classes. Networks are analyzed in detail and are combined and fused with additional (omics)data
to provide context, and mined for new biological insights, while 30-50 interactions are validated to confirm high-
confidence interactions. Most importantly, these GINs will proof central to developing an integrated
understanding of all p...

## Key facts

- **NIH application ID:** 10109433
- **Project number:** 1R21AI156203-01
- **Recipient organization:** BOSTON COLLEGE
- **Principal Investigator:** Tim van Opijnen
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $234,750
- **Award type:** 1
- **Project period:** 2020-11-19 → 2022-10-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10109433

## Citation

> US National Institutes of Health, RePORTER application 10109433, Pooled and dual-guided CRISPRi, a genome-wide tool for genetic interaction mapping in high-throughput (1R21AI156203-01). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10109433. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*