Bacterial proteomics and its role in antibacterial drug discovery

Computational analysis of the effect of a binding protein (RbpA) on the dynamics of Mycobacterium tuberculosis RNA polymerase assembly

BACKGROUND

RNA polymerase-binding protein A (RbpA) is an actinomycetes-specific protein crucial for the growth and survival of the pathogen Mycobacterium tuberculosis. Its role is essential and influences the transcription and antibiotic responses. However, the regulatory mechanisms underlying RbpA-mediated transcription remain unknown. In this study, we employed various computational techniques to investigate the role of RbpA in the formation and dynamics of the RNA polymerase complex.

RESULTS

Our analysis reveals significant structural rearrangements in RNA polymerase happen upon interaction with RbpA. Hotspot residues, crucial amino acids in the RbpA-mediated transcriptional regulation, were identified through our examination. The study elucidates the dynamic behavior within the complex, providing insights into the flexibility and functional dynamics of the RbpA-RNA polymerase interaction. Notably, potential allosteric mechanisms, involving the interface of subunits α1 and α2 were uncovered, shedding light on how RbpA modulates transcriptional activity.

CONCLUSIONS

Finally, potential ligands meant for the α1-α2 binding site were identified through virtual screening. The outcomes of our computational study serve as a foundation for experimental investigations into inhibitors targeting the RbpA-regulated dynamics in RNA polymerase. Overall, this research contributes valuable information for understanding the intricate regulatory networks of RbpA in the context of transcription and suggests potential avenues for the development of RbpA-targeted therapeutics.

Recent Advances and Techniques for Identifying Novel Antibacterial Targets

BACKGROUND

With the emergence of drug-resistant bacteria, the development of new antibiotics is urgently required. Target-based drug discovery is the most frequently employed approach for the drug development process. However, traditional drug target identification techniques are costly and time-consuming. As research continues, innovative approaches for antibacterial target identification have been developed which enabled us to discover drug targets more easily and quickly.

METHODS

In this review, methods for finding drug targets from omics databases have been discussed in detail including principles, procedures, advantages, and potential limitations. The role of phage-driven and bacterial cytological profiling approaches is also discussed. Moreover, current article demonstrates the advancements being made in the establishment of computational tools, machine learning algorithms, and databases for antibacterial target identification.

RESULTS

Bacterial drug targets successfully identified by employing these aforementioned techniques are described as well.

CONCLUSION

The goal of this review is to attract the interest of synthetic chemists, biologists, and computational researchers to discuss and improve these methods for easier and quicker development of new drugs.

Classification of antimicrobial mechanism of action using dynamic bacterial morphology imaging

Antimicrobial resistance is a major threat to human health. Basic knowledge of antimicrobial mechanism of action (MoA) is imperative for patient care and for identification of novel antimicrobials. However, the process of antimicrobial MoA identification is relatively laborious. Here, we developed a simple, quantitative time-lapse fluorescence imaging method, Dynamic Bacterial Morphology Imaging (DBMI), to facilitate this process. It uses a membrane dye and a nucleoid dye to track the morphological changes of single Bacillus subtilis cells in response to antimicrobials for up to 60 min. DBMI of bacterial cells facilitated assignment of the MoAs of 14 distinct, known antimicrobial compounds to the five main classes. We conclude that DBMI is a simple method, which facilitates rapid classification of the MoA of antimicrobials in functionally distinct classes.

Exploration of Chemical Biology Approaches to Facilitate the Discovery and Development of Novel Antibiotics

Approximately 2.8 million people worldwide are infected with bacteria that are deemed resistant to clinically relevant antibiotics. This accounts for 700,000 deaths every year and represents a major public health threat that has been on the rise for the past two decades. In contrast, the pace of antibiotic discovery to treat these resistant pathogens has significantly decreased. Most antibiotics are complex natural products that were isolated from soil microorganisms during the golden era of antibiotic discovery (1940s to 1960s) employing the “Waksman platform”. After the collapse of this discovery platform, other strategies and approaches emerged, including phenotype- or target-based screenings of large synthetic compound libraries. However, these methods have not resulted in the discovery and/or development of new drugs for clinical use in over 30 years. A better understanding of the structure and function of the molecular components that constitute the bacterial system is of paramount importance to design new strategies to tackle drug-resistant pathogens. Herein, we review the traditional approaches as well as novel strategies to facilitate antibiotic discovery that are chemical biology-focused. These include the design and application of chemical probes that can undergo bioorthogonal reactions, such as copper (I)-catalyzed azide-alkyne cycloadditions (CuAAC). By specifically interacting with bacterial proteins or being incorporated in the microorganism’s metabolism, chemical probes are powerful tools in drug discovery that can help uncover new drug targets and investigate the mechanisms of action and resistance of new antibacterial leads.

