Albumen and Yolk Plasma Peptidomics for the Identification and Quantitation of Bioactive Molecules and the Quality Control of Hen Egg Products.

Hen eggs and the corresponding food products are essential components of human diet. In addition to supplying basic nutrients, they contain functional peptides that are released in vivo within the intact raw material following physiological proteolytic events affecting specific proteins or derive from technological processing of albumen and yolk fractions as a result of the dedicated use of proteases from plant and microbial sources. Besides their potential importance for functional applications, peptides released under physiological conditions in intact egg can be used as markers of product storage and deterioration. Therefore, characterization and quantitation of peptides in egg and egg-derived products can be used to implement evaluation of potential bioactivities as well as to assess food product qualitative characteristics. Here, we provide dedicated information on extraction, identification, and quantitative analysis of peptides from albumen and yolk plasma; nano-liquid chromatography-mass spectrometry combined with bioinformatic analysis of resulting raw data by different software tools allowed to assign molecules based on database searching and to evaluate their relative quantity in different samples.

Deep Learning-Assisted Analysis of Immunopeptidomics Data.

Liquid chromatography-coupled mass spectrometry (LC-MS/MS) is the primary method to obtain direct evidence for the presentation of disease- or patient-specific human leukocyte antigen (HLA). However, compared to the analysis of tryptic peptides in proteomics, the analysis of HLA peptides still poses computational and statistical challenges. Recently, fragment ion intensity-based matching scores assessing the similarity between predicted and observed spectra were shown to substantially increase the number of confidently identified peptides, particularly in use cases where non-tryptic peptides are analyzed. In this chapter, we describe in detail three procedures on how to benefit from state-of-the-art deep learning models to analyze and validate single spectra, single measurements, and multiple measurements in mass spectrometry-based immunopeptidomics. For this, we explain how to use the Universal Spectrum Explorer (USE), online Oktoberfest, and offline Oktoberfest. For intensity-based scoring, Oktoberfest uses fragment ion intensity and retention time predictions from the deep learning framework Prosit, a deep neural network trained on a very large number of synthetic peptides and tandem mass spectra generated within the ProteomeTools project. The examples shown highlight how deep learning-assisted analysis can increase the number of identified HLA peptides, facilitate the discovery of confidently identified neo-epitopes, or provide assistance in the assessment of the presence of cryptic peptides, such as spliced peptides.

Physicochemical and Sensory Characterization of Whey Protein-Enriched Semihard Cheese.

In view of potential future changes of German food legislation with regard to cheese product quality parameters, this study aimed to evaluate the quality of whey protein-enriched semihard cheese (WPEC). Model WPEC was produced in a pilot plant and on an industrial scale by adding defined amounts of high-heat (HH) milk to the cheese milk and comprehensively analyzed during cheese processing. The dry matter, total protein, pure protein, fat, and sodium chloride content of six-week ripened cheese samples were not significantly different (p < 0.05) when the technologically necessary heating of the curd was adapted to the amount of HH milk. However, the ripening, firmness, and melting behavior of WPEC was different compared to cheese without HH milk. During ripening, no formation of whey protein peptides was observed, but differences in the amount of some bitter peptides deriving from the casein fraction were found. Sensory data suggested a slightly more bitter taste perception by the panelists for the WPEC. Further technological adjustments are recommended to obtain marketable WPEC.

Mass spectrometry imaging protocol for spatial mapping of lipids, N-glycans and peptides in murine lung tissue.

