Senescence‐associated tissue microenvironment promotes colon cancer formation through the secretory factor GDF15

The risk of colorectal cancer (CRC) varies between people, and the cellular mechanisms mediating the differences in risk are largely unknown. Senescence has been implicated as a causative cellular mechanism for many diseases, including cancer, and may affect the risk for CRC. Senescent fibroblasts that accumulate in tissues secondary to aging and oxidative stress have been shown to promote cancer formation via a senescence‐associated secretory phenotype (SASP). In this study, we assessed the role of senescence and the SASP in CRC formation. Using primary human colon tissue, we found an accumulation of senescent fibroblasts in normal tissues from individuals with advanced adenomas or carcinomas in comparison with individuals with no polyps or CRC. In in vitro and ex vivo model systems, we induced senescence using oxidative stress in colon fibroblasts and demonstrated that the senescent fibroblasts secrete GDF15 as an essential SASP factor that promotes cell proliferation, migration, and invasion in colon adenoma and CRC cell lines as well as primary colon organoids via the MAPK and PI3K signaling pathways. In addition, we observed increased mRNA expression of GDF15 in primary normal colon tissue from people at increased risk for CRC in comparison with average risk individuals. These findings implicate the importance of a senescence‐associated tissue microenvironment and the secretory factor GDF15 in promoting CRC formation.     

Do intraspecific life history patterns follow interspecific predictions? A test using latitudinal variation in ringed seals

Mammals adapted to unpredictable and low-energy environments often evolve a “bet-hedging” life history strategy characterized by less costly reproductive outputs over a longer and slower-growing life. In contrast, species adapted to more predictable (i.e., low variation) and higher energy environments may evolve greater fecundity over a shorter and faster-growing life. We tested whether this known interspecific pattern also occurs within a species. We compared life history traits of the ringed seal (Pusa hispida) in the Canadian High Arctic to those closer to the southern limit of the species' circumpolar distribution. We found that northern seals grew slower than southern seals (Brody growth coefficient), achieved a greater asymptotic body weight (82 and 69 kg vs. 74 and 54 kg female and male, respectively), reached sexual maturity later (6.1 years vs. 4.5 years), had lower fecundity (1.8 years vs. 1.3 years interbirth interval), longer average lifespan (5 years vs. 3 years median age), and greater movements (1,269 vs. 681 km). Mating systems also likely differed with northern seals showing morphological evidence of a promiscuous mating system with potential sperm competition as indicated by greater relative testes size. The northern region was also characterized by more unpredictable environmental timing of seasonal events, such as spring sea ice breakup. Life history variation between the intraspecific groups of seals appears to agree with interspecific patterns and provides a better understanding of how species' life history parameters shift in concert with environmental conditions.     

Smart process development: Application of machine-learning and integrated process modeling for inclusion body purification processes

The development of a biopharmaceutical production process usually occurs sequentially, and tedious optimization of each individual unit operation is very time-consuming. Here, the conditions established as optimal for one-step serve as input for the following step. Yet, this strategy does not consider potential interactions between a priori distant process steps and therefore cannot guarantee for optimal overall process performance. To overcome these limitations, we established a smart approach to develop and utilize integrated process models using machine learning techniques and genetic algorithms. We evaluated the application of the data-driven models to explore potential efficiency increases and compared them to a conventional development approach for one of our development products. First, we developed a data-driven integrated process model using gradient boosting machines and Gaussian processes as machine learning techniques and a genetic algorithm as recommendation engine for two downstream unit operations, namely solubilization and refolding. Through projection of the results into our large-scale facility, we predicted a twofold increase in productivity. Second, we extended the model to a three-step model by including the capture chromatography. Here, depending on the selected baseline-process chosen for comparison, we obtained between 50% and 100% increase in productivity. These data show the successful application of machine learning techniques and optimization algorithms for downstream process development. Finally, our results highlight the importance of considering integrated process models for the whole process chain, including all unit operations.     

