Pressurized Pepsin Digestion in Proteomics: AN AUTOMATABLE ALTERNATIVE TO TRYPSIN FOR INTEGRATED TOP-DOWN BOTTOM-UP PROTEOMICS*

Integrated top-down bottom-up proteomics combined with on-line digestion has great potential to improve the characterization of protein isoforms in biological systems and is amendable to high throughput proteomics experiments. Bottom-up proteomics ultimately provides the peptide sequences derived from the tandem MS analyses of peptides after the proteome has been digested. Top-down proteomics conversely entails the MS analyses of intact proteins for more effective characterization of genetic variations and/or post-translational modifications. Herein, we describe recent efforts toward efficient integration of bottom-up and top-down LC-MS-based proteomics strategies. Since most proteomics separations utilize acidic conditions, we exploited the compatibility of pepsin (where the optimal digestion conditions are at low pH) for integration into bottom-up and top-down proteomics work flows. Pressure-enhanced pepsin digestions were successfully performed and characterized with several standard proteins in either an off-line mode using a Barocycler or an on-line mode using a modified high pressure LC system referred to as a fast on-line digestion system (FOLDS). FOLDS was tested using pepsin and a whole microbial proteome, and the results were compared against traditional trypsin digestions on the same platform. Additionally, FOLDS was integrated with a RePlay configuration to demonstrate an ultrarapid integrated bottom-up top-down proteomics strategy using a standard mixture of proteins and a monkey pox virus proteome.In-depth characterization and quantitation of protein isoforms, including post-translationally modified proteins, are challenging goals of contemporary proteomics. Traditionally, top-down (1, 2) and bottom-up (3, 4) proteomics have been two distinct analytical paths for liquid-based proteomics analysis. Top-down proteomics is the mass spectrometry (MS)-based characterization of intact proteins, whereas bottom-up proteomics requires a chemical or enzymatic proteolytic digestion of all proteins into peptides prior to MS analysis. Both strategies have their own strengths and challenges and can be thought of as complementary rather than competing analytical techniques.In a top-down proteomics approach, proteins are usually separated by one- or two-dimensional liquid chromatography (LC) and identified using high performance MS (5, 6). This approach is very attractive because it allows the identification of protein isoforms arising from various amino acid modifications, genetic variants (e.g. single nucleotide polymorphisms), mRNA splice variants, and multisite modifications (7) (e.g. specific histone modifications) as well as characterization of proteolytic processing events. However, there are several challenges that have limited the broad application of the approach. Typically, intact proteins are less soluble than their peptide complement, which effectively results in greater losses during various stages of sample handling (i.e. limited sensitivity). Similarly, proteins above ∼40–50 kDa in size are more difficult to ionize, detect, and dissociate in most high throughput MS work flows. Additionally, major challenges associated with MS data interpretation and sensitivity, especially for higher molecular mass proteins (>100 kDa) and highly hydrophobic proteins (e.g. integral membrane proteins), remain largely unsolved, thus limiting the applicability of top-down proteomics on a large scale.Bottom-up proteomics approaches have broad application because peptides are easier to separate and analyze via LC coupled with tandem mass spectrometry (MS/MS), offering a basis for more comprehensive protein identification. As this method relies on protein digestion (which produces multiple peptides for each protein), the sample complexity can become exceedingly large, requiring several dimensions of chromatographic separations (e.g. strong cation exchange and/or high pH reversed phase) prior to the final LC separation (typically reversed phase (RP)¹ C₁₈), which is oftentimes directly coupled with the mass spectrometer (3, 8). In general, the bottom-up analysis rarely achieves 100% sequence coverage of the original proteins, which can result in an incorrect/incomplete assessment of protein isoforms and combinatorial PTMs. Additionally, the digested peptides are not detected with uniform efficiency, which challenges and distorts protein quantification efforts.Because the data obtained from top-down and bottom-up work flows are complementary, several attempts have been made to integrate the two strategies (9, 10). Typically, these efforts have utilized extensive fractionation of the intact protein separation followed by bottom-up analysis of the collected fractions. Results so far have encouraged us to consider on-line digestion methods for integrating top-down and bottom-up proteomics in a higher throughput fashion. Such an on-line digestion approach would not only benefit in terms of higher sample throughput and improved overall sensitivity but would also allow a better correlation between the observed intact protein and its peptide digestion products, greatly aiding data analysis and protein characterization efforts.So far, however, none of the on-line integrated methods have proven robust enough for routine high throughput analyses. One of the reasons for