IBC’s 23rd Annual Antibody Engineering, 10th Annual Antibody Therapeutics International Conferences and the 2012 Annual Meeting of The Antibody Society

The 23rd Annual Antibody Engineering, 10th Annual Antibody Therapeutics international conferences, and the 2012 Annual Meeting of The Antibody Society, organized by IBC Life Sciences with contributions from The Antibody Society and two Scientific Advisory Boards, were held December 3–6, 2012 in San Diego, CA. The meeting drew over 800 participants who attended sessions on a wide variety of topics relevant to antibody research and development. As a prelude to the main events, a pre-conference workshop held on December 2, 2012 focused on intellectual property issues that impact antibody engineering. The Antibody Engineering Conference was composed of six sessions held December 3–5, 2012: (1) From Receptor Biology to Therapy; (2) Antibodies in a Complex Environment; (3) Antibody Targeted CNS Therapy: Beyond the Blood Brain Barrier; (4) Deep Sequencing in B Cell Biology and Antibody Libraries; (5) Systems Medicine in the Development of Antibody Therapies/Systematic Validation of Novel Antibody Targets; and (6) Antibody Activity and Animal Models. The Antibody Therapeutics conference comprised four sessions held December 4–5, 2012: (1) Clinical and Preclinical Updates of Antibody-Drug Conjugates; (2) Multifunctional Antibodies and Antibody Combinations: Clinical Focus; (3) Development Status of Immunomodulatory Therapeutic Antibodies; and (4) Modulating the Half-Life of Antibody Therapeutics. The Antibody Society’s special session on applications for recording and sharing data based on GIATE was held on December 5, 2012, and the conferences concluded with two combined sessions on December 5–6, 2012: (1) Development Status of Early Stage Therapeutic Antibodies; and (2) Immunomodulatory Antibodies for Cancer Therapy.     

snoRNPs Regulate Telomerase Activity in Neuroblastoma and Are Associated with Poor Prognosis

Amplification of the MYCN oncogene is strongly associated with poor prognosis in neuroblastoma (NB). In addition to MYCN amplification, many studies have focused on identifying patients with a poor prognosis based on gene expression profiling. The majority of prognostic signatures today are comprised of large gene lists limiting their clinical application. In addition, although of prognostic significance,most of these signatures fail to identify cellular processes that can explain their relation to prognosis. Here, we determined prognostically predictive genes in a data set containing 251 NBs. Gene Ontology analysis was performed on significant genes with a positive hazard ratio to search for cellular processes associated with poor prognosis. An enrichment in ribonucleoproteins (RNPs) was found. Genes involved in the stabilization and formation of the central small nucleolar RNP (snoRNP) complex were scrutinized using a backward conditional Cox regression resulting in an snoRNP signature consisting of three genes: DKC1, NHP2, and GAR1. The snoRNP signature significantly and independently predicted prognosis when compared to the established clinical risk factors. Association of snoRNP protein expression and prognosis was confirmed using tissue microarrays. Knockdown of snoRNP expression in NB cell lines resulted in reduced telomerase activity and an increase in anaphase bridge frequency. In addition, in patient material, expression of the snoRNP complex was significantly associated with telomerase activity, occurrence of segmental aberrations, and expression-based measurements of chromosomal instability. Together, these results underscore the prognostic value of snoRNP complex expression in NB and suggest a role for snoRNPs in telomere maintenance and genomic stability.     

Investigating alginate production and carbon utilization in Pseudomonas fluorescens SBW25 using mass spectrometry-based metabolic profiling

Metabolic profiling of Pseudomonas fluorescens SBW25 and various mutants derived thereof was performed to explore how the bacterium adapt to changes in carbon source and upon induction of alginate synthesis. The experiments were performed at steady-state conditions in nitrogen-limited chemostats using either fructose or glycerol as carbon source. Carbon source consumption was up-regulated in the alginate producing mutant with inactivated anti-sigma factor MucA. The mucA- mutants (also non-alginate producing mucA- control strains) had a higher dry weight yield on carbon source implying a change in carbon and energy metabolism due to the inactivation of the anti-sigma factor MucA. Both LC–MS/MS and GC–MS methods were used for quantitative metabolic profiling, and major reorganization of primary metabolite pools in both an alginate producing and a carbon source dependent manner was observed. Generally, larger changes were observed among the phosphorylated glycolytic metabolites, the pentose phosphate pathway metabolites and the nucleotide pool than among amino acids and citric acid cycle compounds. The most significant observation at the metabolite level was the significantly reduced energy charge of the mucA- mutants (both alginate producing and non-producing control strains) compared to the wild type strain. This reduction was caused more by a strong increase in the AMP pool than changes in the ATP and ADP pools. The alginate-producing mucA- mutant had a slightly increased GTP pool, while the GDP and GMP pools were strongly increased compared to non-producing mucA- strains and to the wild type. Thus, whilst changes in the adenosine phosphate nucleotide pool are attributed to the mucA inactivation, adjustments in the guanosine phosphate nucleotide pool are consequences of the GTP-dependent alginate production induced by the mucA inactivation. This metabolic profiling study provides new insight into carbon and energy metabolism of the alginate producer P. fluorescens.     

