Protein abundance ratios for global studies of prokaryotes

What are We Learning and What Can We Learn from the Human Oral Microbiome Project?

Extraordinary technological advances have greatly accelerated our ability to identify bacteria, at the species level, present in clinical samples taken from the human mouth. In addition, technologies are evolving such that the oral samples can be analyzed for their protein and metabolic products. As a result, pictures are the advent of personalized dental medicine is becoming closer to reality.

Effective correction of experimental errors in quantitative proteomics using stable isotope labeling by amino acids in cell culture (SILAC)

Accurate and reliable quantitative proteomics in cell culture has been considerably facilitated by the introduction of the stable isotope labeling by amino acids in cell culture (SILAC), combined with high resolution mass spectrometry. There are however several major sources of quantification errors that commonly occur with SILAC techniques, i.e. incomplete incorporation of isotopic amino acids, arginine-to-proline conversion, and experimental errors in final sample mixing. Dataset normalization is a widely adopted solution to such errors, however this may not completely prevent introducing incorrect expression ratios. Here we demonstrate that a label-swap replication of SILAC experiments was able to effectively correct experimental errors by averaging ratios measured in individual replicates using quantitative proteomics and phosphoproteomics of ligand treatment of neural cell cultures. Furthermore, this strategy was successfully applied to a SILAC triplet experiment, which presents a much more complicated experimental matrix, affected by both incomplete labeling and arginine-to-proline conversion. Based on our results, we suggest that SILAC experiments should be designed to incorporate label-swap replications for enhanced reliability in expression ratios.

Proteomics of bacterial pathogenicity: therapeutic implications

Identification of the molecular mechanisms of host-pathogen interaction is becoming a key focus of proteomics. Analysis of these interactions holds promise for significant developments in the identification of new therapeutic strategies to combat infectious diseases, a process that will also benefit parallel improvements in molecular diagnostics, biomarker identification and drug discovery. This review highlights recent advances in functional proteomics initiatives in infectious disease with emphasis on studies undertaken within physiologically relevant parameters that enable identification of the infectious proteome rather than that of the vegetative state. Deciphering the molecular details of what constitutes physiologically relevant host-pathogen interactions remains an underdeveloped aspect of research into infectious disease. The magnitude of this deficit will be largely influenced by the ease with which model systems can be established to investigate such interactions. As the selective pressures exerted by the host on an infecting pathogen are numerous, the adequacy of certain model systems should be considered carefully.

Current trends in quantitative proteomics

It was inevitable that as soon as mass spectrometrists were able to tell biologists which proteins were in their samples, the next question would be how much of these proteins were present. This has turned out to be a much more challenging question. In this review, we describe the multiple ways that mass spectrometry has attempted to address this issue, both for relative quantitation and for absolute quantitation of proteins. There is no single method that will work for every problem or for every sample. What we present here is a variety of techniques, with guidelines that we hope will assist the researcher in selecting the most appropriate technique for the particular biological problem that needs to be addressed. We need to emphasize that this is a very active area of proteomics research-new quantitative methods are continuously being introduced and some 'pitfalls' of older methods are just being discovered. However, even though there is no perfect technique--and a better technique may be developed tomorrow--valuable information on biomarkers and pathways can be obtained using these currently available methods.

The transcription unit architecture of the Escherichia coli genome

Bacterial genomes are organized by structural and functional elements, including promoters, transcription start and termination sites, open reading frames, regulatory noncoding regions, untranslated regions and transcription units. Here, we iteratively integrate high-throughput, genome-wide measurements of RNA polymerase binding locations and mRNA transcript abundance, 5' sequences and translation into proteins to determine the organizational structure of the Escherichia coli K-12 MG1655 genome. Integration of the organizational elements provides an experimentally annotated transcription unit architecture, including alternative transcription start sites, 5' untranslated region, boundaries and open reading frames of each transcription unit. A total of 4,661 transcription units were identified, representing an increase of >530% over current knowledge. This comprehensive transcription unit architecture allows for the elucidation of condition-specific uses of alternative sigma factors at the genome scale. Furthermore, the transcription unit architecture provides a foundation on which to construct genome-scale transcriptional and translational regulatory networks.

