A low‐cost,computer‐controlled robotic flower system for behavioral experiments

Human observations during behavioral studies are expensive, time‐consuming, and error prone. For this reason, automatization of experiments is highly desirable, as it reduces the risk of human errors and workload. The robotic system we developed is simple and cheap to build and handles feeding and data collection automatically. The system was built using mostly off‐the‐shelf components and has a novel feeding mechanism that uses servos to perform refill operations. We used the robotic system in two separate behavioral studies with bumblebees (Bombus terrestris): The system was used both for training of the bees and for the experimental data collection. The robotic system was reliable, with no flight in our studies failing due to a technical malfunction. The data recorded were easy to apply for further analysis. The software and the hardware design are open source. The development of cheap open‐source prototyping platforms during the recent years has opened up many possibilities in designing of experiments. Automatization not only reduces workload, but also potentially allows experimental designs never done before, such as dynamic experiments, where the system responds to, for example, learning of the animal. We present a complete system with hardware and software, and it can be used as such in various experiments requiring feeders and collection of visitation data. Use of the system is not limited to any particular experimental setup or even species.     

Linking proteins to signaling pathways for experiment design and evaluation

Biomedical experimental work often focuses on altering the functions of selected proteins. These changes can hit signaling pathways, and can therefore unexpectedly and non-specifically affect cellular processes. We propose PathwayLinker, an online tool that can provide a first estimate of the possible signaling effects of such changes, e.g., drug or microRNA treatments. PathwayLinker minimizes the users' efforts by integrating protein-protein interaction and signaling pathway data from several sources with statistical significance tests and clear visualization. We demonstrate through three case studies that the developed tool can point out unexpected signaling bias in normal laboratory experiments and identify likely novel signaling proteins among the interactors of known drug targets. In our first case study we show that knockdown of the Caenorhabditis elegans gene cdc-25.1 (meant to avoid progeny) may globally affect the signaling system and unexpectedly bias experiments. In the second case study we evaluate the loss-of-function phenotypes of a less known C. elegans gene to predict its function. In the third case study we analyze GJA1, an anti-cancer drug target protein in human, and predict for this protein novel signaling pathway memberships, which may be sources of side effects. Compared to similar services, a major advantage of PathwayLinker is that it drastically reduces the necessary amount of manual literature searches and can be used without a computational background. PathwayLinker is available at http://PathwayLinker.org. Detailed documentation and source code are available at the website.     

Developing functional magnetic resonance imaging techniques for alert macaque monkeys

Functional magnetic resonance imaging (fMRI) has developed rapidly into a major non-invasive tool for studying the human brain. However, due to a variety of technical difficulties, it has yet to be widely adopted for use in alert, trained non-human primates. Our laboratory has been developing techniques for such fMRI studies. As background, we first consider basic principles of fMRI imaging, experimental design, and post-processing. We discuss appropriate MRI system hardware and components for conducting fMRI studies in alert macaques, and the animal preparation and behavior necessary for optimal experiments. Finally, we consider alternative fMRI techniques using exogenous contrast agents, arterial spin labeling, and more direct measures of neural activation.     

Centrifuges and inertial shear forces

Centrifuges are often used in biological studies for 1 x g control samples in space flight microgravity experiments as well as in ground based research. Using centrifugation as a tool to generate an Earth like acceleration introduces unwanted inertial shear forces to the sample. Depending on the centrifuge and the geometry of the experiment hardware used these shear forces may contribute as much as 99% to the total force acting on the cells or tissues. The inertial shear force artifact should be dealt with for future experiment hardware development for Shuttle and the International Space Station (ISS) as well as for the interpretation of previous spaceflight and on-ground research data.     

Supervisory control theory applied to swarm robotics

Currently, the control software of swarm robotics systems is created by ad hoc development. This makes it hard to deploy these systems in real-world scenarios. In particular, it is difficult to maintain, analyse, or verify the systems. Formal methods can contribute to overcome these problems. However, they usually do not guarantee that the implementation matches the specification, because the system’s control code is typically generated manually. Also, there is cultural resistance to apply formal methods; they may be perceived as an additional step that does not add value to the final product. To address these problems, we propose supervisory control theory for the domain of swarm robotics. The advantages of supervisory control theory, and its associated tools, are a reduction in the amount of ad hoc development, the automatic generation of control code from modelled specifications, proofs of properties over generated control code, and the reusability of formally designed controllers between different robotic platforms. These advantages are demonstrated in four case studies using the e-puck and Kilobot robot platforms. Experiments with up to 600 physical robots are reported, which show that supervisory control theory can be used to formally develop state-of-the-art solutions to a range of problems in swarm robotics.     

