Functional cooperativity between the trigger factor chaperone and the ClpXP proteolytic complex

A functional association is uncovered between the ribosome-associated trigger factor (TF) chaperone and the ClpXP degradation complex. Bioinformatic analyses demonstrate conservation of the close proximity of tig, the gene coding for TF, and genes coding for ClpXP, suggesting a functional interaction. The effect of TF on ClpXP-dependent degradation varies based on the nature of substrate. While degradation of some substrates are slowed down or are unaffected by TF, surprisingly, TF increases the degradation rate of a third class of substrates. These include λ phage replication protein λO, master regulator of stationary phase RpoS, and SsrA-tagged proteins. Globally, TF acts to enhance the degradation of about 2% of newly synthesized proteins. TF is found to interact through multiple sites with ClpX in a highly dynamic fashion to promote protein degradation. This chaperone–protease cooperation constitutes a unique and likely ancestral aspect of cellular protein homeostasis in which TF acts as an adaptor for ClpXP

Investigation of ClpXP Protease Mechanism of Function and its Interaction with the Folding Chaperone Trigger Factor

The major chaperones identified in Escherichia coli that assist in protein folding include trigger factor (TF), DnaK/DnaJ/GrpE and GroEL/GroES systems. The main ATP-dependent proteases are ClpXP, ClpAP, HslUV, Lon, and FtsH. From detailed sequence analysis, we found that tig (gene for TF), clpX, and clpP genes co-localize next to each other in most examined bacteria. We hypothesized that TF and ClpXP are functionally associated. TF is a ribosome-associated folding chaperone whereas ClpXP is a degradation complex. ClpX serves as the regulatory ATPase that recognizes substrates, unfolds and translocates polypeptides into ClpP for degradation. I found that TF physically interacts with ClpX, and that they collaborate to enhance degradation of certain ClpXP substrates. It is estimated that TF enhances the degradation of about 2% of newly synthesized E. coli proteins. One of the ClpXP substrates with degradation enhanced by TF was λO, the λ phage replication protein. Furthermore, TF also enhanced the degradation of ribosome-stalled λO nascent chains. Experiments suggest that TF transfers ribosome-stalled λO to ClpX for degradation by ClpP, demonstrating the existence of co-translational protein degradation in E. coli. To understand ClpXP mechanism, we had previously proposed that the degraded peptides are released from ClpP through transient equatorial side pores. To further understand ClpP dynamics, we determined the structure of ClpP(Ala153Cys) in its oxidized state. The structure shows that each opposing pair of protomers is linked by a disulfide bond. Unexpectedly, this structure resembles the compact structures of Streptococcus pneumoniae, Mycobacterium tuberculosis, and Plasmodium falciparum ClpPs, rather than the extended states seen in previous E. coli ClpP structures. Normal mode analysis of ClpP structures suggested that the iii compact structure is a naturally sampled conformation of WT ClpP. My findings provide insights for understanding ClpP dynamics as well as reveal a novel association between ClpXP protease and TF folding chaperone.Ph

Quantitative Genome-Wide Genetic Interaction Screens Reveal Global Epistatic Relationships of Protein Complexes in <i>Escherichia coli</i>

<div><p>Large-scale proteomic analyses in <i>Escherichia coli</i> have documented the composition and physical relationships of multiprotein complexes, but not their functional organization into biological pathways and processes. Conversely, genetic interaction (GI) screens can provide insights into the biological role(s) of individual gene and higher order associations. Combining the information from both approaches should elucidate how complexes and pathways intersect functionally at a systems level. However, such integrative analysis has been hindered due to the lack of relevant GI data. Here we present a systematic, unbiased, and quantitative synthetic genetic array screen in <i>E. coli</i> describing the genetic dependencies and functional cross-talk among over 600,000 digenic mutant combinations. Combining this epistasis information with putative functional modules derived from previous proteomic data and genomic context-based methods revealed unexpected associations, including new components required for the biogenesis of iron-sulphur and ribosome integrity, and the interplay between molecular chaperones and proteases. We find that functionally-linked genes co-conserved among γ-proteobacteria are far more likely to have correlated GI profiles than genes with divergent patterns of evolution. Overall, examining bacterial GIs in the context of protein complexes provides avenues for a deeper mechanistic understanding of core microbial systems.</p></div

RavA and ViaA linked to Fe-S assembly.

<p>(A) Sub-network of GIs of two unannotated genes with Fe-S cluster assembly and cysteine biosynthesis components. (B) Differential growth of select single, double and triple mutants in rich medium (LB) at 32°C over 24 h; expected fitness derived using multiplicative model, <i>p</i>-value calculated using Student's <i>t</i>-test. (C) Impact of ectopic over-expression of Isc Fe-S cluster assembly proteins (pRKISC expression plasmid vs. pRKNMC control empty vector) on growth of <i>ravA-viaA</i> double mutants vs. wild-type (WT) <i>E. coli</i> before (I) and after (II) oxidative stress (sub-lethal concentrations of kanamycin, Kan); OD₆₀₀ readings at 11-hr time point (III) highlight differential responses. Tetracycline (Tet) included in media for plasmid maintenance. Asterisks represent significant (<i>p</i>≤0.01; Student's <i>t</i>-test) difference between WT+ pRKISC vs. WT+ pRKNMC. (D) Slow growth of <i>cysB</i> deletion mutants on liquid LB medium at 32°C. Each data point shows the mean ± SD (error bars) of three independent biological measurements. (E) Growth inhibition profiles of ectopic over-expression of <i>ravA</i> (pRavA) vs. WT (p11) on W-salt medium supplemented with sub-lethal concentration of inorganic (I and II) and organic (III–V) sources of sulphur. (F) Co-immunoprecipitation analysis of endogenous RavA (top) and ViaA (bottom). Immunoblots show chromosomally tagged Isc assembly proteins, expressed at native levels, in input whole cell lysate (WCL) and anti-FLAG immunoprecipitates (IP) as indicated. Untagged parental strain and an irrelevant bait protein (ATP-dependent iron hydroxamate transporter, FhuB), served as negative controls. Molecular masses (kDa) of marker proteins by SDS-PAGE are indicated.</p

Functional crosstalk among chaperones and proteases.

