Multiomics surface receptor profiling of the NCI-60 tumor cell panel uncovers novel theranostics for cancer immunotherapy.

BACKGROUND: Immunotherapy with immune checkpoint inhibitors (ICI) has revolutionized cancer therapy. However, therapeutic targeting of inhibitory T cell receptors such as PD-1 not only initiates a broad immune response against tumors, but also causes severe adverse effects. An ideal future stratified immunotherapy would interfere with cancer-specific cell surface receptors only. METHODS: To identify such candidates, we profiled the surface receptors of the NCI-60 tumor cell panel via flow cytometry. The resulting surface receptor expression data were integrated into proteomic and transcriptomic NCI-60 datasets applying a sophisticated multiomics multiple co-inertia analysis (MCIA). This allowed us to identify surface profiles for skin, brain, colon, kidney, and bone marrow derived cell lines and cancer entity-specific cell surface receptor biomarkers for colon and renal cancer. RESULTS: For colon cancer, identified biomarkers are CD15, CD104, CD324, CD326, CD49f, and for renal cancer, CD24, CD26, CD106 (VCAM1), EGFR, SSEA-3 (B3GALT5), SSEA-4 (TMCC1), TIM1 (HAVCR1), and TRA-1-60R (PODXL). Further data mining revealed that CD106 (VCAM1) in particular is a promising novel immunotherapeutic target for the treatment of renal cancer. CONCLUSION: Altogether, our innovative multiomics analysis of the NCI-60 panel represents a highly valuable resource for uncovering surface receptors that could be further exploited for diagnostic and therapeutic purposes in the context of cancer immunotherapy.

Comprehensive Analysis of Human Cytomegalovirus- and HIV-Mediated Plasma Membrane Remodeling in Macrophages.

The plasma membrane (PM) must be overcome by viruses during entry and release. Furthermore, the PM represents the cellular communication compartment and the immune system interface. Hence, viruses have evolved sophisticated strategies to remodel the PM, for instance to avoid immune sensing and clearance of infected cells. We performed a comprehensive analysis of cell surface dysregulation by two human-pathogenic viruses, human cytomegalovirus (HCMV) and human immunodeficiency virus type 1 (HIV-1), in primary macrophages, which are classical antigen-presenting cells and orchestrators of the immune system. Scanning ion conductance microscopy revealed a loss of roughness and an overall smooth phenotype of HCMV-infected macrophages, in contrast to HIV-1 infection. This phenotype was also evident on the molecular level. When we screened for cell surface receptors modulated by HCMV, 42 of 332 receptors tested were up- or downregulated, whereas HIV-1 affected only 7 receptors. In particular CD164, CD84, and CD180 were targeted by HCMV. Mechanistically, HCMV induced transcriptional silencing of these receptors in an interferon (IFN)-independent manner, and expression was reduced not only by lab-adapted HCMV but also by clinical HCMV isolates. Altogether, our plasma membrane profiling of human macrophages provides clues to understand how viruses evade the immune system and identified novel cell surface receptors targeted by HCMV. IMPORTANCE The PM is a key component that viruses have to cope with. It is a barrier for infection and egress and is critically involved in antiviral immune signaling. We hence asked the question how two immunomodulatory viruses, HIV-1 and HCMV, dysregulate this compartment in infected macrophages, relevant in vivo targets of both viruses. We employed a contact-free microscopic technique to image the PM of infected cells and performed a phenotypic flow cytometry-based screen to identify receptor modulations on a molecular level. Our results show that HIV-1 and HCMV differentially manipulate the PM of macrophages. While HIV-1-mediated changes are relatively subtle, HCMV induces major alterations of the PM. We identify novel immune receptors manipulated by HCMV and define mechanisms of how HCMV interferes with receptor expression. Altogether, our study reveals differential strategies of how two human-pathogenic viruses manipulate infected cells and identifies potential novel pathways of HCMV immune evasion.