RATIONALE: The application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to murine lungs is challenging due to the spongy nature of the tissue. Lungs consist of interconnected air sacs (alveoli) lined by a single layer of flattened epithelial cells, which requires inflation to maintain its natural structure. Therefore, a protocol that is compatible with both lung instillation and high spatial resolution is essential to enable multi-omic studies on murine lung disease models using MALDI-MSI. METHODS AND RESULTS: To maintain the structural integrity of the tissue, murine lungs were inflated with 8% (w/v) gelatin for lipid MSI of fresh frozen tissues or 4% (v/v) paraformaldehyde neutral buffer for N-glycan and peptide MSI of FFPE tissues. Tissues were sectioned and prepared for enzymatic digestion and/or matrix deposition. Glycerol-free PNGase F was applied for N-glycan MSI, while Trypsin Gold was applied for peptide MSI using the iMatrixSpray and ImagePrep Station, respectively. For lipid, N-glycan and peptide MSI, α-cyano-4-hydroxycinnamic acid matrix was deposited using the iMatrixSpray. MS data were acquired with 20 µm spatial resolution using a timsTOF fleX MS instrument followed by MS fragmentation of lipids, N-glycans and peptides. For lipid MSI, trapped ion mobility spectrometry was used to separate isomeric/isobaric lipid species. SCiLS™ Lab was used to visualize all MSI data. For analyte identification, MetaboScape®, GlycoMod and Mascot were used to annotate MS fragmentation spectra of lipids, N-glycans and tryptic peptides, respectively. CONCLUSIONS: Our protocol provides instructions on sample preparation for high spatial resolution MALDI-MSI, MS/MS data acquisition and lipid, N-glycan and peptide annotation and identification from murine lungs. This protocol will allow non-biased analyses of diseased lungs from preclinical murine models and provide further insight into disease models.

Proteomic Analysis of Human Saliva via Solid-Phase Microextraction Coupled with Liquid Chromatography-Mass Spectrometry.

Proteomics of human saliva samples was achieved for the first time via biocompatible solid-phase microextraction (bio-SPME) devices. Upon introduction of a porogen to a conventional C18 coating, porous C18/polyacrylonitrile (PAN) SPME blades were able to extract peptides up to 3.0 kDa and more peptides than commercial SPME blades. Following Trypsin digestion, salivary proteomic analysis was achieved via SPME-LC-MS/MS. Seven endogenous proteins were consistently identified in all saliva samples via bio-SPME. Taking advantage of this strategy, untargeted peptidomics was applied for the comparison of saliva samples between healthy and SARS-CoV-2 positive individuals. The results showed clear peptidomic differences between the viral and healthy saliva samples. This proof-of-concept study demonstrates the potential of bio-SPME-LC-MS/MS for peptidomics and proteomics in biomedical applications.

Addressing common challenges of biotherapeutic protein peptide mapping using recombinant trypsin.

Peptide mapping is the key method for characterization of primary structure of biotherapeutic proteins. This method relies on digestion of proteins into peptides that are then analyzed for amino acid sequence and post-translational modifications. Owing to its high activity and cleavage specificity, trypsin is the protease of choice for peptide mapping. In this study, we investigated critical requirements of peptide mapping and how trypsin affects these requirements. We found that the commonly used MS-grade trypsins contained non-specific, chymotryptic-like cleavage activity causing generation of semi-tryptic peptides and degradation of tryptic-specific peptides. Furthermore, MS-grade trypsins contained pre-existing autoproteolytic peptides and, moreover, additional autoproteolytic peptides were resulting from prominent autoproteolysis during digestion. In our long-standing quest to improve trypsin performance, we developed novel recombinant trypsin and evaluated whether it could address major trypsin drawbacks in peptide mapping. The study showed that the novel trypsin was free of detectable non-specific cleavage activity, had negligible level of autoproteolysis and maintained high activity over the course of digestion reaction. Taking advantage of the novel trypsin advanced properties, especially high cleavage specificity, we established the application for use of large trypsin quantities to digest proteolytically resistant protein sites without negative side effects. We also tested trypsin/Lys-C mix comprising the novel trypsin and showed elimination of non-specific cleavages observed in the digests with the commonly used trypsins. In addition, the improved features of the novel trypsin allowed us to establish the method for accurate and efficient non-enzymatic PTM analysis in biotherapeutic proteins.

SpectiCal: m/z Calibration of MS2 Peptide Spectra Using Known Low Mass Ions.

Most tandem mass spectrometry fragmentation spectra have small calibration errors that can lead to suboptimal interpretation and annotation. We developed SpectiCal, a software tool that can read mzML files from data-dependent acquisition proteomics experiments in parallel, compute m/z calibrations for each file prior to identification analysis based on known low-mass ions, and produce information about frequently observed peaks and their explanations. Using calibration coefficients, the data can be corrected to generate new calibrated mzML files. SpectiCal was tested using five public data sets, creating a table of commonly observed low-mass ions and their identifications. Information about the calibration and individual peaks is written in PDF and TSV files. This includes information for each peak, such as the number of runs in which it appears, the percentage of spectra in which it appears, and a plot of the aggregated region surrounding each peak. SpectiCal can be used to compute MS run calibrations, examine MS runs for artifacts that might hinder downstream analysis, and generate tables of detected low-mass ions for further analysis. SpectiCal is freely available at https://github.com/PlantProteomes/SpectiCal.

