Aldikacti, B. | Search bioRxiv

bioRxiv2021

Plasticity in AAA+ proteases reveals ATP-dependent substrate specificity principles

In bacteria, AAA+ proteases such as Lon and ClpXP degrade substrates with exquisite specificity. These machines capture the energy of ATP hydrolysis to power unfolding and degradation of target substrates. Here, we show that a mutation in the ATP binding site of ClpX shifts protease specificity to promote degradation of normally Lon-restricted substrates. However, this ClpX mutant is worse at degrading ClpXP targets, suggesting an optimal balance in substrate preference for a given protease that is surprisingly easy to alter. In vitro, wildtype ClpXP also degrades Lon-restricted substrates more readily when ATP levels are reduced, similar to the shifted specificity of mutant ClpXP, which has altered ATP hydrolysis kinetics. Based on these results, we suggest that rates of ATP hydrolysis not only power substrate unfolding and degradation, but also tune protease specificity. We consider various models for this effect based on emerging structures of AAA+ machines showing conformationally distinct states. O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/456811v2_ufig1.gif" ALT="Figure 1"> View larger version (67K): org.highwire.dtl.DTLVardef@1b72081org.highwire.dtl.DTLVardef@1b713c7org.highwire.dtl.DTLVardef@73a92aorg.highwire.dtl.DTLVardef@167422d_HPS_FORMAT_FIGEXP M_FIG Graphical Abstract C_FIG eTOCAAA+ proteases, such as Lon and ClpXP, select distinct targets for degradation to maintain proteostasis. Mahmoud et al. show that ATP hydrolysis can tune substrate specificity of ClpX, allowing ClpX to degrade Lon-restricted substrates under limiting ATP conditions or in the presence of a ClpX mutant. HighlightsO_LIA Walker B mutation of the AAA+ protease ClpX alters substrate specificity C_LIO_LIClpX mutant degrades new substrates but degrades canonical substrates less well C_LIO_LIDecreasing ATP levels enhances ClpXP mediated degradation of some classes of substrates C_LIO_LIATP-induced changes in conformational states accompany alterations in ClpX specificity C_LI

molecular biology↗

bioRxiv2021

Model-based identification of conditionally-essential genes from transposon-insertion sequencing data

The understanding of bacterial gene function has been greatly enhanced by recent advancements in the deep sequencing of microbial genomes. Transposon insertion sequencing methods combines next-generation sequencing techniques with transposon mutagenesis for the exploration of the essentiality of genes under different environmental conditions. We propose a model-based method that uses regularized negative binomial regression to estimate the change in transposon insertions attributable to gene-environment changes without transformations or uniform normalization. An empirical Bayes model for estimating the local false discovery rate combines unique and total count information to test for genes that show a statistically significant change in transposon counts. When applied to RB-TnSeq (randomized barcode transposon sequencing) and Tn-seq (transposon sequencing) libraries made in strains of Caulobacter crescentus using both total and unique count data the model was able to identify a set of conditionally essential genes for each target condition that shed light on their functions and roles during various stress conditions. Author summaryTransposon insertion sequencing allows the study of bacterial gene function by combining next-generation sequencing techniques with transposon mutagenesis under different genetic and environmental perturbations. Our proposed regularized negative binomial regression method improves the quality of analysis of this data.

bioinformatics↗