Autoantibody signature in human ductal pancreatic adenocarcinoma

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive malignancy characterized by rapid progression, invasiveness, and resistance to treatment. It is the fourth leading cause of cancer death with a 2% 5-year survival rate. Biomarkers for its early detection are lacking. This study was designed to use a proteomics-based approach as a means of identifying antigens that elicit a humoral response in PDAC patients. Antibodies against PDAC-associated antigens are useful for early cancer diagnosis and therapy. Proteins from PDAC cell lines were separated by 2-DE, and the serum IgG reactivity of 70 PDAC patients, 40 healthy subjects (HS), 30 non-PDAC tumor patients, and 15 chronic pancreatitis (CP) patients was tested by Western blot analysis. Spots specifically recognized by PDAC sera and revealed by mass spectrometry corresponded to metabolic enzymes or cytoskeletal proteins. Most were up-regulated in PDAC tissues. Thus, it seems that metabolic enzymes and cytoskeletal proteins are specific targets of the humoral response during PDAC. The results of further studies of these serological-defined antigens could be of diagnostic and therapeutic significance in PDAC.     

Vesicular polysaccharide export in Cryptococcus neoformans is a eukaryotic solution to the problem of fungal trans-cell wall transport

The mechanisms by which macromolecules are transported through the cell wall of fungi are not known. A central question in the biology of Cryptococcus neoformans, the causative agent of cryptococcosis, is the mechanism by which capsular polysaccharide synthesized inside the cell is exported to the extracellular environment for capsule assembly and release. We demonstrate that C. neoformans produces extracellular vesicles during in vitro growth and animal infection. Vesicular compartments, which are transferred to the extracellular space by cell wall passage, contain glucuronoxylomannan (GXM), a component of the cryptococcal capsule, and key lipids, such as glucosylceramide and sterols. A correlation between GXM-containing vesicles and capsule expression was observed. The results imply a novel mechanism for the release of the major virulence factor of C. neoformans whereby polysaccharide packaged in lipid vesicles crosses the cell wall and the capsule network to reach the extracellular environment.     

Flexible and accurate detection of genomic copy-number changes from aCGH

Genomic DNA copy-number alterations (CNAs) are associated with complex diseases, including cancer: CNAs are indeed related to tumoral grade, metastasis, and patient survival. CNAs discovered from array-based comparative genomic hybridization (aCGH) data have been instrumental in identifying disease-related genes and potential therapeutic targets. To be immediately useful in both clinical and basic research scenarios, aCGH data analysis requires accurate methods that do not impose unrealistic biological assumptions and that provide direct answers to the key question, "What is the probability that this gene/region has CNAs?" Current approaches fail, however, to meet these requirements. Here, we introduce reversible jump aCGH (RJaCGH), a new method for identifying CNAs from aCGH; we use a nonhomogeneous hidden Markov model fitted via reversible jump Markov chain Monte Carlo; and we incorporate model uncertainty through Bayesian model averaging. RJaCGH provides an estimate of the probability that a gene/region has CNAs while incorporating interprobe distance and the capability to analyze data on a chromosome or genome-wide basis. RJaCGH outperforms alternative methods, and the performance difference is even larger with noisy data and highly variable interprobe distance, both commonly found features in aCGH data. Furthermore, our probabilistic method allows us to identify minimal common regions of CNAs among samples and can be extended to incorporate expression data. In summary, we provide a rigorous statistical framework for locating genes and chromosomal regions with CNAs with potential applications to cancer and other complex human diseases.     

A novel interhemispheric interaction: modulation of neuronal cooperativity in the visual areas

Background

The cortical representation of the visual field is split along the vertical midline, with the left and the right hemi-fields projecting to separate hemispheres. Connections between the visual areas of the two hemispheres are abundant near the representation of the visual midline. It was suggested that they re-establish the functional continuity of the visual field by controlling the dynamics of the responses in the two hemispheres.

Methods/Principal Findings

To understand if and how the interactions between the two hemispheres participate in processing visual stimuli, the synchronization of responses to identical or different moving gratings in the two hemi-fields were studied in anesthetized ferrets. The responses were recorded by multiple electrodes in the primary visual areas and the synchronization of local field potentials across the electrodes were analyzed with a recent method derived from dynamical system theory. Inactivating the visual areas of one hemisphere modulated the synchronization of the stimulus-driven activity in the other hemisphere. The modulation was stimulus-specific and was consistent with the fine morphology of callosal axons in particular with the spatio-temporal pattern of activity that axonal geometry can generate.