Combining CRISPRi and metabolomics for functional annotation of compound libraries

Molecular profiling of small-molecules offers invaluable insights into the function of compounds and allows for hypothesis generation about small molecule direct targets and secondary effects. However, current profiling methods are either limited in the number of measurable parameters or throughput. Here, we developed a multiplexed, unbiased framework that, by linking genetic to drug-induced changes in nearly a thousand metabolites, allows for high-throughput functional annotation of compound libraries in Escherichia coli. First, we generated a reference map of metabolic changes from (CRISPR) interference with 352 genes in all major essential biological processes. Next, based on the comparison of genetic with 1342 drug-induced metabolic changes we made de novo predictions of compound functionality and revealed antibacterials with unconventional Modes of Action. We show that our framework, combining dynamic gene silencing with metabolomics, can be adapted as a general strategy for comprehensive high-throughput analysis of compound functionality, from bacteria to human cell lines.

Computational Study on the Dynamics of Mycobacterium Tuberculosis RNA Polymerase Assembly

Gene regulation is an intricate phenomenon involving precise function of many macromolecular complexes. Molecular basis of this phenomenon is highly complex and cannot be fully understood using a single technique. Computational approaches can play a crucial role in overall understanding of functional and mechanistic features of a protein or an assembly. Large amounts of structural data pertaining to these complexes are publicly available. In this project, we took advantage of the availability of the structural information to unravel functional intricacies of Mycobacterium tuberculosis RNA polymerase upon interaction with RbpA. In this article, we discuss how the knowledge on protein structure and dynamics can be exploited to study function using various computational tools and resources. Overall, this article provides an overview of various computational methods which can be efficiently used to understand the role of any protein. We hope especially the nonexperts in the field could benefit from our article.

Bacteriophages as Antimicrobial Agents? Proteomic Insights on Three Novel Lytic Bacteriophages Infecting ESBL-Producing Escherichia coli

With the emergence of multiresistant bacteria, the use of bacteriophages is gaining renewed interest as potential antimicrobial agents. The aim of this study was to analyze the structure of three lytic bacteriophages infecting Escherichia coli (SD1, SD2, and SD3) using a gel-based proteomics approach and the cellular response of this bacterium to phage SD1 infection at the proteome level. The combination of the results of 1-DE and 2-DE followed by mass spectrometry led to the identification of 3, 14, and 9 structure proteins for SD1, SD2, and SD3 phages, respectively. Different protein profiles with common proteins were noticed. We also analyzed phage-induced effects by comparing samples from infected cells to those of noninfected cells. We verified important changes in E. coli proteins expression during phage SD1 infection, where there was an overexpression of proteins involved in stress response. Our results indicated that viral infection caused bacterial oxidative stress and bacterial cells response to stress was orchestrated by antioxidant defense mechanisms. This article makes an empirical scientific contribution toward the concept of bacteriophages as potential antimicrobial agents. With converging ecological threats in the 21st century, novel approaches to address the innovation gaps in antimicrobial development are more essential than ever. Further research on bacteriophages is called for in this broader context of planetary health and integrative biology.

