CRISPR interference screens reveal growth–robustness tradeoffs in Synechocystis sp. PCC 6803 across growth conditions

Author:

Miao Rui1ORCID,Jahn Michael12ORCID,Shabestary Kiyan13ORCID,Peltier Gilles4,Hudson Elton P1ORCID

Affiliation:

1. School of Engineering Sciences in Chemistry, Biotechnology and Health, Science for Life Laboratory, KTH—Royal Institute of Technology , Stockholm, SE-17165, Sweden

2. Max Planck Unit for the Science of Pathogens , 10117 Berlin, Germany

3. Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London , London SW7 2AZ, UK

4. Aix Marseille Univ, CEA, CNRS, Institut de Biosciences et Biotechnologies Aix-Marseille, CEA Cadarache , 13108 Saint Paul-Lez-Durance, France

Abstract

Abstract Barcoded mutant libraries are a powerful tool for elucidating gene function in microbes, particularly when screened in multiple growth conditions. Here, we screened a pooled CRISPR interference library of the model cyanobacterium Synechocystis sp. PCC 6803 in 11 bioreactor-controlled conditions, spanning multiple light regimes and carbon sources. This gene repression library contained 21,705 individual mutants with high redundancy over all open reading frames and noncoding RNAs. Comparison of the derived gene fitness scores revealed multiple instances of gene repression being beneficial in 1 condition while generally detrimental in others, particularly for genes within light harvesting and conversion, such as antennae components at high light and PSII subunits during photoheterotrophy. Suboptimal regulation of such genes likely represents a tradeoff of reduced growth speed for enhanced robustness to perturbation. The extensive data set assigns condition-specific importance to many previously unannotated genes and suggests additional functions for central metabolic enzymes. Phosphoribulokinase, glyceraldehyde-3-phosphate dehydrogenase, and the small protein CP12 were critical for mixotrophy and photoheterotrophy, which implicates the ternary complex as important for redirecting metabolic flux in these conditions in addition to inactivation of the Calvin cycle in the dark. To predict the potency of sgRNA sequences, we applied machine learning on sgRNA sequences and gene repression data, which showed the importance of C enrichment and T depletion proximal to the PAM site. Fitness data for all genes in all conditions are compiled in an interactive web application.

Funder

Novo Nordisk Foundation

Swedish Research Council

Swedish Foundation for Strategic Research

Swedish Research Council Formas

Federation of European Microbiological Societies

Publisher

Oxford University Press (OUP)

Subject

Cell Biology,Plant Science

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