Conclusions/Significance

These findings describe a new kind of interaction between the cerebral hemispheres and highlight the role of axonal geometry in modulating aspects of cortical dynamics responsible for stimulus detection and/or categorization.     

AGGRESCAN: a server for the prediction and evaluation of "hot spots" of aggregation in polypeptides

Background

A tremendous amount of efforts have been devoted to identifying genes for diagnosis and prognosis of diseases using microarray gene expression data. It has been demonstrated that gene expression data have cluster structure, where the clusters consist of co-regulated genes which tend to have coordinated functions. However, most available statistical methods for gene selection do not take into consideration the cluster structure.

Results

We propose a supervised group Lasso approach that takes into account the cluster structure in gene expression data for gene selection and predictive model building. For gene expression data without biological cluster information, we first divide genes into clusters using the K-means approach and determine the optimal number of clusters using the Gap method. The supervised group Lasso consists of two steps. In the first step, we identify important genes within each cluster using the Lasso method. In the second step, we select important clusters using the group Lasso. Tuning parameters are determined using V-fold cross validation at both steps to allow for further flexibility. Prediction performance is evaluated using leave-one-out cross validation. We apply the proposed method to disease classification and survival analysis with microarray data.

Conclusion

We analyze four microarray data sets using the proposed approach: two cancer data sets with binary cancer occurrence as outcomes and two lymphoma data sets with survival outcomes. The results show that the proposed approach is capable of identifying a small number of influential gene clusters and important genes within those clusters, and has better prediction performance than existing methods.     

Towards High-throughput Immunomics for Infectious Diseases: Use of Next-generation Peptide Microarrays for Rapid Discovery and Mapping of Antigenic Determinants