Technologies for High-Throughput Identification of Antibiotic Mechanism of Action

There are two main strategies for antibiotic discovery: target-based and phenotypic screening. The latter has been much more successful in delivering first-in-class antibiotics, despite the major bottleneck of delayed Mechanism-of-Action (MOA) identification. Although finding new antimicrobial compounds is a very challenging task, identifying their MOA has proven equally challenging. MOA identification is important because it is a great facilitator of lead optimization and improves the chances of commercialization. Moreover, the ability to rapidly detect MOA could enable a shift from an activity-based discovery paradigm towards a mechanism-based approach. This would allow to probe the grey chemical matter, an underexplored source of structural novelty. In this study we review techniques with throughput suitable to screen large libraries and sufficient sensitivity to distinguish MOA. In particular, the techniques used in chemical genetics (e.g., based on overexpression and knockout/knockdown collections), promoter-reporter libraries, transcriptomics (e.g., using microarrays and RNA sequencing), proteomics (e.g., either gel-based or gel-free techniques), metabolomics (e.g., resourcing to nuclear magnetic resonance or mass spectrometry techniques), bacterial cytological profiling, and vibrational spectroscopy (e.g., Fourier-transform infrared or Raman scattering spectroscopy) were discussed. Ultimately, new and reinvigorated phenotypic assays bring renewed hope in the discovery of a new generation of antibiotics.

Predicting antimicrobial mechanism-of-action from transcriptomes: A generalizable explainable artificial intelligence approach

To better combat the expansion of antibiotic resistance in pathogens, new compounds, particularly those with novel mechanisms-of-action [MOA], represent a major research priority in biomedical science. However, rediscovery of known antibiotics demonstrates a need for approaches that accurately identify potential novelty with higher throughput and reduced labor. Here we describe an explainable artificial intelligence classification methodology that emphasizes prediction performance and human interpretability by using a Hierarchical Ensemble of Classifiers model optimized with a novel feature selection algorithm called Clairvoyance; collectively referred to as a CoHEC model. We evaluated our methods using whole transcriptome responses from Escherichia coli challenged with 41 known antibiotics and 9 crude extracts while depositing 122 transcriptomes unique to this study. Our CoHEC model can properly predict the primary MOA of previously unobserved compounds in both purified forms and crude extracts at an accuracy above 99%, while also correctly identifying darobactin, a newly discovered antibiotic, as having a novel MOA. In addition, we deploy our methods on a recent E. coli transcriptomics dataset from a different strain and a Mycobacterium smegmatis metabolomics timeseries dataset showcasing exceptionally high performance; improving upon the performance metrics of the original publications. We not only provide insight into the biological interpretation of our model but also that the concept of MOA is a non-discrete heuristic with diverse effects for different compounds within the same MOA, suggesting substantial antibiotic diversity awaiting discovery within existing MOA.

Proteomics of Brucella: Technologies and Their Applications for Basic Research and Medical Microbiology

Brucellosis is a global zoonosis caused by Gram-negative, facultative intracellular bacteria of the genus Brucella (B.). Proteomics has been used to investigate a few B. melitensis and B. abortus strains, but data for other species and biovars are limited. Hence, a comprehensive analysis of proteomes will significantly contribute to understanding the enigmatic biology of brucellae. For direct identification and typing of Brucella, matrix-assisted laser desorption ionization - time of flight mass spectrometry (MALDI - TOF MS) has become a reliable tool for routine diagnosis due to its ease of handling, price and sensitivity highlighting the potential of proteome-based techniques. Proteome analysis will also help to overcome the historic but still notorious Brucella obstacles of infection medicine, the lack of safe and protective vaccines and sensitive serologic diagnostic tools by identifying the most efficient protein antigens. This perspective summarizes past and recent developments in Brucella proteomics with a focus on species identification and serodiagnosis. Future applications of proteomics in these fields are discussed.

Proteomic profiling unveils citral modulating expression of IsaA, CodY and SaeS to inhibit biofilm and virulence in methicillin-resistant Staphylococcus aureus

