Biological fitness landscapes by deep mutational scanning

Mehlhoff, Jacob D.; Ostermeier, Marc

doi:10.1016/bs.mie.2020.04.023

Cited by 30 publications

(9 citation statements)

References 24 publications

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“…One way to probe the importance of native residues in mediating protein–cofactor and protein–protein interactions is to evaluate the effects of mutations on cellular function. − In cases in which a high-throughput selection is available, large numbers of mutations can be evaluated in parallel using laboratory evolution. − With this approach, a library of genes encoding mutant proteins is created, and the library is subjected to next generation sequencing before and after selection for biomolecules with parent-like functions . The changes in the abundance of each mutant are then used to calculate the ratio of sequence counts before and after selection, which can be used to estimate the relative activities of mutant proteins.…”

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confidence: 99%

Determinants of Multiheme Cytochrome Extracellular Electron Transfer Uncovered by Systematic Peptide Insertion

et al. 2022

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The multiheme cytochrome MtrA enables microbial respiration by transferring electrons across the outer membrane to extracellular electron acceptors. While structural studies have identified residues that mediate the binding of MtrA to hemes and to other cytochromes that facilitate extracellular electron transfer (EET), the relative importance of these interactions for EET is not known. To better understand EET, we evaluated how insertion of an octapeptide across all MtrA backbone locations affects Shewanella oneidensis MR-1 respiration on Fe(III). The EET efficiency was found to be inversely correlated with the proximity of the insertion to the heme prosthetic groups. Mutants with decreased EET efficiencies also arose from insertions in a subset of the regions that make residue–residue contacts with the porin MtrB, while all sites contacting the extracellular cytochrome MtrC presented high peptide insertion tolerance. MtrA variants having peptide insertions within the CXXCH motifs that coordinate heme cofactors retained some ability to support respiration on Fe(III), although these variants presented significantly decreased EET efficiencies. Furthermore, the fitness of cells expressing different MtrA variants under Fe(III) respiration conditions correlated with anode reduction. The peptide insertion profile, which represents the first comprehensive sequence–structure–function map for a multiheme cytochrome, implicates MtrA as a strategic protein engineering target for the regulation of EET.

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confidence: 99%

Determinants of Multiheme Cytochrome Extracellular Electron Transfer Uncovered by Systematic Peptide Insertion

et al. 2022

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“…We determined the frequency of each rnc mutant by deep-sequencing at the beginning and end of the competition. From these frequencies, we determined relative fitness ( w ) values, corresponding to the mean growth rate of cells containing a mutant RNase III relative to the mean growth rate of cells containing alleles synonymous to wildtype (Mehlhoff and Ostermeier 2020). We utilize the frequency of wildtype synonymous alleles instead of the frequency of wildtype because wildtype synonyms occurred more frequently in the library and wildtype sequencing counts are more prone to being affected by the artifact of PCR template jumping (Pääbo, et al 1990; Kebschull and Zador 2015) during the preparation of barcoded amplicons for deep-sequencing.…”

Section: Resultsmentioning

confidence: 99%

Fitness and functional landscapes of theE. coliRNase III genernc

Weeks

Ostermeier

2022

Preprint

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How protein properties such as protein activity and protein essentiality affect the distribution of fitness effects (DFE) of mutations are important questions in protein evolution. Deep mutational scanning studies typically measure the effects of a comprehensive set of mutations on either protein activity or fitness. Our understanding of the underpinnings of the DFE would be enhanced by a comprehensive study of both for the same gene. Here, we compared the fitness effects and in vivo protein activity effects of ~4,500 missense mutations in theE. coli rncgene. This gene encodes RNase III, a global regulator enzyme that cleaves diverse RNA substrates including precursor ribosomal RNA and various mRNAs including its own 5' untranslated region (5'UTR). We find that RNase III's ability to cleave dsRNA is the most important determinant of the fitness effects of rnc mutations. The DFE of RNase III was bimodal, with mutations centered around neutral and deleterious effects, consistent with previously reported DFE's of enzymes with a singular physiological role. Fitness was buffered to small effects on RNase III activity. The enzyme's RNase III domain (RIIID), which contains the RNase III signature motif and all active site residues, was more sensitive to mutation than its dsRNA binding domain (dsRBD), which is responsible for recognition and binding to dsRNA. Differential effects on fitness and functional scores for mutations at highly conserved residues G97, G99, and F188 suggest that these positions may be important for RNase III cleavage specificity.

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“…Some recent reviews include [74][75][76][77][78][79][80][81]. Increasingly, the use of 'deep mutational scanning' [82][83][84][85][86][87][88][89][90], sometimes coupled to FACS-based sorting [91] ('sort-seq' [52,82,83,92]), is making available large amounts of sequence-activity pairs [85]. (We ourselves made available one million paired aptamer activity sequences in 2010 [93].)…”

Section: Directed Protein Evolutionmentioning

confidence: 99%

Intelligent host engineering for metabolic flux optimisation in biotechnology

Munro

Kell

2021

Biochemical Journal

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Optimising the function of a protein of length N amino acids by directed evolution involves navigating a ‘search space’ of possible sequences of some 20N. Optimising the expression levels of P proteins that materially affect host performance, each of which might also take 20 (logarithmically spaced) values, implies a similar search space of 20P. In this combinatorial sense, then, the problems of directed protein evolution and of host engineering are broadly equivalent. In practice, however, they have different means for avoiding the inevitable difficulties of implementation. The spare capacity exhibited in metabolic networks implies that host engineering may admit substantial increases in flux to targets of interest. Thus, we rehearse the relevant issues for those wishing to understand and exploit those modern genome-wide host engineering tools and thinking that have been designed and developed to optimise fluxes towards desirable products in biotechnological processes, with a focus on microbial systems. The aim throughput is ‘making such biology predictable’. Strategies have been aimed at both transcription and translation, especially for regulatory processes that can affect multiple targets. However, because there is a limit on how much protein a cell can produce, increasing kcat in selected targets may be a better strategy than increasing protein expression levels for optimal host engineering.

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Biological fitness landscapes by deep mutational scanning

Cited by 30 publications

References 24 publications

Determinants of Multiheme Cytochrome Extracellular Electron Transfer Uncovered by Systematic Peptide Insertion

Determinants of Multiheme Cytochrome Extracellular Electron Transfer Uncovered by Systematic Peptide Insertion

Fitness and functional landscapes of theE. coliRNase III genernc

Intelligent host engineering for metabolic flux optimisation in biotechnology

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