Pressure Cycling Technology Assisted Mass Spectrometric Quantification of Gingival Tissue Reveals Proteome Dynamics during the Initiation and Progression of Inflammatory Periodontal Disease.

Understanding the progression of periodontal tissue destruction is at the forefront of periodontal research. The authors aimed to capture the dynamics of gingival tissue proteome during the initiation and progression of experimental (ligature-induced) periodontitis in mice. Pressure cycling technology (PCT), a recently developed platform that uses ultra-high pressure to disrupt tissues, is utilized to achieve efficient and reproducible protein extraction from ultra-small amounts of gingival tissues in combination with liquid chromatography-tandem mass spectrometry (MS). The MS data are processed using Progenesis QI and the regulated proteins are subjected to METACORE, STRING, and WebGestalt for functional enrichment analysis. A total of 1614 proteins with ≥2 peptides are quantified with an estimated protein false discovery rate of 0.06%. Unsupervised clustering analysis shows that the gingival tissue protein abundance is mainly dependent on the periodontitis progression stage. Gene ontology enrichment analysis reveals an overrepresentation in innate immune regulation (e.g., neutrophil-mediated immunity and antimicrobial peptides), signal transduction (e.g., integrin signaling), and homeostasis processes (e.g., platelet activation and aggregation). In conclusion, a PCT-assisted label-free quantitative proteomics workflow that allowed cataloging the deepest gingival tissue proteome on a rapid timescale and provided novel mechanistic insights into host perturbation during periodontitis progression is applied.

Quantitative Profiling of N-linked Glycosylation Machinery in Yeast Saccharomyces cerevisiae.

Asparagine-linked glycosylation is a common posttranslational protein modification regulating the structure, stability and function of many proteins. The N-linked glycosylation machinery involves enzymes responsible for the assembly of the lipid-linked oligosaccharide (LLO), which is then transferred to the asparagine residues on the polypeptides by the enzyme oligosaccharyltransferase (OST). A major goal in the study of protein glycosylation is to establish quantitative methods for the analysis of site-specific extent of glycosylation. We developed a sensitive approach to examine glycosylation site occupancy in Saccharomyces cerevisiae by coupling stable isotope labeling (SILAC) approach to parallel reaction monitoring (PRM) mass spectrometry (MS). We combined the method with genetic tools and validated the approach with the identification of novel glycosylation sites dependent on the Ost3p and Ost6p regulatory subunits of OST. Based on the observations that alternations in LLO substrate structure and OST subunits activity differentially alter the systemic output of OST, we conclude that sequon recognition is a direct property of the catalytic subunit Stt3p, auxiliary subunits such as Ost3p and Ost6p extend the OST substrate range by modulating interfering pathways such as protein folding. In addition, our proteomics approach revealed a novel regulatory network that connects isoprenoid lipid biosynthesis and LLO substrate assembly.

Targeted Proteomics Guided by Label-free Quantitative Proteome Analysis in Saliva Reveal Transition Signatures from Health to Periodontal Disease.

Periodontal diseases are among the most prevalent worldwide, but largely silent, chronic diseases. They affect the tooth-supporting tissues with multiple ramifications on life quality. Their early diagnosis is still challenging, due to lack of appropriate molecular diagnostic methods. Saliva offers a non-invasively collectable reservoir of clinically relevant biomarkers, which, if utilized efficiently, could facilitate early diagnosis and monitoring of ongoing disease. Despite several novel protein markers being recently enlisted by discovery proteomics, their routine diagnostic application is hampered by the lack of validation platforms that allow for rapid, accurate and simultaneous quantification of multiple proteins in large cohorts. Here we carried out a pipeline of two proteomic platforms; firstly, we applied open ended label-free quantitative (LFQ) proteomics for discovery in saliva (n = 67, including individuals with health, gingivitis, and periodontitis), followed by selected-reaction monitoring (SRM)-targeted proteomics for validation in an independent cohort (n = 82). The LFQ platform led to the discovery of 119 proteins with at least 2-fold significant difference between health and disease. The 65 proteins chosen for the subsequent SRM platform included 50 functionally related proteins derived from the significantly enriched processes of the LFQ data, 11 from literature-mining, and four house-keeping ones. Among those, 60 were reproducibly quantifiable proteins (92% success rate), represented by a total of 143 peptides. Machine-learning modeling led to a narrowed-down panel of five proteins of high predictive value for periodontal diseases with maximum area under the receiver operating curve >0.97 (higher in disease: Matrix metalloproteinase-9, Ras-related protein-1, Actin-related protein 2/3 complex subunit 5; lower in disease: Clusterin, Deleted in Malignant Brain Tumors 1). This panel enriches the pool of credible clinical biomarker candidates for diagnostic assay development. Yet, the quantum leap brought into the field of periodontal diagnostics by this study is the application of the biomarker discovery-through-verification pipeline, which can be used for validation in further cohorts.