Methicillin-resistant Staphylococcus aureus (MRSA) is one of the dangerous human pathogens and it is categorized as a high priority multi-drug resistant bacterium by WHO. Biofilm forming ability of MRSA is responsible for persistent infections and also difficult to eradicate using antibiotic therapy as biofilm is much more resistant to antibiotics. Thus, targeting biofilm and virulence has become an alternative approach to attenuate the pathogenicity of bacterium without affecting the growth. Hence, the present study was aimed at evaluation of antibiofilm potential of citral against MRSA and to decode the possible mode of action. Citral inhibited biofilm formation by MRSA without affecting growth at 100 μg/mL. Microscopic analyses evidenced that citral greatly hampered the surface adherence of MRSA. Effect of citral on cellular proteome of MRSA was studied using two-dimensional gel electrophoresis (2DGE) and differentially regulated proteins were identified using nano LC-MS/MS and MALDI-TOF/TOF analysis. Gene ontology and STRING analysis revealed that citral differentially regulated the proteins involved in pleotropic transcriptional repression (CodY), cell wall homeostasis (IsaA), regulation of exotoxin secretion (SaeS), cell adhesion, hemolysis, capsular polysaccharide biosynthesis and pathogenesis. Gene expression analysis and in vitro assays further validated the alteration in synthesis of slime, hemolysin, lipase, staphyloxanthin and oxidant susceptibility. Thus, the present study unveiled the multiple protein targeted antibiofilm potential of citral and portrays citral as a promising therapeutic agent to combat biofilm mediated MRSA infections with less possibility of resistance development.

Comparative proteomic analysis reveals drug resistance of Staphylococcus xylosus ATCC700404 under tylosin stress

Background

As a kind of opportunist pathogen, Staphylococcus xylosus (S. xylosus) can cause mastitis. Antibiotics are widely used for treating infected animals and tylosin is a member of such group. Thus, the continuous use of antibiotics in dairy livestock enterprise will go a long way in increasing tylosin resistance. However, the mechanism of tylosin-resistant S. xylosus is not clear. Here, isobaric tag for relative and absolute quantitation (iTRAQ)-based quantitative proteomics methods was used to find resistance-related proteins.

Results

We compared the differential expression of S. xylosus in response to tylosin stress by iTRAQ. A total of 155 proteins (59 up-regulated, 96 down-regulated) with the fold-change of >1.2 or <0.8 (p value ≤0.05) were observed between the S. xylosus treated with 1/2 MIC (0.25 μg/mL) tylosin and the untreated S. xylosus. Bioinformatic analysis revealed that these proteins play important roles in stress-response and transcription. Then, in order to verify the relationship between the above changed proteins and mechanism of tylosin-resistant S. xylosus, we induced the tylosin-resistant S. xylosus, and performed quantitative PCR analysis to verify the changes in the transcription proteins and the stress-response proteins in tylosin-resistant S. xylosus at the mRNA level. The data displayed that ribosomal protein L23 (rplw), thioredoxin(trxA) and Aldehyde dehydrogenase A(aldA-1) are up-regulated in the tylosin-resistant S. xylosus, compared with the tylosin-sensitive strains.

Conclusion

Our findings demonstrate the important of stress-response and transcription in the tylosin resistance of S. xylosus and provide an insight into the prevention of this resistance, which would aid in finding new medicines .

Electronic supplementary material

The online version of this article (10.1186/s12917-019-1959-9) contains supplementary material, which is available to authorized users.

Stress response of Escherichia coli to essential oil components - insights on low-molecular-weight proteins from MALDI-TOF

The antibacterial effects of essential oils and their components (EOCs) are usually attributed to effects on membranes and metabolism. Studies of the effects of EOCs on protein expression have primarily analysed proteins larger than 10 kDa using gel electrophoresis. In the present study, we used MALDI-TOF-MS to investigate the effects of EOCs on low-molecular-weight proteins. From 297 m/z features, we identified 94 proteins with important differences in expression among untreated samples, samples treated with EOCs, and samples treated with antibiotics, peroxide, or chlorine. The targets of these treatments obviously differ, even among EOCs. In addition to ribosomal proteins, stress-, membrane- and biofilm-related proteins were affected. These findings may provide a basis for identifying new targets of essential oils and synergies with other antibiotics.

Proteomic Signatures in Staphylococcus aureus

Despite all its apparent limitations proteome analysis based on two-dimensional protein gels combined with mass spectrometry is still the method of choice to study global protein synthesis activity in bacterial cells. Alterations in global protein synthesis play an important role during adaptation of bacteria to changing environmental conditions which are rather the role than the exception in their natural habitats. The protein synthesis pattern in response to a certain stimulus is highly specific and reflects the new challenges the bacterium has to meet. Here we present the techniques to analyze global protein synthesis in bacteria as exemplified by Staphylococcus aureus which is an important human pathogen and one main cause of nosocomial infections with severe outcome.