<p>(A) Summary of chaperone type and GI frequency observed by eSGA. (B) Heatmap showing clusters of correlated GI profiles among select chaperones. Highlighted sub-networks show similar (correlated) GI profiles between the ATP-dependent protein unfoldases <i>clpX</i> and <i>clpA</i> (top), and the small HSPs <i>ibpA</i> and <i>ibpB</i> (bottom). Scatter-plot shows genome-wide correlation coefficient profiles of <i>ibpA</i> (<i>x</i>-axis) versus <i>ibpB</i> (<i>y</i>-axis). (C) Number of alleviating (green) or aggravating (red) GIs of each chaperone mutant (brown bar) with one or more chaperone-containing protein complexes (orange bar), compiled from Ecocyc and our own previous work <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004120#pgen.1004120-Hu1" target="_blank">[2]</a>. (D) Shared (jaccard index) non-chaperone interactors among chaperone-containing protein complexes. (E) Crosstalk among chaperone and protease families. Edge thickness represents degree of GI connectivity within and between families; dark edges indicate statistically significance (<i>p</i>-value ≤0.09; hypergeometric test).</p

YaiF linked to ribosome biogenesis.

<p>(A) Aggravating GIs between <i>yaiF</i> and 30S subunit biogenesis factor, <i>rsgA</i>, and components of the 30S (<i>rpsE</i>) and 50S (<i>rplD</i>, <i>rplW</i>, <i>rpmE</i>, <i>rpmG</i>) ribosomes. (B) Drug hypersensitivity of a <i>yaiF</i> deletion strain to antibiotics targeting the ribosome/translational reported in a recent chemical-genetic screen <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004120#pgen.1004120-Nichols1" target="_blank">[41]</a>. Drug concentration producing a significant phenotype is indicated in parentheses. (C) Sensitivity of <i>yaiF</i> and <i>rsgA</i> single and double mutants versus wild-type cells (WT) to tetracycline (1.0 µg/ml). Panel below shows phenotypic complementation by over-expression <i>in trans</i>. (D) Different ribosome profiles in <i>yaiF</i> deletion mutant vs. WT strains. Quantification of ribosome subunit peak ratios is provided. (E) Increased translational errors, based on read-through of a β-galactosidase reporter (normalized to a control vector), in <i>yaiF</i> and <i>rsgA</i> single and double mutants relative to WT cells. Asterisks indicate significant (Student's <i>t</i>-test) difference between single or double mutant vs. WT strains. (F) Schematic showing the precursor sequences (PS) of the 17S rRNA (I) with oligonucleotide probe annealing (shown as asterisks) sites. The 115 and 33 nucleotides shown in the 5′ and 3′ ends of the 17s rRNA is the precursor rRNA for 30S ribosomal subunit <a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1004120#pgen.1004120-Li1" target="_blank">[107]</a>. Northern hybridization shows the accumulation of 17S rRNA species in mutants and WT strains (II) using the indicated biotinylated oligonucleotide probes. The 16S rRNA probe was used as an internal control.</p

Functional properties of the global <i>E. coli</i> GI network.

<p>(A) Reproducibility of normalized colony sizes of digenic mutants measured in replicate screens. (B) Histogram of GI <i>S</i>-scores; arrows indicate cut-off scores (|<i>S</i>- score±3|; <i>p</i>-value ≤0.05 computed using Fisher's exact test) used to signify significant epistatic (aggravating or alleviating) interactions. (C) Comparison of aggravating-to-alleviating GI ratios observed among essential and non-essential complex components. Numbers represent the total aggravating over alleviating GIs in essential or non-essential complexes. (D) Overlap of GI compared to literature in terms of (I) coverage and (II) statistical significance (black arrow) versus background frequencies generated by random permutation (purple distribution represents 10,000 random null models). Distributions of GI correlation profiles (I) of genes either (E) encoding physically interacting proteins (zoom-in of right tail shown in inset) or (F) within same operon versus randomly drawn gene pairs; significance values computed using two-sample Kolmogorov-Smirnov (KS) test. (II) Representative scatter plots show correlated GI profiles of <i>fepD</i> (<i>y</i>-axis) vs. <i>fepG</i> (<i>x</i>-axis), and <i>tusC</i> (<i>x</i>-axis) vs. <i>tusD</i> (<i>y</i>-axis).</p

Monochromaticity of GIs among bacterial bioprocesses.

<p>(A) Heatmap displaying the distribution of significantly enriched (<i>p</i>-value ≤0.05) aggravating or alleviating GIs between functional categories. Node size represents the number of enriched GIs per process, while the color indicates the monochromaticity type: red for aggravating (monochromatic score of −1) and green for alleviating (monochromatic score of +1). Only representative MultiFun processes (x-axis) are shown. Highlighted (bold) crosstalk processes are shown as separate sub-networks in panels B and C. Heatmaps showing overlapping patterns of alleviating (B) or aggravating (C) GIs for representative genes within particular categories after hierarchical clustering.</p