New Quantitative Mass Spectrometry Approaches Reveal Different ADP-ribosylation Phases Dependent On the Levels of Oxidative Stress.

Oxidative stress is a potent inducer of protein ADP-ribosylation. Although individual oxidative stress-induced ADP-ribosylated proteins have been identified, it is so far not clear to which extent different degrees of stress severity quantitatively and qualitatively alter ADP-ribosylation. Here, we investigated both quantitative and qualitative changes of the hydrogen peroxide (H2O2)-induced ADP-ribosylome using a label-free shotgun quantification and a parallel reaction monitoring (PRM) mass spectrometry approach for a selected number of identified ADP-ribosylated peptides. Although the major part of the basal HeLa ADP-ribosylome remained unchanged upon all tested H2O2 concentrations, some selected peptides change the extent of ADP-ribosylation depending on the degree of the applied oxidative stress. Low oxidative stress (i.e. 4 µm and 16 µm H2O2) caused a reduction in ADP-ribosylation of modified proteins detected under untreated conditions. In contrast, mid to strong oxidative stress (62 µm to 1 mm H2O2) induced a significant increase in ADP-ribosylation of oxidative stress-targeted proteins. The application of the PRM approach to SKOV3 and A2780, ovarian cancer cells displaying different sensitivities to PARP inhibitors, revealed that the basal and the H2O2-induced ADP-ribosylomes of SKOV3 and A2780 differed significantly and that the sensitivity to PARP inhibitors correlated with the level of ARTD1 expression in these cells. Overall, this new PRM-MS approach has proven to be sensitive in monitoring alterations of the ADP-ribosylome and has revealed unexpected alterations in proteins ADP-ribosylation depending on the degree of oxidative stress.

Targeted Proteomics for Multiplexed Verification of Markers of Colorectal Tumorigenesis.

Targeted proteomic methods can accelerate the verification of multiple tumor marker candidates in large series of patient samples. We utilized the targeted approach known as selected/multiple reaction monitoring (S/MRM) to verify potential protein markers of colorectal adenoma identified by our group in previous transcriptomic and quantitative shotgun proteomic studies of a large cohort of precancerous colorectal lesions. We developed SRM assays to reproducibly detect and quantify 25 (62.5%) of the 40 selected proteins in an independent series of precancerous and cancerous tissue samples (19 adenoma/normal mucosa pairs; 17 adenocarcinoma/normal mucosa pairs). Twenty-three proteins were significantly up-regulated (n = 17) or downregulated (n = 6) in adenomas and/or adenocarcinomas, as compared with normal mucosa (linear fold changes ≥ ±1.3, adjusted p value <0.05). Most changes were observed in both tumor types (up-regulation of ANP32A, ANXA3, SORD, LDHA, LCN2, NCL, S100A11, SERPINB5, CDV3, OLFM4, and REG4; downregulation of ARF6 and PGM5), and a five-protein biomarker signature distinguished neoplastic tissue from normal mucosa with a maximum area under the receiver operating curve greater than 0.83. Other changes were specific for adenomas (PPA1 and PPA2 up-regulation; KCTD12 downregulation) or adenocarcinoma (ANP32B, G6PD, RCN1, and SET up-regulation; downregulated AKR1B1, APEX1, and PPA1). Some changes significantly correlated with a few patient- or tumor-related phenotypes. Twenty-two (96%) of the 23 proteins have a potential to be released from the tumors into the bloodstream, and their detectability in plasma has been previously reported. The proteins identified in this study expand the pool of biomarker candidates that can be used to develop a standardized precolonoscopy blood test for the early detection of colorectal tumors.

Reproducible and consistent quantification of the Saccharomyces cerevisiae proteome by SWATH-mass spectrometry.