Evaluation of different isotope dilution mass spectrometry strategies for the characterization of naturally abundant and isotopically labelled peptide standards.

Natural abundance and isotopically labelled tryptic peptides are routinely employed as standards in quantitative proteomics. The certification of the peptide content is usually carried out by amino acid analysis using isotope dilution mass spectrometry (IDMS) after the acid hydrolysis of the peptide. For the validation and traceability of the amino acid analysis procedure, expensive certified peptides must be employed. In this work we evaluate different IDMS alternatives which will reduce the amount of certified peptide required for validation of the amino acid analysis procedure. In this context, the characterization of both natural and isotopically labelled synthetic angiotensin I peptides was carried out. First, we applied a fast procedure for peptide hydrolysis based on microwave-assisted digestion and employed two certified peptide reference materials SRM 998 angiotensin I and CRM 6901-b C-peptide for validation of the hydrolysis procedure. The amino acids proline, leucine, isoleucine, valine, tyrosine, arginine and phenylalanine were evaluated for their suitability for peptide certification by IDMS by both liquid chromatography with tandem mass spectrometry (LC-MS/MS) and gas chromatography with mass spectrometry (GC)-MS/MS. Then, natural angiotensin I and 13C1-labelled angiotensin I were synthesized in-house and purified by preparative liquid chromatography. The concentration of the 13C1-labelled angiotensin I peptide was established by reverse IDMS in its native form using SRM 998 angiotensin I as reference. The concentration of the natural synthesized peptide was determined by IDMS both using the 13C1-labelled peptide in its native form and by amino acid analysis showing comparable results. Finally, the synthetic naturally abundant angiotensin I peptide was employed as "in-house" standard for the validation of subsequent peptide characterization procedures. Therefore, the novelty of this work relies on, first, the development of a faster hydrolysis procedure assisted by focused microwaves, providing complete hydrolysis in 150 min, and secondly, a validation strategy combining GC-MS and LC-MS/MS that allowed us to certify the purity of an in-house-synthesized peptide standard that can be employed as quality control in further experiments.

Nanoparticle enrichment mass-spectrometry proteomics identifies protein-altering variants for precise pQTL mapping.

Proteogenomics studies generate hypotheses on protein function and provide genetic evidence for drug target prioritization. Most previous work has been conducted using affinity-based proteomics approaches. These technologies face challenges, such as uncertainty regarding target identity, non-specific binding, and handling of variants that affect epitope affinity binding. Mass spectrometry-based proteomics can overcome some of these challenges. Here we report a pQTL study using the Proteograph™ Product Suite workflow (Seer, Inc.) where we quantify over 18,000 unique peptides from nearly 3000 proteins in more than 320 blood samples from a multi-ethnic cohort in a bottom-up, peptide-centric, mass spectrometry-based proteomics approach. We identify 184 protein-altering variants in 137 genes that are significantly associated with their corresponding variant peptides, confirming target specificity of co-associated affinity binders, identifying putatively causal cis-encoded proteins and providing experimental evidence for their presence in blood, including proteins that may be inaccessible to affinity-based proteomics.

Host Cell Protein Analysis using Enrichment Beads Coupled with Limited Digestion.

Host cell proteins (HCPs) are impurities that can adversely affect therapeutic proteins, even in small quantities. To evaluate the potential risks associated with drug products, methods have been developed to identify low-abundance HCPs. A crucial approach for developing a sensitive HCP detection method involves enriching HCPs while simultaneously removing monoclonal antibodies (mAbs) before analysis, utilizing liquid chromatography-mass spectrometry (LC-MS). This protocol offers detailed instructions for enriching host cell proteins using commercially available proteome enrichment beads. These beads contain a diverse library of hexapeptide ligands with specific affinities for different proteins. The protocol also incorporates limited digestion and subsequent peptide detection using nano LC-MS/MS. By employing these techniques, HCPs with low abundance can be enriched over 7000-fold, resulting in an impressive detection limit as low as 0.002 ppm. Significantly, this protocol enables the detection of 850 HCPs with a high level of confidence using a NIST mAb. Moreover, it is designed to be user-friendly and includes a video demonstration to assist with its implementation. By following these steps, researchers can effectively enrich and detect HCPs, enhancing the sensitivity and accuracy of risk assessment for drug products.