Physiological adaptation of Corynebacterium glutamicum to benzoate as alternative carbon source - a membrane proteome-centric view

The ability of microorganisms to assimilate aromatic substances as alternative carbon sources is the basis of biodegradation of natural as well as industrial aromatic compounds. In this study, Corynebacterium glutamicum was grown on benzoate as sole carbon and energy source. To extend the scarce knowledge about physiological adaptation processes occurring in this cell compartment, the membrane proteome was investigated under quantitative and qualitative aspects by applying shotgun proteomics to reach a comprehensive survey. Membrane proteins were relatively quantified using an internal standard metabolically labeled with (15)N. Altogether, 40 proteins were found to change their abundance during growth on benzoate in comparison to glucose. A global adaptation was observed in the membrane of benzoate-grown cells, characterized by increased abundance of proteins of the respiratory chain, by a starvation response, and by changes in sulfur metabolism involving the regulator McbR. Additional to the relative quantification, stable isotope-labeled synthetic peptides were used for the absolute quantification of the two benzoate transporters of C. glutamicum, BenK and BenE. It was found that both transporters were expressed during growth on benzoate, suggesting that both contribute substantially to benzoate uptake.

Pathway analysis for intracellular Porphyromonas gingivalis using a strain ATCC 33277 specific database

BACKGROUND

Porphyromonas gingivalis is a Gram-negative intracellular pathogen associated with periodontal disease. We have previously reported on whole-cell quantitative proteomic analyses to investigate the differential expression of virulence factors as the organism transitions from an extracellular to intracellular lifestyle. The original results with the invasive strain P. gingivalis ATCC 33277 were obtained using the genome sequence available at the time, strain W83 [GenBank: AE015924]. We present here a re-processed dataset using the recently published genome annotation specific for strain ATCC 33277 [GenBank: AP009380] and an analysis of differential abundance based on metabolic pathways rather than individual proteins.

RESULTS

Qualitative detection was observed for 1266 proteins using the strain ATCC 33277 annotation for 18 hour internalized P. gingivalis within human gingival epithelial cells and controls exposed to gingival cell culture medium, an improvement of 7% over the W83 annotation. Internalized cells showed increased abundance of proteins in the energy pathway from asparagine/aspartate amino acids to ATP. The pathway producing one short chain fatty acid, propionate, showed increased abundance, while that of another, butyrate, trended towards decreased abundance. The translational machinery, including ribosomal proteins and tRNA synthetases, showed a significant increase in protein relative abundance, as did proteins responsible for transcription.

CONCLUSION

Use of the ATCC 33277 specific genome annotation resulted in improved proteome coverage with respect to the number of proteins observed both qualitatively in terms of protein identifications and quantitatively in terms of the number of calculated abundance ratios. Pathway analysis showed a significant increase in overall protein synthetic and transcriptional machinery in the absence of significant growth. These results suggest that the interior of host cells provides a more energy rich environment compared to the extracellular milieu. Shifts in the production of cytotoxic fatty acids by intracellular P. gingivalis may play a role in virulence. Moreover, despite extensive genomic re-arrangements between strains W83 and 33277, there is sufficient sequence similarity at the peptide level for proteomic abundance trends to be largely accurate when using the heterologous strain annotated genome as the reference for database searching.

Gel-based proteomics approach to the study of metabolic changes in pear tissue during storage

The effect of extreme gas conditions (anoxia and air) on the protein expression profiles of Conference pear slices was assessed with a differential gel electrophoresis (DIGE) approach using robust statistical analysis. Changes in expression, up to 4-fold, were identified in proteins involved in respiration, protein synthesis, and defense mechanisms. In addition, short-term exposure of pear slices to anoxia clearly induced up-regulation of transketolase and polygalacturonase inhibiting protein and down-regulation of several isoforms of the major allergen Pyrc (PR proteins), providing further evidence of the possible involvement of these enzymes in the development of the physiological disorder core breakdown. The role of these PR proteins under anoxia is unknown, but our results suggest that these proteins are involved in protection against abiotic stress such as the anoxic conditions applied.

Quantitative proteomics of nutrient limitation in the hydrogenotrophic methanogen Methanococcus maripaludis

Background

Methanogenic Archaea play key metabolic roles in anaerobic ecosystems, where they use H₂ and other substrates to produce methane. Methanococcus maripaludis is a model for studies of the global response to nutrient limitations.