Targeted mass spectrometry by selected reaction monitoring (S/MRM) has proven to be a suitable technique for the consistent and reproducible quantification of proteins across multiple biological samples and a wide dynamic range. This performance profile is an important prerequisite for systems biology and biomedical research. However, the method is limited to the measurements of a few hundred peptides per LC-MS analysis. Recently, we introduced SWATH-MS, a combination of data independent acquisition and targeted data analysis that vastly extends the number of peptides/proteins quantified per sample, while maintaining the favorable performance profile of S/MRM. Here we applied the SWATH-MS technique to quantify changes over time in a large fraction of the proteome expressed in Saccharomyces cerevisiae in response to osmotic stress. We sampled cell cultures in biological triplicates at six time points following the application of osmotic stress and acquired single injection data independent acquisition data sets on a high-resolution 5600 tripleTOF instrument operated in SWATH mode. Proteins were quantified by the targeted extraction and integration of transition signal groups from the SWATH-MS datasets for peptides that are proteotypic for specific yeast proteins. We consistently identified and quantified more than 15,000 peptides and 2500 proteins across the 18 samples. We demonstrate high reproducibility between technical and biological replicates across all time points and protein abundances. In addition, we show that the abundance of hundreds of proteins was significantly regulated upon osmotic shock, and pathway enrichment analysis revealed that the proteins reacting to osmotic shock are mainly involved in the carbohydrate and amino acid metabolism. Overall, this study demonstrates the ability of SWATH-MS to efficiently generate reproducible, consistent, and quantitatively accurate measurements of a large fraction of a proteome across multiple samples.

Targeted proteomics coming of age - SRM, PRM and DIA performance evaluated from a core facility perspective.

Quantitative mass spectrometry is a rapidly evolving methodology applied in a large number of omics-type research projects. During the past years, new designs of mass spectrometers have been developed and launched as commercial systems while in parallel new data acquisition schemes and data analysis paradigms have been introduced. Core facilities provide access to such technologies, but also actively support the researchers in finding and applying the best-suited analytical approach. In order to implement a solid fundament for this decision making process, core facilities need to constantly compare and benchmark the various approaches. In this article we compare the quantitative accuracy and precision of current state of the art targeted proteomics approaches single reaction monitoring (SRM), parallel reaction monitoring (PRM) and data independent acquisition (DIA) across multiple liquid chromatography mass spectrometry (LC-MS) platforms, using a readily available commercial standard sample. All workflows are able to reproducibly generate accurate quantitative data. However, SRM and PRM workflows show higher accuracy and precision compared to DIA approaches, especially when analyzing low concentrated analytes.

Systematic proteomic analysis identifies ß-site amyloid precursor protein cleaving enzyme 2 and 1 (BACE2 and BACE1) substrates in pancreatic ß-cells.

Expansion of functional islet ß-cell mass is a physiological process to compensate for increased insulin demand. Deficiency or pharmacological inhibition of the plasma membrane protease BACE2 enhances pancreatic ß-cell function and proliferation, and therefore BACE2 is a putative target for the therapeutic intervention under conditions of ß-cell loss and dysfunction. To gain a molecular understanding of BACE2 function, we performed a systematic and quantitative proteomic analysis to map the natural substrate repertoire of BACE2 and its homologue BACE1 in ß-cells. Loss- and gain-of-function studies of in vitro and in vivo models identified specific and functionally heterogeneous targets. Our analysis revealed non-redundant roles of BACE1/2 in ectodomain shedding with BACE1 regulating a broader and BACE2 a more distinct set of ß-cell-enriched substrates including two proteins of the seizure 6 protein family (SEZ6L and SEZ6L2). Lastly, our study provides insights into the global ß-cell sheddome and secretome, an important prerequisite to uncover novel mechanisms contributing to ß-cell homeostasis and a resource for therapeutic target and biomarker discoveries.

Timescales and bottlenecks in miRNA-dependent gene regulation.

MiRNAs are post-transcriptional regulators that contribute to the establishment and maintenance of gene expression patterns. Although their biogenesis and decay appear to be under complex control, the implications of miRNA expression dynamics for the processes that they regulate are not well understood. We derived a mathematical model of miRNA-mediated gene regulation, inferred its parameters from experimental data sets, and found that the model describes well time-dependent changes in mRNA, protein and ribosome density levels measured upon miRNA transfection and induction. The inferred parameters indicate that the timescale of miRNA-dependent regulation is slower than initially thought. Delays in miRNA loading into Argonaute proteins and the slow decay of proteins relative to mRNAs can explain the typically small changes in protein levels observed upon miRNA transfection. For miRNAs to regulate protein expression on the timescale of a day, as miRNAs involved in cell-cycle regulation do, accelerated miRNA turnover is necessary.

