The Escherichia coli proteome: past, present, and future prospects.

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects.     

Proteome of the Escherichia coli envelope and technological challenges in membrane proteome analysis

The envelope of Escherichia coli is a complex organelle composed of the outer membrane, periplasm-peptidoglycan layer and cytoplasmic membrane. Each compartment has a unique complement of proteins, the proteome. Determining the proteome of the envelope is essential for developing an in silico bacterial model, for determining cellular responses to environmental alterations, for determining the function of proteins encoded by genes of unknown function and for development and testing of new experimental technologies such as mass spectrometric methods for identifying and quantifying hydrophobic proteins. The availability of complete genomic information has led several groups to develop computer algorithms to predict the proteome of each part of the envelope by searching the genome for leader sequences, β-sheet motifs and stretches of α-helical hydrophobic amino acids. In addition, published experimental data has been mined directly and by machine learning approaches. In this review we examine the somewhat confusing available literature and relate published experimental data to the most recent gene annotation of E. coli to describe the predicted and experimental proteome of each compartment. The problem of characterizing integral versus membrane-associated proteins is discussed. The E. coli envelope proteome provides an excellent test bed for developing mass spectrometric techniques for identifying hydrophobic proteins that have generally been refractory to analysis. We describe the gel based and solution based proteome analysis approaches along with protein cleavage and proteolysis methods that investigators are taking to tackle this difficult problem.     

Quantification of proteomic and metabolic burdens predicts growth retardation and overflow metabolism in recombinant Escherichia coli

Escherichia coli has been the host organism most frequently investigated for efficient recombinant protein production. However, the production of a foreign protein in recombinant E. coli often leads to growth deterioration and elevated secretion of acetic acid. Such observed phenomena have been widely linked with cell stress responses and metabolic burdens originated particularly from the increased energy demand. In this study, flux balance analysis and dynamic flux balance analysis were applied to investigate the observed growth physiology of recombinant E. coli, incorporating the proteome allocation theory and an adjustable maintenance energy level (ATPM) to capture the proteomic and energetic burdens introduced by recombinant protein synthesis. Model predictions of biomass growth, substrate consumption, acetate excretion, and protein production with two different strains were in good agreement with the experimental data, indicating that the constraint on the available proteomic resource and the change in ATPM might be important contributors governing the growth physiology of recombinant strains. The modeling framework developed in this work, currently with several limitations to overcome, offers a starting point for the development of a practical, model-based tool to guide metabolic engineering decisions for boosting recombinant protein production.     

Proteomic analysis of <Emphasis Type="Italic">Escherichia coli</Emphasis> protein fractions resistant to solubilization by ionic detergents

Amyloids are protein fibrils adopting structure of cross-beta spine exhibiting either pathogenic or functionally significant properties. In prokaryotes, there are several groups of functional amyloids; however, all of them were identified by specialized approaches that do not reveal all cellular amyloids. Here, using our previously developed PSIA (Proteomic Screening and Identification of Amyloids) approach, we have conducted a proteomic screening for candidates for novel amyloid-forming proteins in Escherichia coli as one of the most important model organisms and biotechnological objects. As a result, we identified 61 proteins in fractions resistant to treatment with ionic detergents. We found that a fraction of proteins bearing potentially amyloidogenic regions predicted by bioinformatics algorithms was 3-5-fold more abundant among the identified proteins compared to those observed in the entire E. coli proteome. Almost all identified proteins contained potentially amyloidogenic regions, and four of them (BcsC, MukB, YfbK, and YghJ) have asparagineand glutamine-rich regions underlying a crucial feature of many known amyloids. In this study, we demonstrate for the first time that at the proteome level there is a correlation between experimentally demonstrated detergent-resistance of proteins and potentially amyloidogenic regions predicted by bioinformatics approaches. The data obtained enable further comprehensive characterization of entirety of amyloids (or amyloidome) in bacterial cells.     