Recent advancements in disulfide bridge characterization: Insights from mass spectrometry.

RATIONALE: Disulfide bridges (DSB) play an important role in stabilizing three-dimensional structures of biopharmaceuticals, single purified proteins, and various cyclic peptide drugs that contain disulfide in their structures. Incorrect cross-linking known as DSB scrambling results in misfolded structures that can be inactive, immunogenic, and susceptible to aggregation. Very few articles have been published on the experimental annotation of DSBs in proteins and cyclic peptide drugs. Accurate characterization of the disulfide bond is essential for understanding protein confirmation. METHODS: Characterizing DSBs using mass spectrometry (MS) involves the chemical and enzymatic digestion of samples to obtain smaller peptide fragments, in both reduced and nonreduced forms. Subsequently, these samples are analyzed using MS to locate the DSB, either through interpretation or by employing various software tools. RESULTS: The main challenge in DSB analysis methods using sample preparation is to obtain a sample solution in which nonnative DSBs are not formed due to high pH, temperature, and presence of free sulfhydryl groups. Formation of nonnative DSBs can lead to erroneous annotation of disulfide bond. Sample preparation techniques, fragmentation methods for DSB analysis, and contemporary approaches for DSB mapping using this fragmentation were discussed. CONCLUSIONS: This review presents the latest advancement in MS-based characterization; also a critical perspective is presented for further annotation of DSBs using MS, primarily for single purified proteins or peptides that are densely connected and rich in cysteine. Despite significant breakthroughs resulting from advancements in MS, the analysis of disulfide bonds is not straightforward; it necessitates expertise in sample preparation and interpretation.

Improved detection and consistency of RNA-interacting proteomes using DIA SILAC.

The RNA-interacting proteome is commonly characterized by UV-crosslinking followed by RNA purification, with protein recovery quantified using SILAC labeling followed by data-dependent acquisition (DDA) of proteomic data. However, the low efficiency of UV-crosslinking, combined with limited sensitivity of the DDA approach often restricts detection to relatively abundant proteins, necessitating multiple mass spec injections of fractionated peptides for each biological sample. Here we report an application of data-independent acquisition (DIA) with SILAC in a total RNA-associated protein purification (TRAPP) UV-crosslinking experiment. This gave 15% greater protein detection and lower inter-replicate variation relative to the same biological materials analyzed using DDA, while allowing single-shot analysis of the sample. As proof of concept, we determined the effects of arsenite treatment on the RNA-bound proteome of HEK293T cells. The DIA dataset yielded similar GO term enrichment for RNA-binding proteins involved in cellular stress responses to the DDA dataset while detecting extra proteins unseen by DDA. Overall, the DIA SILAC approach improved detection of proteins over conventional DDA SILAC for generating RNA-interactome datasets, at a lower cost due to reduced machine time. Analyses are described for TRAPP data, but the approach is suitable for proteomic analyses following essentially any RNA-binding protein enrichment technique.

Accumulation of Large Ion Populations with High Ion Densities and Effects Due to Space Charge in Traveling Wave-Based Structures for Lossless Ion Manipulations (SLIM) IMS-MS.

The accumulation of very large ion populations in traveling wave (TW)-based Structures for Lossless ion Manipulations (SLIM) has been studied to better understand aspects of "in-SLIM" ion accumulation, and particularly its use in conjunction with ion mobility spectrometry (IMS). A linear SLIM ion path was implemented that had a "gate" for blocking and accumulating ions for arbitrary time periods. Removing the gate potential caused ions to exit, and the spatial distributions of accumulated ions examined. The ion populations for a set of peptides increased approximately linearly with increased accumulation times until space change effects became significant, after which the peptide precursor ion populations decreased due to growing space charge-related ion activation, reactions, and losses. Ion activation increased with added storage times and the TW amplitude. Lower amplitude TWs in the accumulation/storage region prevented or minimized ion losses or ion heating effects that can also lead to fragmentation. Our results supported the use of an accumulation region close to the SLIM entrance for speeding accumulation, minimizing ion heating, and avoiding ion population profiles that result in IMS peak tailing. Importantly, space charge-driven separations were observed for large populations of accumulated species and attributed to the opposing effects of space charge and the TW. In these separations, ion species form distributions or peaks, sometimes moving against the TW, and are ordered in the SLIM based on their mobilities. Only the highest mobility ions located closest to the gate in the trapped ion population (and where the highest ion densities were achieved) were significantly activated. The observed separations may offer utility for ion prefractionation of ions and increasing the dynamic range measurements, increasing the resolving power of IMS separations by decreasing peak widths for accumulated ion populations, and other purposes benefiting from separations of extremely large ion populations.

