Influence of wood ash pre-treatment on leaching behaviour, liming and fertilising potential.

In Denmark, increasing amounts of woody biomass are being used for the production of renewable energy, resulting in more wood ashes being generated. While these materials have been mainly landfilled, wood ashes may also be utilised for fertilizing and liming purposes on top of soils. Pre-treatments involving hardening or granulation may be carried out prior to soil application. In this study, two Danish wood ash samples were hardened and/or granulated. Lab-hardening induced rapid changes in the shape of the acid neutralisation capacity curve of the ashes. Up-flow column tests, assuming local equilibrium conditions, were employed to investigate the leaching from pre-treated ashes. Granules and loose ashes demonstrated similar leaching behaviours, indicating that similar geochemical processes were governing their leaching. In comparison with untreated fresh ashes, the hardened ashes demonstrated reduced leaching of Ca, Ba, Pb and Zn with concentration levels generally below or close to the analytical limits of quantification; to the contrary, the leaching of As, P, Sb, Si, V and Mg was enhanced in the hardened ashes. The release of alkalinity was reduced by hardening. In general, all granules were barely breakable by finger-pinching and they could withstand one month of continuous leaching, preserving their overall shape. The solubility of phosphorous in neutral ammonium citrate indicated that about 30-51% of the total P content in the ash samples was released, suggesting that the ashes could be potentially valuable as P-fertiliser if applied onto soil.

Genetic redundancy strengthens the circadian clock leading to a narrow entrainment range.

Circadian clocks are internal timekeepers present in almost all organisms. Driven by a genetic network of highly conserved structure, they generate self-sustained oscillations that entrain to periodic external signals such as the 24 h light-dark cycle. Vertebrates possess multiple, functionally overlapping homologues of the core clock genes. Furthermore, vertebrate clocks entrain to a range of periods three times as narrow as that of other organisms. We asked whether genetic redundancies play a role in governing entrainment properties and analysed locomotor activity rhythms of genetically modified mice lacking one set of clock homologues. Exposing them to non-24 h light-dark cycles, we found that the mutant mice have a wider entrainment range than the wild types. Spectral analysis furthermore revealed nonlinear phenomena of periodically forced self-sustained oscillators for which the entrainment range relates inversely to oscillator amplitude. Using the forced oscillator model to explain the observed differences in entrainment range between mutant and wild-type mice, we sought to quantify the overall oscillator amplitude of their clocks from the activity rhythms and found that mutant mice have weaker circadian clocks than wild types. Our results suggest that genetic redundancy strengthens the circadian clock leading to a narrow entrainment range in vertebrates.

Mathematical modeling in chronobiology.

Circadian clocks are autonomous oscillators entrained by external Zeitgebers such as light-dark and temperature cycles. On the cellular level, rhythms are generated by negative transcriptional feedback loops. In mammals, the suprachiasmatic nucleus (SCN) in the anterior part of the hypothalamus plays the role of the central circadian pacemaker. Coupling between individual neurons in the SCN leads to precise self-sustained oscillations even in the absence of external signals. These neuronal rhythms orchestrate the phasing of circadian oscillations in peripheral organs. Altogether, the mammalian circadian system can be regarded as a network of coupled oscillators. In order to understand the dynamic complexity of these rhythms, mathematical models successfully complement experimental investigations. Here we discuss basic ideas of modeling on three different levels (1) rhythm generation in single cells by delayed negative feedbacks, (2) synchronization of cells via external stimuli or cell-cell coupling, and (3) optimization of chronotherapy.

Circadian transcription in liver.

Circadian rhythms regulate a wide range of cellular, physiological, metabolic and behavioral activities in mammals. The complexity of tissue- and day-time specific regulation of thousands of clock controlled genes (CCGs) suggests that many transcriptional regulators are involved. Our bioinformatic analysis is based on two published DNA-array studies from mouse liver. We search overrepresented transcription factor binding sites in promoter regions of CCGs using GC-matched controls. Analyzing a large set of CCG promoters, we find known motifs such as E-boxes, D-boxes and cAMP responsive elements. In addition, we find overrepresented GC-rich motifs (Sp1, ETF, Nrf1), AT-rich motifs (TBP, Fox04, MEF-2), Y-box motifs (NF-Y, C/EBP) and cell cycle regulators (E2F, Elk-1). In a subset of system-driven genes, we find overrepresented motifs of the serum response factor SRF and the estrogen receptor ER. The analysis of published ChIP data reveals that some of our predicted regulators (C/EBP, E2F, HNF-1, Myc, MEF-2) target relatively many clock controlled genes. Our analysis of CCG promoters contributes to an understanding of the complex transcriptional regulation of circadian rhythms in liver.