Complete characterization of antibody specificities associated to natural infections is expected to provide a rich source of serologic biomarkers with potential applications in molecular diagnosis, follow-up of chemotherapeutic treatments, and prioritization of targets for vaccine development. Here, we developed a highly-multiplexed platform based on next-generation high-density peptide microarrays to map these specificities in Chagas Disease, an exemplar of a human infectious disease caused by the protozoan Trypanosoma cruzi. We designed a high-density peptide microarray containing more than 175,000 overlapping 15mer peptides derived from T. cruzi proteins. Peptides were synthesized in situ on microarray slides, spanning the complete length of 457 parasite proteins with fully overlapped 15mers (1 residue shift). Screening of these slides with antibodies purified from infected patients and healthy donors demonstrated both a high technical reproducibility as well as epitope mapping consistency when compared with earlier low-throughput technologies. Using a conservative signal threshold to classify positive (reactive) peptides we identified 2,031 disease-specific peptides and 97 novel parasite antigens, effectively doubling the number of known antigens and providing a 10-fold increase in the number of fine mapped antigenic determinants for this disease. Finally, further analysis of the chip data showed that optimizing the amount of sequence overlap of displayed peptides can increase the protein space covered in a single chip by at least ∼threefold without sacrificing sensitivity. In conclusion, we show the power of high-density peptide chips for the discovery of pathogen-specific linear B-cell epitopes from clinical samples, thus setting the stage for high-throughput biomarker discovery screenings and proteome-wide studies of immune responses against pathogens.Detailed knowledge of antigens and epitopes recognized in the context of naturally acquired human infections has important implications for our understanding of immune system responses against pathogens, and of the immunopathogenesis of infectious diseases. This knowledge is also important for practical clinical applications such as the development of improved vaccines, intervention strategies, and diagnostics.In the last decades, significant progress has been made in the discovery of antigens and epitopes thanks to a number of methodologies such as cDNA expression libraries (1), combinatorial peptide libraries (2), and peptide and protein microarrays (3, 4). However, current knowledge of the B-cell antigens and the epitope repertoire recognized by the immune system in human infections is still scarce. Indeed, the Immune Epitope Database (5) currently contains an average of only 10 antigens with mapped B-cell epitopes recognized from naturally acquired human infections for bacterial or eukaryotic pathogens. The reasons for this are many, but can be largely attributed to different limitations in the mentioned screening technologies. Heterologous expression of cDNA libraries has been used to guide antigen discovery, but mapping of epitopes most often lags behind as it is a much more costly exercise. Similarly, combinatorial peptide libraries greatly facilitate the identification of peptides that are specifically recognized by antibodies, but these peptides have sequences that can greatly differ from those of the native epitopes (they are mimotopes), thus making it difficult to identify the original antigens. As a result, we currently have only limited detailed information on the fine specificities of the antibody response against complex pathogens.The number of tools for studying immune responses has recently expanded with the inclusion of peptide and protein microarrays, which have been used to identify pathogen-specific antigens and linear epitopes (6–13). Although whole-protein arrays can successfully identify antigens recognized by antibodies, they present the typical difficulties associated with the production of recombinant proteins in heterologous or in vitro systems, do not provide information on the nature and precise location of the epitope(s) in a protein, and are more likely to suffer from nonspecific antibody binding because of the exposure of a large number of potentially antigenic regions. In contrast, peptide arrays can provide exquisite detail of epitope localization, but until now had other limitations mostly associated with their reduced capacity, preventing the complete scanning of large numbers of candidate proteins.Recent advances in computerized photolithography and photochemistry have led to the development of a novel high-density peptide microarray technology, where individual peptides can be synthesized in situ on a glass slide at high densities (14–17). This technology makes the production of high-density peptide arrays highly cost effective compared with previous approaches, while allowing the interrogation of complex immune responses with unprecedented throughput and mapping precision. Previous applications of this technology were limited to the fine mapping of epitopes in single proteins, using monoclonal antibodies, or using immunized animal sera as the source of polyclonal antibodies (16–18).Using these high-density peptide arrays, we here describe the first large-scale study of fine antibody specificities associated with Chagas Disease, which is an exemplar of a chronic human infectious disease. Chagas Disease, caused by the protozoan Trypanosoma cruzi, is an endemic disease of the Americas, affecting ∼8 million people (19). The parasite invades and replicates within host cells, and briefly enters the bloodstream to reach other target tissues. Initially, the disease goes through an acute stage, characterized by patent parasitaemia and the appearance of antibodies against acute-phase antigens, such as SAPA (20), followed by a delayed specific humoral response. In general, the parasite-specific immune response mounted during T. cruzi infections is insufficient to completely eradicate the pathogen, leading to chronic infection (19). In this chronic stage circulating parasites are difficult to detect, even by extremely sensitive methods such as PCR. Therefore, detection of antibodies against whole-parasite extracts or defined antigens (21, 22) remains the standard for diagnosis of Chagas Disease.In this work, we screened high-density microarray slides containing peptides derived from T. cruzi proteins with mixtures of immunoglobulins purified directly from blood samples of Chagas Disease patients. This led to the identification of novel antigens and the simultaneous mapping of their linear B-cell epitopes, thus demonstrating the capacity and performance of this platform for studying antibody specificities associated with human infectious diseases.     

Effects of flower dimorphism and light environment on arbuscular mycorrhizal colonisation in a cleistogamous herb

Although it is known that floral dimorphism contributes to the maintenance of mixed breeding systems, the consequences of producing progeny of a contrasting genetic background and seeds with differential resource allocation has been practically ignored regarding establishment of belowground organisms–plant interactions. This article evaluates the combined effect of floral dimorphism with cross type and light environment on interactions between Ruellia nudiflora and arbuscular mycorrhizal fungi (AMF). R. nudiflora produces cleistogamous (CL) flowers that exhibit obligate self‐pollination and chasmogamous (CH) flowers with facultative self‐ (CHs) or cross‐ (CHc) pollination. We evaluated the establishment of the plant–AMF interaction in progeny derived from each floral type, under two light conditions (shaded versus open). We established different scenarios depending on the existence of inbreeding depression (ID) and whether the differential resource allocation (DRA) to CH and CL flowers affected the R. nudiflora–AMF interaction. We predicted that under shaded light conditions there might be an intensification of ID, having a negative effect on AMF colonisation. The percentages of hyphae and vesicles in the harvested roots was significantly higher in the shaded plants (F ≥ 4.11, P < 0.05), while progeny of CHc and CHs presented a higher percentage of hyphae and vesicle colonisation compared to CL progeny (F = 15.26, P < 0.01). The results show that DRA to CH flowers and light availability both determines the establishment of R. nudiflora–AMF interaction. The results also suggest that even under stressful light conditions, endogamy does not affect this interaction, which may explain the success of R. nudiflora as an invasive species.