Simone Pignotti

Abstract Microbiome research is now demonstrating a growing number of bacterial strains and genes that affect our health 1 . Although CRISPR-derived tools have shown great success in editing disease-driving genes in human cells 2 , we currently lack the tools to achieve comparable success for bacterial targets in situ. Here we engineer a phage-derived particle to deliver a base editor and modify Escherichia coli colonizing the mouse gut. Editing of a β-lactamase gene in a model E. coli strain resulted in a median editing efficiency of 93% of the target bacterial population with a single dose. Edited bacteria were stably maintained in the mouse gut for at least 42 days following treatment. This was achieved using a non-replicative DNA vector, preventing maintenance and dissemination of the payload. We then leveraged this approach to edit several genes of therapeutic relevance in E. coli and Klebsiella pneumoniae strains in vitro and demonstrate in situ editing of a gene involved in the production of curli in a pathogenic E. coli strain. Our work demonstrates the feasibility of modifying bacteria directly in the gut, offering a new avenue to investigate the function of bacterial genes and opening the door to the design of new microbiome-targeted therapies.

ABSTRACT Comprehensive collections approaching millions of sequenced genomes have become central information sources in the life sciences. However, the rapid growth of these collections has made it effectively impossible to search these data using tools such as BLAST and its successors. Here, we present a technique called phylogenetic compression, which uses evolutionary history to guide compression and efficiently search large collections of microbial genomes using existing algorithms and data structures. We show that, when applied to modern diverse collections approaching millions of genomes, lossless phylogenetic compression improves the compression ratios of assemblies, de Bruijn graphs, and k -mer indexes by one to two orders of magnitude. Additionally, we develop a pipeline for a BLAST-like search over these phylogeny-compressed reference data, and demonstrate it can align genes, plasmids, or entire sequencing experiments against all sequenced bacteria until 2019 on ordinary desktop computers within a few hours. Phylogenetic compression has broad applications in computational biology and may provide a fundamental design principle for future genomics infrastructure.

Metagenomics is a powerful approach to study genetic content of environmental samples and it has been strongly promoted by Next-Generation Sequencing technologies. The aim of metagenomic classification is to assign each sequence of the metagenome to a corresponding taxonomic unit, or to classify it as “novel”. To cope with increasingly large metagenomic projects, researchers resort to alignment-free methods. The most popular tool – Kraken – provides an extremely rapid read classification, but its index suffers from two major limitations: an enormous memory consumption and a lossy <em>k</em>-mer representation through their lowest common ancestors. We present Prophyle, a metagenomic classifier based on the Burrows-Wheeler Transform. ProPhyle uses a classification algorithm similar to Kraken but with an indexing strategy based on a bottom-up propagation of <em>k</em>-mers in the tree, assembling contigs at each node and matching using a standard full-text search. The obtained index occupies only a fraction of RAM compared to Kraken – 13 GB instead of 90 GB for index construction and 14 GB instead of 72 GB for index querying. The resulting index is also more expressive, allowing users to retrieve a list of <em>all</em> genomes for every queried <em>k</em>-mer. Overall, ProPhyle provides an index for resource-frugal metagenomic classification, which is accurate even with single-species phylogenetic trees. Prophyle is available at http://github.com/karel-brinda/prophyle, released under the MIT license.

Improvements Download databases from Zenodo rather than from NCBI (in order to make the database stable). Improve I/O error messages printed by prophyle_assembler. Improve ProPhyle code.