Potential bioactive peptides obtained after in vitro gastrointestinal digestion of wine lees from sequential fermentations.

The biotechnological reuse of winery by-products has great potential to increase the value and sustainability of the wine industry. Recent studies revealed that yeast biomass can be an exciting source of bioactive peptides with possible benefits for human health, and its incorporation in plant-based foods is considered innovative and sustainable. In this study, we aimed to identify, through in silico analyses, potential bioactive peptides from yeast extracts after in vitro digestion. Wine lees from a non-Saccharomyces oenological yeast, Starmerella bacillaris FRI751, Saccharomyces cerevisiae EC1118, and sequential fermentation performed with both strains (SEQ) were recovered in a synthetic must. Cellular pellets were enzymatically treated with zymolyase, and the yeast extracts were submitted to in vitro gastrointestinal digestions. LC-MS/MS sequenced the hydrolyzed peptides, and their potential bioactivity was inferred. S. bacillaris FRI751 fermentation showed 132 peptide sequences, S. cerevisiae EC1118 60, SEQ 89. A total of 243 unique peptide sequences were identified across the groups. Furthermore, based on the peptide sequence, the FRI751 extract showed the highest potential antihypertensive with 275 bioactive fragments. Other bioactivities, such as antimicrobial and immunomodulatory, were also identified in all yeast extracts. A potential antiobesity bioactive peptide VVP was identified only in the yeast extract from S. bacillaris single strain. The wine lees from S. bacillaris single strain and SEQ fermentation are a richer source of potential bioactive peptides than those from S. cerevisiae fermentation. This study opens new possibilities in the valorization of winemaking by-products.

102-Plex Approach for Accurate and Multiplexed Proteome Quantification.

Hyperplexing approaches have been aimed to meet the demand for large-scale proteomic analyses. Currently, the analysis capacity has expanded to up to 54 samples within a single experiment by utilizing different isotopic and isobaric reagent combinations. In this report, we propose a super multiplexed approach to enable the analysis of up to 102 samples in a single experiment, by the combination of our recently developed TAG-TMTpro and TAG-IBT16 labeling. We systematically investigated the identification and quantification performance of the 102-plex approach using the mixtures of E. coli and HeLa peptides. Our results revealed that all labeling series demonstrated accurate and reliable quantification performance. The combination of TAG-IBT16 and TAG-TMTpro approaches expands the multiplexing capacity to 102 plexes, providing a more multiplexed quantification method for even larger-scale proteomic analysis. Data are available via ProteomeXchange with the identifier PXD042398.

Discovery and identification of interspecies peptide biomarkers in the seahorse species using liquid chromatography tandem mass spectrometry and chemometrics.

Seahorses have important edible and medicinal values including strengthening the body, tonifying the liver and kidneys, and reducing swelling. And there are abundant seahorse species on Earth. Many seahorses have large price differences due to the scarcity of resources, and some seahorses with similar appearances appear to be confused for use. While in market trading, Hippocampus is susceptible to loss of specialized morphology characteristics, making it difficult to distinguish between specific species. Here we report an effective method based on peptide biomarkers for the identification of seahorse species. Peptide biomarkers for each species were predicted using nano-liquid chromatography-tandem mass spectrometry (Nano-LC-MS/MS) combined with chemometrics software. One unique biomarker peptide for each species was synthesized and verified, and finally developed a liquid chromatography tandem mass spectrometry (LC-MS/MS) multiple reaction monitoring method. The results indicate that the method has great potential for species-specific identification of seahorses and their preparations, among others.

Full Mass Range ΦSDM Orbitrap Mass Spectrometry for DIA Proteome Analysis.

