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MotivationThe universal expressibility assumption of Deep Neural Networks (DNNs) is the key motivation behind recent worksin the systems biology community to employDNNs to solve important problems in functional genomics and moleculargenetics. Typically, such investigations have taken a ‘black box’ approach in which the internal structure of themodel used is set purely by machine learning considerations with little consideration of representing the internalstructure of the biological system by the mathematical structure of the DNN. DNNs have not yet been applied to thedetailed modeling of transcriptional control in which mRNA production is controlled by the binding of specific transcriptionfactors to DNA, in part because such models are in part formulated in terms of specific chemical equationsthat appear different in form from those used in neural networks.ResultsIn this paper, we give an example of a DNN whichcan model the detailed control of transcription in a precise and predictive manner. Its internal structure is fully interpretableand is faithful to underlying chemistry of transcription factor binding to DNA. We derive our DNN from asystems biology model that was not previously recognized as having a DNN structure. Although we apply our DNNto data from the early embryo of the fruit fly Drosophila, this system serves as a test bed for analysis of much larger datasets obtained by systems biology studies on a genomic scale. .Availability and implementationThe implementation and data for the models used in this paper are in a zip file in the supplementary material.Supplementary informationSupplementary data are available at Bioinformatics online.

Redox biology has become a major issue in numerous areas of physiology. Reactive oxygen species (ROS) have a broad range of roles from signal transduction to growth control and cell death. To understand the nature of these roles, accurate measurement of the reactive compounds is required. An increasing number of tools for ROS detection is available; however, the specificity and sensitivity of these tools are often insufficient. Furthermore, their specificity has been rarely evaluated in complex physiological conditions. Many ROS probes are sensitive to environmental conditions in particular pH, which may interfere with ROS detection and cause misleading results. Accurate detection of ROS in physiology and pathophysiology faces additional challenges concerning the precise localization of the ROS and the timing of their production and disappearance. Certain ROS are membrane permeable, and certain ROS probes move across cells and organelles. Targetable ROS probes such as fluorescent protein-based biosensors are required for accurate localization. Here we analyze these challenges in more detail, provide indications on the strength and weakness of current tools for ROS detection, and point out developments that will provide improved ROS detection methods in the future. There is no universal method that fits all situations in physiology and cell biology. A detailed knowledge of the ROS probes is required to choose the appropriate method for a given biological problem. The knowledge of the shortcomings of these probes should also guide the development of new sensors.

During mRNA translation, the ribosomal density profile along the coding region of the mRNA molecule affects various fundamental intracellular phenomena. Thus, steering this profile from a given to a desired density is an important biological problem. This paper studies this problem using a dynamical model for mRNA translation, called the ribosome flow model (RFM), in which one views the transition rates along the mRNA molecule as controls.

Motivation: Pattern discovery algorithms are widely used for the analysis of DNA and protein sequences. Most algorithms have been designed to find overrepresented motifs in sparse datasets of long sequences, and ignore most positional information. We introduce an algorithm optimized to exploit spatial information in sparse-but-populous datasets. Results: Our algorithm Tree-based Weighted-Position Pattern Discovery and Classification (T-WPPDC) supports both unsupervised pattern discovery and supervised sequence classification. It identifies positionally enriched patterns using the Kullback–Leibler distance between foreground and background sequences at each position. This spatial information is used to discover positionally important patterns. T-WPPDC then uses a scoring function to discriminate different biological classes. We validated T-WPPDC on an important biological problem: prediction of single nucleotide polymorphisms (SNPs) from flanking sequence. We evaluated 672 separate experiments on 120 datasets derived from multiple species. T-WPPDC outperformed other pattern discovery methods and was comparable to the supervised machine learning algorithms. The algorithm is computationally efficient and largely insensitive to dataset size. It allows arbitrary parameterization and is embarrassingly parallelizable. Conclusions: T-WPPDC is a minimally parameterized algorithm for both pattern discovery and sequence classification that directly incorporates positional information. We use it to confirm the predictability of SNPs from flanking sequence, and show that positional information is a key to this biological problem. Contacts: ruiyan@cs.toronto.edu; paul.boutros@oicr.on.ca; juris@ai.toronto.edu Availability: The algorithm, code and data are available at: http://www.cs.utoronto.ca/~juris/data/TWPPDC Supplementary information: Supplementary data are available at Bioinformatics online.

