N-glycomic Profiling as a Tool to Separate Rectal Adenomas from Carcinomas

All human cells are covered by glycans, the carbohydrate units of glycoproteins, glycolipids, and proteoglycans. Most glycans are localized to cell surfaces and participate in events essential for cell viability and function. Glycosylation evolves during carcinogenesis, and therefore carcinoma-related glycan structures are potential cancer biomarkers. Colorectal cancer is one of the world''s three most common cancers, and its incidence is rising. Novel biomarkers are essential to identify patients for targeted and individualized therapy. We compared the N-glycan profiles of five rectal adenomas and 18 rectal carcinomas of different stages by matrix-assisted laser desorption-ionization time-of-flight mass spectrometry. Paraffin-embedded tumor samples were deparaffinized, and glycans were enzymatically released and purified. We found differences in glycosylation between adenomas and carcinomas: monoantennary, sialylated, pauci-mannose, and small high-mannose N-glycan structures were more common in carcinomas than in adenomas. We also found differences between stage I–II and stage III carcinomas. Based on these findings, we selected two glycan structures: pauci-mannose and sialyl Lewis a, for immunohistochemical analysis of their tissue expression in 220 colorectal cancer patients. In colorectal cancer, poor prognosis correlated with elevated expression of sialyl Lewis a, and in advanced colorectal cancer, poor prognosis correlated with elevated expression of pauci-mannose. In conclusion, by mass spectrometry we found several carcinoma related glycans, and we demonstrate a method of transforming these results into immunohistochemistry, a readily applicable method to study biomarker expression in patient samples.Glycans, the carbohydrate units of glycoproteins, glycolipids, and proteoglycans, that cover all human cells. Around 1% of the human genome participates in the biosynthesis of glycans(1). This biosynthesis is the most complex post-translational modification of proteins, and the great variability in glycan structures contains a tremendous ability to fine-tune the chemical and biological properties of glycoproteins. The glycosylation process occurs most abundantly in the Golgi apparatus and the endoplasmic reticulum, but also occurs in the cytoplasm and nucleus (2). Most glycoconjugates are localized to cell surfaces, where glycans participate in events essential for cell viability and function, such as cell adhesion, motility, and intracellular signaling (2). Changes in these functions are key steps seen when normal cells transform to malignant ones, and these are also reflected in changes of a cell''s glycan profile, observed in many cancers (3, 4). Specific structural changes in glycans may serve as cancer biomarkers (5, 6), and changes in glycosylation profiles are related to aggressive behavior in tumor cells (7–9).Cancer-associated asparagine-linked glycan (N-glycan) structures may play specific roles in supporting tumor progression; growth (10, 11), invasion (12, 13), and angiogenesis (14). Changes in the N-glycan profile emerge in numerous cancers, including lung (15, 16), breast (17), and colorectal cancer (CRC)¹ (16, 18). Balog et al. (18) comparing the N-glycomic profile of CRC tissue to adjacent normal mucosa, reported differences in specific glycan structures. Moreover, serum N-glycosylation profile from patients with CRC differ from those of healthy controls (19).Colorectal cancer is the third most common cause of cancer-related death worldwide and its incidence is rising; 40% of CRCs are of rectal origin. Roughly 40% of patients have localized disease (stage I–II; Dukes A–B), another 40% loco regional disease (stage III; Dukes C), and 20% metastasized disease (stage IV; Dukes D) (20). Although stage at diagnosis is the most important factor determining prognosis, clinical outcome, and response to adjuvant treatment can markedly vary within each stage. Adjuvant therapy routinely goes to stage III patients, but the benefit of adjuvant treatment for stage II patients is unclear. Of stage II patients, 80% are cured by radical surgery alone. To identify patients who will benefit from postoperative treatment, we need novel biomarkers. The glycan profile of the tumor tissue could provide new biomarkers for diagnosis and prognosis of cancer.In this study, we characterized the N-glycomic profiles of rectal adenomas and carcinomas by MALDI-TOF mass spectrometric (MS) profiling of asparagine-linked glycans. Our aim was to identify differences between adenomas and carcinomas, and also between cancers of different stages. Based on glycan profiling, we also chose, for immunohistochemical expression studies of a series of 220 CRC patients, two glycan markers: sialyl Lewis a and pauci-mannose.     