Targeted data extraction of the MS/MS spectra generated by data-independent acquisition: a new concept for consistent and accurate proteome analysis.

Most proteomic studies use liquid chromatography coupled to tandem mass spectrometry to identify and quantify the peptides generated by the proteolysis of a biological sample. However, with the current methods it remains challenging to rapidly, consistently, reproducibly, accurately, and sensitively detect and quantify large fractions of proteomes across multiple samples. Here we present a new strategy that systematically queries sample sets for the presence and quantity of essentially any protein of interest. It consists of using the information available in fragment ion spectral libraries to mine the complete fragment ion maps generated using a data-independent acquisition method. For this study, the data were acquired on a fast, high resolution quadrupole-quadrupole time-of-flight (TOF) instrument by repeatedly cycling through 32 consecutive 25-Da precursor isolation windows (swaths). This SWATH MS acquisition setup generates, in a single sample injection, time-resolved fragment ion spectra for all the analytes detectable within the 400-1200 m/z precursor range and the user-defined retention time window. We show that suitable combinations of fragment ions extracted from these data sets are sufficiently specific to confidently identify query peptides over a dynamic range of 4 orders of magnitude, even if the precursors of the queried peptides are not detectable in the survey scans. We also show that queried peptides are quantified with a consistency and accuracy comparable with that of selected reaction monitoring, the gold standard proteomic quantification method. Moreover, targeted data extraction enables ad libitum quantification refinement and dynamic extension of protein probing by iterative re-mining of the once-and-forever acquired data sets. This combination of unbiased, broad range precursor ion fragmentation and targeted data extraction alleviates most constraints of present proteomic methods and should be equally applicable to the comprehensive analysis of other classes of analytes, beyond proteomics.

PASSEL: the PeptideAtlas SRMexperiment library.

Public repositories for proteomics data have accelerated proteomics research by enabling more efficient cross-analyses of datasets, supporting the creation of protein and peptide compendia of experimental results, supporting the development and testing of new software tools, and facilitating the manuscript review process. The repositories available to date have been designed to accommodate either shotgun experiments or generic proteomic data files. Here, we describe a new kind of proteomic data repository for the collection and representation of data from selected reaction monitoring (SRM) measurements. The PeptideAtlas SRM Experiment Library (PASSEL) allows researchers to easily submit proteomic data sets generated by SRM. The raw data are automatically processed in a uniform manner and the results are stored in a database, where they may be downloaded or browsed via a web interface that includes a chromatogram viewer. PASSELenables cross-analysis of SRMdata, supports optimization of SRMdata collection, and facilitates the review process of SRMdata. Further, PASSELwill help in the assessment of proteotypic peptide performance in a wide array of samples containing the same peptide, as well as across multiple experimental protocols.

Automated workflow for large-scale selected reaction monitoring experiments.

Targeted proteomics allows researchers to study proteins of interest without being drowned in data from other, less interesting proteins or from redundant or uninformative peptides. While the technique is mostly used for smaller, focused studies, there are several reasons to conduct larger targeted experiments. Automated, highly robust software becomes more important in such experiments. In addition, larger experiments are carried out over longer periods of time, requiring strategies to handle the sometimes large shift in retention time often observed. We present a complete proof-of-principle software stack that automates most aspects of selected reaction monitoring workflows, a targeted proteomics technology. The software allows experiments to be easily designed and carried out. The steps automated are the generation of assays, generation of mass spectrometry driver files and methods files, and the import and analysis of the data. All data are normalized to a common retention time scale, the data are then scored using a novel score model, and the error is subsequently estimated. We also show that selected reaction monitoring can be used for label-free quantification. All data generated are stored in a relational database, and the growing resource further facilitates the design of new experiments. We apply the technology to a large-scale experiment studying how Streptococcus pyogenes remodels its proteome under stimulation of human plasma.

Systematic quantification of peptides/proteins in urine using selected reaction monitoring.

