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Seropositivity for anti-citrullinated peptide antibodies (ACPA) in patients with rheumatoid arthritis (RA), a chronic autoimmune arthritis, is associated with worse long-term disease outcomes. ACPA is ubiquitously tested in RA patients, but other autoantibodies exist (in both citrullinated and non-citrullinated form) which may provide additional information on RA subtypes and/or treatment response. We used a multiplex bead-based assay of 376 autoantibodies to test associations between these autoantibodies and treatment response in RA patients. Clusters of patients with similar autoantibody expression were defined and cluster membership was associated with treatment response. Thirty-four autoantibodies were differentially expressed in RA patients compared with healthy controls; citrullinated vimentin was associated with treatment response. A selection of citrullinated autoantibodies was found to be associated with treatment response in a subanalysis of ACPA-negative RA patients. Finer ACPA specificities in ACPA-negative RA patients may be predictive of treatment response and could represent a rich vein of future study.

BackgroundImproved knowledge regarding the prevalence and clinical significance of the broad spectrum of autoantibodies triggered by SARS-CoV2 infection can clarify the underlying pathobiology, enhance approaches to evaluating heterogeneity of COVID-19 clinical manifestations, and potentially guide options for targeting immunosuppressive therapy as the need for more effective interventions continues to evolve. In this study, we sought to determine the prevalence of autoimmune antibodies in diverse cohort of SARS-CoV-2 positive healthcare workers and measure the extent to which factors associated with triggered autoimmunity are activated even following mild and asymptomatic infection.MethodsAntigen microarrays were used to profile reactivity of IgG autoantibodies against 91 proteins and cytokines based on autoantibody profiling studies in autoimmune diseases.ResultsIn this discovery screening study, we found that 90% of the IgG positive individuals demonstrated reactivity to at least one autoantibody. When compared to results of the same assays conducted on samples from pre-COVID-19 controls, our primary cohort of individuals with SARS-CoV-2 IgG antibody positivity had significantly elevated IgG against twelve additional proteins including CHD3, CTLA4, HARS, IFNA4, INS, MIF, MX1, RNF41, S100A9, SRP19, TROVE2, and VEGFA. These findings confirmed that all severity levels of SARS-CoV-2 infection, even asymptomatic infections, trigger a robust and diverse autoimmune response; our results also highlight the utility of multiparametric autoantibody detection in this setting.InterpretationTaken together, our findings underscore the serological diversity underlying the clinical heterogeneity of COVID-19 infection and its sequelae, including the long-Covid phenotypes.FundingThis work was supported in part by Cedars-Sinai Medical Center (JEE; SC), the Erika J Glazer Family Foundation (JEE; JEVE; SC), CSMC Precision Health Grant (JFB), the F. Widjaja Family Foundation (JGB, GYM, DM), the Helmsley Charitable Trust (JGB, GYM, DM), and NIH grants K23-HL153888 (JEE) and DK062413 (DPBM).RESEARCH IN CONTEXTEvidence before this studyCurrently, several studies have shown the possible involvement of autoimmunity in patients affected by coronavirus disease 2019 (COVID-19). In contrast to cytokine storms, which tend to cause systemic, short-duration problems, autoantibodies (AABs) are thought to result in targeted, longer-term damage and development of autoimmune diseases.Added value of this studyAccording to our knowledge, we evaluated the largest number of protein antigens to characterize the prevalence and heterogeneity of the AABs signature in SARS-CoV-2 convalescent individuals. We examined autoimmune reactivity to SARS-CoV-2 in the absence of extreme clinical disease to acknowledge the existence of AABs even among those who had mild-to-moderate or no symptoms during their illness, as a hallmark of ongoing long-COVID syndrome. Through our analysis we suggest that VEGFA, MIF, IFNA4, SPP1 and APOH could be used as hallmark for SARS-CoV-2 infection and activation of the autoimmune system.Implications of all the available evidenceOur study comprehensively characterized the heterogeneity of the AABs signature in SARS-CoV-2 convalescent individuals. The results established a list of diagnostic signatures and potential therapeutic targets for long-Covid-19 patients although follow-up long-term studies are required. We believe that our findings will serve as a valuable resource, to drive further exploration of long-COVID syndrome pathogenesis.

BackgroundAmidst the millions of individuals affected directly by the pandemic, pronounced sex differences in the susceptibility and response to SARS-CoV-2 infection remain poorly understood. Emerging evidence has highlighted the potential importance of autoimmune activation in modulating not only the acute response but also recovery trajectories following SARS-CoV-2 exposure. Given that immune-inflammatory activity can be sex-biased in the setting of severe COVID-19 illness, we deliberately examined sex-specific autoimmune reactivity to SARS-CoV-2 in the absence of extreme clinical disease.MethodsWe used a bead-based array containing over 90 autoantigens previously linked to a range of classic autoimmune diseases to assess autoantibody (AAB) titers in 177 participants. All participants had confirmed evidence of prior SARS-CoV-2 infection based on presence of positive anti-nucleocapsid IgG serology results (Abbott Diagnostics, Abbott Park, Illinois). We used multivariate analysis to determine whether sex-bias was associated with increased rates of AABs reactivity and symptom burden after SARS-CoV2 infection.Results82.4% of AABs reactivity was associated with being male compared to 17.6% with female. We found a diversity of AABs responses that exhibited sex-specific patterns of frequency distribution as well as associations with symptomatology and symptom burden.ConclusionOur results reveal a remarkable sex-specific prevalence and selectivity of AAB responses to SARS-CoV-2. Further understanding of the nature of triggered and persistent AAB activation among men and women exposed to SARS-CoV-2 will be essential for developing effective interventions against immune-mediated sequelae of COVID-19.