Platelets Aggregate With Neutrophils and Promote Skin Pathology in Psoriasis.

Psoriasis is a frequent systemic inflammatory autoimmune disease characterized primarily by skin lesions with massive infiltration of leukocytes, but frequently also presents with cardiovascular comorbidities. Especially polymorphonuclear neutrophils (PMNs) abundantly infiltrate psoriatic skin but the cues that prompt PMNs to home to the skin are not well-defined. To identify PMN surface receptors that may explain PMN skin homing in psoriasis patients, we screened 332 surface antigens on primary human blood PMNs from healthy donors and psoriasis patients. We identified platelet surface antigens as a defining feature of psoriasis PMNs, due to a significantly increased aggregation of neutrophils and platelets in the blood of psoriasis patients. Similarly, in the imiquimod-induced experimental in vivo mouse model of psoriasis, disease induction promoted PMN-platelet aggregate formation. In psoriasis patients, disease incidence directly correlated with blood platelet counts and platelets were detected in direct contact with PMNs in psoriatic but not healthy skin. Importantly, depletion of circulating platelets in mice in vivo ameliorated disease severity significantly, indicating that both PMNs and platelets may be relevant for psoriasis pathology and disease severity.

Metabolomics in serum of patients with non-advanced age-related macular degeneration reveals aberrations in the glutamine pathway.

Age-related macular degeneration (AMD) is a common, progressive multifactorial vision-threatening disease and many genetic and environmental risk factors have been identified. The risk of AMD is influenced by lifestyle and diet, which may be reflected by an altered metabolic profile. Therefore, measurements of metabolites could identify biomarkers for AMD, and could aid in identifying high-risk individuals. Hypothesis-free technologies such as metabolomics have a great potential to uncover biomarkers or pathways that contribute to disease pathophysiology. To date, only a limited number of metabolomic studies have been performed in AMD. Here, we aim to contribute to the discovery of novel biomarkers and metabolic pathways for AMD using a targeted metabolomics approach of 188 metabolites. This study focuses on non-advanced AMD, since there is a need for biomarkers for the early stages of disease before severe visual loss has occurred. Targeted metabolomics was performed in 72 patients with early or intermediate AMD and 72 control individuals, and metabolites predictive for AMD were identified by a sparse partial least squares discriminant analysis. In our cohort, we identified four metabolite variables that were most predictive for early and intermediate stages of AMD. Increased glutamine and phosphatidylcholine diacyl C28:1 levels were detected in non-advanced AMD cases compared to controls, while the rate of glutaminolysis and the glutamine to glutamate ratio were reduced in non-advanced AMD. The association of glutamine with non-advanced AMD corroborates a recent report demonstrating an elevated glutamine level in early AMD using a different metabolomics technique. In conclusion, this study indicates that metabolomics is a suitable method for the discovery of biomarker candidates for AMD. In the future, larger metabolomics studies could add to the discovery of novel biomarkers in yet unknown AMD pathways and expand our insights in AMD pathophysiology.

Measles Virus-Based Treatments Trigger a Pro-inflammatory Cascade and a Distinctive Immunopeptidome in Glioblastoma.

Glioblastoma is an aggressive primary brain tumor with bad prognosis. On the other hand, oncolytic measles virus (MeV) therapy is an experimental glioma treatment strategy with clinical safety and first evidence of anti-tumoral efficacy. Therefore, we investigated the combination of MeV with conventional therapies by cytotoxic survival assays in long-term glioma cell lines LN229, LNZ308, and glioma stem-like GS8 cells, as well as the basal viral infectivity in primary glioblastoma cultures T81/16, T1094/17, and T708/16. We employed Chou-Talalay analysis to identify the synergistic treatment sequence chemotherapy, virotherapy, and finally radiotherapy (CT-VT-RT). RNA sequencing and immunopeptidome analyses were used to delineate treatment-induced molecular and immunological profiles. CT-VT-RT displayed synergistic anti-glioma activity and initiated a type 1 interferon response, along with canonical Janus kinase-signal transducers and activators of transcription (JAK-STAT) signaling, and downstream interferon-stimulated genes were induced, resulting in apoptotic cascades. Furthermore, antigen presentation along with immunostimulatory chemokines was increased in CT-VT-RT-treated glioma cells, indicating a treatment-induced pro-inflammatory phenotype. We identified novel treatment-induced viral and tumor-associated peptides through HLA ligandome analysis. Our data delineate an actionable treatment-induced molecular and immunological signature of CT-VT-RT, and they could be exploited for the design of novel tailored treatment strategies involving virotherapy and immunotherapy.