A novel class of nanobiosensor was developed by integrating a 27-nucleotideAluIfragment of swine cytochrome b (cytb) gene to a 3-nm diameter citrate-tannate coated gold nanoparticle (GNP). The biosensor detected 0.5% and 1% pork in raw and 2.5-h autoclaved pork-beef binary admixtures in a single step without any separation or washing. The hybridization kinetics of the hybrid sensor was studied with synthetic andAluIdigested real pork targets from moderate to extreme target concentrations and a sigmoidal relationship was found. Using the kinetic curve, a convenient method for quantifying and counting target DNA copy number was developed. The accuracy of the method was over 90% and 80% for raw and autoclaved pork-beef binary admixtures in the range of 5–100% pork adulteration. The biosensor probe identified a target DNA sequence that was several-folds shorter than a typical PCR-template. This offered the detection and quantitation of potential targets in highly processed or degraded samples where PCR amplification was not possible due to template crisis. The assay was a viable alternative approach of qPCR for detecting, quantifying and counting copy number of shorter size DNA sequences to address a wide ranging biological problem in food industry, diagnostic laboratories and forensic medicine.

The Vogel-Fulcher-Tammann equation, which is widely applied in condensed matter physics, is for the first time applied to analysis of the hydrogen exchange rates of DNA as a function of temperature. The VFT equation, which for hydrogen exchange should read k(ex) = A exp[-(E/R)/(T-T-0)], contains a constant temperature To. When we analyzed the hydrogen exchange rates for the thrombin binding DNA aptamer d(GGTTGGTGTGGTTGG) as a function of temperature using the VFT equation, we found that To happens to be the melting temperature of the DNA. A quantitative relationship is established between the VFT equation and the Arrhenius equation. Under suitable conditions the VFT equation can be reduced to the Arthenius equation. (c) 2006 Elsevier B.V. All rights reserved.

Phosphatidylinositol is a metabolic precursor of phosphoinositides and soluble inositol phosphates. Both sets of molecules represent versatile intracellular chemical signals in eukaryotes. While much effort has been invested in understanding the enzymes that produce and consume these molecules, central aspects for how phosphoinositide production is controlled and functionally partitioned remain unresolved and largely unappreciated. It is in this regard that phosphatidylinositol (PtdIns) transfer proteins (PITPs) are emerging as central regulators of the functional channeling of phosphoinositide pools produced on demand for specific signaling purposes. The physiological significance of these proteins is amply demonstrated by the consequences that accompany deficits in individual PITPs. Although the biological problem is fascinating, and of direct relevance to disease, PITPs remain largely uncharacterized. Herein, we discuss our perspectives regarding what is known about how PITPs work as molecules, and highlight progress in our understanding of how PITPs are integrated into cellular physiology. This article is part of a Special Issue entitled Phosphoinositides.

Aspen that bear a certain type of black gall have a lower incidence of heartwood rot (caused by the fungus Phellinustremulae) than do nearby non-gall trees. Efforts to determine the chemical nature of this black gall effect are described. The metabolites of some fungi associated with the black gall (Phomaetheridgei, Stachybotryscylindrospora), and of the rotting fungus Phellinustremulae, are described. Extracts of the black gall tissue have a very high concentration of benzoic acid and it is suggested that the benzoic acid may play a role in the protection of the galled trees. Keywords: fungal metabolites, aspen, benzoic acid, salicylic acid, black galls on aspen, Phellinustremulae.

Coarse-graining is a powerful approach for modeling biomolecules that, over the last few decades, has been extensively applied to proteins. Coarse-grain models offer access to large systems and to slow processes without becoming computationally unmanageable. In addition, they are very versatile, enabling both the protein representation and the energy function to be adapted to the biological problem in hand. This review concentrates on modeling soluble proteins and their assemblies. It presents an overview of the coarse-grain representations, of the associated interaction potentials, and of the optimization procedures used to define them. It then shows how coarse-grain models have been used to understand processes involving proteins, from their initial folding to their functional properties, their binary interactions, and the assembly of large complexes.