OBJECTIVE To investigate the role of epitope spreading in established systemic lupus erythematosus (SLE). METHODS IgG autoantibody reactivity with 398 distinct recombinant proteins was measured over a period of 6 years in 69 SLE patients and compared to that in 45 controls. Changes in mean fluorescence intensity (MFI), number of autoantibodies to distinct antigens, and reactivity with distinct clones of established antigenic targets (e.g., U1 RNP, Sm, and ribosomal P) representing epitope fine mapping were assessed. Linear mixed modeling, adjusted with Bonferroni correction for age and sex, was applied. RESULTS The total number of autoantibodies, mean MFI, and number of autoantibodies in epitope fine mapping were higher in SLE patients compared to controls (P < 0.0001). The total number of antibodies to distinct autoantigens remained stable over time, while the mean MFI decreased over time in SLE (P < 0.021). SLE patients showed variable recognition of epitopes in fine mapping over time. In particular, in SLE patients, more clones of the U1 RNP complex were recognized at the time of new organ involvement (+0.65) (P = 0.007). Mean MFI was higher in patients with lupus nephritis (P = 0.047). The time-averaged MFIs of 22 individual autoantibodies (including double-stranded DNA [dsDNA]) were higher, after Bonferroni correction, in SLE (P < 0.0001). The MFIs of dsDNA and histone cluster 2 H3c were associated with scores on the Systemic Lupus Activity Measure (P < 0.0001). CONCLUSION Longitudinal surveillance of the IgG autoantibody repertoire in established SLE reveals evidence of sustained breadth of autoantibody repertoire without significant expansion. Associations of disease activity with dsDNA and with histone H3 autoantibodies were confirmed.

Additional file 2 : Supplemental Figure 1.A, Mass spectrometric analysis of in vitro citrullinated fibrinogen. Citrullination is a posttranslational modification of arginine resulting in a monoisotopic mass increase of + 0.984016 Da, which can be measured with mass spectrometry. Following in-vitro citrullination, proteins were digested by trypsin and resulting peptides were analysis by LC-ESI-MS using a Q Exactive Orbitrap mass spectrometer (ThermoFisherScientific, Bremen, Germany. Peptide spetra were investigated using MASCOT (Matrix Sciences, London, UK). The MASCOT search result of citrullinated fibrinogen are shown. Deamidated (citrullinated) peptides are indicated. B, Western Blot detection of in vitro citrullinated fibrinogen. Human fibrinogen (huFib, Sigma) was incubated with peptidylarginine deiminase for four hours. Afterwards proteins were separated by SDS-PAGE and subjected to Western blot analysis using a mouse monoclonal antibody that specifically detects citrullinated fibrinogen (anti-hFibC; Modiquest, AB Oss, Netherlands). Two different citrullinated antigens FibCit2 and FibCit4 (Modiquest, AB Oss, Netherlands) were included to confirm positive reactivity of the anti-huFIbC antibody. C, representative example of Reactivity of control sera with citrullinated und non-citrullinated antigen-coupled beads.

Additional file 1.

558 Background: The AA profile may be altered in malignancies and provide insights into tumor biology and the immune state. We hypothesized that the longitudinal AA profiling of mUC pts receiving an immune checkpoint inhibitor (ICI) may provide insights into the immune response, which may be associated with immune events and help discover new therapeutic targets. Methods: We utilized serum from mUC pts receiving an ICI or platinum-based chemotherapy (PBC) at the Dana-Farber Cancer Institute. Age and sex matched healthy controls were also studied. The SeroTag immuno-oncology discovery array (Oncimmune) was utilized, with quantification of the AA reactivity towards 1150 antigens. Bound autoantibodies were detected using an anti-IgG-specific detection antibody conjugated to the fluorescent reporter dye phycoerythrin. The AA reactivity was reported as the median fluorescence intensity (MFI) for each color and sample using a Luminex FlexMAP3D analyzer. A significance analysis of microarrays was performed to identify AAs with elevated levels in bladder cancer compared to matched healthy controls (HCs). AAs with > 1.5 increase between pre- and post-treatment were reported. Scatter and box-whisker plots were reported for all pts and antigens, respectively. Results: Pre- (n = 66) and post treatment (n = 65) serum samples were available from mUC pts receiving pembrolizumab (n = 25), atezolizumab (n = 21), nivolumab (n = 5), avelumab (n = 1), durvalumab + tremelimumab (n = 1), nivolumab plus vaccine (n = 1), and 12 pts who received PBC (cisplatin n = 8, carboplatin n = 4). The median duration between the pre- and post-therapy samples was 6 months, median age was 67.7 years (range 40-91) with 51 men (77.3%). Overall, significant heterogeneity of AAs between pts was observed with 37 AAs showing higher reactivity in pre-treatment mUC pts vs. 47 HCs, notably anti-CTAG1 (NY-ESO-1), CTAG2 (NY-ESO-2), MAGE B-18, KRAS, GRB2, RARRES2, HSP72 and FGFR3 (all p < 0.05). Pre- and post-therapy AA profiles were similar with unique changes seen in each patient. Notably, 3 pts receiving an ICI developed AAs to NY-ESO-1. Pts receiving PBC less frequently developed new AAs, although pts treated with cisplatin appeared to develop AAs more frequently compared to carboplatin-treated pts. Conclusions: This is the first report of a comprehensive AA profile using a novel platform in mUC pts. The study identified multiple elevated AAs in mUC pts vs. HCs, most notably NY-ESO-1, which also developed in some pts following ICIs. Pts treated with PBC did not develop new AAs frequently, although there appeared to be a difference between cisplatin and carboplatin-based chemotherapy. Further development of this platform is warranted to provide data that is orthogonal to genomic/transcriptomic profiling and shed insights on potential therapeutically actionable antigens.

Objective Diagnosis of SLE relies on the detection of autoantibodies. We aimed to assess the diagnostic potential of histone H4 and H2A variant antibodies in SLE. Methods IgG-autoantibodies to histones H4 (HIST1H4A), H2A type 2-A (HIST2H2AA3) and H2A type 2-C (HIST2H2AC) were measured along with a standard antibody (SA) set including SSA, SSB, Sm, U1-RNP and RPLP2 in a multiplex magnetic microsphere-based assay in 153 SLE patients [85% female, 41 (13.5) years] and 81 healthy controls [77% female, 43.3 (12.4) years]. Receiver operating characteristic analysis was performed to assess diagnostic performance of individual markers. Logistic regression analysis was performed on a random split of samples to determine the additional value of histone antibodies in comparison with SA by likelihood ratio test and determination of diagnostic accuracy in the remaining validation samples. Results Microsphere-based assay showed good interclass correlation (mean 0.85, range 0.73-0.99) and diagnostic performance in receiver operating characteristic analysis (area under the curve (AUC) range 84.8-93.2) compared with routine assay for SA parameters. HIST1H4A-IgG was the marker with the best individual diagnostic performance for SLE vs healthy (AUC 0.97, sensitivity 95% at 90% specificity). HIST1H4A-IgG was an independent significant predictor for the diagnosis of SLE in multivariate modelling (P < 0.0001), and significantly improved prediction of SLE over SA parameters alone (residual deviance 45.9 vs 97.1, P = 4.3 × 10-11). Diagnostic accuracy in the training and validation samples was 89 and 86% for SA, and 95 and 89% with the addition of HIST1H4A-IgG. Conclusion HIST1H4A-IgG antibodies improve diagnostic accuracy for SLE vs healthy.