Results

We used high-coverage quantitative proteomics to determine the response of M. maripaludis to growth-limiting levels of H₂, nitrogen, and phosphate. Six to ten percent of the proteome changed significantly with each nutrient limitation. H₂ limitation increased the abundance of a wide variety of proteins involved in methanogenesis. However, one protein involved in methanogenesis decreased: a low-affinity [Fe] hydrogenase, which may dominate over a higher-affinity mechanism when H₂ is abundant. Nitrogen limitation increased known nitrogen assimilation proteins. In addition, the increased abundance of molybdate transport proteins suggested they function for nitrogen fixation. An apparent regulon governed by the euryarchaeal nitrogen regulator NrpR is discussed. Phosphate limitation increased the abundance of three different sets of proteins, suggesting that all three function in phosphate transport.

Conclusion

The global proteomic response of M. maripaludis to each nutrient limitation suggests a wider response than previously appreciated. The results give new insight into the function of several proteins, as well as providing information that should contribute to the formulation of a regulatory network model.

Proteomics of Porphyromonas gingivalis within a model oral microbial community

BACKGROUND

Porphyromonas gingivalis is a periodontal pathogen that resides in a complex multispecies microbial biofilm community known as dental plaque. Confocal laser scanning microscopy showed that P. gingivalis can assemble into communities in vitro with Streptococcus gordonii and Fusobacterium nucleatum, common constituents of dental plaque. Whole cell quantitative proteomics, along with mutant construction and analysis, were conducted to investigate how P. gingivalis adapts to this three species community.

RESULTS

1156 P. gingivalis proteins were detected qualitatively during comparison of the three species model community with P. gingivalis incubated alone under the same conditions. Integration of spectral counting and summed signal intensity analyses of the dataset showed that 403 proteins were down-regulated and 89 proteins up-regulated. The proteomics results were inspected manually and an ontology analysis conducted using DAVID. Significant decreases were seen in proteins involved in cell shape and the formation of the cell envelope, as well as thiamine, cobalamin, and pyrimidine synthesis and DNA repair. An overall increase was seen in proteins involved in protein synthesis. HmuR, a TonB dependent outer membrane receptor, was up-regulated in the community and an hmuR deficient mutant was deficient in three species community formation, but was unimpaired in its ability to form mono- or dual-species biofilms.

CONCLUSION

Collectively, these results indicate that P. gingivalis can assemble into a heterotypic community with F. nucleatum and S. gordonii, and that a community lifestyle provides physiologic support for P. gingivalis. Proteins such as HmuR, that are up-regulated, can be necessary for community structure.

The oligopeptide transport system is essential for the development of natural competence in Streptococcus thermophilus strain LMD-9

In gram-positive bacteria, oligopeptide transport systems, called Opp or Ami, play a role in nutrition but are also involved in the internalization of signaling peptides that take part in the functioning of quorum-sensing pathways. Our objective was to reveal functions that are controlled by Ami via quorum-sensing mechanisms in Streptococcus thermophilus, a nonpathogenic bacterium widely used in dairy technology in association with other bacteria. Using a label-free proteomic approach combining one-dimensional electrophoresis with liquid chromatography-tandem mass spectrometry analysis, we compared the proteome of the S. thermophilus LMD-9 to that of a mutant deleted for the subunits C, D, and E of the ami operon. Both strains were grown in a chemically defined medium (CDM) without peptides. We focused our attention on proteins that were no more detected in the ami deletion mutant. In addition to the three subunits of the Ami transporter, 17 proteins fulfilled this criterion and, among them, 7 were similar to proteins that have been identified as essential for transformation in S. pneumoniae. These results led us to find a condition of growth, the early exponential state in CDM, that allows natural transformation in S. thermophilus LMD-9 to turn on spontaneously. Cells were not competent in M17 rich medium. Furthermore, we demonstrated that the Ami transporter controls the triggering of the competence state through the control of the transcription of comX, itself controlling the transcription of late competence genes. We also showed that one of the two oligopeptide-binding proteins of strain LMD-9 plays the predominant role in the control of competence.

