Methods and applications of absolute protein quantification in microbial systems

Protocol for absolute quantification of proteins in Gram-negative bacteria based on QconCAT-based labeled peptides

Mass-spectrometry-based absolute protein quantification uses labeled quantification concatamer (QconCAT) as internal standards (ISs). To calculate the amount of protein(s), the ion intensity ratio between the analyte and its cognate IS is compared in each biological sample. The present protocol describes a systematic workflow to design, produce, and purify QconCATs and to quantify soluble proteins in Pseudomonas putida KT2440. Our methodology enables the quantification of detectable peptide and serves as a versatile platform to produce ISs for different biological systems.

Sample Preparation for Mass Spectrometry-Based Absolute Quantification of Bacterial Proteins in Antibiotic Stress Research

Absolute protein quantification is an essential tool for system biology approaches and elucidation of stoichiometry of multi-protein complexes. In this updated chapter, a universal protocol for gel-free absolute protein quantification in bacterial systems is described, which provides adapted methods for cytosolic and membrane proteins. This protocol can be used for sample preparation prior to miscellaneous mass spectrometry-based quantification workflows like AQUA, Hi3, and emPAI. In addition, a focus has been set to the specific challenges in antibiotic stress research.

Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum

Microbes that can recycle one-carbon (C₁) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO₂ and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model acetogen Clostridium autoethanogenum grown autotrophically on three gas mixtures (CO, CO+H₂, or CO+CO₂+H₂). We detect the prioritization of proteome allocation for C₁ fixation and the significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are likely relevant in vivo for CO oxidation, H₂ metabolism, and ethanol production. The integration of proteomic and metabolic flux data demonstrated that enzymes catalyze high fluxes with high concentrations and high in vivo catalytic rates. We show that flux adjustments were dominantly accompanied by changing enzyme catalytic rates rather than concentrations.

IMPORTANCE Acetogen bacteria are important for maintaining biosustainability as they can recycle gaseous C₁ waste feedstocks (e.g., industrial waste gases and syngas from gasified biomass or municipal solid waste) into fuels and chemicals. Notably, the acetogen Clostridium autoethanogenum is being used as a cell factory in industrial-scale gas fermentation. Here, we perform reliable absolute proteome quantification for the first time in an acetogen. This is important as our work advances both rational metabolic engineering of acetogen cell factories and accurate in silico reconstruction of their phenotypes. Furthermore, this absolute proteomics data set serves as a reference toward a better systems-level understanding of the ancient metabolism of acetogens.

Absolute quantification of viral proteins during single-round replication of MDCK suspension cells

Madin-Darby canine kidney (MDCK) cells are widely used in basic research and for the propagation of influenza A viruses (IAV) for vaccine production. To identify targets for antiviral therapies and to optimize vaccine manufacturing, a detailed understanding of the viral life cycle is important. This includes the characterization of virus entry, the synthesis of the various viral RNAs and proteins, the transfer of viral compounds in the cell and virus budding. In case quantitative information is available, the analysis can be complemented by mathematical modelling approaches. While comprehensive studies focusing on IAV entry as well as viral mRNA, vRNA and cRNA accumulation in the nucleus of cells have been performed, quantitative data regarding IAV protein synthesis and accumulation was mostly lacking. In this study, we present a mass spectrometry (MS)-based method to evaluate whether an absolute quantification of viral proteins is possible for single-round replication in suspension MDCK cells. Using influenza A/PR/8/34 (H1N1, RKI) as a model strain at a multiplicity of infection of ten, defined amounts of isotopically labelled peptides of synthetic origin of four IAV proteins (hemagglutinin, neuraminidase, nucleoprotein, matrix protein 1) were added as an internal standard before tryptic digestion of samples for absolute quantification (AQUA). The first intracellular protein detected was NP at 1 h post infection (hpi). A maximum extracellular concentration of 7.7E+12 copies/mL was achieved. This was followed by hemagglutinin (3 hpi, maximum 4.1E+12 copies/mL at 13 hpi), matrix protein 1 (5 hpi, maximum 2.2E+12 copies/mL at 13 hpi) and neuraminidase (5 hpi, 6.0E+11 copies/mL at 13 hpi). In sum, for the first time absolute IAV protein copy numbers were quantified by a MS-based method for infected MDCK cells providing important insights into viral protein dynamics during single-round virus replication. SIGNIFICANCE: Influenza A virus is a significant human pathogen worldwide. To improve therapies against influenza and overcome bottlenecks in vaccine production in cell culture, it is critical to gain a detailed understanding of the viral life cycle. In addition to qPCR-based models, this study will examine the dynamics of influenza virus proteins during infection of producer cells to gain initial insights into changes in absolute copy numbers.