// Dagmar Quandt 1 , Hans Dieter Zucht 2 , Arno Amann 3 , Anne Wulf-Goldenberg 4 , Carl Borrebaeck 5 , Michael Cannarile 6 , Diether Lambrechts 7 , Herbert Oberacher 8 , James Garrett 9 , Tapan Nayak 10 , Michael Kazinski 11 , Charles Massie 12 , Heidi Schwarzenbach 13 , Michele Maio 14 , Robert Prins 15 , Bjorn Wendik 16 , Richard Hockett 17 , Daniel Enderle 18 , Mikkel Noerholm 18 , Hans Hendriks 19 , Heinz Zwierzina 3 and Barbara Seliger 1 1 Institute of Medical Immunology, Martin Luther University Halle-Wittenberg, Halle, Germany 2 Protagen, Dortmund, Germany 3 Department of Haematology and Oncology, Medical University Innsbruck, Innsbruck, Austria 4 Experimental Pharmacology and Oncology, Berlin-Buch GmbH, Berlin, Germany 5 Create Health Translational Cancer Center, Lund University, Lund, Sweden 6 Roche Pharmaceutical Research and Early Development, Roche Innovation Center, Munich, Germany 7 Laboratory for Translational Genetics, VIB Center for Cancer Biology, Leuven, Belgium 8 Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria 9 Global Drug Development, Novartis Institutes for BioMedical Research, Cambridge, Massachusetts, USA 10 Roche Pharmaceutical Research and Early Development, Roche Innovation Center Basel, Basel, Switzerland 11 Qiagen, Hilden, Germany 12 CRUK Cambridge Institute, Cambridge, UK 13 University Medical Center Hamburg-Eppendorf, Department of Tumor Biology Hamburg, Hamburg, Germany 14 Medical Oncology and Immunotherapy, University Hospital of Siena, Siena, Italy 15 Department of Neurosurgery, David Geffen School of Medicine at UCLA, Los Angeles, California, USA 16 Perkin Elmer, Hamburg, Germany 17 Biodesix, Boulder, Colorado, USA 18 Exosome Diagnostics GmbH, Martinsried, Germany 19 Hendriks Pharmaceutical Consulting, Purmerend, The Netherlands Correspondence to: Barbara Seliger, email: Barbara.Seliger@uk-halle.de Keywords: liquid biopsy, biomarker, tumor, high throughput analysis, immunotherapy Received: February 08, 2017 Accepted: April 04, 2017 Published: April 24, 2017 ABSTRACT During the last decade, novel immunotherapeutic strategies, in particular antibodies directed against immune checkpoint inhibitors, have revolutionized the treatment of different malignancies leading to an improved survival of patients. Identification of immune-related biomarkers for diagnosis, prognosis, monitoring of immune responses and selection of patients for specific cancer immunotherapies is urgently required and therefore areas of intensive research. Easily accessible samples in particular liquid biopsies (body fluids), such as blood, saliva or urine, are preferred for serial tumor biopsies. Although monitoring of immune and tumor responses prior, during and post immunotherapy has led to significant advances of patients’ outcome, valid and stable prognostic biomarkers are still missing. This might be due to the limited capacity of the technologies employed, reproducibility of results as well as assay stability and validation of results. Therefore solid approaches to assess immune regulation and modulation as well as to follow up the nature of the tumor in liquid biopsies are urgently required to discover valuable and relevant biomarkers including sample preparation, timing of the collection and the type of liquid samples. This article summarizes our knowledge of the well-known liquid material in a new context as liquid biopsy and focuses on collection and assay requirements for the analysis and the technical developments that allow the implementation of different high-throughput assays to detect alterations at the genetic and immunologic level, which could be used for monitoring treatment efficiency, acquired therapy resistance mechanisms and the prognostic value of the liquid biopsies.

Background RA patients who are ACPA-positive (ACPA+) are known to have worse prognosis. Less is known regarding predictors of treatment outcomes in ACPA-negative (ACPA-) patients. Objectives We investigated whether autoantibodies captured on a custom array were associated with response to therapy in ACPA- RA patients. Methods RA patients were recruited to either the Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS, starting adalimumab, established disease) or the RA Medication Study (RAMS, starting methotrexate, early disease). Serum samples were collected at pre-treatment and 3/6 months in BRAGGSS/RAMS, respectively. Treatment groups were pooled for analysis. ACPA was measured using a commercially available ELISA (Axis-Shield Diagnostics Ltd, Dundee, UK). Pre-treatment RA and healthy blood donor control (HC) serum samples were incubated on a bead-based assay (Luminex FlexMap 3D) containing 376 human protein antigens associated with autoimmune disease (39 in citrullinated (cit) form) to detect autoantibodies. Median fluorescence intensity (MFI) values were calculated for each autoantibody for RA and HC, then normalised and log2-transformed. The 95th percentile for each autoantibody in HC was used to determine whether an RA sample was positive/negative for that autoantibody. Proteins with Results 168 patients with RA were included in analysis (mean age 59.6 years, mean disease duration 14.3 years, 126 (75%) female patients, 90 (53.6%) ACPA+ patients). 34 autoantibodies were differentially expressed in RA patients, only one of which (TNF ligand superfamily member 13, TNFSF13) was lower than in HC. 29/34 autoantigens were in cit-form. In multivariate models of all differentially expressed autoantibodies, heterogeneous nuclear ribonucleoprotein A1 (HNRNPA1) was significantly associated with EULAR response (coefficient (coef) 0.7, 95% CI 0.1-1.3), and cit-vimentin (VIM) was significantly associated with poor EULAR response (ORadj 4.2, 95% CI 1.1-18.3) and reduced odds of good EULAR response (ORadj 0.2, 95% CI 0.1-0.8). ACPA remained the best predictor of treatment response. In a subanalysis of the 78 ACPA-patients, cit-cleavage and polyadenylation specificity factor subunit 6 (CPSF6) was significantly associated with worse DAS28 (coef (-1.8), 95% CI (-3.6)-(-0.1)). cit-DnaJ homolog subfamily B member 1 (DNAJB1) was significantly associated with DAS28 improvement (coef 2.2, 95% CI 0.6-3.8). No autoantibody was associated with EULAR response. Conclusion A subset of ACPA-patients have ACPA fine specificities not seen by a commercial assay. Larger ACPA profiling may provide additional information on treatment response. This requires validation with larger sample sizes and replication in an independent cohort. Reference [1] Ann Rheum Dis2013;72:844. 2. Arthritis Res Ther2016;18:235. Disclosure of Interests Stephanie Ling: None declared, Nisha Nair: None declared, Darren Plant: None declared, Hans-Dieter Zucht Employee of: Hans-Dieter Zucht is an employee of Protagen AG, Petra Budde Employee of: Petra Budde is an employee of Protagen AG, Peter Schulz-Knappe Shareholder of: Peter Schulz-Knappe is a shareholder of Protagen AG, Consultant for: Peter Schulz-Knappe is a consultant to Protagen AG, Employee of: Peter Schulz-Knappe was an employee of Protagen AG, MATURA Consortium: None declared, Anne Barton: None declared