Preclinical Assessment of a 68Ga-DOTA-Functionalized Depsipeptide as a Radiodiagnostic Infection Imaging Agent

The study assessed a radiolabeled depsipeptide conjugate (⁶⁸Ga-DOTA-TBIA101) for its potential as an imaging agent targeting infection or infection-associated inflammation. ⁶⁸Ga-labeled DOTA-TBIA101 imaging was performed in (NZR1) healthy rabbits; (NZR2) rabbits bearing muscular sterile inflammation and Staphylococcus aureus (SA) infection; and (NZR3) rabbits infected with Mycobacterium tuberculosis (MTB) combined with a subcutaneous scruff infection of SA in the same animal. All animals were imaged using a PET/CT scanner at 5 and 60 min post injection. Images showed elevated accumulation of ⁶⁸Ga-DOTA-TBIA101 in the sterile muscular inflammation site (T/NT ratio = 2.6 ± 0.37 (5 min) and 2.8 ± 2.3 (60 min)) and muscles infected with MTB (T/NT ratio = 2.6 ± 0.35 (5 min) and 2.8 ± 0.16 (60 min)). The findings suggest that ⁶⁸Ga-DOTA-TBIA101-PET/CT may detect MTB-associated inflammation, although more foundational studies need to be performed to rationalize the diagnostic value of this technique.

Proteomics Evidence for the Activity of the Putative Antibacterial Plant Alkaloid (-)-Roemerine: Mainstreaming Omics-Guided Drug Discovery

Discovery of new antibacterials with novel mechanisms is important to counteract the ingenious resistance mechanisms of bacteria. In this connection, omics-guided drug discovery offers a rigorous method in the quest of new antibacterials. (-)-Roemerine is a plant alkaloid that has been reported to possess putative antibacterial activity against Escherichia coli, Bacillus subtilis, and Salmonella typhimurium. The aim of the present study was to characterize the activity of (-)-roemerine in Escherichia coli TB1 using proteomics tools. With (-)-roemerine treatment, we found limited permeability through the outer membrane and repression of transport proteins involved in carbohydrate metabolism, resulting in poor carbon source availability. The shortfall of intracellular carbon sources in turn led to impaired cell growth. The reduction in the abundance of proteins related to translational machinery, amino acid biosynthesis, and metabolism was accompanied by a nutrient-limited state. The latter finding could suggest a metabolic shutdown in E. coli cells. High osmolarity was clearly not one of the reasons of bacterial death by (-)-roemerine. These observations collectively attest to the promise of plant omics and profiling of putative drug candidates using proteomics tools. Omics-guided drug discovery deserves greater attention in mainstream pharmacology so as to better understand the plants' medicinal potentials.

Breaking the Spell: Combating Multidrug Resistant 'Superbugs'

Multidrug-resistant (MDR) bacteria have become a severe threat to community wellbeing. Conventional antibiotics are getting progressively more ineffective as a consequence of resistance, making it imperative to realize improved antimicrobial options. In this review we emphasized the microorganisms primarily reported of being resistance, referred as ESKAPE pathogens (Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Enterobacteriaceae) accentuating their capacity to "escape" from routine antimicrobial regimes. The upcoming antimicrobial agents showing great potential and can serve as alternative therapeutic options are discussed. We also provided succinct overview of two evolving technologies; specifically network pharmacology and functional genomics profiling. Furthermore, In vivo imaging techniques can provide novel targets and a real time tool for potential lead molecule assessment. The employment of such approaches at prelude of a drug development process, will enables more informed decisions on candidate drug selection and will maximize or predict therapeutic potential before clinical testing.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Application of zwitterionic detergent to the solubilization of Klebsiella pneumoniae outer membrane proteins for two-dimensional gel electrophoresis

Klebsiella pneumoniae is a frequent cause of nosocomial respiratory, urinary and gastrointestinal tract infections and septicemia with the multidrug-resistant K. pneumoniae being a major public health concern. Outer membrane proteins (OMPs) are important virulence factors responsible for the appropriate adaptation to the host environment. They constitute of the antigens being the first in contact with infected organism. However, K. pneumoniae strains are heavily capsulated and it is important to establish the OMPs isolation procedure prior to proteomics extensive studies. In this study we used Zwittergent Z 3-14® as a detergent to isolate the OMPs from K. pneumoniae cells and resolve them using two-dimensional electrophoresis (2-DE). As a result we identified 134 protein spots. The OMPs identified in this study are possible candidates for the development of a protein-based vaccine against K. pneumoniae infections.