SysBioMed report: advancing systems biology for medical applications.

The following report selects and summarises some of the conclusions and recommendations generated throughout a series of workshops and discussions that have lead to the publication of the Science Policy Briefing (SPB) Nr. 35, published by the European Science Foundation. (Large parts of the present text are directly based on the ESF SPB. Detailed recommendations with regard to specific application areas are not given here but can be found in the SPB. Issues related to mathematical modelling, including training and the need for an infrastructure supporting modelling are discussed in greater detail in the present text.)The numerous reports and publications about the advances within the rapidly growing field of systems biology have led to a plethora of alternative definitions for key concepts. Here, with 'mathematical modelling' the authors refer to the modelling and simulation of subcellular, cellular and macro-scale phenomena, using primarily methods from dynamical systems theory. The aim of such models is encoding and testing hypotheses about mechanisms underlying the functioning of cells. Typical examples are models for molecular networks, where the behaviour of cells is expressed in terms of quantitative changes in the levels of transcripts and gene products. Bioinformatics provides essential complementary tools, including procedures for pattern recognition, machine learning, statistical modelling (testing for differences, searching for associations and correlations) and secondary data extracted from databases.Dynamical systems theory is the natural language to investigate complex biological systems demonstrating nonlinear spatio-temporal behaviour. However, the generation of experimental data suitable to parameterise, calibrate and validate such models is often time consuming and expensive or not even possible with the technology available today. In our report, we use the term 'computational model' when mathematical models are complemented with information generated from bioinformatics resources. Hence, 'the model' is, in reality, an integrated collection of data and models from various (possibly heterogeneous) sources. The present report focuses on a selection of topics, which were identified as appropriate case studies for medical systems biology, and adopts a particular perspective which the authors consider important. We strongly believe that mathematical modelling represents a natural language with which to integrate data at various levels and, in doing so, to provide insight into complex diseases: 1. Modelling necessitates the statement of explicit hypotheses, a process which often enhances comprehension of the biological system and can uncover critical points where understanding is lacking. 2. Simulations can reveal hidden patterns and/or counter-intuitive mechanisms in complex systems. 3. Theoretical thinking and mathematical modelling constitute powerful tools to integrate and make sense of the biological and clinical information being generated and, more importantly, to generate new hypotheses that can then be tested in the laboratory.Medical Systems Biology projects carried out recently across Europe have revealed a need for action: 4. While the need for mathematical modelling and interdisciplinary collaborations is becoming widely recognised in the biological sciences, with substantial implications for the training and research funding mechanisms within this area, the medical sciences have yet to follow this lead. 5. To achieve major breakthroughs in Medical Systems Biology, existing academic funding schemes for large-scale projects need to be reconsidered. 6. The hesitant stance of the pharmaceutical industry towards major investment in systems biology research has to be addressed. 7. Leading medical journals should be encouraged to promote mathematical modelling.

Phase response curves elucidating the dynamics of coupled oscillators.

Phase response curves (PRCs) are widely used in circadian clocks, neuroscience, and heart physiology. They quantify the response of an oscillator to pulse-like perturbations. Phase response curves provide valuable information on the properties of oscillators and their synchronization. This chapter discusses biological self-sustained oscillators (circadian clock, physiological rhythms, etc.) in the context of nonlinear dynamics theory. Coupled oscillators can synchronize with different frequency ratios, can generate toroidal dynamics (superposition of independent frequencies), and may lead to deterministic chaos. These nonlinear phenomena can be analyzed with the aid of a phase transition curve, which is intimately related to the phase response curve. For illustration purposes, this chapter discusses a model of circadian oscillations based on a delayed negative feedback. In a second part, the chapter provides a step-by-step recipe to measure phase response curves. It discusses specifications of this recipe for circadian rhythms, heart rhythms, neuronal spikes, central pattern generators, and insect communication. Finally, it stresses the predictive power of measured phase response curves. PRCs can be used to quantify the coupling strength of oscillations, to classify oscillator types, and to predict the complex dynamics of periodically driven oscillations.