Identifying subgroup markers in heterogeneous populations

Traditional methods that aim to identify biomarkers that distinguish between two groups, like Significance Analysis of Microarrays or the t-test, perform optimally when such biomarkers show homogeneous behavior within each group and differential behavior between the groups. However, in many applications, this is not the case. Instead, a subgroup of samples in one group shows differential behavior with respect to all other samples. To successfully detect markers showing such imbalanced patterns of differential signal, a different approach is required. We propose a novel method, specifically designed for the Detection of Imbalanced Differential Signal (DIDS). We use an artificial dataset and a human breast cancer dataset to measure its performance and compare it with three traditional methods and four approaches that take imbalanced signal into account. Supported by extensive experimental results, we show that DIDS outperforms all other approaches in terms of power and positive predictive value. In a mouse breast cancer dataset, DIDS is the only approach that detects a functionally validated marker of chemotherapy resistance. DIDS can be applied to any continuous value data, including gene expression data, and in any context where imbalanced differential signal is manifested.     

Fungizide: Risiken der resistenzentwicklung und suche nach neuen targets

Trotz intensiver Bemühungen im Bereich des Pflanzenschutzes sind weltweit erhebliche Verluste im Bereich pflanzlicher Erntegüter zu verzeichnen. Rund ein Drittel der Verluste werden mikrobiellen Schaderregern, also Pilzen, Bakterien und Viren, zugeschrieben. Besonders schwierig ist der Tatsache zu begegnen, dass Pilze gegenüber spezifisch wirkenden Fungiziden Insensitivitäten bzw. Resistenzen entwickeln. Aus diesem Grunde muss über geeignete Strategien beim Fungizideinsatz, beim ‘Disease management’ und bei der Suche nach neuen, hochwirksamen Fungiziden nachgedacht werden. Der Erfolg bei der Suche nach neuen Fungiziden wird stark davon abhängen, ob neue Zielmoleküle für potentielle Fungizide entdeckt werden können. Dabei können moderne molekulargenetische Techniken von großem Nutzen sein.     

A new Pliocene mollusk fauna from Mejillones, northern Chile

A new Pliocene (3.4 Ma) mollusk fauna from Mejillones Peninsula, northern Chile is described and compared with the Pliocene La Cueva fauna of little constrained age from central Chile and some species from the Huenteguapi Sandstone overlying the Ranquil Formation on Arauco Peninsula, south central Chile. Preliminary correlation is based on faunal similarities. A total of 45 taxa were identified, of which Cyclocardia kieli sp. nov. is new to science. New combinations are Macron escalonia (Vermeij and DeVries, 1997), Austrofusus steinmanni (Möricke, 1896) and Leukoma antiqua (King, 1832). For several species, the oldest occurrences and range extensions are reported. Co-occurrence of warm water taxa, previously assigned to MIS 11, and typical Pliocene taxa on Mejillones cannot be confirmed. Pliocene and Pleistocene mollusk faunas from Mejillones are listed for comparison.     

Ion-specific Effects on Prion Nucleation and Strain Formation

Ordered, fibrous, self-seeding aggregates of misfolded proteins known as amyloids are associated with important diseases in mammals and control phenotypic traits in fungi. A given protein may adopt multiple amyloid conformations, known as variants or strains, each of which leads to a distinct disease pattern or phenotype. Here, we study the effect of Hofmeister ions on amyloid nucleation and strain generation by the prion domain-containing fragment (Sup35NM) of a yeast protein Sup35p. Strongly hydrated anions (kosmotropes) initiate nucleation quickly and cause rapid fiber elongation, whereas poorly hydrated anions (chaotropes) delay nucleation and mildly affect the elongation rate. For the first time, we demonstrate that kosmotropes favor formation of amyloid strains that are characterized by lower thermostability and higher frangibility in vitro and stronger phenotypic and proliferation patterns effectively in vivo as compared with amyloids formed in chaotropes. These phenomena point to inherent differences in the biochemistry of Hofmeister ions. Our work shows that the ionic composition of a solution not only influences the kinetics of amyloid nucleation but also determines the amyloid strain that is preferentially formed.