Background We introduce a method to analyze the states of regulatory Boolean models that identifies important network states and their biological influence on the global network dynamics. It consists in (1) finding the states of the network that are most frequently visited and (2) the identification of variable and frozen nodes of the network. The method, along with a simulation that includes random features, is applied to the study of stomata closure by abscisic acid (ABA) in A. thaliana proposed by Albert and coworkers. Results We find that for the case of study, that the dynamics of wild and mutant networks have just two states that are highly visited in their space of states and about a third of all nodes of the wild network are variable while the rest remain frozen in True or False states. This high number of frozen elements explains the low cardinality of the space of states of the wild network. Similar results are observed in the mutant networks. The application of the method allowed us to explain how wild and mutants behave dynamically in the SS and determined an essential feature of the activation of the closure node (representing stomata closure), i.e. its synchronization with the AnionEm node (representing anion efflux at the plasma membrane). The dynamics of this synchronization explains the efficiency reached by the wild and each of the mutant networks. Conclusions For the biological problem analyzed, our method allows determining how wild and mutant networks differ ‘phenotypically’. It shows that the different efficiencies of stomata closure reached among the simulated wild and mutant networks follow from a dynamical behavior of two nodes that are always synchronized. Additionally, we predict that the involvement of the anion efflux at the plasma membrane is crucial for the plant response to ABA. Availability The algorithm used in the simulations is available upon request.

Before reporting the preliminary results obtained by our group, we first review the main problems to be solved in the preservation of organs at very low temperature, before being transplanted. This cryopreservation is being presently explored in order to increase the preservation time of transplants and to contribute to a better control of the donor recipient compatibility. We recall that, for the isolated cells to be preserved at nitrogen liquid temperatures, as now successfully performed at industrial scale, it is necessary to immerse the cells in a solution containing more or less toxical additives (so-called cryoprotectants). Furthermore cooling and warming rates must be specific of each type of cells. We then show that cryopreservation could be extrapolated to whole organs by means of vitrification, the only way to avoid any ice crystallization. This vitrification will be the result of two directions of research, the one on the elaboration of cryoprotective solutions, the least toxic possible, the other on the obtention of high enough and homogeneous cooling and warming rates. After having briefly summarized the state of research on the heart and kidneys of small mammals, we present the first results that we have obtained on perfusion at 4 o C and the auto-transplantation of rabbit kidneys, on the toxicity of a new cryoprotectant, 2,3-butanediol, on the heart rate, and on the cooling of experimental models of organs

Aspen that bear a certain type of black gall have a lower incidence of heartwood rot (caused by the fungus Phellinustremulae) than do nearby non-gall trees. Efforts to determine the chemical nature of this black gall effect are described. The metabolites of some fungi associated with the black gall (Phomaetheridgei, Stachybotryscylindrospora), and of the rotting fungus Phellinustremulae, are described. Extracts of the black gall tissue have a very high concentration of benzoic acid and it is suggested that the benzoic acid may play a role in the protection of the galled trees. Keywords: fungal metabolites, aspen, benzoic acid, salicylic acid, black galls on aspen, Phellinustremulae.

Formation of phosphate esters by kinases has long been recognized as an important process in biochemistry, but the reverse reaction, hydrolysis of phosphate esters by phosphatases, has attracted less attention. Recent work suggests that phosphatases are as important as kinases in regulatory processes, and that they constitute a diverse group of enzymes that utilize a variety of chemical means to accelerate phosphate ester hydrolysis.

It was inevitable that as soon as mass spectrometrists were able to tell biologists which proteins were in their samples, the next question would be how much of these proteins were present. This has turned out to be a much more challenging question. In this review, we describe the multiple ways that mass spectrometry has attempted to address this issue, both for relative quantitation and for absolute quantitation of proteins. There is no single method that will work for every problem or for every sample. What we present here is a variety of techniques, with guidelines that we hope will assist the researcher in selecting the most appropriate technique for the particular biological problem that needs to be addressed. We need to emphasize that this is a very active area of proteomics research-new quantitative methods are continuously being introduced and some 'pitfalls' of older methods are just being discovered. However, even though there is no perfect technique--and a better technique may be developed tomorrow--valuable information on biomarkers and pathways can be obtained using these currently available methods.

An informal poll of neurobiologists indicates the following widely-held misconceptions about cGMP: (1) we know very little about it; (2) it must not be very different from cAMP; and (3) no new biological principles are likely to emerge from studying it. In fact, despite these prejudices, our understanding of the cGMP second messenger cascade has increased dramatically in the last few years. We now know that it is very different from the cAMP system in almost every particular, and the differences reveal interesting and novel solutions to the biological problem of receptor effector coupling.