10011 Background: Increasing evidence suggests that the B cell response in cancer patients is an important component of anti-tumour immunity. Autoantibodies targeting tumour and self-antigens may serve as biomarkers of anti-tumour and auto-immunity. As they can be measured in patient' sera, they have great potential as clinical routine biomarkers. The objective of this study was to explore if autoantibodies are associated with survival and immune related adverse events (irAE) in patients with metastatic melanoma under checkpoint inhitibor (CPI) therapy. Methods: Pre-treatment serum samples from 333 metastatic melanoma patients receiving CPI therapy at 5 European centers were retrospectively used to identify autoantibody signatures for survival and irAE. We designed a cancer immunotherapy antigen array comprising 832 autoimmune and tumour antigens as well as immune and cancer pathway proteins. Statistical tests were separately performed for patients treated with anti-CTLA4 (alone or in combination) and with anti-PD1 antibody monotherapy. Cox-regression analysis and univariate statistical tests were applied for biomarker discovery. Progression free and overall survival was measured from treatment initiation to tumor progression or death date. irAE were recorded including onset date and grade (CTC-AE). Results: For each therapy group we identified a set of autoantibody reactivities in untreated melanoma patients that were associated with the development of irAEs and/or survival. The identified autoantibodies target a diverse set of antigens comprising neoantigens (p53), cancer testis antigens (MAGEB4), paraneoplastic antigens (gephyrin), autoantigens (ribosomal proteins, Nor-90) and FGFR1. Autoantigens that correlated with irAE and survival were e.g. anti-MAGEB4 and anti-FGFR1. Elevated anti-MAGEB4 pre-treatment levels were associated with longer overall survival (p = 0.002, HR = 0.77) and the development of irAEs (p = 0.002, HR = 1.27) in ipilimumab +/- nivolumab treated patients. Higher pre-treatment anti-FGFR1 antibodies were associated with shorter survival (p = 0.008, HR = 1.27) and a lower a lower frequency of irAEs (p = 0.04, HR = 0.69) in these patients. Conclusions: We identified autoantibody targets suggesting a diverse B cell response to antigens expressed in tumours and those associated with autoimmunity. Depending on the specific antigen, the immune response towards those antigens may be associated with anti-tumour or pro-tumour responses.

Along with the rise in the use chemical allergens in in fragrances and cosmetic products, increased reporting of allergic contact dermatitis (ACD) continues to be a public health concern. So far, risk assessment of potential allergens essentially relies upon animal testing. New proteomics technologies combined with appropriate cell culture models and bioinformatics tools open up the window to transfer logical pathway information into biomarker assays. Sensiderm™ TMT-SRM 10-plex is a multiparametric assay, which is based on the established principles of selected reaction monitoring (SRM) mass spectrometry. The assay uses the human dendritic model MUTZ-3 exposed to chemical sensitizers to measure a response signature of ten proteins. In a model-building phase, the ten protein targets were initially discovered using a set of chemical sensitizers provided by the European Integrated Project Sens-it-iv. Currently, the Sensiderm assay has been pre-validated in two analytical laboratories, and a set of testing chemicals has been investigated in both non-blinded and blinded manner. In summary, the Sensiderm 10-plex assay reflects the activation of different sensitization-related pathways. A proper interpretation of this information may be integrated in decision-making processes of suspicious chemicals.

Background High throughput protein expression studies can be performed using bead-based protein immunoassays, such as the Luminex® xMAP® technology. Technical variability is inherent to these experiments and may lead to systematic bias and reduced power. To reduce technical variability, data pre-processing is performed. However, no recommendations exist for the pre-processing of Luminex® xMAP® data. Results We compared 37 different data pre-processing combinations of transformation and normalization methods in 42 samples on 384 analytes obtained from a multiplex immunoassay based on the Luminex® xMAP® technology. We evaluated the performance of each pre-processing approach with 6 different performance criteria. Three performance criteria were plots. All plots were evaluated by 15 independent and blinded readers. Four different combinations of transformation and normalization methods performed well as pre-processing procedure for this bead-based protein immunoassay. Conclusions The following combinations of transformation and normalization were suitable for pre-processing Luminex® xMAP® data in this study: weighted Box-Cox followed by quantile or robust spline normalization (rsn), asinh transformation followed by loess normalization and Box-Cox followed by rsn. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2888-7) contains supplementary material, which is available to authorized users.

Supplementary figures. All results for the QQ-, Mean-SD, Bland-Altman and Volcano plots. (PDF 5133Â kb)

Supplementary table. Detailed results for the evaluation criteria skewness, tail length and coefficient of variation. (PDF 54Â kb)

e15141Background: Immune reactions in cancer involve cellular and humoral response and defense mechanisms. For example, therapies which target CTLA-4 and PD-1/PD-L1 pathways have led to significant...

This review addresses the concepts, limitations and perspectives for the application of peptidomics science and technologies to discover putative biomarkers in blood specimens. Peptidomics can be defined as the comprehensive multiplex analysis of endogenous peptides contained within a biological sample under defined conditions to describe the multitude of native peptides in a biological compartment. In addition to the discovery of disease associated biomarkers, an emerging field in peptidomics is the analysis of peptides to describe in vivo effects of protease inhibitors. The development and application of peptidomics technologies represent an arena of biomarker research that has the potential for adding significant clinical value.