Oncogenic HRAS suppresses clusterin expression through promoter hypermethylation.

Silencing of gene expression by methylation of CpG islands in regulatory elements is frequently observed in cancer. However, an influence of the most common oncogenic signalling pathways onto DNA methylation has not yet been investigated thoroughly. To address this issue, we identified genes suppressed in HRAS-transformed rat fibroblasts but upregulated after treatment with the demethylating agent 5-Aza-2-deoxycytidine and with the MEK1,2 inhibitor U0126. Analysis of gene expression by microarray and Northern blot analysis revealed the MEK/ERK target genes clusterin, matrix metalloproteinase 2 (Mmp2), peptidylpropyl isomerase C-associated protein, syndecan 4, Timp2 and Thbs1 to be repressed in the HRAS-transformed FE-8 cells in a MEK/ERK- and methylation-dependent manner. Hypermethylation of putative regulatory elements in HRAS-transformed cells as compared to immortalized fibroblasts was detected within a CpG island 14.5 kb upstream of clusterin, within the clusterin promoter and within a CpG island of the Mmp2 promoter by bisulphite sequencing. Furthermore, hypermethylation of the clusterin promoter was observed 10 days after induction of HRAS in immortalized rat fibroblasts and a clear correlation between reduced clusterin expression and hypermethlyation could also be observed in distinct rat tissues. These results suggest that silencing of individual genes by DNA methylation is controlled by oncogenic signalling pathways, yet the mechanisms responsible for initial target gene suppression are variable.

Is there a bias in proteome research?

Advances in technology have enabled us to take a fresh look at data acquired by traditional single experiments and to compare them with genomewide data. The differences can be tremendous, as we show here, in the field of proteomics. We have compared data sets of protein-protein interactions in Saccharomyces cerevisiae that were detected by an identical underlying technical method, the yeast two-hybrid system. We found that the individually identified protein-protein interactions are considerably different from those identified by two genomewide scans. Interacting proteins in the pooled database from single publications are much more closely related to each other with respect to transcription profiles when compared to genomewide data. This difference may have been introduced by two factors: by a selection process in individual publications and by false positives in the whole-genome scans. If we assume that the differences are a result of false positives in the whole-genome data, the scans would contain 47%, 44%, and 91% of false positives for the UETZ, ITO-core, and ITO-full data, respectively. If, however, the true fraction of false positives is considerably lower than estimated here, the data from hypothesis-driven experiments must have been subjected to a serious selection process.

Combining frequency and positional information to predict transcription factor binding sites.

MOTIVATION: Even though a number of genome projects have been finished on the sequence level, still only a small proportion of DNA regulatory elements have been identified. Growing amounts of gene expression data provide the possibility of finding coregulated genes by clustering methods. By analysis of the promoter regions of those genes, rather weak signals of transcription factor binding sites may be detected. RESULTS: We introduce the new algorithm ITB, an Integrated Tool for Box finding, which combines frequency and positional information to predict transcription factor binding sites in upstream regions of coregulated genes. Motifs are extracted by exhaustive analysis of regular expression-like patterns and by estimating probabilities of positional clusters of motifs. ITB detects consensus sequences of experimentally verified transcription factor binding sites of the yeast Saccharomyces cerevisiae. Moreover, a number of new binding site candidates with significant scores are predicted. Besides applying ITB on yeast upstream regions, the program is run on human promoter sequences. AVAILABILITY: ITB is available upon request.

Statistical analysis of the DNA sequence of human chromosome 22.

We study statistical patterns in the DNA sequence of human chromosome 22, the first completely sequenced human chromosome. We find that (i). the 33.4 x 10(6) nucleotide long human chromosome exhibits long-range power-law correlations over more than four orders of magnitude, (ii). the entropies H(n) of the frequency distribution of oligonucleotides of length n (n-mers) grow sublinearly with increasing n, indicating the presence of higher-order correlations for all of the studied lengths 1

The harmonic-to-noise ratio applied to dog barks.