Web-accessible proteome databases for microbial research

The analysis of proteomes of biological organisms represents a major challenge of the post-genome era. Classical proteomics combines two-dimensional electrophoresis (2-DE) and mass spectrometry (MS) for the identification of proteins. Novel technologies such as isotope coded affinity tag (ICAT)-liquid chromatography/mass spectrometry (LC/MS) open new insights into protein alterations. The vast amount and diverse types of proteomic data require adequate web-accessible computational and database technologies for storage, integration, dissemination, analysis and visualization. A proteome database system (http://www.mpiib-berlin.mpg.de/2D-PAGE) for microbial research has been constructed which integrates 2-DE/MS, ICAT-LC/MS and functional classification data of proteins with genomic, metabolic and other biological knowledge sources. The two-dimensional polyacrylamide gel electrophoresis database delivers experimental data on microbial proteins including mass spectra for the validation of protein identification. The ICAT-LC/MS database comprises experimental data for protein alterations of mycobacterial strains BCG vs. H37Rv. By formulating complex queries within a functional protein classification database "FUNC_CLASS" for Mycobacterium tuberculosis and Helicobacter pylori the researcher can gather precise information on genes, proteins, protein classes and metabolic pathways. The use of the R language in the database architecture allows high-level data analysis and visualization to be performed "on-the-fly". The database system is centrally administrated, and investigators without specific bioinformatic competence in database construction can submit their data. The database system also serves as a template for a prototype of a European Proteome Database of Pathogenic Bacteria. Currently, the database system includes proteome information for six strains of microorganisms.     

Protein folding stabilities are a major determinant of oxidation rates for buried methionine residues

The oxidation of protein-bound methionines to form methionine sulfoxides has a broad range of biological ramifications, making it important to delineate factors that influence methionine oxidation rates within a given protein. This is especially important for biopharmaceuticals, where oxidation can lead to deactivation and degradation. Previously, neighboring residue effects and solvent accessibility have been shown to impact the susceptibility of methionine residues to oxidation. In this study, we provide proteome-wide evidence that oxidation rates of buried methionine residues are also strongly influenced by the thermodynamic folding stability of proteins. We surveyed the Escherichia coli proteome using several proteomic methodologies and globally measured oxidation rates of methionine residues in the presence and absence of tertiary structure, as well as the folding stabilities of methionine-containing domains. These data indicated that buried methionines have a wide range of protection factors against oxidation that correlate strongly with folding stabilities. Consistent with this, we show that in comparison to E. coli, the proteome of the thermophile Thermus thermophilus is significantly more stable and thus more resistant to methionine oxidation. To demonstrate the utility of this correlation, we used native methionine oxidation rates to survey the folding stabilities of E. coli and T. thermophilus proteomes at various temperatures and propose a model that relates the temperature dependence of the folding stabilities of these two species to their optimal growth temperatures. Overall, these results indicate that oxidation rates of buried methionines from the native state of proteins can be used as a metric of folding stability.     

Putting the Pieces Together: High-performance LC-MS/MS Provides Network-, Pathway-, and Protein-level Perspectives in Populus