Cancer cells exhibit specific changes in protein expression and alterations in proteolytic activities. Peptides are capable of reflecting these pathological changes and are educible by dedicated analytical technologies. Oncopeptidomics can be defined as the comprehensive multiplexed analysis of endogenous peptides from a biological sample, under defined conditions, to discover probable valid peptide tumor biomarker. Here, mass spectrometry has shown its potential as a comprehensive peptide profiling tool. The efforts to arrive at diagnostically relevant biomarkers may have been underestimated. The establishment of novel cancer biomarkers will necessitate a multidisciplinary effort and presumably require a duration comparable to the drug development process. This review will address current concepts, new perspectives and the developmental process leading to clinically useful peptide tumor markers.

The objective of this work was the application of peptidomics®1 technologies for the detection and identification of reliable and robust biomarkers for Alzheimers disease (AD) contributing to facilitate and further improve the diagnosis of AD. Using a new method for the comprehensive and comparative profiling of peptides, the differential peptide display® (DPD), 312 cerebrospinal fluid (CSF) samples from AD patients, cognitively unimpaired subjects and from patients suffering from other primary dementia disorders were analysed as four independent analytical sets. By combination with a cross validation procedure, candidates were selected from a total of more than 6,000 different peptide signals based on their discriminating power. Twelve candidates were identified using mass-spectrometric techniques as fragments of the possibly neuroprotective neuroendocrine protein VGF and another one as the complement factor C3 descendent C3f. The combination of peptide profiling and cross validation resulted in the detection of novel potential biomarkers with remarkable robustness and a close relation to AD pathophysiology.

This report will provide a brief overview of the application of data mining in proteomic peptide profiling used for medical biomarker research. Mass spectrometry based profiling of peptides and proteins is frequently used to distinguish disease from non-disease groups and to monitor and predict drug effects. It has the promising potential to enter clinical laboratories as a general purpose diagnostic tool. Data mining methodologies support biomedical science to manage the vast data sets obtained from these instrumentations. Here we will review the typical workflow of peptide profiling, together with typical data mining methodology. Mass spectrometric experiments in peptidomics raise numerous questions in the fields of signal processing, statistics, experimental design and discriminant analysis.

Peptides are a paramount example of how nature diversifies from one single gene to release multiple, regulated functionalities at the desired sites and time. To achieve this, peptides are sequentially generated by a complex network of more than 500 proteases, acting at intracellular sites, upon secretion, in extracellular environments, and, finally, serving (regulated) degradation. This cycle of maturation, activation, and degradation points out that the peptidome is mechanistically linked to the proteome: the distribution between both is regulated by proteases and counter-regulated by protease inhibitors. Given the high diversity of peptides in living systems and their involvement in key regulatory processes, a need for improved peptide discovery, ideally combining peptide sequence identification with peptide profiling, has emerged. Standard proteomic approaches are not suitable for a systematic peptide analysis, since they do not cover the low molecular mass window. The new direction in proteomic research to analyse this "terra incognita" is peptidomics. This novel concept aims at the comprehensive visualization and analysis of small polypeptides, thus covering the mass range between proteomics and metabonomics. The pacemakers for the development of peptidomics technologies are modern mass spectrometry and bioinformatics. They are ideally suited for sensitive and comprehensive peptide analysis, especially in combination with the massive information content of today's genomic and transcriptomic databases. Given the high diversity of native peptides in living systems, clinical chemistry and modern medicine are the prime application areas. The discovery of relevant peptide biomarkers and drug targets will strongly benefit from peptidomics.

Profiling of peptides and small proteins from either human body fluids or tissues by chromatography and subsequent mass spectrometry reveals several thousand individual peptide signals per sample. Any peptide is an intermediate in the course of biosynthesis, post-translational modification (PTM), proteolytic processing and degradation. Changes in the concentration of one peptide often affects the concentration of the other, hence a challenge consists in the development of suitable tools to turn this large amount of data into biologically relevant information. Comprehensive statistical analysis of the peptide profiling data allows associating peptides, which are closely related in terms of peptide biochemistry. Here, the bioinformatic concept of peptide networks, correlation-associated peptide networks (CANs), is introduced. Peptides with statistical similarity of their concentrations are grouped in form of networks, and these networks are interpreted in terms of peptide biochemistry. The spectrum of functional relationships found in cerebrospinal fluid CAN covers PTM and proteolytic degradation of peptides, clearance processing in the complement cascade, common secretion of peptides by neuroendocrine cells as well as ubiquitin-mediated degradation. Our results indicate that CAN is a powerful bioinformatic tool for the systematic analysis and interpretation of large peptidomics and proteomics data and helps to discover novel bioactive and diagnostic peptides.

Peptides, such as many hormones, cytokines and growth factors play a central role in biological processes. Furthermore, as degradation products and processed forms of larger proteins they are part of the protein turnover. Thus, they can reflect disease-related changes in an organism’s homeostasis in several ways. Since two-dimensional gel electrophoresis is restricted to analysis and display of proteins with relative molecular masses above 5000, we developed Differential Peptide Display (DPD), a new technology for analysis and visualization of peptides. Here we describe its application to cerebrospinal fluid of three subjects without a disease of the central nervous system (CNS) undergoing routine myelography and of two patients suffering from a primary CNS lymphoma. Peptides with a relative molecular mass below 20 000 were extracted and analysed by a combination of chromatography and mass spectrometry. The peptide pattern of a sample was depicted as a multi-dimensional peptide mass fingerprint with each peptide’s position being characterized by its molecular mass and chromatographic behaviour. Such a fingerprint of a CNS sample consists of more than 6000 different signals. Data analysis of peptide patterns from patients with CNS lymphoma compared to controls revealed obvious differences regarding the peptide content of the samples. By analysing peptides within a mass range of 750–20 000, DPD extends 2D gel electrophoresis, thus offering the chance to investigate CNS diseases on the level of peptides. This represents a new approach for diagnosis and possible therapy.

The large intestine of breast-fed infants is colonized predominantly by bifidobacteria, which have a protective effect against acute diarrhea. In this study we report for the first time the identification of human milk peptides that selectively stimulate the growth of bifidobacteria. Several bifidogenic peptides were purified chromatographically from pepsin-treated human milk and identified as proteolytically generated fragments from the secretory component of the soluble polyimmunoglobulin receptor and lactoferrin; both of these proteins exhibit antimicrobial effects. Hydrolysis of the identified peptides with the gastrointestinal proteases pepsin, trypsin and chymotrypsin did not lead to the loss of bifidogenic activity, indicating their potential function in vivo. Sequential comparison revealed a similar structural motif within the identified peptides. A correspondingly designed small peptide (prebiotic lactoferrin-derived peptide-I, PRELP-I) was found to stimulate the growth of bifidobacteria as effectively as the native peptides. The combination of antimicrobial and bifidobacterial growth stimulatory activity in human milk proteins leads to highly specific compounds capable of regulating the microbial composition of infants' large intestine.