After genomics, what proteomics tools could help us understand the antimicrobial resistance of Escherichia coli?

Proteomic approaches have been considerably improved during the past decade and have been used to investigate the differences in protein expression profiles of cells grown under a broad spectrum of growth conditions and with different stress factors including antibiotics. In Europe, the most significant disease threat remains the presence of microorganisms that have become resistant to antimicrobials and so it is important that different scientific tools are combined to achieve the largest amount of knowledge in this area of expertise. The emergence and spread of the antibiotic-resistant Gram-negative pathogens, such as Escherichia coli, can lead to serious problem public health in humans. E. coli, a very well described prokaryote, has served as a model organism for several biological and biotechnological studies increasingly so since the completion of the E. coli genome-sequencing project. The purpose of this review is to present an overview of the different proteomic approaches to antimicrobial-resistant E. coli that will be helpful to obtain a better knowledge of the antibiotic-resistant mechanism(s). This can also aid to understand the molecular determinants involved with pathogenesis, which is essential for the development of effective strategies to combat infection and to reveal new therapeutic targets. This article is part of a Special Issue entitled: Proteomics: The clinical link.

Proteomic signature of fatty acid biosynthesis inhibition available for in vivo mechanism-of-action studies

Fatty acid biosynthesis is a promising novel antibiotic target. Two inhibitors of fatty acid biosynthesis, platencin and platensimycin, were recently discovered and their molecular targets identified. Numerous structure-activity relationship studies for both platencin and platensimycin are currently being undertaken. We established a proteomic signature for fatty acid biosynthesis inhibition in Bacillus subtilis using platencin, platensimycin, cerulenin, and triclosan. The induced proteins, FabHA, FabHB, FabF, FabI, PlsX, and PanB, are enzymes involved in fatty acid biosynthesis and thus linked directly to the target pathway. The proteomic signature can now be used to assess the in vivo mechanisms of action of compounds derived from structure-activity relationship programs, as demonstrated for the platensimycin-inspired chromium bioorganometallic PM47. It will further serve as a reference signature for structurally novel natural and synthetic antimicrobial compounds with unknown mechanisms of action. In summary, we described a proteomic signature in B. subtilis consisting of six upregulated proteins that is diagnostic of fatty acid biosynthesis inhibition and thus can be applied to advance antibacterial drug discovery programs.

Challenges of antibacterial discovery

The discovery of novel small-molecule antibacterial drugs has been stalled for many years. The purpose of this review is to underscore and illustrate those scientific problems unique to the discovery and optimization of novel antibacterial agents that have adversely affected the output of the effort. The major challenges fall into two areas: (i) proper target selection, particularly the necessity of pursuing molecular targets that are not prone to rapid resistance development, and (ii) improvement of chemical libraries to overcome limitations of diversity, especially that which is necessary to overcome barriers to bacterial entry and proclivity to be effluxed, especially in Gram-negative organisms. Failure to address these problems has led to a great deal of misdirected effort.

Postgenomic strategies in antibacterial drug discovery

During the last decade the field of antibacterial drug discovery has changed in many aspects including bacterial organisms of primary interest, discovery strategies applied and pharmaceutical companies involved. Target-based high-throughput screening had been disappointingly unsuccessful for antibiotic research. Understanding of this lack of success has increased substantially and the lessons learned refer to characteristics of targets, screening libraries and screening strategies. The ‘genomics’ approach was replaced by a diverse array of discovery strategies, for example, searching for new natural product leads among previously abandoned compounds or new microbial sources, screening for synthetic inhibitors by targeted approaches including structure-based design and analyses of focused libraries and designing resistance-breaking properties into antibiotics of established classes. Furthermore, alternative treatment options are being pursued including anti-virulence strategies and immunotherapeutic approaches. This article summarizes the lessons learned from the genomics era and describes discovery strategies resulting from that knowledge.