The evaluation of biomarkers in bodily fluids necessitates the development of robust methods to quantify proteins in a complex background, using large sets of samples. The ability to multiplex numerous analytes in a single assay expedites the process. Liquid chromatography-mass spectrometry (LC-MS) analyses performed in selected reaction monitoring (SRM) in conjunction with stable isotope dilution MS present an effective way to detect and quantify biomarker candidates in bodily fluids. The strategy presented involves an initial qualification of predefined sets of proteins in urine. The technique was applied to detect and quantify peptides in urine samples as surrogates for a few endogenous proteins. Multiplexed assays were developed to analyze proteins associated with bladder cancer; a few exogenous proteins were added as internal standards. The sample preparation and the analytical protocols were optimized to ensure reproducibility, analytical precision, and quantification limits in the low nanogram per milliliter range. Analyses were performed using known amounts of isotopically labeled peptides. Systematic replication of the measurements indicated intra-assay and inter-assay variability, with CVs in the range of 10%. The differences measured for two targeted proteins were correlated with their level of expression in the corresponding tumors using immunohistochemistry.

Toward a standardized urine proteome analysis methodology.

Urine is an easily accessible bodily fluid particularly suited for the routine clinical analysis of disease biomarkers. Actually, the urinary proteome is more diverse than anticipated a decade ago. Hence, significant analytical and practical issues of urine proteomics such as sample collection and preparation have emerged, in particular for large-scale studies. We have undertaken a systematic study to define standardized and integrated analytical protocols for a biomarker development pipeline, employing two LC-MS analytical platforms, namely accurate mass and time tags and selected reaction monitoring, for the discovery and verification phase, respectively. Urine samples collected from hospital patients were processed using four different protocols, which were evaluated and compared on both analytical platforms. Addition of internal standards at various stages of sample processing allowed the estimation of protein extraction yields and the absolute quantification of selected urinary proteins. Reproducibility of the entire process and dynamic range of quantification were also evaluated. Organic solvent precipitation followed by in-solution digestion provided the best performances and was thus selected as the standard method common to the discovery and verification phases. Finally, we applied this protocol for platforms' cross-validation and obtained excellent consistency between urinary protein concentration estimates by both analytical methods performed in parallel in two laboratories.

Translational Proteomics Analysis of Anthracycline-Induced Cardiotoxicity From Cardiac Microtissues to Human Heart Biopsies.

Anthracyclines, including doxorubicin, idarubicin, and epirubicin, are common antitumor drugs as well as well-known cardiotoxic agents. This study analyzed the proteomics alteration in cardiac tissues caused by these 3 anthracyclines analogs. The in vitro human cardiac microtissues were exposed to drugs in 2 weeks; the proteomic data were measured at 7 time points. The heart biopsy data were collected from heart failure patients, in which some patients underwent anthracycline treatment. The anthracyclines-affected proteins were separately identified in the in vitro and in vivo dataset using the WGCNA method. These proteins engage in different cellular pathways including translation, metabolism, mitochondrial function, muscle contraction, and signaling pathways. From proteins detected in 2 datasets, a protein-protein network was established with 4 hub proteins, and 7 weighted proteins from both cardiac microtissue and human biopsies data. These 11 proteins, which involve in mitochondrial functions and the NF-κB signaling pathway, could provide insights into the anthracycline toxic mechanism. Some of them, such as HSPA5, BAG3, and SH3BGRL, are cardiac therapy targets or cardiotoxicity biomarkers. Other proteins, such as ATP5F1B and EEF1D, showed similar responses in both the in vitro and in vivo data. This suggests that the in vitro outcomes could link to clinical phenomena in proteomic analysis.

Proteome and Microbiome Mapping of Human Gingival Tissue in Health and Disease.

