Targeted serum proteomics of longitudinal samples from newly diagnosed youth with type 1 diabetes distinguishes markers of disease and C-peptide trajectory.

AIMS/HYPOTHESIS: There is a growing need for markers that could help indicate the decline in beta cell function and recognise the need and efficacy of intervention in type 1 diabetes. Measurements of suitably selected serum markers could potentially provide a non-invasive and easily applicable solution to this challenge. Accordingly, we evaluated a broad panel of proteins previously associated with type 1 diabetes in serum from newly diagnosed individuals during the first year from diagnosis. To uncover associations with beta cell function, comparisons were made between these targeted proteomics measurements and changes in fasting C-peptide levels. To further distinguish proteins linked with the disease status, comparisons were made with measurements of the protein targets in age- and sex-matched autoantibody-negative unaffected family members (UFMs). METHODS: Selected reaction monitoring (SRM) mass spectrometry analyses of serum, targeting 85 type 1 diabetes-associated proteins, were made. Sera from individuals diagnosed under 18 years (n=86) were drawn within 6 weeks of diagnosis and at 3, 6 and 12 months afterwards (288 samples in total). The SRM data were compared with fasting C-peptide/glucose data, which was interpreted as a measure of beta cell function. The protein data were further compared with cross-sectional SRM measurements from UFMs (n=194). RESULTS: Eleven proteins had statistically significant associations with fasting C-peptide/glucose. Of these, apolipoprotein L1 and glutathione peroxidase 3 (GPX3) displayed the strongest positive and inverse associations, respectively. Changes in GPX3 levels during the first year after diagnosis indicated future fasting C-peptide/glucose levels. In addition, differences in the levels of 13 proteins were observed between the individuals with type 1 diabetes and the matched UFMs. These included GPX3, transthyretin, prothrombin, apolipoprotein C1 and members of the IGF family. CONCLUSIONS/INTERPRETATION: The association of several targeted proteins with fasting C-peptide/glucose levels in the first year after diagnosis suggests their connection with the underlying changes accompanying alterations in beta cell function in type 1 diabetes. Moreover, the direction of change in GPX3 during the first year was indicative of subsequent fasting C-peptide/glucose levels, and supports further investigation of this and other serum protein measurements in future studies of beta cell function in type 1 diabetes.

Umbilical cord blood DNA methylation in children who later develop type 1 diabetes.

AIMS/HYPOTHESIS: Distinct DNA methylation patterns have recently been observed to precede type 1 diabetes in whole blood collected from young children. Our aim was to determine whether perinatal DNA methylation is associated with later progression to type 1 diabetes. METHODS: Reduced representation bisulphite sequencing (RRBS) analysis was performed on umbilical cord blood samples collected within the Finnish Type 1 Diabetes Prediction and Prevention (DIPP) Study. Children later diagnosed with type 1 diabetes and/or who tested positive for multiple islet autoantibodies (n = 43) were compared with control individuals (n = 79) who remained autoantibody-negative throughout the DIPP follow-up until 15 years of age. Potential confounding factors related to the pregnancy and the mother were included in the analysis. RESULTS: No differences in the umbilical cord blood methylation patterns were observed between the cases and controls at a false discovery rate <0.05. CONCLUSIONS/INTERPRETATION: Based on our results, differences between children who progress to type 1 diabetes and those who remain healthy throughout childhood are not yet present in the perinatal DNA methylome. However, we cannot exclude the possibility that such differences would be found in a larger dataset.

Enterovirus-associated changes in blood transcriptomic profiles of children with genetic susceptibility to type 1 diabetes.