High-performance mass spectrometry (MS)-based proteomics enabled the construction of a detailed proteome atlas for Populus, a woody perennial plant model organism. Optimization of experimental procedures and implementation of current state-of-the-art instrumentation afforded the most detailed look into the predicted proteome space of Populus, offering varying proteome perspectives: (1) network-wide, (2) pathway-specific, and (3) protein-level viewpoints. Together, enhanced protein retrieval through a detergent-based lysis approach and maximized peptide sampling via the dual-pressure linear ion trap mass spectrometer (LTQ Velos), have resulted in the identification of 63,056 tryptic peptides. The technological advancements, specifically spectral-acquisition and sequencing speed, afforded the deepest look into the Populus proteome, with peptide abundances spanning 6 orders of magnitude and mapping to ∼25% of the predicted proteome space. In total, tryptic peptides mapped to 11,689 protein assignments across four organ-types: mature (fully expanded, leaf plastichronic index (LPI) 10–12) leaf, young (juvenile, LPI 4–6) leaf, root, and stem. To resolve protein ambiguity, identified proteins were grouped by sequence similarity (≥ 90%), thereby reducing the protein assignments into 7538 protein groups. In addition, this large-scale data set features the first systems-wide survey of protein expression across different Populus organs. As a demonstration of the precision and comprehensiveness of the semiquantitative analysis, we were able to contrast two stages of leaf development, mature versus young leaf. Statistical comparison through ANOVA analysis revealed 1432 protein groups that exhibited statistically significant (p ≤ 0.01) differences in protein abundance. Experimental validation of the metabolic circuitry expected in mature leaf (characterized by photosynthesis and carbon fixation) compared with young leaf (characterized by rapid growth and moderate photosynthetic activities) strongly testifies to the credibility of the approach. Instead of quantitatively comparing a few proteins, a systems view of all the changes associated with a given cellular perturbation could be made.Mass spectrometry (MS)-based proteomics has experienced tremendous growth in recent years, leading to the establishment of numerous protocols, platforms, and workflows for the characterization of protein expression at the genome level (1). Although these advancements have facilitated comprehensive proteomic investigations of simple bacterial isolates and microbial communities, the application of MS-based proteomics for plants and other higher eukaryotes remains underdeveloped. Recently, large-scale proteomic studies have been directed at characterization of Populus, a woody perennial model organism. With the recent release and subsequent curation of the P. trichocarpa genome (2), these large-scale MS-based proteomic investigations offer the potential to introduce new biological insights into woody perennial plant biology (3, 4, 5). For example, we have recently demonstrated the ability to measure ∼17% of the Populus proteome by coupling multidimensional liquid chromatography (MudPIT)¹ with nano-electrospray tandem mass spectrometry (2D-LC-MS/MS) (6). Relative to the two-dimensional gel-based approaches (7), MudPIT provides enhanced separation and when used in conjunction with MS/MS, surpasses the throughput and number of identifiable proteins detected in complex mixtures (8). Although we have demonstrated the general effectiveness of this approach, the identification and quantitation of the proteins expressed in a plant cell or tissue are still notoriously complicated by a number of factors, including the size and complexity of plant genomes, abundance of protein variants, as well as the dynamic range of protein identification. To overcome these challenges, improvements are needed in sample preparation, MS instrumentation, and data interpretation.The architecture of plant cell walls provides resistance to chemical and biological degradation, thus requiring mechanical and detergent-based lysis for optimal proteome analysis. However, this criterion presents a major challenge for plant proteomic research using electrospray mass spectrometry, as detergent-containing solutions can impede enzymatic digestion and cause significant analyte suppression (9). Therefore, most plant proteomic studies using the “MudPIT” strategy apply mechanical disruption in conjunction with a detergent-free preparation method (10). Typically, strong chaotropic agents such as urea and guanidine hydrochloride are used for the extraction, denaturation, and digestion of proteins. In a recent study, Mann et al. (2009) introduced a filter-aided sample preparation (FASP) method that uses and effectively removes sodium dodecyl sulfate (SDS) before enzymatic digestion and electrospray analysis (11). This study demonstrated enhanced retrieval of peptides from biological materials, yielding a more accurate representation of the proteome. We developed a similar experimental approach for extraction of proteins from plant tissue to obtain a more comprehensive, unbiased proteome characterization well beyond that achievable with currently available methods. Similar to the FASP method, we demonstrate the power of SDS for proteomic sample preparation, not only in its ability to more-thoroughly lyse cells, but also its ability to better solubilize both hydrophilic and hydrophobic proteins. This powerful attribute gives proteolytic enzymes maximum opportunity to generate peptides specific to their cleavage potential so that at least a few representative peptides can be obtained for proteins that would have otherwise been discarded or lost because of insolubility, e.g. membrane-bound proteins. Rather than performing a buffer exchange with urea, depletion of SDS is achieved by precipitating proteins out of solution using trichloroacetic acid.Characterization of protein expression in plants is further complicated by the heterogeneous mixture of various cell types, each with a unique proteome signature and individualized response to environmental chemical or physical signals. This inherent complexity of plant proteomes and the large dynamic range in protein abundance overwhelms current analytical platforms (12). Moreover, biochemical regulatory networks in plants are more elaborate and dynamic than in microbial species; consequently, many biological components are left undiscovered, including modified peptides and low-abundance proteins (13, 14, 15). Recent developments in ion-trap MS instrumentation, namely the dual-pressure linear ion trap mass spectrometer (LTQ Velos), have demonstrated improved ability to comprehensively characterize complex proteomics samples (16). Featuring a newly designed ion source and a two-chamber ion trap mass analyzer, the LTQ Velos achieves greater dynamic range, sensitivity, and speed of spectral acquisition when applied to complex proteomic samples. Cumulatively, the technological advancements afford substantial increases in the detection and identification of both proteins and unique peptides when compared with existing state-of-the-art technologies. Therefore, to satisfy the need for depth of proteome characterization in plants, we apply the newly developed LTQ Velos for mass spectrometry measurements of the Populus proteome.For most terrestrial plants, life begins and ends in the same physical location. For woody perennial plants, this sedentary lifestyle may last thousands of years. One consequence of this lifestyle is that each plant typically experiences dramatic changes in its ambient environment throughout its lifetime and, at any given time, equilibrium between endogenous growth processes and exogenous constraints exerted by the environment must be tightly controlled. To survive under varying environmental conditions, temporal plastic responses evoke patterns of protein expression that progressively influence morphological, anatomical, and functional traits of three principal organs—leaf, root, and stem. Collectively and individually, these organs operate to perceive and respond to periodic and chronic environment conditions. Currently, a comprehensive understanding of the spatial variation in protein expression patterns across the organ types is lacking for woody perennial plants, in which most large-scale proteome analyses with Populus were performed on isolated organs, tissues, organelles, or subcellular structures. For this reason, we combined the state-of-the-art LTQ-Velos platform with the SDS/TCA sample preparation methodology to generate a high-coverage proteome atlas of the principal organ types from Populus.     