BackgroundThe study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia.MethodsThree multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty-six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays.ResultsSixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%).ConclusionsWe have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.

Peripheral blood mononuclear cells (PBMCs) are an easy accessible cellular part of the blood organ and, along with platelets, represent the only site of active gene expression in blood. These cells undergo immunophenotypic changes in various diseases and represent a peripheral source of monitoring gene expression and posttranslational modifications relevant to many diseases. Little is known about the source of many blood proteins and we hypothesise that release from PBMCs through active and passive mechanisms may account for a substantial part of the plasma proteome. The use of state-of-the-art proteomic profiling methods in PBMCs will enable minimally invasive monitoring of disease progression or response to treatment and discovery of biomarkers. To achieve this goal, detailed mapping of the PBMC proteome using a sensitive, robust, and quantitative methodological setup is required. We have applied an indepth gel-free proteomics approach using tandem mass tags (TMT), unfractionated and SCX fractionated PBMC samples, and LC-MS/MS with various modulations. This study represents a benchmark in deciphering the PBMC proteome as we provide a deep insight by identifying 4129 proteins and 25503 peptides. The identified proteome defines the scope that enables PBMCs to be characterised as cellular major biomarker pool within the blood organ.

Objective:\ud LC-MS/MS phospho-proteomics is an essential technology to help unravel the complex molecular events that lead to and propagate cancer. We have developed a global phospho-proteomic workflow to determine activity of signaling pathways and drug targets in pancreatic cancer tissue for clinical application.\ud \ud Methods:\ud Peptides resulting from tryptic digestion of proteins extracted from frozen tissue of pancreatic ductal adenocarcinoma and background pancreas (n = 12), were labelled with tandem mass tags (TMT 8-plex), separated by strong cation exchange chromatography, then were analysed by LC-MS/MS directly or first enriched for phosphopeptides using IMAC and TiO2, prior to analysis. In-house, commercial and freeware bioinformatic platforms were used to identify relevant biological events from the complex dataset.\ud \ud Results:\ud Of 2,101 proteins identified, 152 demonstrated significant difference in abundance between tumor and non-tumor tissue. They included proteins that are known to be up-regulated in pancreatic cancer (e.g. Mucin-1), but the majority were new candidate markers such as HIPK1 & MLCK. Of the 6,543 unique phosphopeptides identified (6,284 unique phosphorylation sites), 635 showed significant regulation, particularly those from proteins involved in cell migration (Rho guanine nucleotide exchange factors & MRCKα) and formation of focal adhesions. Activator phosphorylation sites on FYN, AKT1, ERK2, HDAC1 and other drug targets were found to be highly modulated (≥2 fold) in different cases highlighting their predictive power.\ud \ud Conclusion:\ud Here we provided critical information enabling us to identify the common and unique molecular events likely contributing to cancer in each case. Such information may be used to help predict more bespoke therapy suitable for an individual case.

A strategy was established for the identification of novel antimicrobial peptides from human milk. For the generation of bioactive peptides human milk was acidified and proteolyzed with pepsin simulating the digest in infants stomachs. Separation of proteins and resulting fragments was performed by means of reversed-phase chromatography detecting the antimicrobial activity of each fraction using a sensitive radial diffusion assay. In order to avoid the purification of the known abundant antimicrobial milk protein lysozyme, it was identified in HPLC fractions by its enzymatic activity and by matrix-assisted laser desorption ionization–mass spectrometry (MALDI–MS). On condition that lysozyme was not detectable and antibacterial activity of HPLC fractions was caused by a peptide, which was confirmed by proteolytic cleavage leading to a loss of activity, further purification was performed by consecutive chromatographic steps guided by the antibacterial assay. Using this strategy, an as yet unknown casein fragment exhibiting antimicrobial activity was purified in addition to antimicrobial lactoferrin fragments. The new antimicrobial peptide resembles a proteolytic fragment of human casein-κ (residues 63–117) and inhibits the growth of Gram-positive, Gram-negative bacteria, and yeasts. Our results confirm that antimicrobially-active peptides are liberated from human milk proteins during proteolytic hydrolysis and may play an important role in the host defense system of the newborn.

Proteinase inhibitors are important negative regulators of proteinase action in vivo. We have succeeded in isolating two previously unknown polypeptides (HF6478 and HF7665) from human blood filtrate that are parts of a larger precursor protein containing two typical Kazal-type serine proteinase inhibitor motifs. The entire precursor protein, as deduced from the nucleotide sequence of the cloned cDNA, exhibits 15 potential inhibitory domains, including the Kazal-type domains, HF6478, HF7665, and 11 additional similar domains. An inhibitory effect of HF7665 on trypsin activity is demonstrated. Because all of the 13 HF6478- and HF7665-related domains share partial homology to the typical Kazal-type domain but lack one of the three conserved disulfide bonds, they may represent a novel type of serine proteinase inhibitor. The gene encoding the multidomain proteinase inhibitor, which we have termed LEKTI, was localized on human chromosome 5q31-32. As shown by reverse transcriptase-polymerase chain reaction and Northern blot analysis, it is expressed in the thymus, vaginal epithelium, Bartholin's glands, oral mucosa, tonsils, and the parathyroid glands. From these results, we assume that LEKTI may play a role in anti-inflammatory and/or antimicrobial protection of mucous epithelia.

Guanylin and uroguanylin are structurally related intestinal peptide hormones which were purified from a limited number of mammals and are capable of activating the particulate guanylate cyclase-C. Although the biological functions of guanylin and uroguanylin are not yet clarified in detail, they are involved in the regulation of the intestinal water and electrolyte balance. In order to verify the general importance of this hormone system in mammals, we cloned the corresponding cDNAs from pig. Here, we present the nucleotide sequences and the deduced amino acid sequences representing porcine guanylin and uroguanylin. The expression patterns of the corresponding genes, as shown by Northern hybridization and RT-PCR analysis, resemble those of the human homologues. Further, we demonstrate the bioactivity of both porcine peptide hormones by inducing the intracellular cGMP production in human T84 cells and by ion transport experiments using porcine intestinal mucosa in the Ussing chamber.