AIMS/HYPOTHESIS: Enterovirus infections have been associated with the development of type 1 diabetes in multiple studies, but little is known about enterovirus-induced responses in children at risk for developing type 1 diabetes. Our aim was to use genome-wide transcriptomics data to characterise enterovirus-associated changes in whole-blood samples from children with genetic susceptibility to type 1 diabetes. METHODS: Longitudinal whole-blood samples (356 samples in total) collected from 28 pairs of children at increased risk for developing type 1 diabetes were screened for the presence of enterovirus RNA. Seven of these samples were detected as enterovirus-positive, each of them collected from a different child, and transcriptomics data from these children were analysed to understand the individual-level responses associated with enterovirus infections. Transcript clusters with peaking or dropping expression at the time of enterovirus positivity were selected as the enterovirus-associated signals. RESULTS: Strong signs of activation of an interferon response were detected in four children at enterovirus positivity, while transcriptomic changes in the other three children indicated activation of adaptive immune responses. Additionally, a large proportion of the enterovirus-associated changes were specific to individuals. An enterovirus-induced signature was built using 339 genes peaking at enterovirus positivity in four of the children, and 77 of these genes were also upregulated in human peripheral blood mononuclear cells infected in vitro with different enteroviruses. These genes separated the four enterovirus-positive samples clearly from the remaining 352 blood samples analysed. CONCLUSIONS/INTERPRETATION: We have, for the first time, identified enterovirus-associated transcriptomic profiles in whole-blood samples from children with genetic susceptibility to type 1 diabetes. Our results provide a starting point for understanding the individual responses to enterovirus infections in blood and their potential connection to the development of type 1 diabetes. DATA AVAILABILITY: The datasets analysed during the current study are included in this published article and its supplementary information files ( www.btk.fi/research/computational-biomedicine/1234-2 ) or are available from the Gene Expression Omnibus (GEO) repository (accession GSE30211).

Post-transcriptional regulation of human breast cancer cell proteome by unliganded estrogen receptor ß via microRNAs.

Estrogen receptor ß (ERß) is a member of the nuclear receptor family of homeostatic regulators that is frequently lost in breast cancer (BC), where its presence correlates with a better prognosis and a less aggressive clinical outcome of the disease. In contrast to ERα, its closest homolog, ERß shows significant estrogen-independent activities, including the ability to inhibit cell cycle progression and regulate gene transcription in the absence of the ligand. Investigating the nature and extent of this constitutive activity of ERß in BC MCF-7 and ZR-75.1 cells by means of microRNA (miRNA) sequencing, we identified 30 miRNAs differentially expressed in ERß+ versus ERß- cells in the absence of ligand, including up-regulated oncosuppressor miRs such miR-30a. In addition, a significant fraction of >1,600 unique proteins identified in MCF-7 cells by iTRAQ quantitative proteomics were either increased or decreased by ERß, revealing regulation of multiple cell pathways by ligand-free receptors. Transcriptome analysis showed that for a large number of proteins regulated by ERß, the corresponding mRNAs are unaffected, including a large number of putative targets of ERß-regulated miRNAs, indicating a central role of miRNAs in mediating BC cell proteome regulation by ERß. Expression of a mimic of miR-30a-5p, a direct target and downstream effector of ERß in BC, led to the identification of several target transcripts of this miRNA, including 11 encoding proteins whose intracellular concentration was significantly affected by unliganded receptor. These results demonstrate a significant effect of ligand-free ERß on BC cell functions via modulation of the cell proteome and suggest that miRNA regulation might represent a key event in the control of the biological and clinical phenotype of hormone-responsive BC by this nuclear receptor.

Phosphoproteomics combined with quantitative 14-3-3-affinity capture identifies SIRT1 and RAI as novel regulators of cytosolic double-stranded RNA recognition pathway.

Viral double-stranded RNA (dsRNA) is the most important viral structure recognized by cytosolic pattern-recognition receptors of the innate immune system, and its recognition results in the activation of signaling cascades that stimulate the production of antiviral cytokines and apoptosis of infected cells. 14-3-3 proteins are ubiquitously expressed regulatory molecules that participate in a variety of cellular processes, and 14-3-3 protein-mediated signaling pathways are activated by cytoplasmic dsRNA in human keratinocytes. However, the functional role of 14-3-3 protein-mediated interactions during viral dsRNA stimulation has remained uncharacterized. Here, we used functional proteomics to identify proteins whose phosphorylation and interaction with 14-3-3 is modulated by dsRNA and to characterize the signaling pathways activated during cytosolic dsRNA-induced innate immune response in human HaCaT keratinocytes. Phosphoproteome analysis showed that several MAPK- and immune-response-related signaling pathways were activated after dsRNA stimulation. Interactome analysis identified RelA-associated inhibitor, high-mobility group proteins, and several proteins associated with host responses to viral infection as novel 14-3-3 target proteins. Functional studies showed that RelA-associated inhibitor regulated dsRNA-induced apoptosis and TNF production. Integrated network analyses of proteomic data revealed that sirtuin1 was a central molecule regulated by 14-3-3s during dsRNA stimulation. Further experiments showed that sirtuin 1 negatively regulated dsRNA-induced NFκB transcriptional activity, suppressed expression of antiviral cytokines, and protected cells from apoptosis in dsRNA-stimulated and encephalomyocarditis-virus-infected keratinocytes. In conclusion, our data highlight the importance of 14-3-3 proteins in antiviral responses and identify RelA-associated inhibitor and sirtuin 1 as novel regulators of antiviral innate immune responses.