Food-habitat relationship of harbour seals and black cormorants in Skagerrak and Kattegat

Comparative studies on the food of the black cormorant Phalacrocorax carbo and the harbour seal Phoca vitulina were carried out in two contrasting habitat types. Both species feed predominantly on bottom-dwelling fish. Black cormorants are able to utilize fish found both on vegetation-covered and naked sea beds at a water depth of less than 10 m, while harbour seals feed mainly on soft sea bottoms above 30 m where vegetation is scarce or lacking. The food overlap of the two piscivores is large in environments where large shallow sea bottoms are available, and small in areas where sea bottoms of soft material is found at greater depth. In areas where the shallow bottoms are covered by vegetation only, cormorants are able to feed on the fish species inhabiting this kind of environment. There is no evidence that these predators make a choice regarding prey species.     

Scaffold-hopping with zwitterionic CCR3 antagonists: Identification and optimisation of a series with good potency and pharmacokinetics leading to the discovery of AZ12436092

The discovery and optimisation of a series of zwitterionic CCR3 antagonists is described. Optimisation of the structure led to AZ12436092, a compound with excellent selectivity over activity at hERG and outstanding pharmacokinetics in preclinical species.     

Development of a denaturation/renaturation-based production process for ferritin nanoparticles

Recently, we presented a simple method for generating biological functional protein-based nanoparticles that are ready for use as label agents in bioaffinity assays (J??skel?inen et al., 2007 Small 3:1362-1367). In this process, the particle shell (ferritin protein) and binding molecules are conjugated via genetic fusion, and particles with binding capacity are produced in a single bacterial cultivation. Production is combined with simple, non-chromatographic purification during which Europium ions are introduced into particles to serve as marker agents. Denaturation-refolding has previously performed by means of pH changes. Here, we test urea as an alternative agent for denaturation, and examine techniques to improve refolding of the functional particles. Three different types of binding molecules were employed in our experiments: biotin carboxyl carrier protein (a small protein with 87 amino acids), single chain antibody fragment (a complex binding protein) and calmodulin-binding peptide (27 amino acids). Urea was successfully utilized to generate functional particles with inherent binding activity and label function. Additionally, particle yield was effectively optimized by analyzing various refolding and bacterial production conditions. Our results clearly demonstrate that this simple biological method of producing functional ferritin-based particles is flexible, and different types of binding moieties can be applied by adjusting the production conditions.     

Genome-Wide Scoring of Positive and Negative Epistasis through Decomposition of Quantitative Genetic Interaction Fitness Matrices

Recent technological developments in genetic screening approaches have offered the means to start exploring quantitative genotype-phenotype relationships on a large-scale. What remains unclear is the extent to which the quantitative genetic interaction datasets can distinguish the broad spectrum of interaction classes, as compared to existing information on mutation pairs associated with both positive and negative interactions, and whether the scoring of varying degrees of such epistatic effects could be improved by computational means. To address these questions, we introduce here a computational approach for improving the quantitative discrimination power encoded in the genetic interaction screening data. Our matrix approximation model decomposes the original double-mutant fitness matrix into separate components, representing variability across the array and query mutants, which can be utilized for estimating and correcting the single-mutant fitness effects, respectively. When applied to three large-scale quantitative interaction datasets in yeast, we could improve the accuracy of scoring various interaction classes beyond that obtained with the original fitness data, especially in synthetic genetic array (SGA) and in genetic interaction mapping (GIM) datasets. In addition to the known pairs of interactions used in the evaluation of the computational approach, a number of novel interaction pairs were also predicted, along with underlying biological mechanisms, which remained undetected by the original datasets. It was shown that the optimal choice of the scoring function depends heavily on the screening approach and on the interaction class under analysis. Moreover, a simple preprocessing of the fitness matrix could further enhance the discrimination power of the epistatic miniarray profiling (E-MAP) dataset. These systematic evaluation results provide in-depth information on the optimal analysis of the future, large-scale screening experiments. In general, the modeling framework, enabling accurate identification and classification of genetic interactions, provides a solid basis for completing and mining the genetic interaction networks in yeast and other organisms.     