this limited success relates to the choice of the proteolytic enzyme used for the bottom-up segment. Trypsin is by far the most widely used enzyme for proteome analyses because it is affordable (relative to other proteases), it has been well characterized for proteome research, and it offers a nice array of detectable peptides due to a fairly even distribution of lysines and arginines across most proteins. However, protein/peptide RPLC separations (optimal at low pH) are fundamentally incompatible with on-line trypsin digestion (optimal at pH ∼ 8) (11, 12). Therefore, on-line coupling of trypsin digestion and RPLC separations is fraught with technological challenges, and proposed solutions (12) have not proven to be robust enough for integration into demanding high throughput platforms.Our approach to this challenge was to investigate alternative proteases that may be more compatible with automated on-line digestion, peptide separation, and MS detection. Pepsin, which is acid-compatible (i.e. it acts in the stomach to initially aid in the digestion of food) (13), is a particularly promising candidate. This protease has previously been successfully used for the targeted analyses of protein complexes, hydrogen/deuterium exchange experiments (14, 15), and characterization of biopharmaceuticals (16, 17). Generally, pepsin preferentially cleaves the peptide bond located on the N-terminal side of hydrophobic amino acids, such as leucine and phenylalanine, although with less specificity than the preferential cleavage observed for trypsin at arginine and lysine. The compatibility of pepsin with typical LC-MS operation makes it an ideal choice for the development of novel approaches combining protein digestion, protein/peptide separation, and MS-based protein/peptide identification.To develop an automated system capable of simultaneously capturing top-down and bottom-up data, enzyme kinetics of the chosen protease must be extremely fast (because one cannot wait hours as is typical when performing off-line proteolysis). Another requirement is the use of immobilized enzyme or a low enough concentration of the enzyme such that autolysis products do not obscure the detection of substrate peptides. The latter was a concern when using pepsin because prior hydrogen/deuterium exchange experiments used enzyme:substrate ratios up to 1:2 (18, 19). To test whether or not such a large concentration of pepsin was necessary, we performed pepsin digestion at ratios of 1:20. Many alternative energy inputs into the system were considered for speeding up the digestion. For instance, it has been shown that an input of ultrasonic energy could accelerate the reaction rate of a typical trypsin digestion while using small amounts of a protease (20). Because ultrasonic energy results in an increase of temperature and microenvironments of high pressure, it has been hypothesized that the higher temperature was the component responsible for the enhanced enzyme activity (21). López-Ferrer et al. (22, 23), however, have demonstrated that application of higher pressure with incorporation of a Barocycler alone can make trypsin display faster enzyme kinetics. This phenomenon can easily be integrated with an LC separation (which already operates at elevated pressure) to enable an automatable ultrarapid on-line digestion LC-MS proteomics platform. Herein, we refer to this platform as the fast on-line digestion system (FOLDS) (23). Although FOLDS has been described before using trypsin, here the system is characterized with pepsin, and the results obtained are compared with results attainable with trypsin. Like trypsin, pepsin produced efficient protein digestion in just a few minutes when placed under pressure. Because of the natural maximal activity of pepsin at low pH, the FOLDS can be incorporated with a RePlay (Advion Biosciences, Ithaca, NY) system, and this powerful combination is what ultimately makes the integration of top-down and bottom-up proteomics analyses possible. The integrated analysis begins with a chromatographic separation of intact proteins. The separated proteins are then split into two streams. One stream proceeds directly to the mass spectrometer for MS and/or tandem MS analysis. The second stream is split into a long capillary where the chromatographic separation of the proteins is maintained, but their arrival to the mass spectrometer for detection is delayed. This is in essence the concept of RePlay (24, 25). Herein, we have taken the RePlay a step further by implementing our FOLDS technology into the second split delayed stream of proteins. While these delayed proteins travel down the long and narrow capillary, we exposed them to pepsin where, in combination with the pressure, the proteins are quickly and reproducibly digested. These peptide fragments are subsequently subjected to MS and/or tandem MS analysis. The FOLDS RePlay system allows the rapid and robust incorporation of the integrated top-down bottom-up proteomics work flow with the ability to not only identify proteins but also to sequence multisite/combinatorial PTMs because all detected peptides (from the FOLDS analysis) are confined to the original chromatographic peak of the protein they were derived from. The analysis of protein mixtures using this integrated strategy reduces the total amount of samples required to obtain both the top-down and bottom-up data, increases throughput, and improves protein sequence coverage.     