Simultaneous quantification of total carbohydrate and protein amounts from aqueous solutions by the sulfuric acid ultraviolet absorption method (SA-UV method)

Based on the sulfuric acid-ultraviolet assay (SA-UV, developed by Albalasmeh et al., 2013), we have further expanded this method for the simultaneous quantification of saccharides (carbohydrates) and proteins by ultraviolet spectrophotometry. The absorbance of saccharides depends on the formation of furfurals by dehydration in the presence of concentrated sulfuric acid, whereas proteins are unaffected and can be quantified by UV active peptide bonds and aromatic amino acid residues. In saccharide/protein mixtures the SA-UV assay offers a good alternative and substitutes the need for two different methods, like the phenol-sulfuric acid (PSA, developed by DuBois et al., 1951) and bicinchoninic acid (BCA, developed by Smith et al., 1985) assays. For the development of this method, we used glucose and BSA as model substrates and performed a method validation in terms of linearity, LOD, LOQ, accuracy, and precision. Simultaneous quantification in glucose/BSA mixtures is possible down to 20 mg/L from 30 μL sample volumes, and even low content mixtures with concentrations down to 2 mg/L can appropriately be quantified from higher volumes by an evaporation technique.

Bringing New Methods to the Seed Proteomics Platform: Challenges and Perspectives

For centuries, crop plants have represented the basis of the daily human diet. Among them, cereals and legumes, accumulating oils, proteins, and carbohydrates in their seeds, distinctly dominate modern agriculture, thus play an essential role in food industry and fuel production. Therefore, seeds of crop plants are intensively studied by food chemists, biologists, biochemists, and nutritional physiologists. Accordingly, seed development and germination as well as age- and stress-related alterations in seed vigor, longevity, nutritional value, and safety can be addressed by a broad panel of analytical, biochemical, and physiological methods. Currently, functional genomics is one of the most powerful tools, giving direct access to characteristic metabolic changes accompanying plant development, senescence, and response to biotic or abiotic stress. Among individual post-genomic methodological platforms, proteomics represents one of the most effective ones, giving access to cellular metabolism at the level of proteins. During the recent decades, multiple methodological advances were introduced in different branches of life science, although only some of them were established in seed proteomics so far. Therefore, here we discuss main methodological approaches already employed in seed proteomics, as well as those still waiting for implementation in this field of plant research, with a special emphasis on sample preparation, data acquisition, processing, and post-processing. Thereby, the overall goal of this review is to bring new methodologies emerging in different areas of proteomics research (clinical, food, ecological, microbial, and plant proteomics) to the broad society of seed biologists.

Metabolic kinetic modeling provides insight into complex biological questions, but hurdles remain

Metabolic models containing kinetic information can answer unique questions about cellular metabolism that are useful to metabolic engineering. Several kinetic modeling frameworks have recently been developed or improved. In addition, techniques for systematic identification of model structure, including regulatory interactions, have been reported. Each framework has advantages and limitations, which can make it difficult to choose the most appropriate framework. Common limitations are data availability and computational time, especially in large-scale modeling efforts. However, recently developed experimental techniques, parameter identification algorithms, as well as model reduction techniques help alleviate these computational bottlenecks. Opportunities for additional improvements may come from the rich literature in catalysis and chemical networks. In all, kinetic models are positioned to make significant impact in cellular engineering.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Absolute Protein Quantification Using AQUA-Calibrated 2D-PAGE