Optimizing data-independent acquisition methods for proteomics applications often requires balancing spectral resolution and acquisition speed. Here, we describe a real-time full mass range implementation of the phase-constrained spectrum deconvolution method (ΦSDM) for Orbitrap mass spectrometry that increases mass resolving power without increasing scan time. Comparing its performance to the standard enhanced Fourier transformation signal processing revealed that the increased resolving power of ΦSDM is beneficial in areas of high peptide density and comes with a greater ability to resolve low-abundance signals. In a standard 2 h analysis of a 200 ng HeLa digest, this resulted in an increase of 16% in the number of quantified peptides. As the acquisition speed becomes even more important when using fast chromatographic gradients, we further applied ΦSDM methods to a range of shorter gradient lengths (21, 12, and 5 min). While ΦSDM improved identification rates and spectral quality in all tested gradients, it proved particularly advantageous for the 5 min gradient. Here, the number of identified protein groups and peptides increased by >15% in comparison to enhanced Fourier transformation processing. In conclusion, ΦSDM is an alternative signal processing algorithm for processing Orbitrap data that can improve spectral quality and benefit quantitative accuracy in typical proteomics experiments, especially when using short gradients.

Fast proteomics with dia-PASEF and analytical flow-rate chromatography.

Increased throughput in proteomic experiments can improve accessibility of proteomic platforms, reduce costs, and facilitate new approaches in systems biology and biomedical research. Here we propose combination of analytical flow rate chromatography with ion mobility separation of peptide ions, data-independent acquisition, and data analysis with the DIA-NN software suite, to achieve high-quality proteomic experiments from limited sample amounts, at a throughput of up to 400 samples per day. For instance, when benchmarking our workflow using a 500-µL/min flow rate and 3-min chromatographic gradients, we report the quantification of 5211 proteins from 2 µg of a mammalian cell-line standard at high quantitative accuracy and precision. We further used this platform to analyze blood plasma samples from a cohort of COVID-19 inpatients, using a 3-min chromatographic gradient and alternating column regeneration on a dual pump system. The method delivered a comprehensive view of the COVID-19 plasma proteome, allowing classification of the patients according to disease severity and revealing plasma biomarker candidates.

Improved Sample Preparation Method for Protein and Peptide Identification from Human Hair.

A fast and sensitive direct extraction (DE) method developed in our group can efficiently extract proteins in 30 min from a 5 cm-long hair strand. Previously, we coupled DE to downstream analysis using gel electrophoresis followed by in-gel digestion, which can be time-consuming. In searching for a better alternative, we found that a combination of DE with a bead-based method (SP3) can lead to significant improvements in protein discovery in human hair. Since SP3 is designed for general applications, we optimized it to process hair proteins following DE and compared it to several other in-solution digestion methods. Of particular concern are genetically variant peptides (GVPs), which can be used for human identification in forensic analysis. Here, we demonstrated improved GVP discovery with the DE and SP3 workflow, which was 3 times faster than the previous in-gel digestion method and required significantly less instrument time depending on the number of gel slices processed. Additionally, it led to an increased number of identified proteins and GVPs. Among the tested in-solution digestion methods, DE combined with SP3 showed the highest sequence coverage, with higher abundances of the identified peptides. This provides a significantly enhanced means for identifying proteins and GVPs in human hair.

Absolute quantification of targeted rabbit liver- and meat tissue-specific peptide markers in highly processed food products.

A highly sensitive and selective method for the simultaneous absolute quantification of peptides unique to rabbit meat- and liver-specific tissue was developed using liquid chromatography - triple quadrupole mass spectrometry. Two rabbit skeletal muscle-specific peptides (SSVFVADPK and PHSHPALTPEQK), three rabbit liver tissue-specific peptides (FNLEALVTHTLPFEK, AILNYVANK, and TELAEPTSTR) and one peptide specific to both rabbit offal and skeletal muscle tissue (AFFGHYLYEVAR) were monitored. Analyses were performed using peptides labelled with stable isotopes (13C and 15N) as internal standards. Fifteen food samples containing rabbit meat and/or liver were analysed to verify compliance of the rabbit meat and liver composition with product labelling. One sample was adulterated with undeclared rabbit liver. The limit of detection and limit of quantification for the selected peptides of interest were in the range of 0.17 to 0.35 ng/mg and 0.57 to 1.17 ng/mg, respectively. The method may be useful for the determination of rabbit meat and liver tissue in highly processed food samples.