Identification, expression, and functional analyses of a thylakoid ATP/ADP carrier from Arabidopsis

In plants the chloroplast thylakoid membrane is the site of light-dependent photosynthetic reactions coupled to ATP synthesis. The ability of the plant cell to build and alter this membrane system is essential for efficient photosynthesis. A nucleotide translocator homologous to the bovine mitochondrial ADP/ATP carrier (AAC) was previously found in spinach thylakoids. Here we have identified and characterized a thylakoid ATP/ADP carrier (TAAC) from Arabidopsis.(i) Sequence homology with the bovine AAC and the prediction of chloroplast transit peptides indicated a putative carrier encoded by the At5g01500 gene, as a TAAC. (ii) Transiently expressed TAAC-green fluorescent protein fusion construct was targeted to the chloroplast. Western blotting using a peptide-specific antibody together with immunogold electron microscopy revealed a major location of TAAC in the thylakoid membrane. Previous proteomic analyses identified this protein in chloroplast envelope preparations. (iii) Recombinant TAAC protein specifically imports ATP in exchange for ADP across the cytoplasmic membrane of Escherichia coli. Studies on isolated thylakoids from Arabidopsis confirmed these observations. (iv) The lack of TAAC in an Arabidopsis T-DNA insertion mutant caused a 30-40% reduction in the thylakoid ATP transport and metabolism. (v) TAAC is readily expressed in dark-grown Arabidopsis seedlings, and its level remains stable throughout the greening process. Its expression is highest in developing green tissues and in leaves undergoing senescence or abiotic stress. We propose that the TAAC protein supplies ATP for energy-dependent reactions during thylakoid biogenesis and turnover in plants.     

Tandem affinity purification of functional TAP-tagged proteins from human cells

Tandem affinity purification (TAP) is a generic two-step affinity purification protocol for isolation of TAP-tagged proteins together with associated proteins. We used bacterial artificial chromosome to heterologously express TAP-tagged murine Sgo1 protein in human HeLa cells. This allowed us to test the functionality of the Sgo1-TAP protein by RNA interference-mediated depletion of the endogenous human Sgo1. Here, we present an optimized protocol for purification of TAP-tagged Sgo1 protein as well as KIAA1387 from HeLa cells with detailed instructions. The purification protocol can be completed in 1 day and it should be applicable to other proteins.     

In vivo glyco-engineered antibody with improved lytic potential produced by an innovative non-mammalian expression system

Recent studies have demonstrated that the reduction of the core fucosylation on N-glycans of human IgGs is responsible for a clearly enhanced antibody-dependent cellular cytotoxicity (ADCC). This finding might give access to improved active therapeutic antibodies. Here, the expression of the tumor antigen-specific antibody IGN311 was performed in a glyco-optimized strain of the moss Physcomitrella patens. Removal of plant specific N-glycan structures in this plant expression host was achieved by targeted knockout of corresponding genes and included quantitative elimination of core fucosylation. Antibodies transiently expressed and secreted by such genetically modified moss protoplasts assembled correctly, showed an unaltered antigen-binding affinity and, in extensive tests, revealed an up to 40-fold enhanced ADCC. Thus, the glyco-engineered moss-based transient expression platform combines a rapid technology with the subsequent analysis of glycooptimized therapeutics with regard to advanced properties.     

A genomic background based method for association analysis in related individuals

Background

Feasibility of genotyping of hundreds and thousands of single nucleotide polymorphisms (SNPs) in thousands of study subjects have triggered the need for fast, powerful, and reliable methods for genome-wide association analysis. Here we consider a situation when study participants are genetically related (e.g. due to systematic sampling of families or because a study was performed in a genetically isolated population). Of the available methods that account for relatedness, the Measured Genotype (MG) approach is considered the ‘gold standard’. However, MG is not efficient with respect to time taken for the analysis of genome-wide data. In this context we proposed a fast two-step method called Genome-wide Association using Mixed Model and Regression (GRAMMAR) for the analysis of pedigree-based quantitative traits. This method certainly overcomes the drawback of time limitation of the measured genotype (MG) approach, but pays in power. One of the major drawbacks of both MG and GRAMMAR, is that they crucially depend on the availability of complete and correct pedigree data, which is rarely available.

Methodology

In this study we first explore type 1 error and relative power of MG, GRAMMAR, and Genomic Control (GC) approaches for genetic association analysis. Secondly, we propose an extension to GRAMMAR i.e. GRAMMAR-GC. Finally, we propose application of GRAMMAR-GC using the kinship matrix estimated through genomic marker data, instead of (possibly missing and/or incorrect) genealogy.

Conclusion

Through simulations we show that MG approach maintains high power across a range of heritabilities and possible pedigree structures, and always outperforms other contemporary methods. We also show that the power of our proposed GRAMMAR-GC approaches to that of the ‘gold standard’ MG for all models and pedigrees studied. We show that this method is both feasible and powerful and has correct type 1 error in the context of genome-wide association analysis in related individuals.