Phosphoproteome characterization reveals that Sendai virus infection activates mTOR signaling in human epithelial cells.

Sendai virus (SeV) is a common respiratory pathogen in mice, rats, and hamsters. Host cell recognition of SeV is mediated by pathogen recognition receptors, which recognize viral components and induce intracellular signal transduction pathways that activate the antiviral innate immune response. Viruses use host proteins to control the activities of signaling proteins and their downstream targets, and one of the most important host protein modifications regulated by viral infection is phosphorylation. In this study, we used phosphoproteomics combined with bioinformatics to get a global view of the signaling pathways activated during SeV infection in human lung epithelial cells. We identified altogether 1347 phosphoproteins, and our data shows that SeV infection induces major changes in protein phosphorylation affecting the phosphorylation of almost one thousand host proteins. Bioinformatics analysis showed that SeV infection activates known pathways including MAPK signaling, as well as signaling pathways previously not linked to SeV infection including Rho family of GTPases, HIPPO signaling, and mammalian target of rapamycin (mTOR)-signaling pathway. Further, we performed functional studies with mTOR inhibitors and siRNA approach, which revealed that mTOR signaling is needed for both the host IFN response as well as viral protein synthesis in SeV-infected human lung epithelial cells.

Monosodium urate activates Src/Pyk2/PI3 kinase and cathepsin dependent unconventional protein secretion from human primary macrophages.

Monosodium urate (MSU) is an endogenous danger signal that is crystallized from uric acid released from injured cells. MSU is known to activate inflammatory response in macrophages but the molecular mechanisms involved have remained uncharacterized. Activated macrophages start to secrete proteins to activate immune response and to recruit other immune cells to the site of infection and/or tissue damage. Secretome characterization after activation of innate immune system is essential to unravel the details of early phases of defense responses. Here, we have analyzed the secretome of human primary macrophages stimulated with MSU using quantitative two-dimensional gel electrophoresis based proteomics as well as high-throughput qualitative GeLC-MS/MS approach combining protein separation by SDS-PAGE and protein identification by liquid chromatography-MS/MS. Both methods showed that MSU stimulation induced robust protein secretion from lipopolysaccharide-primed human macrophages. Bioinformatic analysis of the secretome data showed that MSU stimulation strongly activates unconventional, vesicle mediated protein secretion. The unconventionally secreted proteins included pro-inflammatory cytokines like IL-1ß and IL-18, interferon-induced proteins, and danger signal proteins. Also active forms of lysosomal proteases cathepsins were secreted on MSU stimulation, and cathepsin activity was essential for MSU-induced unconventional protein secretion. Additionally, proteins associated to phosphorylation events including Src family tyrosine kinases were increased in the secretome of MSU-stimulated cells. Our functional studies demonstrated that Src, Pyk2, and PI3 kinases act upstream of cathepsins to activate the overall protein secretion from macrophages. In conclusion, we provide the first comprehensive characterization of protein secretion pathways activated by MSU in human macrophages, and reveal a novel role for cathepsins and Src, Pyk2, PI3 kinases in the activation of unconventional protein secretion.

Quantitative subcellular proteome and secretome profiling of influenza A virus-infected human primary macrophages.