MultiMSOAR 2.0: an accurate tool to identify ortholog groups among multiple genomes

The identification of orthologous genes shared by multiple genomes plays an important role in evolutionary studies and gene functional analyses. Based on a recently developed accurate tool, called MSOAR 2.0, for ortholog assignment between a pair of closely related genomes based on genome rearrangement, we present a new system MultiMSOAR 2.0, to identify ortholog groups among multiple genomes in this paper. In the system, we construct gene families for all the genomes using sequence similarity search and clustering, run MSOAR 2.0 for all pairs of genomes to obtain the pairwise orthology relationship, and partition each gene family into a set of disjoint sets of orthologous genes (called super ortholog groups or SOGs) such that each SOG contains at most one gene from each genome. For each such SOG, we label the leaves of the species tree using 1 or 0 to indicate if the SOG contains a gene from the corresponding species or not. The resulting tree is called a tree of ortholog groups (or TOGs). We then label the internal nodes of each TOG based on the parsimony principle and some biological constraints. Ortholog groups are finally identified from each fully labeled TOG. In comparison with a popular tool MultiParanoid on simulated data, MultiMSOAR 2.0 shows significantly higher prediction accuracy. It also outperforms MultiParanoid, the Roundup multi-ortholog repository and the Ensembl ortholog database in real data experiments using gene symbols as a validation tool. In addition to ortholog group identification, MultiMSOAR 2.0 also provides information about gene births, duplications and losses in evolution, which may be of independent biological interest. Our experiments on simulated data demonstrate that MultiMSOAR 2.0 is able to infer these evolutionary events much more accurately than a well-known software tool Notung. The software MultiMSOAR 2.0 is available to the public for free.     

Dissecting protein-induced DNA looping dynamics in real time

Many proteins that interact with DNA perform or enhance their specific functions by binding simultaneously to multiple target sites, thereby inducing a loop in the DNA. The dynamics and energies involved in this loop formation influence the reaction mechanism. Tethered particle motion has proven a powerful technique to study in real time protein-induced DNA looping dynamics while minimally perturbing the DNA–protein interactions. In addition, it permits many single-molecule experiments to be performed in parallel. Using as a model system the tetrameric Type II restriction enzyme SfiI, that binds two copies of its recognition site, we show here that we can determine the DNA–protein association and dissociation steps as well as the actual process of protein-induced loop capture and release on a single DNA molecule. The result of these experiments is a quantitative reaction scheme for DNA looping by SfiI that is rigorously compared to detailed biochemical studies of SfiI looping dynamics. We also present novel methods for data analysis and compare and discuss these with existing methods. The general applicability of the introduced techniques will further enhance tethered particle motion as a tool to follow DNA–protein dynamics in real time.     

Positional artifacts in microarrays: experimental verification and construction of COP, an automated detection tool

Microarray technology is currently one of the most widely-used technologies in biology. Many studies focus on inferring the function of an unknown gene from its co-expressed genes. Here, we are able to show that there are two types of positional artifacts in microarray data introducing spurious correlations between genes. First, we find that genes that are close on the microarray chips tend to have higher correlations between their expression profiles. We call this the 'chip artifact'. Our calculations suggest that the carry-over during the printing process is one of the major sources of this type of artifact, which is later confirmed by our experiments. Based on our experiments, the measured intensity of a microarray spot contains 0.1% (for fully-hybridized spots) to 93% (for un-hybridized ones) of noise resulting from this artifact. Secondly, we, for the first time, show that genes that are close on the microtiter plates in microarray experiments also tend to have higher correlations. We call this the 'plate artifact'. Both types of artifacts exist with different severity in all cDNA microarray experiments that we analyzed. Therefore, we develop an automated web tool-COP (COrrelations by Positional artifacts) to detect these artifacts in microarray experiments. COP has been integrated with the microarray data normalization tool, ExpressYourself, which is available at http://bioinfo.mbb.yale.edu/ExpressYourself/. Together, the two can eliminate most of the common noises in microarray data.     

