Development of liquid microjunction extraction strategy for improving protein identification from tissue sections

The challenge of on-tissue digestion for MALDI MSI- a comparison of different protocols to improve imaging experiments

Mass spectrometry imaging (MSI) has become a powerful and successful tool in the context of biomarker detection especially in recent years. This emerging technique is based on the combination of histological information of a tissue and its corresponding spatial resolved mass spectrometric information. The identification of differentially expressed protein peaks between samples is still the method's bottleneck. Therefore, peptide MSI compared to protein MSI is closer to the final goal of identification since peptides are easier to measure than proteins. Nevertheless, the processing of peptide imaging samples is challenging due to experimental complexity. To address this issue, a method development study for peptide MSI using cryoconserved and formalin-fixed paraffin-embedded (FFPE) rat brain tissue is provided. Different digestion times, matrices, and proteases were tested to define an optimal workflow for peptide MSI. All practical experiments were done in triplicates and analyzed by the SCiLS Lab software, using structures derived from myelin basic protein (MBP) peaks, principal component analysis (PCA) and probabilistic latent semantic analysis (pLSA) to rate the experiments' quality. Blinded experimental evaluation in case of defining countable structures in the datasets was performed by three individuals. Such an extensive method development for peptide matrix-assisted laser desorption/ionization (MALDI) imaging experiments has not been performed so far, and the resulting problems and consequences were analyzed and discussed.

Emerging proteomic technologies for elucidating context-dependent cellular signaling events: A big challenge of tiny proportions

Aberrant cell signaling events either drive or compensate for nearly all pathologies. A thorough description and quantification of maladaptive signaling flux in disease is a critical step in drug development, and complex proteomic approaches can provide valuable mechanistic insights. Traditional proteomics-based signaling analyses rely heavily on in vitro cellular monoculture. The characterization of these simplified systems generates a rich understanding of the basic components and complex interactions of many signaling networks, but they cannot capture the full complexity of the microenvironments in which pathologies are ultimately made manifest. Unfortunately, techniques that can directly interrogate signaling in situ often yield mass-limited starting materials that are incompatible with traditional proteomics workflows. This review provides an overview of established and emerging techniques that are applicable to context-dependent proteomics. Analytical approaches are illustrated through recent proteomics-based studies in which selective sample acquisition strategies preserve context-dependent information, and where the challenge of minimal starting material is met by optimized sensitivity and coverage. This review is organized into three major technological themes: (i) LC methods in line with MS; (ii) antibody-based approaches; (iii) MS imaging with a discussion of data integration and systems modeling. Finally, we conclude with future perspectives and implications of context-dependent proteomics.

Parafilm-assisted microdissection: a sampling method for mass spectrometry-based identification of differentially expressed prostate cancer protein biomarkers

Profiling of tumors using a combined MALDI MS imaging and parafilm-assisted microdissection (PAM) workflow identified candidate biomarkers of prostate cancer.

A MALDI-Mass Spectrometry Imaging method applicable to different formalin-fixed paraffin-embedded human tissues

The paper shows a new method for the application of Matrix Assisted Laser Desorption/Ionisation (MALDI) Mass Spectrometry Imaging (MSI) technology on formalin-fixed paraffin-embedded (FFPE) tissue samples.

Top-down and bottom-up identification of proteins by liquid extraction surface analysis mass spectrometry of healthy and diseased human liver tissue

Liquid extraction surface analysis mass spectrometry (LESA MS) has the potential to become a useful tool in the spatially-resolved profiling of proteins in substrates. Here, the approach has been applied to the analysis of thin tissue sections from human liver. The aim was to determine whether LESA MS was a suitable approach for the detection of protein biomarkers of nonalcoholic liver disease (nonalcoholic steatohepatitis, NASH), with a view to the eventual development of LESA MS for imaging NASH pathology. Two approaches were considered. In the first, endogenous proteins were extracted from liver tissue sections by LESA, subjected to automated trypsin digestion, and the resulting peptide mixture was analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) (bottom-up approach). In the second (top-down approach), endogenous proteins were extracted by LESA, and analyzed intact. Selected protein ions were subjected to collision-induced dissociation (CID) and/or electron transfer dissociation (ETD) mass spectrometry. The bottom-up approach resulted in the identification of over 500 proteins; however identification of key protein biomarkers, liver fatty acid binding protein (FABP1), and its variant (Thr→Ala, position 94), was unreliable and irreproducible. Top-down LESA MS analysis of healthy and diseased liver tissue revealed peaks corresponding to multiple (~15-25) proteins. MS/MS of four of these proteins identified them as FABP1, its variant, α-hemoglobin, and 10 kDa heat shock protein. The reliable identification of FABP1 and its variant by top-down LESA MS suggests that the approach may be suitable for imaging NASH pathology in sections from liver biopsies.