Influenza A viruses are important pathogens that cause acute respiratory diseases and annual epidemics in humans. Macrophages recognize influenza A virus infection with their pattern recognition receptors, and are involved in the activation of proper innate immune response. Here, we have used high-throughput subcellular proteomics combined with bioinformatics to provide a global view of host cellular events that are activated in response to influenza A virus infection in human primary macrophages. We show that viral infection regulates the expression and/or subcellular localization of more than one thousand host proteins at early phases of infection. Our data reveals that there are dramatic changes in mitochondrial and nuclear proteomes in response to infection. We show that a rapid cytoplasmic leakage of lysosomal proteins, including cathepsins, followed by their secretion, contributes to inflammasome activation and apoptosis seen in the infected macrophages. Also, our results demonstrate that P2X7 receptor and src tyrosine kinase activity are essential for inflammasome activation during influenza A virus infection. Finally, we show that influenza A virus infection is associated with robust secretion of different danger-associated molecular patterns (DAMPs) suggesting an important role for DAMPs in host response to influenza A virus infection. In conclusion, our high-throughput quantitative proteomics study provides important new insight into host-response against influenza A virus infection in human primary macrophages.

Recognition of cytoplasmic RNA results in cathepsin-dependent inflammasome activation and apoptosis in human macrophages.

dsRNA is an important pathogen-associated molecular pattern that is primarily recognized by cytosolic pattern-recognition receptors of the innate-immune system during virus infection. This recognition results in the activation of inflammasome-associated caspase-1 and apoptosis of infected cells. In this study, we used high-throughput proteomics to identify secretome, the global pattern of secreted proteins, in human primary macrophages that had been activated through the cytoplasmic dsRNA-recognition pathway. The secretome analysis revealed cytoplasmic dsRNA-recognition pathway-induced secretion of several exosome-associated proteins, as well as basal and dsRNA-activated secretion of lysosomal protease cathepsins and cysteine protease inhibitors (cystatins). Inflammasome activation was almost completely abolished by cathepsin inhibitors in response to dsRNA stimulation, as well as encephalomyocarditis virus and vesicular stomatitis virus infections. Interestingly, Western blot analysis showed that the mature form of cathepsin D, but not cathepsin B, was secreted simultaneously with IL-18 and inflammasome components ASC and caspase-1 in cytoplasmic dsRNA-stimulated cells. Furthermore, small interfering RNA-mediated silencing experiments confirmed that cathepsin D has a role in inflammasome activation. Caspase-1 activation was followed by proteolytic processing of caspase-3, indicating that inflammasome activation precedes apoptosis in macrophages that had recognized cytoplasmic RNA. Like inflammasome activation, apoptosis triggered by dsRNA stimulation and virus infection was effectively blocked by cathepsin inhibition. In conclusion, our results emphasize the importance of cathepsins in the innate immune response to virus infection.

Serum APOC1 levels are decreased in young autoantibody positive children who rapidly progress to type 1 diabetes.

Better understanding of the early events in the development of type 1 diabetes is needed to improve prediction and monitoring of the disease progression during the substantially heterogeneous presymptomatic period of the beta cell damaging process. To address this concern, we used mass spectrometry-based proteomics to analyse longitudinal pre-onset plasma sample series from children positive for multiple islet autoantibodies who had rapidly progressed to type 1 diabetes before 4 years of age (n = 10) and compared these with similar measurements from matched children who were either positive for a single autoantibody (n = 10) or autoantibody negative (n = 10). Following statistical analysis of the longitudinal data, targeted serum proteomics was used to verify 11 proteins putatively associated with the disease development in a similar yet independent and larger cohort of children who progressed to the disease within 5 years of age (n = 31) and matched autoantibody negative children (n = 31). These data reiterated extensive age-related trends for protein levels in young children. Further, these analyses demonstrated that the serum levels of two peptides unique for apolipoprotein C1 (APOC1) were decreased after the appearance of the first islet autoantibody and remained relatively less abundant in children who progressed to type 1 diabetes, in comparison to autoantibody negative children.

Permutation-based significance analysis reduces the type 1 error rate in bisulphite sequencing data analysis of human umbilical cord blood samples.