Two-dimensional gels for toxicological drug discovery applications

Two-dimensional gel electrophoresis (2DGE) continues to be a useful approach to study protein expression. Although liquid chromatographic and mass spectrometric approaches that overcome some of the limitations and labour intensity of 2DGE are increasingly popular, this electrophoretic approach still has exceptional relevance in toxicology. Despite the technical challenges, pharmacologists/toxicologists continue to use gel-based proteomics to assess the biological and health effects of chemical treatment and exposure. This brief review addresses the use of 2DGE-based proteomics in drug development and toxicology, emphasising its unique strengths and weaknesses, and considers recent developments in this strategy that have evolved to directly confront the issues of dynamic range and reproducibility that have previously limited the overall use of 2D electrophoresis.

2-DE analysis indicates that Acinetobacter baumannii displays a robust and versatile metabolism

BACKGROUND

Acinetobacter baumannii is a nosocomial pathogen that has been associated with outbreak infections in hospitals. Despite increasing awareness about this bacterium, its proteome remains poorly characterised, however recently the complete genome of A. baumannii reference strain ATCC 17978 has been sequenced. Here, we have used 2-DE and MALDI-TOF/TOF approach to characterise the proteome of this strain.

RESULTS

The membrane and cytoplasmatic protein extracts were analysed separately, these analyses revealed the reproducible presence of 239 and 511 membrane and cytoplamatic protein spots, respectively. MALDI-TOF/TOF characterisation identified a total of 192 protein spots (37 membrane and 155 cytoplasmatic) and revealed that the identified membrane proteins were mainly transport-related proteins, whereas the cytoplasmatic proteins were of diverse nature, although mainly related to metabolic processes.

CONCLUSION

This work indicates that A. baumannii has a versatile and robust metabolism and also reveal a number of proteins that may play a key role in the mechanism of drug resistance and virulence. The data obtained complements earlier reports of A. baumannii proteome and provides new tools to increase our knowledge on the protein expression profile of this pathogen.

Integrative analysis of transcriptomic and proteomic data: challenges, solutions and applications

Recent advances in high-throughput technologies enable quantitative monitoring of the abundance of various biological molecules and allow determination of their variation between biological states on a genomic scale. Two popular platforms are DNA microarrays that measure messenger RNA transcript levels, and gel-free proteomic analyses that quantify protein abundance. Obviously, no single approach can fully unravel the complexities of fundamental biology and it is equally clear that integrative analysis of multiple levels of gene expression would be valuable in this endeavor. However, most integrative transcriptomic and proteomic studies have thus far either failed to find a correlation or only observed a weak correlation. In addition to various biological factors, it is suggested that the poor correlation could be quite possibly due to the inadequacy of available statistical tools to compensate for biases in the data collection methodologies. To address this issue, attempts have recently been made to systematically investigate the correlation patterns between transcriptomic and proteomic datasets, and to develop sophisticated statistical tools to improve the chances of capturing a relationship. The goal of these efforts is to enhance understanding of the relationship between transcriptomes and proteomes so that integrative analyses may be utilized to reveal new biological insights that are not accessible through one-dimensional datasets. In this review, we outline some of the challenges associated with integrative analyses and present some preliminary statistical solutions. In addition, some new applications of integrated transcriptomic and proteomic analysis to the investigation of post-transcriptional regulation are also discussed.

Transcriptome and proteome analyses in response to 2-methylhydroquinone and 6-brom-2-vinyl-chroman-4-on reveal different degradation systems involved in the catabolism of aromatic compounds inBacillus subtilis