qPortal: A platform for data-driven biomedical research.

Modern biomedical research aims at drawing biological conclusions from large, highly complex biological datasets. It has become common practice to make extensive use of high-throughput technologies that produce big amounts of heterogeneous data. In addition to the ever-improving accuracy, methods are getting faster and cheaper, resulting in a steadily increasing need for scalable data management and easily accessible means of analysis. We present qPortal, a platform providing users with an intuitive way to manage and analyze quantitative biological data. The backend leverages a variety of concepts and technologies, such as relational databases, data stores, data models and means of data transfer, as well as front-end solutions to give users access to data management and easy-to-use analysis options. Users are empowered to conduct their experiments from the experimental design to the visualization of their results through the platform. Here, we illustrate the feature-rich portal by simulating a biomedical study based on publically available data. We demonstrate the software's strength in supporting the entire project life cycle. The software supports the project design and registration, empowers users to do all-digital project management and finally provides means to perform analysis. We compare our approach to Galaxy, one of the most widely used scientific workflow and analysis platforms in computational biology. Application of both systems to a small case study shows the differences between a data-driven approach (qPortal) and a workflow-driven approach (Galaxy). qPortal, a one-stop-shop solution for biomedical projects offers up-to-date analysis pipelines, quality control workflows, and visualization tools. Through intensive user interactions, appropriate data models have been developed. These models build the foundation of our biological data management system and provide possibilities to annotate data, query metadata for statistics and future re-analysis on high-performance computing systems via coupling of workflow management systems. Integration of project and data management as well as workflow resources in one place present clear advantages over existing solutions.

Proteome and phosphoproteome analysis of commensally induced dendritic cell maturation states.

Dendritic cells (DCs) can shape the immune system towards an inflammatory or tolerant state depending on the bacterial antigens and the environment they encounter. In this study we provide a proteomic catalogue of differentially expressed proteins between distinct DC maturation states, brought about by bacteria that differ in their endotoxicity. To achieve this, we have performed proteomics and phosphoproteomics on murine DC cultures. Symbiont and pathobiont bacteria were used to direct dendritic cells into a semi-mature and fully-mature state, respectively. The comparison of semi-mature and fully-mature DCs revealed differential expression in 103 proteins and differential phosphorylation in 118 phosphosites, including major regulatory factors of central immune processes. Our analyses predict that these differences are mediated by upstream elements such as SOCS1, IRF3, ABCA1, TLR4, and PTGER4. Our analyses indicate that the symbiont bacterial strain affects DC proteome in a distinct way, by downregulating inflammatory proteins and activating anti-inflammatory upstream regulators. Biological significance In this study we have investigated the responses of immune cells to distinct bacterial stimuli. We have used the symbiont bacterial strain B. vulgatus and the pathobiont E. coli strain to stimulate cultured primary dendritic cells and performed a shotgun proteome analysis to investigate the protein expression and phosphorylation level differences on a genome level. We have observed expression and phosphorylation level differences in key immune regulators, transcription factors and signal transducers. Moreover, our subsequent bioinformatics analysis indicated regulation at several signaling pathways such as PPAR signaling, LXR/RXR activation and glucocorticoid signaling pathways, which are not studied in detail in an inflammation and DC maturation context. Our phosphoproteome analysis showed differential phosphorylation in 118 phosphosites including those belonging to epigenetic regulators, transcription factors and major cell cycle regulators. We anticipate that our study will facilitate further investigation of immune cell proteomes under different inflammatory and non-inflammatory conditions.

