Impact of protein stability, cellular localization, and abundance on proteomic detection of tumor-derived proteins in plasma

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins.     

The ten grand challenges of synthetic life

The construction of artificial life is one of the main scientific challenges of the Synthetic Biology era. Advances in DNA synthesis and a better understanding of regulatory processes make the goal of constructing the first artificial cell a realistic possibility. This would be both a fundamental scientific milestone and a starting point of a vast range of applications, from biofuel production to drug design. However, several major issues might hamper the objective of achieving an artificial cell. From the bottom-up to the selection-based strategies, this work encompasses the ten grand challenges synthetic biologists will have to be aware of in order to cope with the task of creating life in the lab.     

The amino-terminus of nitric oxide sensitive guanylyl cyclase α₁ does not affect dimerization but influences subcellular localization

Background

Nitric oxide sensitive guanylyl cyclase (NOsGC) is a heterodimeric enzyme formed by an α- and a β₁-subunit. A splice variant (C-α₁) of the α₁-subunit, lacking at least the first 236 amino acids has been described by Sharina et al. 2008 and has been shown to be expressed in differentiating human embryonic cells. Wagner et al. 2005 have shown that the amino acids 61–128 of the α₁-subunit are mandatory for quantitative heterodimerization implying that the C-α₁-splice variant should lose its capacity to dimerize quantitatively.

Methodology/Principal Findings

In the current study we demonstrate preserved quantitative dimerization of the C-α₁-splice by co-purification with the β₁-subunit. In addition we used fluorescence resonance energy transfer (FRET) based on fluorescence lifetime imaging (FLIM) using fusion proteins of the β₁-subunit and the α₁-subunit or the C-α₁ variant with ECFP or EYFP. Analysis of the respective combinations in HEK-293 cells showed that the fluorescence lifetime was significantly shorter (≈0.3 ns) for α₁/β₁ and C-α₁/β₁ than the negative control. In addition we show that lack of the amino-terminus in the α₁ splice variant directs it to a more oxidized subcellular compartment.

Conclusions/Significance

We conclude that the amino-terminus of the α₁-subunit is dispensable for dimerization in-vivo and ex-vivo, but influences the subcellular trafficking.     

Can Score Databanks Help Teaching?

Background

Basic courses in most medical schools assess students'' performance by conferring scores. The objective of this work is to use a large score databank for the early identification of students with low performance and to identify course trends based on the mean of students'' grades.

Methodology/Principal Findings

We studied scores from 2,398 medical students registered in courses over a period of 10 years. Students in the first semester were grouped into those whose ratings remained in the lower quartile in two or more courses (low-performance) and students who had up to one course in the lower quartile (high-performance). ROC curves were built, aimed at the identification of a cut-off average score in the first semesters that would be able to predict low performances in future semesters. Moreover, to follow the long-term pattern of each course, the mean of all scores conferred in a semester was compared to the overall course mean obtained by averaging 10 years of data. Individuals in the low-performance group had a higher risk of being in the lower quartile of at least one course in the second semester (relative risk 3.907; 95% CI: 3.378–4.519) and in the eighth semester (relative risk 2.873; 95% CI: 2.495–3.308). The prediction analysis revealed that an average score of 7.188 in the first semester could identify students that presented scores below the lower quartiles in both the second and eighth semesters (p<0.0001 for both AUC). When scores conferred by single courses were compared over time, three time-trend patterns emerged: low variation, upward trend and erratic pattern.

Conclusion/Significance

An early identification of students with low performance may be useful in promoting pedagogical strategies for these individuals. Evaluation of the time trend of scores conferred by courses may help departments monitoring changes in personnel and methodology that may affect a student''s performance.     

Advancing biodiversity assessments with environmental DNA: Long‐read technologies help reveal the drivers of Amazonian fungal diversity

Fungi are a key component of tropical biodiversity. However, due to their inconspicuous and largely subterranean nature, they are usually neglected in biodiversity inventories. The goal of this study was to identify the key determinants of fungal richness, community composition, and turnover in tropical rainforests. We tested specifically for the effect of soil properties, habitat, and locality in Amazonia. For these analyses, we used high‐throughput sequencing data of short and long reads of fungal DNA present in soil and organic litter samples, combining existing and novel genomic data. Habitat type (phytophysiognomy) emerges as the strongest factor explaining fungal community composition. Naturally open areas—campinas—are the richest habitat overall. Soil properties have different effects depending on the soil layer (litter or mineral soil) and the choice of genetic marker. We suggest that campinas could be a neglected hotspot of fungal diversity. An underlying cause for their rich diversity may be the overall low soil fertility, which increases the reliance on biotic interactions essential for nutrient absorption in these environments, notably ectomycorrhizal fungi–plant associations. Our results highlight the advantages of using both short and long DNA reads produced through high‐throughput sequencing to characterize fungal diversity. While short reads can suffice for diversity and community comparison, long reads add taxonomic precision and have the potential to reveal population diversity.     