Re-examination of the "3/4-law" of metabolism

We examine the scaling law B is proportional to M(alpha)which connects organismal resting metabolic rate B with organismal mass M, where alpha is commonly held to be 3/4. Since simple dimensional analysis suggests alpha = 2/3, we consider this to be a null hypothesis testable by empirical studies. We re-analyse data sets for mammals and birds compiled by Heusner, Bennett and Harvey, Bartels, Hemmingsen, Brody, and Kleiber, and find little evidence for rejecting alpha = 2/3 in favor of alpha = 3/4. For mammals, we find a possible breakdown in scaling for larger masses reflected in a systematic increase in alpha. We also review theoretical justifications of alpha = 3/4 based on dimensional analysis, nutrient-supply networks, and four-dimensional biology. We find that present theories for alpha = 3/4 require assumptions that render them unconvincing for rejecting the null hypothesis that alpha = 2/3.     

The human APO-1 (APT) antigen maps to 10q23, a region that is syntenic with mouse chromosome 19.

The APO-1 (APT) antigen is a cell surface antigen expressed on a variety of normal and malignant cells. Binding of anti-APO-1 antibody to the APO-1 antigen induces programmed cell death (apoptosis). The APO-1 antigen shows homology to the members of the tumor necrosis factor receptor/nerve growth factor receptor superfamily. Using cosmid DNA containing the APO-1 gene as a probe for fluorescence in situ hybridization, we have mapped the gene to a subregion of chromosomal band 10q23. The human APO-1 locus lies within a conserved synteny segment present on mouse chromosome 19 consistent with the previous chromosomal assignment of the corresponding mouse antigen.     

Leaf extraction and analysis framework graphical user interface: segmenting and analyzing the structure of leaf veins and areoles

Interest in the structure and function of physical biological networks has spurred the development of a number of theoretical models that predict optimal network structures across a broad array of taxonomic groups, from mammals to plants. In many cases, direct tests of predicted network structure are impossible given the lack of suitable empirical methods to quantify physical network geometry with sufficient scope and resolution. There is a long history of empirical methods to quantify the network structure of plants, from roots, to xylem networks in shoots and within leaves. However, with few exceptions, current methods emphasize the analysis of portions of, rather than entire networks. Here, we introduce the Leaf Extraction and Analysis Framework Graphical User Interface (LEAF GUI), a user-assisted software tool that facilitates improved empirical understanding of leaf network structure. LEAF GUI takes images of leaves where veins have been enhanced relative to the background, and following a series of interactive thresholding and cleaning steps, returns a suite of statistics and information on the structure of leaf venation networks and areoles. Metrics include the dimensions, position, and connectivity of all network veins, and the dimensions, shape, and position of the areoles they surround. Available for free download, the LEAF GUI software promises to facilitate improved understanding of the adaptive and ecological significance of leaf vein network structure.     

Quantifying enzymatic lysis: estimating the combined effects of chemistry, physiology and physics

The number of microbial pathogens resistant to antibiotics continues to increase even as the rate of discovery and approval of new antibiotic therapeutics steadily decreases. Many researchers have begun to investigate the therapeutic potential of naturally occurring lytic enzymes as an alternative to traditional antibiotics. However, direct characterization of lytic enzymes using techniques based on synthetic substrates is often difficult because lytic enzymes bind to the complex superstructure of intact cell walls. Here we present a new standard for the analysis of lytic enzymes based on turbidity assays which allow us to probe the dynamics of lysis without preparing a synthetic substrate. The challenge in the analysis of these assays is to infer the microscopic details of lysis from macroscopic turbidity data. We propose a model of enzymatic lysis that integrates the chemistry responsible for bond cleavage with the physical mechanisms leading to cell wall failure. We then present a solution to an inverse problem in which we estimate reaction rate constants and the heterogeneous susceptibility to lysis among target cells. We validate our model given simulated and experimental turbidity assays. The ability to estimate reaction rate constants for lytic enzymes will facilitate their biochemical characterization and development as antimicrobial therapeutics.