The Mass Distance Fingerprint: a statistical framework for de novo detection of predominant modifications using high-accuracy mass spectrometry

We describe a statistical measure, Mass Distance Fingerprint, for automatic de novo detection of predominant peptide mass distances, i.e., putative protein modifications. The method's focus is to globally detect mass differences, not to assign peptide sequences or modifications to individual spectra. The Mass Distance Fingerprint is calculated from high accuracy measured peptide masses. For the data sets used in this study, known mass differences are detected at electron mass accuracy or better. The proposed method is novel because it works independently of protein sequence databases and without any prior knowledge about modifications. Both modified and unmodified peptides have to be present in the sample to be detected. The method can be used for automated detection of chemical/post-translational modifications, quality control of experiments and labeling approaches, and to control the modification settings of protein identification tools. The algorithm is implemented as a web application and is distributed as open source software.     

A workflow to increase the detection rate of proteins from unsequenced organisms in high-throughput proteomics experiments

We present and evaluate a strategy for the mass spectrometric identification of proteins from organisms for which no genome sequence information is available that incorporates cross-species information from sequenced organisms. The presented method combines spectrum quality scoring, de novo sequencing and error tolerant BLAST searches and is designed to decrease input data complexity. Spectral quality scoring reduces the number of investigated mass spectra without a loss of information. Stringent quality-based selection and the combination of different de novo sequencing methods substantially increase the catalog of significant peptide alignments. The de novo sequences passing a reliability filter are subsequently submitted to error tolerant BLAST searches and MS-BLAST hits are validated by a sampling technique. With the described workflow, we identified up to 20% more groups of homologous proteins in proteome analyses with organisms whose genome is not sequenced than by state-of-the-art database searches in an Arabidopsis thaliana database. We consider the novel data analysis workflow an excellent screening method to identify those proteins that evade detection in proteomics experiments as a result of database constraints.     

Identification of liver‐derived bone morphogenetic protein (BMP)‐9 as a potential new candidate for treatment of colorectal cancer

Colorectal cancer (CRC) is a high‐incidence malignancy worldwide which still needs better therapy options. Therefore, the aim of the present study was to investigate the responses of normal or malignant human intestinal epithelium to bone morphogenetic protein (BMP)‐9 and to find out whether the application of BMP‐9 to patients with CRC or the enhancement of its synthesis in the liver could be useful strategies for new therapy approaches. In silico analyses of CRC patient cohorts (TCGA database) revealed that high expression of the BMP‐target gene ID1, especially in combination with low expression of the BMP‐inhibitor noggin, is significantly associated with better patient survival. Organoid lines were generated from human biopsies of colon cancer (T‐Orgs) and corresponding non‐malignant areas (N‐Orgs) of three patients. The N‐Orgs represented tumours belonging to three different consensus molecular subtypes (CMS) of CRC. Overall, BMP‐9 stimulation of organoids promoted an enrichment of tumour‐suppressive gene expression signatures, whereas the stimulation with noggin had the opposite effects. Furthermore, treatment of organoids with BMP‐9 induced ID1 expression (independently of high noggin levels), while treatment with noggin reduced ID1.In summary, our data identify the ratio between ID1 and noggin as a new prognostic value for CRC patient outcome. We further show that by inducing ID1, BMP‐9 enhances this ratio, even in the presence of noggin. Thus, BMP‐9 is identified as a novel target for the development of improved anti‐cancer therapies of patients with CRC.     

Analysis of eighteen antidepressants,four atypical antipsychotics and active metabolites in serum by liquid chromatography: a simple tool for therapeutic drug monitoring

Therapeutic drug monitoring necessitates efficient, fast and reliable analytical methods validated by external quality control. We therefore devised an isocratic reversed-phase HPLC method with ultraviolet detection and optimised this to quantify mirtazapine, reboxetine, moclobemide, venlafaxine, O-desmethylvenlafaxine, paroxetine, fluvoxamine, fluoxetine, norfluoxetine, sertraline, citalopram, amitriptyline, nortriptyline, imipramine, desipramine, doxepin, nordoxepin, clomipramine, norclomipramine, trimipramine, mianserine, maprotiline, normaprotiline, amisulpride, clozapine, norclozapine, quetiapine, risperidone and 9-OH-risperidone in human serum. After solid-phase extraction of the drugs and metabolites, the chromatographic separation was achieved on a Nucleosil 100-Protect 1 column with acetonitrile-potassium dihydrogenphosphate buffer as mobile phase. The method was validated for therapeutic and toxic serum ranges. A linear relationship (r>0.998) was obtained between the concentration and the detector signal. Recoveries were between 75 and 99% for the drugs and metabolites. The accuracy of the quality control samples, expressed as percent recovery, ranged from 91 to 118%; intra- and inter-assay-relative standard deviations were 0.9-10.2% and 0.9-9.7%, respectively. Additional external quality control is carried out since 3 years. This method is applicable to rapidly and effectively analyze serum or plasma samples for therapeutic drug monitoring of about 30 antidepressants and atypical antipsychotics.     