Dog barks are typically a mixture of regular components and irregular (noisy) components. The regular part of the signal is given by a series of harmonics and is most probably due to regular vibrations of the vocal folds, whereas noise refers to any nonharmonic (irregular) energy in the spectrum of the bark signal. The noise components might be due to chaotic vibrations of the vocal-fold tissue or due to turbulence of the air. The ratio of harmonic to nonharmonic energy in dog barks is quantified by applying the harmonics-to-noise ratio (HNR). Barks of a single dog breed were recorded in the same behavioral context. Two groups of dogs were considered: a group of ten healthy dogs (the normal sample), and a group of ten unhealthy dogs, i.e., dogs treated in a veterinary clinic (the clinic sample). Although the unhealthy dogs had no voice disease, differences in emotion or pain or impacts of surgery might have influenced their barks. The barks of the dogs were recorded for a period of 6 months. The HNR computation is based on the Fourier spectrum of a 50-ms section from the middle of the bark. A 10-point moving average curve of the spectrum on a logarithmic scale is considered as estimator of the noise level in the bark, and the maximum difference of the original spectrum and the moving average is defined as the HNR measure. It is shown that a reasonable ranking of the voices is achievable based on the measurement of the HNR. The HNR-based classification is found to be consistent with perceptual evaluation of the barks. In addition, a multiparametric approach confirms the classification based on the HNR. Hence, it may be concluded that the HNR might be useful as a novel parameter in bioacoustics for quantifying the noise within a signal.

Spatio-temporal analysis of irregular vocal fold oscillations: biphonation due to desynchronization of spatial modes.

This report is on direct observation and modal analysis of irregular spatio-temporal vibration patterns of vocal fold pathologies in vivo. The observed oscillation patterns are described quantitatively with multiline kymograms, spectral analysis, and spatio-temporal plots. The complex spatio-temporal vibration patterns are decomposed by empirical orthogonal functions into independent vibratory modes. It is shown quantitatively that biphonation can be induced either by left-right asymmetry or by desynchronized anterior-posterior vibratory modes, and the term "AP (anterior-posterior) biphonation" is introduced. The presented phonation examples show that for normal phonation the first two modes sufficiently explain the glottal dynamics. The spatio-temporal oscillation pattern associated with biphonation due to left-right asymmetry can be explained by the first three modes. Higher-order modes are required to describe the pattern for biphonation induced by anterior-posterior vibrations. Spatial irregularity is quantified by an entropy measure, which is significantly higher for irregular phonation than for normal phonation. Two asymmetry measures are introduced: the left-right asymmetry and the anterior-posterior asymmetry, as the ratios of the fundamental frequencies of left and right vocal fold and of anterior-posterior modes, respectively. These quantities clearly differentiate between left-right biphonation and anterior-posterior biphonation. This paper proposes methods to analyze quantitatively irregular vocal fold contour patterns in vivo and complements previous findings of desynchronization of vibration modes in computer modes and in in vitro experiments.

Optimization of coding potentials using positional dependence of nucleotide frequencies.

We study the coding potential of human DNA sequences, using the positional asymmetry function (D(p)) and the positional information function (I(q)). Both D(p)and I(q)are based on the positional dependence of single nucleotide frequencies. We investigate the accuracy of D(p)and I(q)in distinguishing coding and non-coding DNA as a function of the parameters p and q, respectively, and explore at which parameters p(opt)and q(opt)both D(p)and I(q)distinguish coding and non-coding DNA most accurately. We compare our findings with classically used parameter values and find that optimized coding potentials yield comparable accuracies as classical frame-independent coding potentials trained on prior data. We find that p(opt)and q(opt)vary only slightly with the sequence length.

Species independence of mutual information in coding and noncoding DNA.

We explore if there exist universal statistical patterns that are different in coding and noncoding DNA and can be found in all living organisms, regardless of their phylogenetic origin. We find that (i) the mutual information function [symbol: see text] has a significantly different functional form in coding and noncoding DNA. We further find that (ii) the probability distributions of the average mutual information [symbol: see text] are significantly different in coding and noncoding DNA, while (iii) they are almost the same for organisms of all taxonomic classes. Surprisingly, we find that [symbol: see text] is capable of predicting coding regions as accurately as organism-specific coding measures.

Are noncoding sequences of Rickettsia prowazekii remnants of "neutralized" genes?