Platforms and Pipelines for Proteomics Data Analysis and Management.

Since mass spectrometry was introduced as the core technology for large-scale analysis of the proteome, the speed of data acquisition, dynamic ranges of measurements, and data quality are continuously improving. These improvements are triggered by regular launches of new methodologies and instruments.

The Pig PeptideAtlas: A resource for systems biology in animal production and biomedicine.

Biological research of Sus scrofa, the domestic pig, is of immediate relevance for food production sciences, and for developing pig as a model organism for human biomedical research. Publicly available data repositories play a fundamental role for all biological sciences, and protein data repositories are in particular essential for the successful development of new proteomic methods. Cumulative proteome data repositories, including the PeptideAtlas, provide the means for targeted proteomics, system-wide observations, and cross-species observational studies, but pigs have so far been underrepresented in existing repositories. We here present a significantly improved build of the Pig PeptideAtlas, which includes pig proteome data from 25 tissues and three body fluid types mapped to 7139 canonical proteins. The content of the Pig PeptideAtlas reflects actively ongoing research within the veterinary proteomics domain, and this article demonstrates how the expression of isoform-unique peptides can be observed across distinct tissues and body fluids. The Pig PeptideAtlas is a unique resource for use in animal proteome research, particularly biomarker discovery and for preliminary design of SRM assays, which are equally important for progress in research that supports farm animal production and veterinary health, as for developing pig models with relevance to human health research.

Quantitative proteomics and bioinformatic analysis provide new insight into the dynamic response of porcine intestine to Salmonella Typhimurium.

The enteropathogen Salmonella Typhimurium (S. Typhimurium) is the most commonly non-typhoideal serotype isolated in pig worldwide. Currently, one of the main sources of human infection is by consumption of pork meat. Therefore, prevention and control of salmonellosis in pigs is crucial for minimizing risks to public health. The aim of the present study was to use isobaric tags for relative and absolute quantification (iTRAQ) to explore differences in the response to Salmonella in two segment of the porcine gut (ileum and colon) along a time course of 1, 2, and 6 days post infection (dpi) with S. Typhimurium. A total of 298 proteins were identified in the infected ileum samples of which, 112 displayed significant expression differences due to Salmonella infection. In colon, 184 proteins were detected in the infected samples of which 46 resulted differentially expressed with respect to the controls. The higher number of changes in protein expression was quantified in ileum at 2 dpi. Further biological interpretation of proteomics data using bioinformatics tools demonstrated that the expression changes in colon were found in proteins involved in cell death and survival, tissue morphology or molecular transport at the early stages and tissue regeneration at 6 dpi. In ileum, however, changes in protein expression were mainly related to immunological and infection diseases, inflammatory response or connective tissue disorders at 1 and 2 dpi. iTRAQ has proved to be a proteomic robust approach allowing us to identify ileum as the earliest response focus upon S. Typhimurium in the porcine gut. In addition, new functions involved in the response to bacteria such as eIF2 signaling, free radical scavengers or antimicrobial peptides (AMP) expression have been identified. Finally, the impairment at of the enterohepatic circulation of bile acids and lipid metabolism by means the under regulation of FABP6 protein and FXR/RXR and LXR/RXR signaling pathway in ileum has been established for the first time in pigs. Taken together, our results provide a better understanding of the porcine response to Salmonella infection and the molecular mechanisms underlying Salmonella-host interactions.

Evaluation of preparation methods for MS-based analysis of intestinal epithelial cell proteomes.