The optimisation and application of a metabolite profiling procedure for the metabolic phenotyping of Bacillus species

The rapid advances in sequencing technologies over the last decade have enabled routine sequencing of microbial genomes. Despite notable achievements, metabolomics/metabolite profiling has not progressed with the same rapidity, which in part is due to the intrinsic complex chemical nature of the metabolome. However, well characterised metabolomes are essential if a comprehensive understanding of biological function and biotechnological applications are to be revealed and implemented. In the present study a hyphenated MS metabolite profiling procedure has been developed, predominantly for Bacillus species. The approach has been systematic in its development, delivering optimised procedures for the quenching of bacterial metabolism, extraction of metabolites, the separation and detection of components as well as data analysis, integration and visualisation workflows. Collectively, the procedure has enabled the detection of 27 % of the predicted Bacillus subtilis metabolome in the industrial HU36 strain. The analytical platform developed has been used to assess the chemotype of commercially used probiotic Bacillus strains, including a novel pigmented Bacillus strain HU36 that has potential either as a probiotic or source of antioxidants. The results are discussed in a biochemical context, revealing: (i), specific metabolic networks associated with pigment biosynthesis in HU36 and (ii), biotechnological applications through the demonstration of substantial equivalence.     

In vivo assessment and potential diagnosis of xenobiotics that perturb the thyroid pathway: Proteomic analysis of Xenopus laevis brain tissue following exposure to model T4 inhibitors

As part of a multi-endpoint systems approach to develop comprehensive methods for assessing endocrine stressors in vertebrates, differential protein profiling was used to investigate expression patterns in the brain of the amphibian model (Xenopus laevis) following in vivo exposure to a suite of T4 synthesis inhibitors. We specifically address the application of Two Dimensional Polyacrylamide Gel Electrophoresis (2D PAGE), Isobaric Tags for Relative and Absolute Quantitation (iTRAQ®) and LC–MS/MS to assess changes in relative protein expression levels. 2D PAGE and iTRAQ proved to be effective complementary techniques for distinguishing protein changes in the developing amphibian brain in response to T4 synthesis inhibition. This information served to evaluate the use of distinctive protein profiles as a potential mechanism to screen chemicals for endocrine activity in anurans. Regulatory pathways associated with proteins expressed as a result of chemical effect are reported. To our knowledge, this is also the first account of the anuran larvae brain proteome characterization using proteomic technologies. Correlation of protein changes to other cellular and organism-level responses will aid in the development of a more rapid and cost-effective, non-mammalian screening assay for thyroid axis-disrupting chemicals.     