Bacillus subtilis is exposed to a variety of antimicrobial compounds in the soil. In this paper, we report on the response of B. subtilis to the fungal-related antimicrobials 6-brom-2-vinyl-chroman-4-on (chromanon) and 2-methylhydroquinone (2-MHQ) using proteome and transcriptome analyses. Chromanon, a derivative of aposphaerins from Aposphaeria species caused predominant protein damage in B. subtilis as indicated by the induction of the HrcA, CtsR, and Spx regulons. The expression profile of the ganomycin-related substance 2-MHQ was similar to that of catechol as reflected by the common induction of the thiol-specific oxidative stress response. Several putative ring-cleavage dioxygenases and oxidoreductases were differentially up-regulated by 2-MHQ, catechol, and chromanon including yfiDE, ydfNOP, yodED, ycnDE, yodC, and ykcA. The nitroreductase encoding yodC gene is induced in response to catechol, 2-MHQ, and chromanon, which depend on the MarR-type repressor YodB. The yfiDE (catDE) operon encodes a catechol-2,3-dioxygenase which is most strongly induced by catechol. The yodED (mhqED), ydfNOP (mhqNOP) operons, and ykcA (mhqA) respond most strongly to 2-MHQ and encode putative hydroquinone-specific extradiol dioxygenases. The ycnDE operon was most strongly induced by chromanon. Mutational analyses revealed that the putative hydroquinone-specific dioxygenases MhqO and MhqA confer resistance to 2-MHQ in B. subtilis.

Proteomic profiling of cellular stresses in Bacillus subtilis reveals cellular networks and assists in elucidating antibiotic mechanisms of action

Proteomic profiling provides a global view of the protein composition of the cell. In contrast to the static nature of the genome sequence, which provides the blueprint for all protein-based cellular building blocks, the proteome is highly dynamic. The protein composition is constantly adjusting to facilitate survival, growth, and reproduction in an ever-changing environment. In a quest to understand the regulation of cellular networks in bacteria and the role of individual proteins in the adaptation process, the proteomic response to stress and starvation was analyzed in wild-type and mutant strains. The knowledge derived from these proteomic studies was applied to investigating the bacterial response to antibiotics. It was found that proteomics presents a powerful tool for hypothesis generation regarding antibiotic mechanism of action.

Comparative proteomics analysis to annexin B1 DNA and protein vaccination in mice

DNA vaccines have been widely reported to elicit both effective humoral and cellular immune responses, but the mechanisms of antigen processing and presentation in DNA immunization is still ambiguous. Aiming to molecular mechanisms involved in DNA immunization, comparative serum proteomics was introduced to discover differentially expressed proteins after different immunizations. Using two-dimensional electrophoresis and matrix-assisted laser desorption ionisation-time-of-flight mass spectrometry, 23 three-fold or greater up-regulated proteins were separated and identified, including 14 from ANXB1 DNA immunized mice and 9 from annexin B1 protein immunized mice. The histocompatibility class I molecule H2-Q10 (HA10_MOUSE) and proteasome activator PA28 alpha-subunit (PSME1_MOUSE) were found up-regulated in ANXB1 DNA immunized mice, which may contribute to the augmented activation of T lymphocytes. These proteins may serve as potential surrogate markers of successful vaccination and provide research targets for molecular mechanisms of vaccinology.

Technologies for bacterial surface proteomics

Proteins from bacterial membranes are notoriously difficult to analyze using the traditional technologies encompassed under the term 'proteomics'. This is because of several factors, including the comparatively low abundance of most membrane proteins within a complex mixture containing cytoplasmic metabolic enzymes, the poor solubility of membrane components such as phospholipids, lipopolysaccharides and peptidoglycans, and the inherent hydrophobicity of many integral membrane proteins that contain up to 15 transmembrane-spanning regions. Recent advances in gel-based and chromatographic separations, coupled with protein and peptide labelling and the exquisite sensitivity of mass spectrometry, are finally beginning to overcome these problems. New technologies in membrane proteomics enable comparative analysis of these recalcitrant proteins from bacteria under a variety of biological conditions.

Proteobionics: Biomimetics in Proteomics

Proteomics was established 10 years ago by the analysis of microbial genomes via their protein complement or proteome. Bionics is an ancient art, which converts structures optimized by nature into advanced technical products. Previously, we analyzed survival modalities in nanobacteria and converted the interplay between survival-oriented protein functions and nanoscale mineral shells into models for advanced drug delivery. Exploiting protein functions observed in nature to design biomedical products and therapies could be named proteobionics. Here, we present examples for this new branch of nanoproteomics.