A new dimension for the development of fluorescence-based assays in solution: from physical principles of FCS detection to biological applications

Ultrasensitive detection methods such as laser-induced fluorescence represent the current state-of-the-art in analytics. Single-molecule detection in solution has received a remarkable amount of attention in the last few years because of its applicability to life sciences. Studies have been performed on the fundamentals of the detection processes themselves and on some biological systems. Fluorescence correlation spectroscopy (FCS) is the link for ultrasensitive multicomponent analysis, showing possibilities for experiments on molecular interactions. Based on the theoretical background of FCS, this article gives full explanation of FCS and an update of highlights in experimental biology and medicine studied by FCS. We focus on a repertoire of diverse immunoglobulin specificities, a ribosome display system, single-molecule DNA sequencing, and a mutant enzyme generated by random mutagenesis of amino acids. We describe the usefulness and the enormous potential of the methodology. Further, this contribution clearly indicates that FCS is a valuable tool for solution-phase single-molecule (SPSM) experiments in immunobiology and medicine. In experiments with the Goodpasture autoantibody, we worked out conditions for the design of experiments on a complex single molecule in solution. The possibility to use SPSM-FCS as a quantitation methodology opens up other important applications beyond the scope of this article. Original results extending the published studies are presented for the rational foundation of SPSM-FCS. In this original contribution, we deal with experimental systems for biology and medicine where the number of molecules in solution is very small. This article is mandatory for gaining confidence in the interpretation of experimental SPSM-FCS results on the selfsame, individual single molecule in solution.     

The hydraulic system of trees: theoretical framework and numerical simulation

Empirical studies pose the problem of the physiological integration of the tree organism, which is also important on the scale of ecosystems. Recently, spatially distributed models emerged, which approach this problem by reflecting the close linkage between physiological processes and the structures of trees and tree stands. In the case of water flow, the tree organism can be regarded as hydraulic system and the branched tree architecture as hydraulic network. Previous models of the hydraulic system either did not take into account the network structure, or they had shortcomings regarding the translation of the underlying physiological assumptions by the discrete computation method. We have developed a theoretical framework which takes the form of a numerical simulation model of tree water flow. A discrete initial boundary value problem (IBVP) combines the phenomena of Darcy flow, water storage and conductivity losses in the hydraulic network. The software HYDRA computes the solution of the IBVP. The theoretical derivation and model tests corroborate the consistent translation of the physiological assumptions by the computational method. Simulation studies enabled us to formulate hypotheses on the following points: (1) differences in the hydraulic segmentation between Picea abies and Thuja occidentalis, (2) responses of the hydraulic system to rapid transpiration changes and to a scenario of drought stress, and (3) how these responses depend on architectural quantities of the trees. The simulation studies demonstrated our possibilities of deriving theoretically well-founded hypotheses about the functioning of the hydraulic system and its relation to system structure. The numerical simulation model is designed as a tool for structure-function studies, which is able to treat tree architecture as independent variable. The model supports the integration of data on tree level, and it can be used for computer experiments which quantify the dynamics of the hydraulic system according to the concepts of system theory. Copyright 1999 Academic Press.     

Methionine scanning as an NMR tool for detecting and analyzing biomolecular interaction surfaces

Methyl NMR spectroscopy is a powerful tool for studying protein structure, dynamics, and interactions. Yet difficulties with resonance assignment and the low abundance of methyl groups can preclude detailed NMR studies, particularly the determination of continuous interaction surfaces. Here we present a straightforward strategy that overcomes these problems. We systematically substituted solvent-exposed residues with reporter methionines in the expected binding site and performed chemical shift perturbation (CSP) experiments using methyl-TROSY spectra. We demonstrate the utility of this approach for the interaction between the HECT domain of the Rsp5p ubiquitin ligase and its cognate E2, Ubc4. Using these mutants, we could instantaneously assign all newly arising reporter methyl signals, determine the Ubc4 interaction surface on a per-residue basis, and investigate the importance of each individual mutation for ligand binding. Our data show that methionine scanning significantly extends the applicability, information content, and spatial resolution of methyl CSP experiments.     