Absolute protein quantification for the analysis of proteome dynamics is more and more required by the scientific community. Therefore a number of methods have recently been reported that aim at determining concentrations of single proteins in complex samples, all of them having their advantages and limitations. However, for all of these methods an accurate and protein unspecific determination of the total protein amount in a given sample is urgently needed. Here a ninhydrin-based assay established to reach this goal is described. Moreover, an optimized protocol for protein digestion is an inevitable prerequisite for all mass spectrometry-based approaches aiming at absolute protein quantification. In this chapter, various aspects are described which have to be considered during validation of a suitable digestion method and a detailed protocol is presented that can be applied to the digestion of soluble proteins originated from microbes.In order to provide an absolute protein quantification workflow applicable for small scale and large scale approaches, a step-by-step guide is provided for the so-called AQUA-strategy (AQUA = absolute quantification), including selection of suited standard peptides, the development of optimized MS methods and the determination of absolute protein concentration using stable isotope dilution and selected reaction monitoring (SID-SRM). Subsequently, a workflow is introduced that combines targeted mass spectrometry and two-dimensional polyacrylamide gel electrophoresis for the large-scale determination of absolute protein amounts.

Sample Preparation for Mass-Spectrometry Based Absolute Protein Quantification in Antibiotic Stress Research

Absolute protein quantification is an essential tool for system biology approaches and elucidation of stoichiometry of multi-protein complexes. In this chapter, a universal protocol for gel free absolute protein quantification in bacterial systems is described, which can be used for sample preparation prior to miscellaneous mass-spectrometry-based quantification workflows like AQUA, Hi3, and emPAI. In addition, a focus has been set to the specific challenges in antibiotic stress research.

Characterizing the Syphilis-Causing Treponema pallidum ssp. pallidum Proteome Using Complementary Mass Spectrometry

BACKGROUND

The spirochete bacterium Treponema pallidum ssp. pallidum is the etiological agent of syphilis, a chronic multistage disease. Little is known about the global T. pallidum proteome, therefore mass spectrometry studies are needed to bring insights into pathogenicity and protein expression profiles during infection.

METHODOLOGY/PRINCIPAL FINDINGS

To better understand the T. pallidum proteome profile during infection, we studied T. pallidum ssp. pallidum DAL-1 strain bacteria isolated from rabbits using complementary mass spectrometry techniques, including multidimensional peptide separation and protein identification via matrix-assisted laser desorption ionization-time of flight (MALDI-TOF/TOF) and electrospray ionization (ESI-LTQ-Orbitrap) tandem mass spectrometry. A total of 6033 peptides were detected, corresponding to 557 unique T. pallidum proteins at a high level of confidence, representing 54% of the predicted proteome. A previous gel-based T. pallidum MS proteome study detected 58 of these proteins. One hundred fourteen of the detected proteins were previously annotated as hypothetical or uncharacterized proteins; this is the first account of 106 of these proteins at the protein level. Detected proteins were characterized according to their predicted biological function and localization; half were allocated into a wide range of functional categories. Proteins annotated as potential membrane proteins and proteins with unclear functional annotations were subjected to an additional bioinformatics pipeline analysis to facilitate further characterization. A total of 116 potential membrane proteins were identified, of which 16 have evidence supporting outer membrane localization. We found 8/12 proteins related to the paralogous tpr gene family: TprB, TprC/D, TprE, TprG, TprH, TprI and TprJ. Protein abundance was semi-quantified using label-free spectral counting methods. A low correlation (r = 0.26) was found between previous microarray signal data and protein abundance.

CONCLUSIONS

This is the most comprehensive description of the global T. pallidum proteome to date. These data provide valuable insights into in vivo T. pallidum protein expression, paving the way for improved understanding of the pathogenicity of this enigmatic organism.