Crystal structure of the BEACH domain reveals an unusual fold and extensive association with a novel PH domain

The BEACH domain is highly conserved in a large family of eukaryotic proteins, and is crucial for their functions in vesicle trafficking, membrane dynamics and receptor signaling. However, it does not share any sequence homology with other proteins. Here we report the crystal structure at 2.9 A resolution of the BEACH domain of human neurobeachin. It shows that the BEACH domain has a new and unusual polypeptide backbone fold, as the peptide segments in its core do not assume regular secondary structures. Unexpectedly, the structure also reveals that the BEACH domain is in extensive association with a novel, weakly conserved pleckstrin-homology (PH) domain. Consistent with the structural analysis, biochemical studies show that the PH and BEACH domains have strong interactions, suggesting they may function as a single unit. Functional studies in intact cells demonstrate the requirement of both the PH and the BEACH domains for activity. A prominent groove at the interface between the two domains may be used to recruit their binding partners.     

Do allopatric male Calopteryx virgo damselflies learn species recognition?

There is a growing amount of empirical evidence that premating reproductive isolation of two closely related species can be reinforced by natural selection arising from avoidance of maladaptive hybridization. However, as an alternative for this popular reinforcement theory, it has been suggested that learning to prefer conspecifics or to discriminate heterospecifics could cause a similar pattern of reinforced premating isolation, but this possibility is much less studied. Here, we report results of a field experiment in which we examined (i) whether allopatric Calopteryx virgo damselfly males that have not encountered heterospecific females of the congener C. splendens initially show discrimination, and (ii) whether C. virgo males learn to discriminate heterospecifics or learn to associate with conspecifics during repeated experimental presentation of females. Our experiment revealed that there was a statistically nonsignificant tendency for C. virgo males to show initial discrimination against heterospecific females but because we did not use sexually naïve individuals in our experiment, we were not able to separate the effect of innate or associative learning. More importantly, however, our study revealed that species discrimination might be further strengthened by learning, especially so that C. virgo males increase their association with conspecific females during repeated presentation trials. The role of learning to discriminate C. splendens females was less clear. We conclude that learning might play a role in species recognition also when individuals are not naïve but have already encountered potential conspecific mates.     

Enhanced casein kinase II activity in human tumour cell cultures

Casein kinase II (CKII) activity is enhanced as much as 2–3 fold in established and 4–5-fold in transformed human cell lines when compared to that of fibroblasts and primary human tumour cell cultures where CKII activity never exceeded a basic level. The high activity of CKII in transformed cells and in established cell lines was reduced to about the same basic level after treatment with heparin, a highly specific inhibitor of CKII activity. The activity of the cAMP-dependent protein kinase was virtually the same in fibroblasts and various human tumour cell lines investigated.     

Modeling denitrification in aquatic sediments

Sediment denitrification is a major pathway of fixed nitrogen loss from aquatic systems. Due to technical difficulties in measuring this process and its spatial and temporal variability, estimates of local, regional and global denitrification have to rely on a combination of measurements and models. Here we review approaches to describing denitrification in aquatic sediments, ranging from mechanistic diagenetic models to empirical parameterizations of nitrogen fluxes across the sediment-water interface. We also present a compilation of denitrification measurements and ancillary data for different aquatic systems, ranging from freshwater to marine. Based on this data compilation we reevaluate published parameterizations of denitrification. We recommend that future models of denitrification use (1) a combination of mechanistic diagenetic models and measurements where bottom-waters are temporally hypoxic or anoxic, and (2) the much simpler correlations between denitrification and sediment oxygen consumption for oxic bottom waters. For our data set, inclusion of bottom water oxygen and nitrate concentrations in a multivariate regression did not improve the statistical fit.     

Systems biology towards life in silico: mathematics of the control of living cells

Systems Biology is the science that aims to understand how biological function absent from macromolecules in isolation, arises when they are components of their system. Dedicated to the memory of Reinhart Heinrich, this paper discusses the origin and evolution of the new part of systems biology that relates to metabolic and signal-transduction pathways and extends mathematical biology so as to address postgenomic experimental reality. Various approaches to modeling the dynamics generated by metabolic and signal-transduction pathways are compared. The silicon cell approach aims to describe the intracellular network of interest precisely, by numerically integrating the precise rate equations that characterize the ways macromolecules’ interact with each other. The non-equilibrium thermodynamic or ‘lin–log’ approach approximates the enzyme rate equations in terms of linear functions of the logarithms of the concentrations. Biochemical Systems Analysis approximates in terms of power laws. Importantly all these approaches link system behavior to molecular interaction properties. The latter two do this less precisely but enable analytical solutions. By limiting the questions asked, to optimal flux patterns, or to control of fluxes and concentrations around the (patho)physiological state, Flux Balance Analysis and Metabolic/Hierarchical Control Analysis again enable analytical solutions. Both the silicon cell approach and Metabolic/Hierarchical Control Analysis are able to highlight where and how system function derives from molecular interactions. The latter approach has also discovered a set of fundamental principles underlying the control of biological systems. The new law that relates concentration control to control by time is illustrated for an important signal transduction pathway, i.e. nuclear hormone receptor signaling such as relevant to bone formation. It is envisaged that there is much more Mathematical Biology to be discovered in the area between molecules and Life.