Recycling of the High Valence States of Heme Proteins by Cysteine Residues of Thimet-Oligopeptidase

The peptidolytic enzyme THIMET-oligopeptidase (TOP) is able to act as a reducing agent in the peroxidase cycle of myoglobin (Mb) and horseradish peroxidase (HRP). The TOP-promoted recycling of the high valence states of the peroxidases to the respective resting form was accompanied by a significant decrease in the thiol content of the peptidolytic enzyme. EPR (electron paramagnetic resonance) analysis using DBNBS spin trapping revealed that TOP also prevented the formation of tryptophanyl radical in Mb challenged by H₂O₂. The oxidation of TOP thiol groups by peroxidases did not promote the inactivating oligomerization observed in the oxidation promoted by the enzyme aging. These findings are discussed towards a possible occurrence of these reactions in cells.     

Antitumor Activity of Hierridin B,a Cyanobacterial Secondary Metabolite Found in both Filamentous and Unicellular Marine Strains

Cyanobacteria are widely recognized as a valuable source of bioactive metabolites. The majority of such compounds have been isolated from so-called complex cyanobacteria, such as filamentous or colonial forms, which usually display a larger number of biosynthetic gene clusters in their genomes, when compared to free-living unicellular forms. Nevertheless, picocyanobacteria are also known to have potential to produce bioactive natural products. Here, we report the isolation of hierridin B from the marine picocyanobacterium Cyanobium sp. LEGE 06113. This compound had previously been isolated from the filamentous epiphytic cyanobacterium Phormidium ectocarpi SAG 60.90, and had been shown to possess antiplasmodial activity. A phylogenetic analysis of the 16S rRNA gene from both strains confirmed that these cyanobacteria derive from different evolutionary lineages. We further investigated the biological activity of hierridin B, and tested its cytotoxicity towards a panel of human cancer cell lines; it showed selective cytotoxicity towards HT-29 colon adenocarcinoma cells.     

The Making of a Slicer: Activation of Human Argonaute-1

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Disentangling Biodiversity and Climatic Determinants of Wood Production

Background

Despite empirical support for an increase in ecosystem productivity with species diversity in synthetic systems, there is ample evidence that this relationship is dependent on environmental characteristics, especially in structurally more complex natural systems. Empirical support for this relationship in forests is urgently needed, as these ecosystems play an important role in carbon sequestration.

Methodology/Principal Findings

We tested whether tree wood production is positively related to tree species richness while controlling for climatic factors, by analyzing 55265 forest inventory plots in 11 forest types across five European countries. On average, wood production was 24% higher in mixed than in monospecific forests. Taken alone, wood production was enhanced with increasing tree species richness in almost all forest types. In some forests, wood production was also greater with increasing numbers of tree types. Structural Equation Modeling indicated that the increase in wood production with tree species richness was largely mediated by a positive association between stand basal area and tree species richness. Mean annual temperature and mean annual precipitation affected wood production and species richness directly. However, the direction and magnitude of the influence of climatic variables on wood production and species richness was not consistent, and vary dependent on forest type.

Conclusions

Our analysis is the first to find a local scale positive relationship between tree species richness and tree wood production occurring across a continent. Our results strongly support incorporating the role of biodiversity in management and policy plans for forest carbon sequestration.     

Contribution of Multiparameter Flow Cytometry Immunophenotyping to the Diagnostic Screening and Classification of Pediatric Cancer

Pediatric cancer is a relatively rare and heterogeneous group of hematological and non-hematological malignancies which require multiple procedures for its diagnostic screening and classification. Until now, flow cytometry (FC) has not been systematically applied to the diagnostic work-up of such malignancies, particularly for solid tumors. Here we evaluated a FC panel of markers for the diagnostic screening of pediatric cancer and further classification of pediatric solid tumors. The proposed strategy aims at the differential diagnosis between tumoral vs. reactive samples, and hematological vs. non-hematological malignancies, and the subclassification of solid tumors. In total, 52 samples from 40 patients suspicious of containing tumor cells were analyzed by FC in parallel to conventional diagnostic procedures. The overall concordance rate between both approaches was of 96% (50/52 diagnostic samples), with 100% agreement for all reactive/inflammatory and non-infiltrated samples as well as for those corresponding to solid tumors (n = 35), with only two false negative cases diagnosed with Hodgkin lymphoma and anaplastic lymphoma, respectively. Moreover, clear discrimination between samples infiltrated by hematopoietic vs. non-hematopoietic tumor cells was systematically achieved. Distinct subtypes of solid tumors showed different protein expression profiles, allowing for the differential diagnosis of neuroblastoma (CD56^hi/GD2⁺/CD81^hi), primitive neuroectodermal tumors (CD271^hi/CD99⁺), Wilms tumors (>1 cell population), rhabdomyosarcoma (_nuMYOD1⁺/_numyogenin⁺), carcinomas (CD45⁻/EpCAM⁺), germ cell tumors (CD56⁺/CD45⁻/NG2⁺/CD10⁺) and eventually also hemangiopericytomas (CD45⁻/CD34⁺). In summary, our results show that multiparameter FC provides fast and useful complementary data to routine histopathology for the diagnostic screening and classification of pediatric cancer.