DNA methylation patterns are largely established in-utero and might mediate the impacts of in-utero conditions on later health outcomes. Associations between perinatal DNA methylation marks and pregnancy-related variables, such as maternal age and gestational weight gain, have been earlier studied with methylation microarrays, which typically cover less than 2% of human CpG sites. To detect such associations outside these regions, we chose the bisulphite sequencing approach. We collected and curated clinical data on 200 newborn infants; whose umbilical cord blood samples were analysed with the reduced representation bisulphite sequencing (RRBS) method. A generalized linear mixed-effects model was fit for each high coverage CpG site, followed by spatial and multiple testing adjustment of P values to identify differentially methylated cytosines (DMCs) and regions (DMRs) associated with clinical variables, such as maternal age, mode of delivery, and birth weight. Type 1 error rate was then evaluated with a permutation analysis. We discovered a strong inflation of spatially adjusted P values through the permutation analysis, which we then applied for empirical type 1 error control. The inflation of P values was caused by a common method for spatial adjustment and DMR detection, implemented in tools comb-p and RADMeth. Based on empirically estimated significance thresholds, very little differential methylation was associated with any of the studied clinical variables, other than sex. With this analysis workflow, the sex-associated differentially methylated regions were highly reproducible across studies, technologies, and statistical models.

Pancreas Whole Tissue Transcriptomics Highlights the Role of the Exocrine Pancreas in Patients With Recently Diagnosed Type 1 Diabetes.

Although type 1 diabetes (T1D) is primarily a disease of the pancreatic beta-cells, understanding of the disease-associated alterations in the whole pancreas could be important for the improved treatment or the prevention of the disease. We have characterized the whole-pancreas gene expression of patients with recently diagnosed T1D from the Diabetes Virus Detection (DiViD) study and non-diabetic controls. Furthermore, another parallel dataset of the whole pancreas and an additional dataset from the laser-captured pancreatic islets of the DiViD patients and non-diabetic organ donors were analyzed together with the original dataset to confirm the results and to get further insights into the potential disease-associated differences between the exocrine and the endocrine pancreas. First, higher expression of the core acinar cell genes, encoding for digestive enzymes, was detected in the whole pancreas of the DiViD patients when compared to non-diabetic controls. Second, In the pancreatic islets, upregulation of immune and inflammation related genes was observed in the DiViD patients when compared to non-diabetic controls, in line with earlier publications, while an opposite trend was observed for several immune and inflammation related genes at the whole pancreas tissue level. Third, strong downregulation of the regenerating gene family (REG) genes, linked to pancreatic islet growth and regeneration, was observed in the exocrine acinar cell dominated whole-pancreas data of the DiViD patients when compared with the non-diabetic controls. Fourth, analysis of unique features in the transcriptomes of each DiViD patient compared with the other DiViD patients, revealed elevated expression of central antiviral immune response genes in the whole-pancreas samples, but not in the pancreatic islets, of one DiViD patient. This difference in the extent of antiviral gene expression suggests different statuses of infection in the pancreas at the time of sampling between the DiViD patients, who were all enterovirus VP1+ in the islets by immunohistochemistry based on earlier studies. The observed features, indicating differences in the function, status and interplay between the exocrine and the endocrine pancreas of recent onset T1D patients, highlight the importance of studying both compartments for better understanding of the molecular mechanisms of T1D.

Persistent coxsackievirus B1 infection triggers extensive changes in the transcriptome of human pancreatic ductal cells.

Enteroviruses, particularly the group B coxsackieviruses (CVBs), have been associated with the development of type 1 diabetes. Several CVB serotypes establish chronic infections in human cells in vivo and in vitro. However, the mechanisms leading to enterovirus persistency and, possibly, beta cell autoimmunity are not fully understood. We established a carrier-state-type persistent infection model in human pancreatic cell line PANC-1 using two distinct CVB1 strains and profiled the infection-induced changes in cellular transcriptome. In the current study, we observed clear changes in the gene expression of factors associated with the pancreatic microenvironment, the secretory pathway, and lysosomal biogenesis during persistent CVB1 infections. Moreover, we found that the antiviral response pathways were activated differently by the two CVB1 strains. Overall, our study reveals extensive transcriptional responses in persistently CVB1-infected pancreatic cells with strong opposite but also common changes between the two strains.

Comparative proteome cataloging of Lactobacillus rhamnosus strains GG and Lc705.