Flow injection electrospray mass spectrometry (FIE-MS) metabolite fingerprinting is widely used as a 'first pass' screen for compositional differences, where discrimination between samples can be achieved without any preconceptions. Powerful data analysis algorithms can be used to select and rank FIE-MS fingerprint variables highly explanatory of the biological problem under investigation. We describe how to create a species-specific FIE-MS/MS(n) metabolite database and how to then query the database to predict the identity of highly significant variables within FIE-MS fingerprints. The protocol details how to interpret m/z signals within the explanatory variable list based on a correlation analysis in conjunction with an investigation of mathematical relationships regarding (de)protonated molecular ions, salt adducts, neutral losses and dimeric associations routinely observed in FIE-MS fingerprints. Although designed for use by biologists/analytical chemists, collaboration with data-mining experts is generally advised. The protocol is applicable in any areas of bioscience research involving FIE-MS fingerprinting.

The formation of inorganic materials with complex form is a widespread biological phenomenon (biomineralization). Among the most spectacular examples of biomineralization is the production by diatoms (a group of eukaryotic microalgae) of intricately nanopatterned to micropatterned cell walls made of silica (SiO2). Understanding the molecular mechanisms of diatom silica biomineralization is not only a fundamental biological problem, but also of great interest in materials engineering, as the biological self-assembly of three-dimensional (3D) inorganic nanomaterials has no man-made analog. Recently, insight into the molecular mechanism of diatom silica formation has been obtained by structural and functional analysis of biomolecules that are involved in this process. Furthermore, the rapid development of diatom molecular genetics has provided new tools for investigating the silica forming machinery of diatoms and for manipulating silica biogenesis. This has opened the door for the production, through genetic engineering, of unique 3D nanomaterials with designed structures and functionalities.

A model for the aggregation of molecules with two internal states is studied by kinetic Monte Carlo simulations. Molecules are represented by simple beads, discarding all stereochemical specificity. Monomers are placed in a three-dimensional lattice and diffusion processes are simulated, as well as internal state conversions of the molecules. The two internal states feature a stable (S) not assembly competent configuration, and an unstable assembly competent (A) configuration. Monomers in A state are given a higher energy if isolated, but they can reach the lowest energy level through short-range interactions between each other, so that their aggregation is promoted. Kinetics of cluster formation are examined, as well as the basic mechanisms ruling growth in our system. The simulations show that the aggregation process is preceded by a lag phase, which is followed by a fast growth phase. The duration of the lag phase is determined by the strength of the A-A interaction, whereas the time slope of the growth phase is mainly influenced by the conversion rate between internal states. The whole work has been inspired by the biological problem of amyloid aggregation, whose aggregation curves often present a sigmoidal behavior which is reproduced by the present model.

The fragment molecular orbital (FMO) method has been introduced in detail, with the emphasis on physical ideas constituting the foundation of the method. The recent theoretical development incorporating electron correlation at various levels has been covered. The means to compute the amount of interactions between fragments, including polarization and charge transfer, have been elucidated, with practical applications to a model system and a biological problem. The absolute and relative accuracy of the FMO total energies have been scrupulously established by comparison with ab initio methods. The practical issues of applying the method to real-life problems have been dealt with, including fragmentation, the choice of basis sets and parallelization. It is hoped that this very detailed description enables a general reader to apply the method to practical problems, as well as to extract a physical picture of the interactions therein.

Wilson and Menkes diseases epitomise the fundamental biological problem of the transport and utilisation of copper in the human body — coping with an element which is essential, but toxic. We must have evolved very efficient systems for transporting copper safely to the sites within the body cells where it is needed. The two diseases represent failures of this sophisticated system due to faults in two different genes which encode two of the proteins involved in the copper transport system. In Wilson disease we see toxic consequences of copper accumulation, and in Menkes disease we meet most of the effects that have ever been ascribed to copper deficiency in other species. Recently, the genes have been cloned in Wilson disease [1] and Menkes disease [2]. They are so similar that sequences from the Menkes disease gene were used to isolate Wilson disease cDNA. More detailed analyses must be awaited before complete explanations of pathogenesis can be given.