Cloning and sequencing of the upstream region of the gene of the CC chemokine HCC-1 led to the discovery of an adjacent gene coding for a CC chemokine that was named “HCC-2.” The two genes are separated by 12-kbp and reside in a head-to-tail orientation on chromosome 17. At variance with the genes for HCC-1 and other human CC chemokines, which have a three-exon-two-intron structure, the HCC-2 gene consists of four exons and three introns. Expression of HCC-2 and HCC-1 as studied by Northern analysis revealed, in addition to the regular, monocistronic mRNAs, a common, bicistronic transcript. In contrast to HCC-1, which is expressed constitutively in numerous human tissues, HCC-2 is expressed only in the gut and the liver. HCC-2 shares significant sequence homology with CKβ8 and the murine chemokines C10, CCF18/MRP-2, and macrophage inflammatory protein 1γ, which all contain six instead of four conserved cysteines. The two additional cysteines of HCC-2 form a third disulfide bond, which anchors the COOH-terminal domain to the core of the molecule. Highly purified recombinant HCC-2 was tested on neutrophils, eosinophils, monocytes, and lymphocytes and was found to exhibit marked functional similarities to macrophage inflammatory protein 1α. It is a potent chemoattractant and inducer of enzyme release in monocytes and a moderately active attractant for eosinophils. Desensitization studies indicate that HCC-2 acts mainly via CC chemokine receptor CCR1.

The complete cell biological analysis of human guanylin, a recently discovered regulatory peptide, is offered in this investigation: (i) the nucleotide sequence of the gene, (ii) the isolation and characterization of its circulating molecular form, and (iii) its localization in enterochromaffin cells of the gut. As determined by molecular cloning, DNA sequencing, and comparison with the known cDNA sequence, the approximately 2.6-kbp large gene consists of three exons interrupted by two introns. The putative promoter region contains a TTTAAAA sequence motif and several potential binding sites for transcription factors such as AP-1, AP-2, Sp 1, and glucocorticoid receptors. The isolated hormonal form of guanylin is a 94-amino acid peptide with a molecular mass of 10.3 kDa. Western blot analysis of RP-HPLC fractions from blood plasma confirms this molecular form. Thus, guanylin is synthesized by gut enterochromaffin cells as a prohormone of 115 amino acids and is processed to the molecular form of 94 amino acids circulating in the blood.

Clusterin, complement C3, complement C3a, serum amyloid P component (SAP), alpha-2-macroglobulin (A2M), gelsolin, fibrinogen gamma-chain (FGG) and complement factor H (CFH) have emerged as candidate AD biomarkers from discovery exercises using twodimensional gel electrophoresis and TMT labeling technologies (Hye et al., 2006; Thambisetty et al., 2010; Guntert et al., 2010). Furthermore, possession of the apolipoprotein E (Apo E) E4 allele is the only unequivocal genetic risk factor known to-date for late-onset AD and the protein expression of this genetic association may translate as an AD biomarker. The expression levels and absolute quantitative amounts of these proteins across large patient populations have yet to be described. We have now developed two mass spectrometry assay methods based on using isotopically labelled synthetic peptides (TMT-SRM) or a whole plasma digest reference (TMTOrbi) to assess candidate biomarker levels in plasma and present the results from the analysis of a subset of samples from an extensive, well characterised cohort of AD, MCI and Control patients.

Dipeptidyl peptidase 4 (DPP4) inhibitors represent a novel class of oral anti-hyperglycemic agents. The complete pharmacological profile of these protease inhibitors remains unclear. In order to gain deeper insight into the in vivo effects caused by DPP4 inhibition, two different DPP4 inhibitors (vildagliptin and AB192) were analyzed using differential peptide display. Wistar rats were treated with the DPP4 inhibitors (0.3mgkg(-1); 1mgkg(-1) or 3mgkg(-1) body weight) and DPP4 activity was measured before and at the end of the experiment. One hour after compound administration, blood plasma samples were collected to generate peptide displays and to subsequently identify differentially regulated peptides. A dose-dependent decrease in blood plasma DPP4 activity was measured for both inhibitors. DPP4 inhibition influenced collagen metabolism leading to depletion of collagen derived peptides (e.g. collagen alpha 1 (III) 521-554) and accumulation of related N-terminally extended collagen derived peptides (e.g. collagen alpha 1 (III) 519-554). Furthermore, the intact amyloid rat BRI (1-23) peptide was detected in plasma following in vivo DPP4 inhibition. DPP4 catalyzed cleavage kinetics of the BRI peptide were determined in vitro. The k(cat) and K(m) for cleavage by DPP4 were 5.2s(-1) and 14microM, respectively, resulting in a specificity constant k(cat)/K(m) of 0.36 x 10(6)s(-1)M(-1). Our results demonstrate that differential peptide analysis can be applied to monitor action of DPP4 inhibition in blood plasma. For the first time effects on basal collagen metabolism following DPP4 inhibition in vivo were demonstrated and the BRI amyloid peptide was identified as a novel DPP4 substrate.

During the course of biosynthesis, processing and degradation of a peptide, many structurally related intermediate peptide products are generated. Human body fluids and tissues contain several thousand peptides that can be profiled by reversed-phase chromatography and subsequent MALDI-ToF-mass spectrometry. Correlation-Associated Peptide Networks (CAN) efficiently detect structural and biological relations of peptides, based on statistical analysis of peptide concentrations. We combined CAN with recognition of probable cleavage sites for peptidases and proteases in cerebrospinal fluid, resulting in a model able to predict the sequence of unknown peptides with high accuracy. On the basis of this approach, identification of peptide coordinates can be prioritized, and a rapid overview of the peptide content of a novel sample source can be obtained.

Mass spectrometric plasma analysis for biomarker discovery has become an exploratory focus in proteomic research: the challenges of analyzing plasma samples by mass spectrometry have become apparent not only since the human proteome organization (HUPO) has put much emphasis on the human plasma proteome. This work demonstrates fundamental proteomic research to reveal sensitivity and quantification capabilities of our Peptidomics technologies by detecting distinct changes in plasma peptide composition in samples after challenging healthy volunteers with orally administered glucose. Differential Peptide Display (DPD) is a technique for peptidomics studies to compare peptides from distinct biological samples. Mass spectrometry (MS) is used as a qualitative and quantitative analysis tool without previous trypsin digestion or labeling of the samples. Circulating peptides (15 kDa) were extracted from 1.3 mL plasma samples and the extracts separated by liquid chromatography into 96 fractions. Each fraction was subjected to MALDI MS, and mass spectra of all fractions were combined resulting in a 2D-display of2,000 peptides from each sample. Endogenous peptides that responded to oral glucose challenge were detected by DPD of pre-and post-challenge plasma samples from 16 healthy volunteers and subsequently identified by nESI-qTOF MS. Two of the 15 MS peaks that were significantly modulated by glucose challenge were subsequently identified as insulin and C-peptide. These results were validated by using immunoassays for insulin and C-peptide. This paper serves as a proof of principle for proteomic biomarker discovery down to the pM concentration range by using small amounts of human plasma.