It has been hypothesized that a large fraction of 24% noncoding DNA in R. prowazekii consists of degraded genes. This hypothesis has been based on the relatively high G+C content of noncoding DNA. However, a comparison with other genomes also having a low overall G+C content shows that this argument would also apply to other bacteria. To test this hypothesis, we study the coding potential in sets of genes, pseudogenes, and intergenic regions. We find that the correlation function and the chi(2)-measure are clearly indicative of the coding function of genes and pseudogenes. However, both coding potentials make almost no indication of a preexisting reading frame in the remaining 23% of noncoding DNA. We simulate the degradation of genes due to single-nucleotide substitutions and insertions/deletions and quantify the number of mutations required to remove indications of the reading frame. We discuss a reduced selection pressure as another possible origin of this comparatively large fraction of noncoding sequences.

Nonlinear phenomena in the natural howling of a dog-wolf mix.

It was reported to the first author that a female dog-wolf mix showed anomalously rough-sounding vocalization. Spectral analysis of recordings of the vocalization revealed frequency occurrences of subharmonics, biphonation (two independent pitches) and chaos. Since these nonlinear phenomena are currently widely discussed as integral to mammalian vocalization [Wilden et al., Bioacoustics 9, 171-196 (1988)] or as indicators of vocal pathologies [Herzel et al., J. Speech Hearing Res. 37, 1008-1019 (1994); Riede et al., Z. Sgtkde 62 Suppl: 198-203 (1997)], we sought to understand the production mechanism of the observed vocal instabilities. First the frequency of nonlinear phenomena in the calls was determined for the female and four additional individuals. It turned out that these phenomena appear, but much less frequently in the repertoire of the four other animals. The larynges of the female and two other individuals were dissected post mortem. There was no apparent asymmetry of the vocal folds but a slight asymmetry of the arytenoid cartilages. The most pronounced difference, however, was an upward extension of both vocal folds of the female. This feature is reminiscent of "vocal lips" (syn. "vocal membranes") in some primates and bats. Spectral analysis of the female's voice showed clear similarities with an intensively studied voice of a human who produces biphonation intentionally. Finally, the possible communicative relevance of nonlinear phenomena is discussed.

Information content of protein sequences.

The complexity of large sets of non-redundant protein sequences is measured. This is done by estimating the Shannon entropy as well as applying compression algorithms to estimate the algorithmic complexity. The estimators are also applied to randomly generated surrogates of the protein data. Our results show that proteins are fairly close to random sequences. The entropy reduction due to correlations is only about 1%. However, precise estimations of the entropy of the source are not possible due to finite sample effects. Compression algorithms also indicate that the redundancy is in the order of 1%. These results confirm the idea that protein sequences can be regarded as slightly edited random strings. We discuss secondary structure and low-complexity regions as causes of the redundancy observed. The findings are related to numerical and biochemical experiments with random polypeptides.

Average mutual information of coding and noncoding DNA.

One basic problem in the analysis of DNA sequences is the recognition of protein-coding genes. Computer algorithms to facilitate gene identification have become important as genome sequencing projects have turned from mapping to large-scale sequencing, resulting in an exponentially growing number of sequenced nucleotides that await their annotation. Many statistical patterns have been discovered that are different in coding and noncoding DNA, but most of them vary from species to species, and hence require prior training on organism-specific data sets. Here, we investigate if there exist species-independent statistical patterns that are different in coding and noncoding DNA. We introduce an information-theoretic quantity, the average mutual information (AMI), and we find that the probability distribution functions of the AMI are significantly different in coding and noncoding DNA, while they are almost identical for different species. This finding suggests that the AMI might be useful for the recognition of protein-coding regions in genomes for which training sets do not exist.

Normalization strategies for cDNA microarrays.

Multiple Arabidopsis thaliana clones from an experimental series of cDNA microarrays are evaluated in order to identify essential sources of noise in the spotting and hybridization process. Theoretical and experimental strategies for an improved quantitative evaluation of cDNA microarrays are proposed and tested on a series of differently diluted control clones. Several sources of noise are identified from the data. Systematic and stochastic fluctuations in the spotting process are reduced by control spots and statistical techniques. The reliability of slide to slide comparison is critically assessed within the statistical framework of pattern matching and classification.