Science, marketing and wishful thinking in quantitative proteomics

In a recent editorial (J. Proteome Res. 2007, 6, 1633) and elsewhere questions have been raised regarding the lack of attention paid to good analytical practice with respect to the reporting of quantitative results in proteomics. Using those comments as a starting point, several issues are discussed that relate to the challenges involved in achieving adequate sampling with MS-based methods in order to generate valid data for large-scale studies. The discussion touches on the relationships that connect sampling depth and the power to detect protein abundance change, conflict of interest, and strategies to overcome bureaucratic obstacles that impede the use of peer-to-peer technologies for transfer and storage of large data files generated in such experiments.

Tools for interpreting large-scale protein profiling in microbiology

Quantitative proteomic analysis of microbial systems generates large datasets that can be difficult and time-consuming to interpret. Fortunately, many of the data display and gene-clustering tools developed to analyze large transcriptome microarray datasets are also applicable to proteomes. Plots of abundance ratio vs. total signal or spectral counts can highlight regions of random error and putative change. Displaying data in the physical order of the genes in the genome sequence can highlight potential operons. At a basic level of transcriptional organization, identifying operons can give insights into regulatory pathways as well as provide corroborating evidence for proteomic results. Classification and clustering algorithms can group proteins together by their abundance changes under different conditions, helping to identify interesting expression patterns, but often work poorly with noisy data such as typically generated in a large-scale proteomic analysis. Biological interpretation can be aided more directly by overlaying differential protein abundance data onto metabolic pathways, indicating pathways with altered activities. More broadly, ontology tools detect altered levels of protein abundance for different metabolic pathways, molecular functions, and cellular localizations. In practice, pathway analysis and ontology are limited by the level of database curation associated with the organism of interest.

Comprehensive proteomics of Methylobacterium extorquens AM1 metabolism under single carbon and nonmethylotrophic conditions

In order to validate a gel free quantitative proteomics assay for the model methylotrophic bacterium Methylobacterium extorquens AM1, we examined the M. extorquens AM1 proteome under single carbon (methanol) and multicarbon (succinate) growth, conditions that have been studied for decades and for which extensive corroborative data have been compiled. In total, 4447 proteins from a database containing 7556 putative ORFs from M. extorquens AM1 could be identified with two or more peptide sequences, corresponding to a qualitative proteome coverage of 58%. Statistically significant nonzero (log(2) scale) differential abundance ratios of methanol/succinate could be detected for 317 proteins using summed ion intensity measurements and 585 proteins using spectral counting, at a q-value cut-off of 0.01, a measure of false discovery rate. The results were compared to recent microarray studies performed under equivalent chemostat conditions. The M. extorquens AM1 studies demonstrated the feasibility of scaling up the multidimensional capillary HPLC MS/MS approach to a prokaryotic organism with a proteome more than three times the size of microbes we have investigated previously, while maintaining a high degree of proteome coverage and reliable quantitative abundance ratios.

Quantitative proteomics of intracellular Porphyromonas gingivalis

Whole-cell quantitative proteomic analyses were conducted to investigate the change from an extracellular to intracellular lifestyle for Porphyromonas gingivalis, a Gram-negative intracellular pathogen associated with periodontal disease. Global protein abundance data for P. gingivalis strain ATCC 33277 internalized for 18 h within human gingival epithelial cells and controls exposed to gingival cell culture medium were obtained at sufficient coverage to provide strong evidence that these changes are profound. A total of 385 proteins were overexpressed in internalized P. gingivalis relative to controls; 240 proteins were shown to be underexpressed. This represented in total about 28% of the protein encoding ORFs annotated for this organism, and slightly less than half of the proteins that were observed experimentally. Production of several proteases, including the classical virulence factors RgpA, RgpB, and Kgp, was decreased. A separate validation study was carried out in which a 16-fold dilution of the P. gingivalis proteome was compared to the undiluted sample in order to assess the quantitative false negative rate (all ratios truly alternative). Truly null (no change) abundance ratios from technical replicates were used to assess the rate of quantitative false positives over the entire proteome. A global comparison between the direction of abundance change observed and previously published bioinformatic gene pair predictions for P. gingivalis will assist with future studies of P. gingivalis gene regulation and operon prediction.