Identification of homologs in insignificant blast hits by exploiting extrinsic gene properties

Background  

Homology is a key concept in both evolutionary biology and genomics. Detection of homology is crucial in fields like the functional annotation of protein sequences and the identification of taxon specific genes. Basic homology searches are still frequently performed by pairwise search methods such as BLAST. Vast improvements have been made in the identification of homologous proteins by using more advanced methods that use sequence profiles. However additional improvement could be made by exploiting sources of genomic information other than the primary sequence or tertiary structure.     

Evolutionary dynamics of the kinetochore network in eukaryotes as revealed by comparative genomics

During eukaryotic cell division, the sister chromatids of duplicated chromosomes are pulled apart by microtubules, which connect via kinetochores. The kinetochore is a multiprotein structure that links centromeres to microtubules, and that emits molecular signals in order to safeguard the equal distribution of duplicated chromosomes over daughter cells. Although microtubule‐mediated chromosome segregation is evolutionary conserved, kinetochore compositions seem to have diverged. To systematically inventory kinetochore diversity and to reconstruct its evolution, we determined orthologs of 70 kinetochore proteins in 90 phylogenetically diverse eukaryotes. The resulting ortholog sets imply that the last eukaryotic common ancestor (LECA) possessed a complex kinetochore and highlight that current‐day kinetochores differ substantially. These kinetochores diverged through gene loss, duplication, and, less frequently, invention and displacement. Various kinetochore components co‐evolved with one another, albeit in different manners. These co‐evolutionary patterns improve our understanding of kinetochore function and evolution, which we illustrated with the RZZ complex, TRIP13, the MCC, and some nuclear pore proteins. The extensive diversity of kinetochore compositions in eukaryotes poses numerous questions regarding evolutionary flexibility of essential cellular functions.     

Comprehensive structure-activity-relationship of azaindoles as highly potent FLT3 inhibitors

Acute myeloid leukemia (AML) is characterized by fast progression and low survival rates, in which Fms-like tyrosine kinase 3 (FLT3) receptor mutations have been identified as a driver mutation in cancer progression in a subgroup of AML patients. Clinical trials have shown emergence of drug resistant mutants, emphasizing the ongoing need for new chemical matter to enable the treatment of this disease. Here, we present the discovery and topological structure-activity relationship (SAR) study of analogs of isoquinolinesulfonamide H-89, a well-known PKA inhibitor, as FLT3 inhibitors. Surprisingly, we found that the SAR was not consistent with the observed binding mode of H-89 in PKA. Matched molecular pair analysis resulted in the identification of highly active sub-nanomolar azaindoles as novel FLT3-inhibitors. Structure based modelling using the FLT3 crystal structure suggested an alternative, flipped binding orientation of the new inhibitors.     

Metabolic isotopomer labeling systems. Part II: structural flux identifiability analysis

Metabolic flux analysis using carbon labeling experiments (CLEs) is an important tool in metabolic engineering where the intracellular fluxes have to be computed from the measured extracellular fluxes and the partially measured distribution of 13C labeling within the intracellular metabolite pools. The relation between unknown fluxes and measurements is described by an isotopomer labeling system (ILS) (see Part I [Math. Biosci. 169 (2001) 173]). Part II deals with the structural flux identifiability of measured ILSs in the steady state. The central question is whether the measured data contains sufficient information to determine the unknown intracellular fluxes. This question has to be decided a priori, i.e. before the CLE is carried out. In structural identifiability analysis the measurements are assumed to be noise-free. A general theory of structural flux identifiability for measured ILSs is presented and several algorithms are developed to solve the identifiability problem. In the particular case of maximal measurement information, a symbolical algorithm is presented that decides the identifiability question by means of linear methods. Several upper bounds of the number of identifiable fluxes are derived, and the influence of the chosen inputs is evaluated. By introducing integer arithmetic this algorithm can even be applied to large networks. For the general case of arbitrary measurement information, identifiability is decided by a local criterion. A new algorithm based on integer arithmetic enables an a priori local identifiability analysis to be performed for networks of arbitrary size. All algorithms have been implemented and flux identifiability is investigated for the network of the central metabolic pathways of a microorganism. Moreover, several small examples are worked out to illustrate the influence of input metabolite labeling and the paradox of information loss due to network simplification.     

Comparative genomics for reliable protein-function prediction from genomic data

Genomic data provide invaluable, yet unreliable information about protein function. However, if the overlap in information among various genomic datasets is taken into account, one observes an increase in the reliability of the protein-function predictions that can be made. Recently published approaches achieved this either by comparing the same type of data from multiple species (horizontal comparative genomics) or by using subtle, Bayesian methods to compare different types of genomic data from a single species (vertical comparative genomics). In this article, we discuss these methods, illustrating horizontal comparative genomics by comparing yeast two-hybrid (Y2H) data from Saccharomyces cerevisiae with Y2H data from Drosophila melanogaster, and illustrating vertical comparative genomics by comparing RNA expression data with proteomic data from Plasmodium falciparum.     

The thrombomodulin-protein C system is essential for the maintenance of pregnancy

Disruption of the mouse gene encoding the blood coagulation inhibitor thrombomodulin (Thbd) leads to embryonic lethality caused by an unknown defect in the placenta. We show that the abortion of thrombomodulin-deficient embryos is caused by tissue factor-initiated activation of the blood coagulation cascade at the feto-maternal interface. Activated coagulation factors induce cell death and growth inhibition of placental trophoblast cells by two distinct mechanisms. The death of giant trophoblast cells is caused by conversion of the thrombin substrate fibrinogen to fibrin and subsequent formation of fibrin degradation products. In contrast, the growth arrest of trophoblast cells is not mediated by fibrin, but is a likely result of engagement of protease-activated receptors (PAR)-2 and PAR-4 by coagulation factors. These findings show a new function for the thrombomodulin-protein C system in controlling the growth and survival of trophoblast cells in the placenta. This function is essential for the maintenance of pregnancy.