The gut epithelium formed between an organism and the environment plays an essential role in host-microbe interactions, yet remains one of the least characterized mammalian tissues. Especially the membrane proteins, which are critical to bacterial adhesion, are understudied, because these proteins are low in abundance, and large amounts of sample is needed for their preparation and for undertaking MS-based analysis. The aim of this study was to evaluate three different methods for isolation and preparation of pig intestinal epithelial cells for MS-based analysis of the proteome. Samples were analyzed by LC and electrospray QTOF-MS. The methods were evaluated according to efficiency, purity, transmembrane protein recovery, as well as for suitability to large-scale preparations. Our data clearly demonstrate that mucosal shaving is by far the best-suited method for in-depth MS analysis in terms of ease and speed of sample preparation, as well as protein recovery. In comparison, more gentle methods where intestinal epithelial cells are harvested by shaking are more time consuming, result in lower protein yield, and are prone to increased technical variation due to multiple steps involved.

LC-MS/MS analysis of visceral and subcutaneous adipose tissue proteomes in young goats with focus on innate immunity and inflammation related proteins.

The endocrine role of adipose tissue and its involvement in several physiological and pathological processes are well recognized. Studies on human, mouse and rat adipose tissues have made clear that subcutaneous and visceral deposits play different roles, which is also reflected by different protein and gene expression patterns. In ruminants, fat tissues play important biological roles not only for animal health, but also for quality and gain in meat and milk production. Yet very few studies have explored the ruminant adipose tissue proteomes. The aim of our study was to compare subcutaneous and visceral adipose tissues of goat, focusing on proteins involved in immune and inflammatory response. A 2-D LC-MS/MS approach followed by cluster analysis shows a clear distinction between subcutaneous and visceral fat tissue proteomes, and qualitative RT-PCR based analysis of 30 potential adipokines further confirmed the individual expression patterns of 26 of these, including 7 whose mRNA expression was observed for the first time in adipose tissues. This study provides a first description of adipose tissue proteomes in goat, and presents observations on novel proteins related to metabolic and inflammatory pathways. The mass spectrometry data have been deposited to the ProteomeXchange Consortium with the data set identifier PXD000564. BIOLOGICAL SIGNIFICANCE: The proteomic analysis of different subcutaneous and visceral adipose tissue deposits showed tissue specific differences in protein expressions of well known as well as novel adipokines. This highlights the importance of sampling site when studying adipose tissue's metabolic roles. The protein expression characteristics of adipose tissues was evaluated by quantitative RT-PCR, and confirmed that adipose tissues play a central role in controlling inflammation, detoxification and coagulation pathways, as well as regulation of body fat mobilization in dairy animals. These findings are of particular interest in farm animals where health and production traits are important for animal welfare and for economic gains.

Large pore dermal microdialysis and liquid chromatography-tandem mass spectroscopy shotgun proteomic analysis: a feasibility study.

BACKGROUND/AIMS: The purpose of the present pilot study was to investigate the feasibility of combining large pore dermal microdialysis with shotgun proteomic analysis in human skin. METHODS: Dialysate was recovered from human skin by 2000 kDa microdialysis membranes from one subject at three different phases of the study; trauma due to implantation of the dialysis device, a post implantation steady-state period, and after induction of vasodilatation and plasma extravasation. For shotgun proteomics, the proteins were extracted and digested with trypsin. Peptides were separated by capillary and nanoflow HPLC systems, followed by tandem mass spectrometry (MS/MS) on a Quadrupole-TOF hybrid instrument. The MS/MS spectra were merged and mapped to a human target protein database to achieve peptide identification and protein inference. RESULTS: Results showed variation in protein amounts and profiles for each of the different sampling phases. The total protein concentration was 1.7, 0.6, and 1.3 mg/mL during the three phases, respectively. A total of 158 different proteins were identified. Immunoglobulins and the major classes of plasma proteins, including proteases, coagulation factors, apolipoproteins, albumins, and complement factors, make up the major load of proteins in all three test conditions. CONCLUSION: Shotgun proteomics allowed the identification of more than 150 proteins in microdialysis samples from human skin. This highlights the opportunities of LC-MS/MS to study the complex molecular interactions in the skin.