Delayed density-dependent parasitism of eggs and pupae as a contributor to the cyclic population dynamics of the autumnal moth

Many populations of forest Lepidoptera exhibit 10-year cycles in densities, with impressive outbreaks across large regions. Delayed density-dependent interactions with natural enemies are recognized as key factors driving these cyclic population dynamics, but emphasis has typically been on the larval stages. Eggs, pupae and adults also suffer mortality from predators, parasitoids and pathogens, but little is known about possible density relationships between mortality factors and these non-feeding life stages. In a long-term field study, we experimentally deployed autumnal moth (Epirrita autumnata) eggs and pupae to their natural enemies yearly throughout the 10-year population cycle in northern Norway. The abundance of another geometrid, the winter moth (Operophtera brumata), increased in the study area, permitting comparisons between the two moth species in predation and parasitism. Survival of autumnal moth eggs and pupae was related to the moth abundance in an inverse and delayed manner. Egg and pupal parasitoids dominated as density-dependent mortality factors and predicted the subsequent growth rate of the host population size. In contrast, effects of egg and pupal predators were weakly density dependent, and generally predation remained low. Parasitism rates did not differ between the autumnal and winter moth pupae, whereas predators preferred winter moth pupae over those of the autumnal moth. We conclude that parasitism of the autumnal moth by egg and pupal parasitoids can be related to the changes of the moth density in a delayed density-dependent manner. Furthermore, egg and pupal parasitoids cannot be overlooked as causal factors for the population cycles of forest Lepidoptera in general.     

From plants to birds: higher avian predation rates in trees responding to insect herbivory

BACKGROUND: An understanding of the evolution of potential signals from plants to the predators of their herbivores may provide exciting examples of co-evolution among multiple trophic levels. Understanding the mechanism behind the attraction of predators to plants is crucial to conclusions about co-evolution. For example, insectivorous birds are attracted to herbivore-damaged trees without seeing the herbivores or the defoliated parts, but it is not known whether birds use cues from herbivore-damaged plants with a specific adaptation of plants for this purpose. METHODOLOGY: We examined whether signals from damaged trees attract avian predators in the wild and whether birds could use volatile organic compound (VOC) emissions or net photosynthesis of leaves as cues to detect herbivore-rich trees. We conducted a field experiment with mountain birches (Betula pubescens ssp. czerepanovii), their main herbivore (Epirrita autumnata) and insectivorous birds. Half of the trees had herbivore larvae defoliating trees hidden inside branch bags and half had empty bags as controls. We measured predation rate of birds towards artificial larvae on tree branches, and VOC emissions and net photosynthesis of leaves. PRINCIPAL FINDINGS AND SIGNIFICANCE: The predation rate was higher in the herbivore trees than in the control trees. This confirms that birds use cues from trees to locate insect-rich trees in the wild. The herbivore trees had decreased photosynthesis and elevated emissions of many VOCs, which suggests that birds could use either one, or both, as cues. There was, however, large variation in how the VOC emission correlated with predation rate. Emissions of (E)-DMNT [(E)-4,8-dimethyl-1,3,7-nonatriene], beta-ocimene and linalool were positively correlated with predation rate, while those of highly inducible green leaf volatiles were not. These three VOCs are also involved in the attraction of insect parasitoids and predatory mites to herbivore-damaged plants, which suggests that plants may not have specific adaptations to signal only to birds.     

Glycomics of bone marrow-derived mesenchymal stem cells can be used to evaluate their cellular differentiation stage

Human mesenchymal stem cells (MSCs) are adult multipotent progenitor cells. They hold an enormous therapeutic potential, but at the moment there is little information on the properties of MSCs, including their surface structures. In the present study, we analyzed the mesenchymal stem cell glycome by using mass spectrometric profiling as well as a panel of glycan binding proteins. Structural verifications were obtained by nuclear magnetic resonance spectroscopy, mass spectrometric fragmentation, and glycosidase digestions. The MSC glycome was compared to the glycome of corresponding osteogenically differentiated cells. More than one hundred glycan signals were detected in mesenchymal stem cells and osteoblasts differentiated from them. The glycan profiles of MSCs and osteoblasts were consistently different in biological replicates, indicating that stem cells and osteoblasts have characteristic glycosylation features. Glycosylation features associated with MSCs rather than differentiated cells included high-mannose type N-glycans, linear poly-N-acetyllactosamine chains and α2-3-sialylation. Mesenchymal stem cells expressed SSEA-4 and sialyl Lewis x epitopes. Characteristic glycosylation features that appeared in differentiated osteoblasts included abundant sulfate ester modifications. The results show that glycosylation analysis can be used to evaluate MSC differentiation state.