Proteome analysis of the plant-pathogenic bacterium Xanthomonas oryzae pv. oryzae

The plant-pathogenic bacterium Xanthomonas oryzae pv. oryzae (Xoo) is the causal agent of bacterial blight, which is one of the most serious diseases of rice. Xoo has been studied for over one century, and much has been learned about it, but proteomic investigation has been neglected. In this study, proteome reference maps of Xoo were constructed by two-dimensional gel electrophoresis, and 628 spots in the gels representing 469 different protein species were identified with MALDI-TOF/TOF MS. The identified spots were assigned to 15 functional categories according to the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and the annotations from the National Center for Biotechnology Information (NCBI) database. The data set has been deposited in the World-2DPAGE database (Database ID: 0044). In addition, comparative proteomic analysis revealed that proteins related to the TonB-dependent transportation system and energy metabolism are involved in the phenazine-1-carboxylic acid resistance in Xoo. In conclusion, we have established a proteome database for Xoo and have used this database in a comparative proteomic analysis that identified proteins potentially contributing to phenazine-1-carboxylic acid resistance in Xoo.     

Global Identification of Prokaryotic Glycoproteins Based on an Escherichia coli Proteome Microarray

Glycosylation is one of the most abundant protein posttranslational modifications. Protein glycosylation plays important roles not only in eukaryotes but also in prokaryotes. To further understand the roles of protein glycosylation in prokaryotes, we developed a lectin binding assay to screen glycoproteins on an Escherichia coli proteome microarray containing 4,256 affinity-purified E.coli proteins. Twenty-three E.coli proteins that bound Wheat-Germ Agglutinin (WGA) were identified. PANTHER protein classification analysis showed that these glycoprotein candidates were highly enriched in metabolic process and catalytic activity classes. One sub-network centered on deoxyribonuclease I (sbcB) was identified. Bioinformatics analysis suggests that prokaryotic protein glycosylation may play roles in nucleotide and nucleic acid metabolism. Fifteen of the 23 glycoprotein candidates were validated by lectin (WGA) staining, thereby increasing the number of validated E. coli glycoproteins from 3 to 18. By cataloguing glycoproteins in E.coli, our study greatly extends our understanding of protein glycosylation in prokaryotes.     

From coarse to fine: the absolute Escherichia coli proteome under diverse growth conditions

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data‐independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non‐metabolic stresses, and non‐planktonic states. The resulting high‐quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low‐abundant proteins under various metabolic limitations, the non‐specificity of catabolic enzymes upregulated under carbon limitation, the lack of large‐scale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain‐dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi‐omics studies of gene regulation and metabolic control in E. coli.     

Characterizing phosphoproteins and phosphoproteomes using mass spectrometry.

The reversible phosphorylation of proteins plays a major role in many vital cellular processes by modulating protein function and transmitting signals within cellular pathways and networks. Because phosphorylation is dynamic and the sites of modification cannot be predicted by an organism's genome, proteomic measurements are required to identify sites of and changes in the phosphorylation state of proteins. The low stoichiometry of phosphorylation sites that accompany the multifarious nature of protein phosphorylation in biological systems continues to challenge the dynamic range of present mass spectrometry (MS) technologies and proteomic measurements, despite the preponderance of research and analytical methods devoted to this area. This review addresses some of the strategies and limitations involving the use of MS to map and quantify changes in protein phosphorylation sites for samples that range from a single protein to an entire proteome, and presents several compelling reasons as to why comprehensive phosphorylation site analysis has proven to be so elusive without a hypothesis-driven experimental approach to elicit more meaningful and confident results.     