Proteomics: a new tool in bovine claw disease research.

Claw horn disruption (CHD) is a common underlying cause of lameness in dairy cattle which leads to compromised animal welfare and production losses. Despite an intense research effort over the last two decades, progress in reducing the prevalence of lameness due to CHD has been limited. In addition to current research strategies there is a need to develop novel approaches and methods that expand understanding of the disease mechanisms involved in CHD. The objectives of the present study were to explore the potential of liquid chromatography tandem mass spectrometry (LC-MS/MS) in mapping protein expression in three different bovine claw tissues, and to provide a relevant functional annotation of the proteins characterized in these tissues. LC-MS/MS was used to characterize protein expression in coronary band skin (C), claw dermal (D) and lamellar (L) tissues from two heifers. A total of 388 different proteins were identified, with 146 proteins available for identification in C, 279 proteins in D and 269 proteins in L. A functional annotation of the identified proteins was obtained using the on-line Blast2GO tool. Three hundred and sixteen of the identified proteins could be subsequently grouped manually to one or more of five major functional groups related to metabolism, cell structure, immunity, apoptosis and angiogenesis. These were chosen to represent basic cell functions and biological processes potentially involved in the pathogenesis of CHD. The LC-MS/MS-based proteomic analysis presented here is the largest published survey, so far, of the bovine claw tissue proteome.

A Bovine PeptideAtlas of milk and mammary gland proteomes.

Proteome information resources of farm animals are lagging behind those of the classical model organisms despite their important biological and economic relevance. Here, we present a Bovine PeptideAtlas, representing a first collection of Bos taurus proteome data sets within the PeptideAtlas framework. This database was built primarily as a source of information for designing selected reaction monitoring assays for studying milk production and mammary gland health, but it has an intrinsic general value for the farm animal research community. The Bovine PeptideAtlas comprises 1921 proteins at 1.2% false discovery rate (FDR) and 8559 distinct peptides at 0.29% FDR identified in 107 samples from six tissues. The PeptideAtlas web interface has a rich set of visualization and data exploration tools, enabling users to interactively mine information about individual proteins and peptides, their prototypic features, genome mappings, and supporting spectral evidence.

Quantotypic properties of QconCAT peptides targeting bovine host response to Streptococcus uberis.

Mammalian host response to pathogens is associated with fluctuations in high abundant proteins in body fluids as well as in regulation of proteins expressed in relatively low copy numbers like cytokines secreted from immune cells and endothelium. Hence, efficient monitoring of proteins associated with host response to pathogens remains a challenging task. In this paper, we present a targeted proteome analysis of a panel of 20 proteins that are widely believed to be key players and indicators of bovine host response to mastitis pathogens. Stable isotope-labeled variants of two concordant proteotypic peptides from each of these 20 proteins were obtained through the QconCAT method. We present the quantotypic properties of these 40 proteotypic peptides and discuss their application to research in host-pathogen interactions. Our results clearly demonstrate a robust monitoring of 17 targeted host-response proteins. Twelve of these were readily quantified in a simple extraction of mammary gland tissues, while the expression levels of the remaining proteins were too low for direct and stable quantification; hence, their accurate quantification requires further fractionation of mammary gland tissues.

Progesterone profiles around the time of insemination do not show clear differences between of pregnant and not pregnant dairy cows.