The present study reports an in-depth proteome analysis of two Lactobacillus rhamnosus strains, the well-known probiotic strain GG and the dairy strain Lc705. We used GeLC-MS/MS, in which proteins are separated using 1-DE and identified using nanoLC-MS/MS, to generate high-quality protein catalogs. To maximize the number of identifications, all data sets were searched against the target databases using two search engines, Mascot and Paragon. As a result, over 1600 high-confidence protein identifications, covering nearly 60% of the predicted proteomes, were obtained from each strain. This approach enabled identification of more than 40% of all predicted surfome proteins, including a high number of lipoproteins, integral membrane proteins, peptidoglycan associated proteins, and proteins predicted to be released into the extracellular environment. A comparison of both data sets revealed the expression of more than 90 proteins in GG and 150 in Lc705, which lack evolutionary counterparts in the other strain. Differences were noted in proteins with a likely role in biofilm formation, phage-related functions, reshaping the bacterial cell wall, and immunomodulation. The present study provides the most comprehensive catalog of the Lactobacillus proteins to date and holds great promise for the discovery of novel probiotic effector molecules.

Pripper: prediction of caspase cleavage sites from whole proteomes.

BACKGROUND: Caspases are a family of proteases that have central functions in programmed cell death (apoptosis) and inflammation. Caspases mediate their effects through aspartate-specific cleavage of their target proteins, and at present almost 400 caspase substrates are known. There are several methods developed to predict caspase cleavage sites from individual proteins, but currently none of them can be used to predict caspase cleavage sites from multiple proteins or entire proteomes, or to use several classifiers in combination. The possibility to create a database from predicted caspase cleavage products for the whole genome could significantly aid in identifying novel caspase targets from tandem mass spectrometry based proteomic experiments. RESULTS: Three different pattern recognition classifiers were developed for predicting caspase cleavage sites from protein sequences. Evaluation of the classifiers with quality measures indicated that all of the three classifiers performed well in predicting caspase cleavage sites, and when combining different classifiers the accuracy increased further. A new tool, Pripper, was developed to utilize the classifiers and predict the caspase cut sites from an arbitrary number of input sequences. A database was constructed with the developed tool, and it was used to identify caspase target proteins from tandem mass spectrometry data from two different proteomic experiments. Both known caspase cleavage products as well as novel cleavage products were identified using the database demonstrating the usefulness of the tool. Pripper is not restricted to predicting only caspase cut sites, but it gives the possibility to scan protein sequences for any given motif(s) and predict cut sites once a suitable cut site prediction model for any other protease has been developed. Pripper is freely available and can be downloaded from http://users.utu.fi/mijopi/Pripper. CONCLUSIONS: We have developed Pripper, a tool for reading an arbitrary number of proteins in FASTA format, predicting their caspase cleavage sites and outputting the cleaved sequences to a new FASTA format sequence file. We show that Pripper is a valuable tool in identifying novel caspase target proteins from modern proteomics experiments.

Compid: a new software tool to integrate and compare MS/MS based protein identification results from Mascot and Paragon.

Tandem mass spectrometry-based proteomics experiments produce large amounts of raw data, and different database search engines are needed to reliably identify all the proteins from this data. Here, we present Compid, an easy-to-use software tool that can be used to integrate and compare protein identification results from two search engines, Mascot and Paragon. Additionally, Compid enables extraction of information from large Mascot result files that cannot be opened via the Web interface and calculation of general statistical information about peptide and protein identifications in a data set. To demonstrate the usefulness of this tool, we used Compid to compare Mascot and Paragon database search results for mitochondrial proteome sample of human keratinocytes. The reports generated by Compid can be exported and opened as Excel documents or as text files using configurable delimiters, allowing the analysis and further processing of Compid output with a multitude of programs. Compid is freely available and can be downloaded from http://users.utu.fi/lanatr/compid. It is released under an open source license (GPL), enabling modification of the source code. Its modular architecture allows for creation of supplementary software components e.g. to enable support for additional input formats and report categories.

Cytosolic RNA recognition pathway activates 14-3-3 protein mediated signaling and caspase-dependent disruption of cytokeratin network in human keratinocytes.