Biomarker discovery in human urine has become an evolving and potentially valuable topic in relation to renal function and diseases of the urinary tract. In order to deliver on the promises and to facilitate the development of validated biomarkers or biomarker panels, protein and peptide profiling techniques need high sample throughput, speed of analysis, and reproducibility of results. Here, we outline the performance characteristics of the liquid chromatography/MALDI-TOF-MS based differential peptide display (DPD(1)) approach for separating, detecting, abundance profiling and identification of native peptides derived from human urine. The typical complexity of peptides in human urine (resolution of the technique with respect to detectable number of peptides), the reproducibility (coefficient of variation for abundance profiles of all peptides detected in biological samples) and dynamic range of the technique as well as the lower limit of detection were characterized. A substantial number of peptides present in normal human urine were identified and compared to findings in four published proteome studies. In an explorative approach, pathological urines from patients suffering from post-renal-filtration diseases were qualitatively compared to normal urine. In conclusion, the peptidomics technology as shown here has a great potential for high throughput and high resolution urine peptide profiling analyses. It is a promising tool to study not only renal physiology and pathophysiology and to determine new biomarkers of renal diseases; it also has the potential to study remotely localized or systemic aberrations within human biology.

Publisher Summary Peptides and proteins define the actual phenotype of an organism and thus reflect the current physiology as well as any pathogenic processes. Proteomics is regarded as a central technology in describing the transition from genotype to phenotype and, in more practical terms, from health to disease by describing the underlying mechanisms at a molecular level that is specific to time, quantity, and localization. This chapter focuses on a certain aspect of the proteome—the smaller native endogenous peptides. The research area and technologies addressing this field of endogenous peptides in general are referred to as “peptidomics.” Specifically, the field of clinical peptidomics, by analyzing blood samples from patients within clinical trials, is evolving rapidly. The prerequisites for this type of research are addressed in the chapter. It may be considered as a general principle that peptide precursors sometimes carry several distinct biological activities that are silent after protein biosynthesis. Only at certain times and in specific compartments are they activated by different proteolytic processes. This mechanistic way for the regulated release of biologically active compounds from inactive precursor molecules is probably a very safe way to assure the presence of the molecules at the desired concentration and conformation at the precise location and time when they are needed. In addition to the several modes of intracellular processing, extracellular processing of proteins is a frequently used way to tailor proteins and peptides. In a relevant number of instances, peptidases can liberate biologically active peptides.

Expression profiling of RNAs or proteins has become a promising means to investigate the heterogeneity of histopathologically defined classes of cancer. Peptides, representing degradation as well as processing products of proteins offer an even closer insight into cell physiology. Peptides are related to the turnover of cellular proteins and are capable to reflect disease-related changes in homoeostasis of the human body. Furthermore, peptides derived from tumor cells are potentially useful markers in the early detection of cancer. In this study, we introduced a method called differential peptide display (DPD) for separating, detecting, and identifying native peptides derived from whole cell extracts. This method is a highly standardized procedure, combining the power of reversed-phase chromatography with mass spectrometry. This technology is suitable to analyze cell lines, various tissue types and human body fluids. Peptide-based profiling of normal human mammary epithelial cells (HMEC) and the breast cancer cell line MCF-7 revealed complex peptide patterns comprising of up to 2300 peptides. Most of these peptides were common to both cell lines whereas about 8% differed in their abundance. Several of the differentially expressed peptides were identified as fragments of known proteins such as intermediate filament proteins, thymosins or Cathepsin D. Comparing cell lines with native tumors, overlapping peptide patterns were found between HMEC and a phylloides tumor (CP) on the one hand and MCF-7 cells and tissue from a invasive ductal carcinoma (DC) on the other hand.

The large intestine of breast-fed infants is colonized predominantly by bifidobacteria, which have a protective effect against acute diarrhea. In this study we report for the first time the identification of human milk peptides that selectively stimulate the growth of bifidobacteria. Several bifidogenic peptides were purified chromatographically from pepsin-treated human milk and identified as proteolytically generated fragments from the secretory component of the soluble polyimmunoglobulin receptor and lactoferrin; both of these proteins exhibit antimicrobial effects. Hydrolysis of the identified peptides with the gastrointestinal proteases pepsin, trypsin and chymotrypsin did not lead to the loss of bifidogenic activity, indicating their potential function in vivo. Sequential comparison revealed a similar structural motif within the identified peptides. A correspondingly designed small peptide (prebiotic lactoferrin-derived peptide-I, PRELP-I) was found to stimulate the growth of bifidobacteria as effectively as the native peptides. The combination of antimicrobial and bifidobacterial growth stimulatory activity in human milk proteins leads to highly specific compounds capable of regulating the microbial composition of infants' large intestine.

Guanylin/GCAP-I and uroguanylin/GCAP-II are two structurally related peptides which play an important role in the regulation of water/electrolyte balance within the gut. In order to enable the investigation and comparison of both peptide hormones at the genomic level, we decided to clone the corresponding genes. The human gene for guanylin/GCAP-I and its 5′-flanking region have been described recently. Here, we report the three exon/two intron structure of the human uroguanylin/GCAP-II gene and its localization on chromosome 1 p35-34, as determined by radiation hybrid mapping. Together with data obtained for the guanylin/GCAP-I gene we show that these genes are localized in the same chromosomal area with other guanlyl cyclase-activating peptides like ANP etc. Northern hybridization revealed that the expression of the uroguanylin/GCAP-II gene is highest in the intestinal mucosa, especially in the ileum and colon. By means of polymerase chain reaction (PCR), an expression was also observed in the stomach where no guanylin/GCAP-I expression is detectable. Using immunohistochemical methods, uroguanylin/GCAP-II immunoreactive material was distinctly localized in D-type gastric and intestinal endocrine cells. Although the comparable data on the genomic organisation of both peptide hormones verify their high degree of relationship, this finding indicates a special task of uroguanylin/GCAP-II within the stomach, such as regulatory functions in gastric secretion. The redundant expression of the GCAP/GC-C system in the small and large intestine, however, is as yet unclear.