In this study, features of progesterone profiles were examined in relation to the outcome of insemination. Three groups of estrous cycles were analyzed: resulting in pregnancy, not resulting in pregnancy and resulting in lost pregnancy. The aim of the study was to identify a complex of progesterone profile features associated with successful insemination. The features used were (1) from the estrous cycle preceding the artificial insemination: estrus progesterone concentration, post-estrus maximum rate of increase in progesterone, luteal phase peak, pre-estrus maximum rate of decline in progesterone and the length of follicular and luteal phase and (2) from the estrous cycle following insemination: estrus progesterone concentration, post-estrus maximum rate of increase in progesterone and days from estrus to post-estrus maximum rate of increase in progesterone. A discriminant analysis did not reveal clear differences between the groups. However, the analysis correctly classified 75% of true pregnant cows. Conversely, only 60% of not pregnant animals were classified as such by the discriminate analysis. Individual analysis of progesterone profile features in pregnant and not pregnant groups of estrous cycles showed that a shorter follicular phase preceding insemination is associated with proper timing of post-ovulatory luteinisation and therefore is more likely to result in pregnancy.

Mahalanobis distance screening of Arabidopsis mutants with chlorophyll fluorescence.

Rapid nondestructive screening of mutants is a common step in many research projects in plant biology. Here we report the development of a method that uses kinetic imaging of chlorophyll fluorescence to detect phenotypes that differ from wild-type plants. The method uses multiple fluorescence features simultaneously in order to catch different types of photosynthesis-related mutants with a single assay. The Mahalanobis distance was used to evaluate the degree of similarity in fluorescence features between the wild-type and test plants, and plants differing strongly from the wild-type were classified as mutants. The method was tested on a collection of photosynthesis-related mutants of Arabidopsis thaliana. The plants were evaluated from images in which the color of each pixel depended on the Mahalanobis distance of the fluorescence features. Two parameters of the color-coding procedure were used to adjust the trade-off between detection of true mutants and erratic classification of wild-type plants as mutants. We found that a large percentage of photosynthesis-related mutants can be detected with this method. Scripts for the free statistics software R are provided to facilitate the practical application of the method.

Quantitative milk proteomics--host responses to lipopolysaccharide-mediated inflammation of bovine mammary gland.

Intramammary infusion of lipopolysaccharide (LPS) in cows induces udder inflammation that partly simulates mastitis caused by infection with Gram-negative bacteria. We have used this animal model to characterize the quantitiative response in the milk proteome during the time course before and immediately after the LPS challenge. Milk samples from three healthy cows collected 3 h before the LPS challenge were compared with milk samples collected 4 and 7 h after the LPS challenge, making it possible to describe the inflammatory response of individual cows. Quantitative protein profiles were obtained for 80 milk proteins, of which 49 profiles changed significantly for the three cows during LPS challenge. New information obtained in this study includes the quantified increase of apolipoproteins and other anti-inflammatory proteins in milk, which are important for the cow's ability to balance the immune response, and the upregulation of both complement C3 and C4 indicates that more than one complement pathway could be activated during LPS-induced mastitis. In the future, this analytical approach may provide valuable information about the differences in the ability of individual cows to resist and recover from mastitis.

Tools for computational processing of LC-MS datasets: a user's perspective.

Liquid chromatography-mass spectrometry (LC-MS) profiling of clinical samples for quantifying absolute ion abundances of peptides and proteins has emerged as a promising approach. Quantitation of changes in protein abundance of large number of samples is challenging and requires automatic processing means. The development of data analysis software is laborious and time-consuming. Fortunately, freely available tools have been recently introduced, which incorporate algorithms for visualization and data processing and allow the user to embed external routines for data analysis. A relevant issue related to the design and evaluation of such tools concerns usability. Properties such as easy access, large datasets management, modularity, integration with other tools, etc, are important for performing large-scale integrative data analysis with methods and visual techniques from different (possibly integrated) tools. In this paper, we consider four freely available tools recently introduced in top international journals in order to identify a list of such usability descriptors. We propose 10 descriptors that can be used both as guidelines when developing new tools and as parameters for assessing usability of existing tools. The considered tools show satisfactory usability properties, and the most recent tools exhibit improved flexibility, indicating a trend towards the design of tools that give the user a more central role in the selection, use and integration of methods and tools.