The skin is the primary boundary between the body and the environment. In addition to its properties as a physical barrier, skin keratinocytes actively participate in many defense mechanisms. Viral double-stranded RNA (dsRNA) is the most important viral structure involved in activation of immune response. Intracellular detection of dsRNA by cytoplasmic receptors activates well-characterized antiviral response, as well as pro-inflammatory response and apoptosis of virus-infected cells. Here, we have used quantitative subcellular proteomics to characterize the signaling pathways activated by cytosolic dsRNA recognition pathway in human keratinocytes. Cytoplasmic and mitochondrial proteomes were analyzed using 2-DE in combination with MS, immunoblotting and confocal microscopy. We have identified 239 reproducibly differentially expressed proteins upon dsRNA stimulation. The identified proteins include several key proteins involved in cytoskeletal dynamics, cell signaling, cell death, and stress response. Our analysis provides novel information how the cytokeratin network is disrupted in a caspase-dependent manner upon dsRNA stimulation as well as Encephalomyocarditis virus or Vesicular stomatitis virus infection. We show that this caspase-dependent disruption of cytokeratin is activated by cytoplasmic RNA recognition pathway. In addition, we show that viral infection activates 14-3-3 protein mediated signaling pathways in human keratinocytes which suggest an important role of 14-3-3 proteins in antiviral innate immune response.

An additive Gaussian process regression model for interpretable non-parametric analysis of longitudinal data.

Biomedical research typically involves longitudinal study designs where samples from individuals are measured repeatedly over time and the goal is to identify risk factors (covariates) that are associated with an outcome value. General linear mixed effect models are the standard workhorse for statistical analysis of longitudinal data. However, analysis of longitudinal data can be complicated for reasons such as difficulties in modelling correlated outcome values, functional (time-varying) covariates, nonlinear and non-stationary effects, and model inference. We present LonGP, an additive Gaussian process regression model that is specifically designed for statistical analysis of longitudinal data, which solves these commonly faced challenges. LonGP can model time-varying random effects and non-stationary signals, incorporate multiple kernel learning, and provide interpretable results for the effects of individual covariates and their interactions. We demonstrate LonGP's performance and accuracy by analysing various simulated and real longitudinal -omics datasets.

Coxsackievirus B Persistence Modifies the Proteome and the Secretome of Pancreatic Ductal Cells.

The group B Coxsackieviruses (CVB), belonging to the Enterovirus genus, can establish persistent infections in human cells. These persistent infections have been linked to chronic diseases including type 1 diabetes. Still, the outcomes of persistent CVB infections in human pancreas are largely unknown. We established persistent CVB infections in a human pancreatic ductal-like cell line PANC-1 using two distinct CVB1 strains and profiled infection-induced changes in cellular protein expression and secretion using mass spectrometry-based proteomics. Persistent infections, showing characteristics of carrier-state persistence, were associated with a broad spectrum of changes, including changes in mitochondrial network morphology and energy metabolism and in the regulated secretory pathway. Interestingly, the expression of antiviral immune response proteins, and also several other proteins, differed clearly between the two persistent infections. Our results provide extensive information about the protein-level changes induced by persistent CVB infection and the potential virus-associated variability in the outcomes of these infections.

Characterization and non-parametric modeling of the developing serum proteome during infancy and early childhood.

Children develop rapidly during the first years of life, and understanding the sources and associated levels of variation in the serum proteome is important when using serum proteins as markers for childhood diseases. The aim of this study was to establish a reference model for the evolution of a healthy serum proteome during early childhood. Label-free quantitative proteomics analyses were performed for 103 longitudinal serum samples collected from 15 children at birth and between the ages of 3-36 months. A flexible Gaussian process-based probabilistic modelling framework was developed to evaluate the effects of different variables, including age, living environment and individual variation, on the longitudinal expression profiles of 266 reliably identified and quantified serum proteins. Age was the most dominant factor influencing approximately half of the studied proteins, and the most prominent age-associated changes were observed already during the first year of life. High inter-individual variability was also observed for multiple proteins. These data provide important details on the maturing serum proteome during early life, and evaluate how patterns detected in cord blood are conserved in the first years of life. Additionally, our novel modelling approach provides a statistical framework to detect associations between covariates and non-linear time series data.