Efforts to map gingival tissue proteomes and microbiomes have been hampered by lack of sufficient tissue extraction methods. The pressure cycling technology (PCT) is an emerging platform for reproducible tissue homogenisation and improved sequence retrieval coverage. Therefore, we employed PCT to characterise the proteome and microbiome profiles in healthy and diseased gingival tissue. Healthy and diseased contralateral gingival tissue samples (total n = 10) were collected from five systemically healthy individuals (51.6 ± 4.3 years) with generalised chronic periodontitis. The tissues were then lysed and digested using a Barocycler, proteins were prepared and submitted for mass spectrometric analysis and microbiome DNA for 16S rRNA profiling analysis. Overall, 1,366 human proteins were quantified (false discovery rate 0.22%), of which 69 proteins were differentially expressed (≥2 peptides and p < 0.05, 62 up, 7 down) in periodontally diseased sites, compared to healthy sites. These were primarily extracellular or vesicle-associated proteins, with functions in molecular transport. On the microbiome level, 362 species-level operational taxonomic units were identified. Of those, 14 predominant species accounted for >80% of the total relative abundance, whereas 11 proved to be significantly different between healthy and diseased sites. Among them, Treponema sp. HMT253 and Fusobacterium naviforme and were associated with disease sites and strongly interacted (r > 0.7) with 30 and 6 up-regulated proteins, respectively. Healthy-site associated strains Streptococcus vestibularis, Veillonella dispar, Selenomonas sp. HMT478 and Leptotrichia sp. HMT417 showed strong negative interactions (r < -0.7) with 31, 21, 9, and 18 up-regulated proteins, respectively. In contrast the down-regulated proteins did not show strong interactions with the regulated bacteria. The present study identified the proteomic and intra-tissue microbiome profile of human gingiva by employing a PCT-assisted workflow. This is the first report demonstrating the feasibility to analyse full proteome profiles of gingival tissues in both healthy and disease sites, while deciphering the tissue site-specific microbiome signatures.

Network integration and modelling of dynamic drug responses at multi-omics levels.

Uncovering cellular responses from heterogeneous genomic data is crucial for molecular medicine in particular for drug safety. This can be realized by integrating the molecular activities in networks of interacting proteins. As proof-of-concept we challenge network modeling with time-resolved proteome, transcriptome and methylome measurements in iPSC-derived human 3D cardiac microtissues to elucidate adverse mechanisms of anthracycline cardiotoxicity measured with four different drugs (doxorubicin, epirubicin, idarubicin and daunorubicin). Dynamic molecular analysis at in vivo drug exposure levels reveal a network of 175 disease-associated proteins and identify common modules of anthracycline cardiotoxicity in vitro, related to mitochondrial and sarcomere function as well as remodeling of extracellular matrix. These in vitro-identified modules are transferable and are evaluated with biopsies of cardiomyopathy patients. This to our knowledge most comprehensive study on anthracycline cardiotoxicity demonstrates a reproducible workflow for molecular medicine and serves as a template for detecting adverse drug responses from complex omics data.

Ovine liver proteome: Assessing mechanisms of seasonal weight loss tolerance between Merino and Damara sheep.

The effect of feed restriction on the liver protein profiles of two different breeds of sheep was studied. We compared Merino with the Damara, breeds with respectively low and high tolerance to nutritional stress. Each breed was grouped into two nutritional treatments: restricted (12-14% loss of live weight) and control (maintenance). The trial lasted 42 days. Animals were sacrificed and liver samples subjected to label free shotgun proteomics. The resultant proteins had both their fold change and statistical significance in an unpaired t-test calculated to identify differential protein abundance. The tool WebGestalt was utilized to perform an Overrepresentation Enrichment Analysis (ORA) for gene ontology terms associated with the significant proteins. We further validated shotgun proteomics findings using a selected reaction monitoring (SRM)-based targeted proteomics approach, where similar trends in regulation were obtained for a subset of relevant proteins across an independent cohort of animals. Results confirm that Damara has adapted to nutritional stress by mobilizing stored fatty acids within adipose tissue and converting them to energy more efficiently than Merino. Finally, Merino had an overabundance pattern primarily directed to protein synthesis pathways. Regulated proteins identified may be used as a basis for marker selection towards tolerance to nutritional stress. BIOLOGICAL SIGNIFICANCE: Sheep are one of the most important livestock animals. They remain however poorly understudied and described. Seasonal weight loss (SWL) due to pasture scarcity during the dry season is one of the most limiting conditions to ruminant production in the tropics. To counter SWL, farmers may use supplementation, expensive or difficult to implement. A more suitable long-term solution would be to use breeds that are naturally adapted to nutritional stress. This work contrasts two breeds with different levels of tolerance to SWL, the Damara and the Merino, respectively well and poorly adapted. Comparison is conducted at the level of the hepatic tissue and using label free proteomics. This work identifies a series of pathways in the liver of the Damara via label free proteomics that suggest a unique fatty acid metabolic process within this breed. Proteins that have increased abundance in the Damara in association with fatty acid metabolism may be used as potential markers of tolerance to nutritional stress. This research will pave the way for more viable, long-term solutions for farmers facing annual production problems due to drought in the tropics and the Mediterranean region.