The aim of this paper is to describe an emerging methodology which appears to offer new capabilities for the measurement of the concentration of oxygen ([O2]) in complex biological systems in vitro and in vivo with the sensitivity and accuracy needed to make these measurements under conditions that are pertinent for physiological and pathological processes. The method uses electron paramagnetic resonance (EPR or, equivalently, ESR); the approach is often termed EPR oximetry. In particular EPR oximetry can make measurements selectively in the intracellular compartment and in tissues in vivo and can detect [O2] as low as 0.1 micromolar. Our use of EPR to measure intracellular [O2] with nitroxides has been described previously (1–2) and therefore this paper will concentrate on the methodology to make measurements in vivo and also, at very low [O2]. We will review the basis of the methodology briefly but will emphasize results in tissues which illustrate the capabilities of this new technique. Because of the newness of this approach the results obtained so far have been aimed at determining and illustrating the potential of this technique, rather than providing detailed information on a specific biological problem. A companion paper illustrates a more detailed application of the new technology, the measurement of [O2] in skeletal muscle (3).

The aim of this project was to try to understand the adaptive mechanisms that organisms develop in order to respond to a sudden transformation in their environment to a salt shock.'' To study this problem we used a fresh water oxygenic photosynthetic cyanobacterium known as Synecoccus 6311. This organism suffers injury after this sudden exposure to high concentrations of sodium chloride equivalent to or even higher than that in sea water. Yet they are able to re-establish their photosynthetic activity which is partially injured and return to virtually normal growth rates. Identification of the temporal sequence of changes involved in adaptation to this stress was the rationale. Indeed this project employed a wide variety of biochemical and biophysical methods, including electron spin resonance techniques and nuclear magnetic resonance to study the bioenergetics and transport mechanisms, growth and energy changes in these organisms and how the structural components of the cells changed in response to adaptation to growth at high salinity. The problem has relevance for higher plants because most of the arable farmland in the work is already under use and that which is not used is usually in salite environments. Hence, understanding basic mechanisms of salt tolerance is amore » fundamental biological problem with great applications for bioproductivity and agriculture. 18 refs.« less

Secondary ion mass spectrometry (SIMS) is a potentially valuable but not fully exploited technique for problems in biological research. It is valuable because of: (1) detection of all elements and isotopes from mass 1, hydrogen; (2) high sensitivity for physiologically important elements, Na, K, Mg, Ca; (3) ion imaging of elements in areas as large as 250 micrometers in diameter with a lateral resolution of 0.5 micrometers; (4) promising efforts at quantitation at levels as low as 0.1 mmol/kg; (5) ability to analyse sequential layers to form a three-dimensional analysis. The problems which complicate its use are primarily variations in ion emission, presence of poly-atomic interferences and tissue preparation. Examples are cited of SIMS analysis of biomineralization, botany, toxicology and physiology, mostly by ion imaging techniques. SIMS has not yet been fully exploited for any single biological problem. In particular, studies using isotope discrimination, quantitative analysis and depth profiling will enhance the usefulness of SIMS as a technique for biological research.

A regularizing algorithm is constructed for the problem of reconstructing a function from its radon transformation. The two-dimensional case is considered.

Action spectra of UV damage to plants must be used as weighting functions to (1) evaluate the relative increase of solar UV radiation that would result from a decreased atmospheric ozone layer, the radiation amplification factor—RAF, (2) evaluate the existing natural gradients of solar UV irradiance on the earth, and (3) compare UV radiation from lamp systems in experiments with solar UV radiation in nature. Only if the relevant biological action spectra have certain characteristics is there a potential biological problem that would result from ozone reduction. Similarly the existence of a natural latitudinal solar UV gradient is dependent on action spectrum characteristics.

It is well recognized that immunoglobulins consist of heterogeneous populations of antibody proteins which are synthesized following a complicated series of cellular events induced by antigen stimulation. Chemical studies of purified antibodies suggested that antibodies of different specificities may differ from one another in their primary protein structure (Koshland and Englberger, 1963). The mechanism by which this tremendous variety of immunoglobulins are synthesized has thus been a very interesting biological problem. Biochemical knowledge concerning transcription and translation of the genetic messages for the synthesis of these proteins is, however, extremely deficient. This is due mainly to the difficulty in obtaining for study a sufficient quantity of lymphoid tissue with a given homogeneity of antibody production.

The etiology of tetanus and gas gangrene presents a biological problem of an unusual nature. When the organisms which cause these diseases are deprived of toxin, by washing in tap-water saline or by washing and then heating, they are non-pathogenic to laboratory animals. In a recent investigation of the problem we have shown that soluble ionisable calcium salts enable detoxicated B. tetani, B. Welchii, B. oedematiens and vibrion septique to exert their pathogenic powers. We concluded that calcium owes this property to its local action on the tissues.