Rapid detection of peptide markers for authentication purposes in raw and cooked meat using ambient liquid extraction surface analysis mass spectrometry

In this Article, our previously developed ambient LESA-MS methodology is implemented to analyze five types of thermally treated meat species, namely, beef, pork, horse, chicken, and turkey meat, to select and identify heat-stable and species-specific peptide markers. In-solution tryptic digests of cooked meats were deposited onto a polymer surface, followed by LESA-MS analysis and evaluation using multivariate data analysis and tandem electrospray MS. The five types of cooked meat were clearly discriminated using principal component analysis and orthogonal partial least-squares discriminant analysis. 23 heat stable peptide markers unique to species and muscle protein were identified following data-dependent tandem LESA-MS analysis. Surface extraction and direct ambient MS analysis of mixtures of cooked meat species was performed for the first time and enabled detection of 10% (w/w) of pork, horse, and turkey meat and 5% (w/w) of chicken meat in beef, using the developed LESA-MS/MS analysis. The study shows, for the first time, that ambient LESA-MS methodology displays specificity sufficient to be implemented effectively for the analysis of processed and complex peptide digests. The proposed approach is much faster and simpler than other measurement tools for meat speciation; it has potential for application in other areas of meat science or food production.

Workflow for combined proteomics and glycomics profiling from histological tissues

Extracellular matrixes comprise glycoproteins, glycosaminoglycans and proteoglycans that order the environment through which cells receive signals and communicate. Proteomic and glycomic molecular signatures from tissue surfaces can add diagnostic power to the immunohistochemistry workflows. Acquired in a spatially resolved manner, such proteomic and glycomic information can help characterize disease processes and be easily applied in a clinical setting. Our aim toward obtaining integrated omics datasets was to develop the first workflow applicable for simultaneous analysis of glycosaminoglycans, N-glycans and proteins/peptides from tissue surface areas as small as 1.5 mm in diameter. Targeting small areas is especially important in the case of glycans, as their distribution can be very heterogeneous between different tissue regions. We first established reliable and reproducible digestion protocols for the individual compound classes by applying standards on the tissue using microwave irradiation to achieve reduced digestion times. Next, we developed a multienzyme workflow suitable for analysis of the different compound classes. Applicability of the workflow was demonstrated on serial mouse brain and liver sections, both fresh frozen and formalin-fixed. The glycomics data from the 1.5 mm diameter tissue surface area was consistent with data published on bulk mouse liver and brain tissues, which demonstrates the power of the workflow in obtaining combined molecular signatures from very small tissue regions.

Sampling reliability, spatial resolution, spatial precision, and extraction efficiency in droplet-based liquid microjunction surface sampling

RATIONALE

Droplet-based liquid extraction approaches for spatially resolved surface sampling coupled with high-performance liquid chromatography/mass spectrometry (HPLC/MS) provide the ability to deal with complex sample matrices and to identify isomeric compounds not distinguishable by MS methods alone. Improvements in sampling reliability, spatial resolution, spatial precision and extraction efficiency are required to further the analytical utility of such sampling systems.

METHODS

An autosampler capable of droplet-based liquid extraction was coupled with an HPLC/MS system. Visual inspection of the junction formation between the probe and a glass surface allowed evaluation of the liquid junction formation reliability, spatial location and size as a function of variable parameters such as solvent composition, probe-to-surface distance and droplet volume during solvent dispense and aspiration. Quantitative analysis of a component from a model surface using a weak extraction solvent was used to evaluate the effect of extraction time and number of extraction cycles on analyte extraction efficiency.

RESULTS

Reliable junction formation, independent of other variable parameters, was realized simply by maintaining a maximum distance of 0.4 mm between the probe and the sample surface. The smallest liquid junction diameter (1.6 mm) was observed when using a 1 μL dispensed volume and 90% aqueous extraction solvent with either methanol or acetonitrile. Good sampling precision was always achieved using an extraction solvent with at least 50% methanol or acetonitrile by volume. Quantitative sampling of rhodamine B from a magenta Sharpie ink surface using a weak extraction solvent showed that extraction efficiency could be improved by increasing the extraction time or the number of extraction cycles.

CONCLUSIONS

A platform employing a commercially available autosampler coupled to HPLC/MS was developed and successfully applied to investigate the effect of different sampling parameters on the reliability, spatial resolution, spatial precision and extraction efficiency of the liquid junction surface sampling process. This article is a U.S. Government work and is in the public domain in the USA.

HFIP extraction followed by 2D CTAB/SDS-PAGE separation: a new methodology for protein identification from tissue sections after MALDI mass spectrometry profiling for personalized medicine research

Matrix-assisted laser desorption ionization mass spectrometry imaging (MALDI-MSI) and profiling technology have become the easiest methods for quickly accessing the protein composition of a tissue area. Unfortunately, the demand for the identification of these proteins remains unmet. To overcome this bottleneck, we combined several strategies to identify the proteins detected via MALDI profiling including on-tissue protein extraction using hexafluoroIsopropanol (1,1,1,3,3,3-hexafluoro-2-propanol, HFIP) coupled with two-dimensional cetyl trimethylammonium bromide/sodium dodecyl sulfate-polyacrylamide gel electrophoresis (2D CTAB/SDS-PAGE) for separation followed by trypsin digestion and MALDI-MS analyses for identification. This strategy was compared with an on-tissue bottom-up strategy that we previously developed. The data reflect the complementarity of the approaches. An increase in the number of specific proteins identified has been established. This approach demonstrates the potential of adapted extraction procedures and the combination of parallel identification approaches for personalized medicine applications. The anatomical context provides important insight into identifying biomarkers and may be considered a first step for tissue-based biomarker research, as well as the extemporaneous examination of biopsies during surgery.