The Modular Organization of Protein Interactions in Escherichia coli

Escherichia coli serves as an excellent model for the study of fundamental cellular processes such as metabolism, signalling and gene expression. Understanding the function and organization of proteins within these processes is an important step towards a ‘systems’ view of E. coli. Integrating experimental and computational interaction data, we present a reliable network of 3,989 functional interactions between 1,941 E. coli proteins (∼45% of its proteome). These were combined with a recently generated set of 3,888 high-quality physical interactions between 918 proteins and clustered to reveal 316 discrete modules. In addition to known protein complexes (e.g., RNA and DNA polymerases), we identified modules that represent biochemical pathways (e.g., nitrate regulation and cell wall biosynthesis) as well as batteries of functionally and evolutionarily related processes. To aid the interpretation of modular relationships, several case examples are presented, including both well characterized and novel biochemical systems. Together these data provide a global view of the modular organization of the E. coli proteome and yield unique insights into structural and evolutionary relationships in bacterial networks.     

The 15N isotope effect in Escherichia coli: A neutron can make the difference

Several techniques based on stable isotope labeling are used for quantitative MS. These include stable isotope metabolic labeling methods for cells in culture as well as live organisms with the assumption that the stable isotope has no effect on the proteome. Here, we investigate the ¹⁵N isotope effect on Escherichia coli cultures that were grown in either unlabeled (¹⁴N) or ¹⁵N‐labeled media by LC‐ESI‐MS/MS‐based relative protein quantification. Consistent protein expression level differences and altered growth rates were observed between ¹⁴N and ¹⁵N‐labeled cultures. Furthermore, targeted metabolite analyses revealed altered metabolite levels between ¹⁴N and ¹⁵N‐labeled bacteria. Our data demonstrate for the first time that the introduction of the ¹⁵N isotope affects protein and metabolite levels in E. coli and underline the importance of implementing controls for unbiased protein quantification using stable isotope labeling techniques.     

Deep Profiling of Cellular Heterogeneity by Emerging Single‐Cell Proteomic Technologies

The ability to comprehensively profile cellular heterogeneity in functional proteome is crucial in advancing the understanding of cell behavior, organism development, and disease mechanisms. Conventional bulk measurement by averaging the biological responses across a population often loses the information of cellular variations. Single‐cell proteomic technologies are becoming increasingly important to understand and discern cellular heterogeneity. The well‐established methods for single‐cell protein analysis based on flow cytometry and fluorescence microscopy are limited by the low multiplexing ability owing to the spectra overlap of fluorophores for labeling antibodies. Recent advances in mass spectrometry (MS), microchip, and reiterative staining‐based techniques for single‐cell proteomics have enabled the evaluation of cellular heterogeneity with high throughput, increased multiplexity, and improved sensitivity. In this review, the principles, developments, advantages, and limitations of these advanced technologies in analysis of single‐cell proteins, along with their biological applications to study cellular heterogeneity, are described. At last, the remaining challenges, possible strategies, and future opportunities that will facilitate the improvement and broad applications of single‐cell proteomic technologies in cell biology and medical research are discussed.     

Escherichia coli Proteome Microarrays Identified the Substrates of ClpYQ Protease

Proteolysis is a vital mechanism to regulate the cellular proteome in all kingdoms of life, and ATP-dependent proteases play a crucial role within this process. In Escherichia coli, ClpYQ is one of the primary ATP-dependent proteases. In addition to function with removals of abnormal peptides in the cells, ClpYQ degrades regulatory proteins if necessary and thus let cells adjust to various environmental conditions. In E. coli, SulA, RcsA, RpoH and TraJ as well as RNase R, have been identified as natural protein substrates of ClpYQ. ClpYQ contains ClpY and ClpQ. The ATPase ClpY is responsible for protein recognition, unfolding, and translocation into the catalytic core of ClpQ. In this study, we use an indirect identification strategy to screen possible ClpY targets with E. coli K12 proteome chips. The chip assay results showed that YbaB strongly bound to ClpY. We used yeast two-hybrid assay to confirm the interactions between ClpY and YbaB protein and determined the K_d between ClpY and YbaB by quartz crystal microbalance. Furthermore, we validated that YbaB was successfully degraded by ClpYQ protease activity using ClpYQ in vitro and in vivo degradation assay. These findings demonstrated the YbaB is a novel substrate of ClpYQ protease. This work also successfully demonstrated that with the use of recognition element of a protease can successfully screen its substrates by indirect proteome chip screening assay.