Tryptic digestion coupled with ambient desorption electrospray ionization and liquid extraction surface analysis mass spectrometry enabling identification of skeletal muscle proteins in mixtures and distinguishing between beef, pork, horse, chicken, and turkey meat

The use of ambient desorption electrospray ionization mass spectrometry (DESI-MS) and liquid extraction surface analysis mass spectrometry (LESA-MS) is explored for the first time to analyze skeletal muscle proteins obtained from a mixture of standard proteins and raw meat. Single proteins and mixtures of up to five proteins (myoglobin, troponin C, actin, bovine serum albumin (BSA), tropomyosin) were deposited onto a polymer surface, followed by in situ tryptic digestion and comparative analysis using DESI-MS and LESA-MS using tandem electrospray MS. Peptide peaks specific to individual proteins were readily distinguishable with good signal-to-noise ratio in the five-component mixture. LESA-MS gave a more stable analysis and greater sensitivity compared with DESI-MS. Meat tryptic digests were subjected to peptidomics analysis by DESI-MS and LESA-MS. Bovine, horse, pig, chicken, and turkey muscle digests were clearly discriminated using multivariate data analysis (MVA) of the peptidomic data sets. The most abundant skeletal muscle proteins were identified and correctly classified according to the species following MS/MS analysis. The study shows, for the first time, that ambient ionization techniques such as DESI-MS and LESA-MS have great potential for species-specific analysis and differentiation of skeletal muscle proteins by direct surface desorption.

MALDI imaging mass spectrometry and analysis of endogenous peptides

In recent years, MALDI imaging mass spectrometry (MALDI-IMS) has developed as a promising tool to investigate the spatial distribution of biomolecules in intact tissue specimens. Ion densities of various molecules can be displayed as heat maps while preserving anatomical structures. In this short review, an overview of different biomolecules that can be analyzed by MALDI-IMS is given. Many reviews have covered imaging of lipids, small metabolites, whole proteins and enzymatically digested proteins in the past. However, little is known about imaging of endogenous peptides, for example, in the rat brain, and this will therefore be highlighted in this review. Furthermore, sample preparation of frozen or formalin-fixed, paraffin-embedded (FFPE) tissue is crucial for imaging experiments. Therefore, some aspects of sample preparation will be addressed, including washing and desalting, the choice of MALDI matrix and its deposition. Apart from mapping endogenous peptides, their reliable identification in situ still remains challenging and will be discussed as well.

MSiMass list: a public database of identifications for protein MALDI MS imaging

The clinical application of mass spectrometry imaging has developed into a sizable subdiscipline of proteomics and metabolomics because its seamless integration with pathology enables biomarkers and biomarker profiles to be determined that can aid patient and disease stratification (diagnosis, prognosis, and response to therapy). Confident identification of the discriminating peaks remains a challenge owing to the presence of nontryptic protein fragments, large mass-to-charge ratio ions that are not efficiently fragmented via tandem mass spectrometry or a high density of isobaric species. A public database of identifications has been initiated to aid the clinical development and implementation of mass spectrometry imaging. The MSiMass list database ( www.maldi-msi.org/mass ) enables users to assign identities to the peaks observed in their experiments and provides the methods by which the identifications were obtained. In contrast with existing protein databases, this list is designed as a community effort without a formal review panel. In this concept, authors can freely enter data and can comment on existing entries. In such, the database itself is an experiment on sharing knowledge, and its ability to rapidly provide quality data will be evaluated in the future.

Ambient DESI and LESA-MS analysis of proteins adsorbed to a biomaterial surface using in-situ surface tryptic digestion

The detection and identification of proteins adsorbed onto biomaterial surfaces under ambient conditions has significant experimental advantages but has proven to be difficult to achieve with conventional measuring technologies. In this study, we present an adaptation of desorption electrospray ionization (DESI) and liquid extraction surface analysis (LESA) mass spectrometry (MS) coupled with in-situ surface tryptic digestion to identify protein species from a biomaterial surface. Cytochrome c, myoglobin, and BSA in a combination of single and mixture spots were printed in an array format onto Permanox slides, followed by in-situ surface digestion and detection via MS. Automated tandem MS performed on surface peptides was able to identify the proteins via MASCOT. Limits of detection were determined for DESI-MS and a comparison of DESI and LESA-MS peptide spectra characteristics and sensitivity was made. DESI-MS images of the arrays were produced and analyzed with imaging multivariate analysis to automatically separate peptide peaks for each of the proteins within a mixture into distinct components. This is the first time that DESI and LESA-MS have been used for the in-situ detection of surface digested proteins on biomaterial surfaces and presents a promising proof of concept for the use of ambient MS in the rapid and automated analysis of surface proteins.