HugeIndex: a database with visualization tools for high-density oligonucleotide array data from normal human tissues

High-density oligonucleotide arrays are a powerful tool for uncovering changes in global gene expression in various disease states. To this end, it is essential to first characterize the variations of gene expression in normal physiological processes. We established the Human Gene Expression (HuGE) Index database (www.HugeIndex.org) to serve as a public repository for gene expression data on normal human tissues using high-density oligonucleotide arrays. This resource currently contains the results of 59 gene expression experiments on 19 human tissues. We provide interactive tools for researchers to query and visualize our data over the Internet. To facilitate data analysis, we cross-reference each gene on the array with its annotation in the LocusLink database at NCBI.     

A case for spiking neural network simulation based on configurable multiple-FPGA systems

Recent neuropsychological research has begun to reveal that neurons encode information in the timing of spikes. Spiking neural network simulations are a flexible and powerful method for investigating the behaviour of neuronal systems. Simulation of the spiking neural networks in software is unable to rapidly generate output spikes in large-scale of neural network. An alternative approach, hardware implementation of such system, provides the possibility to generate independent spikes precisely and simultaneously output spike waves in real time, under the premise that spiking neural network can take full advantage of hardware inherent parallelism. We introduce a configurable FPGA-oriented hardware platform for spiking neural network simulation in this work. We aim to use this platform to combine the speed of dedicated hardware with the programmability of software so that it might allow neuroscientists to put together sophisticated computation experiments of their own model. A feed-forward hierarchy network is developed as a case study to describe the operation of biological neural systems (such as orientation selectivity of visual cortex) and computational models of such systems. This model demonstrates how a feed-forward neural network constructs the circuitry required for orientation selectivity and provides platform for reaching a deeper understanding of the primate visual system. In the future, larger scale models based on this framework can be used to replicate the actual architecture in visual cortex, leading to more detailed predictions and insights into visual perception phenomenon.     

Inertial shear forces and the use of centrifuges in gravity research. What is the proper control?

Centrifuges are used for 1 x g controls in space flight microgravity experiments and in ground based research. Using centrifugation as a tool to generate an Earth like acceleration introduces unwanted inertial shear forces to the sample. Depending on the centrifuge and the geometry of the experiment hardware used these shear forces contribute significantly to the total force acting on the cells or tissues. The inertial shear force artifact should be dealt with for future experiment hardware development for Shuttle and the International Space Station (ISS) as well as for the interpretation of previous space-flight and on-ground research data.     

Integrating biological information into the statistical analysis and design of microarray experiments

Microarray technology is a powerful tool for animal functional genomics studies, with applications spanning from gene identification and mapping, to function and control of gene expression. Microarray assays, however, are complex and costly, and hence generally performed with relatively small number of animals. Nevertheless, they generate data sets of unprecedented complexity and dimensionality. Therefore, such trials require careful planning and experimental design, in addition to tailored statistical and computational tools for their appropriate data mining. In this review, we discuss experimental design and data analysis strategies, which incorporate prior genomic and biological knowledge, such as genotypes and gene function and pathway membership. We focus the discussion on the design of genetical genomics studies, and on significance testing for detection of differential expression. It is shown that the use of prior biological information can improve the efficiency of microarray experiments.     

A pre-equilibrium before nucleotide binding limits fingers subdomain closure by Klentaq1

Numerous studies have been undertaken to establish the mechanism of dNTP binding and template-directed incorporation by DNA polymerases. It has been established by kinetic experiments that a rate-limiting step, crucial for dNTP selection, occurs before chemical bond formation. Crystallographic studies indicated that this step may be due to a large open-to-closed conformational transition affecting the fingers subdomain. In previous studies, we established a fluorescence resonance energy transfer system to monitor the open-to-closed transition in the fingers subdomain of Klentaq1. By comparing the rates of the fingers subdomain closure with that of the rate-limiting step for Klentaq1, we showed that fingers subdomain motion was significantly faster than the rate-limiting step. We have now used this system to characterize DNA binding as well as to complete a more extensive characterization of incorporation of all four dNTPs. The data indicate that DNA binding occurs by a two-step association and that dissociation of the DNA is significantly slower in the case of the closed ternary complex. The data for nucleotide incorporation indicate a step occurring before dNTP binding, which differs for all four nucleotides. As the only difference between the (E x p/t) complexes is the templating base, it would suggest an important role for the templating base in initial ground state selection.     

Technologies for large-scale physical mapping of human chromosomes

Developing and characterization ordered clone collection from human chromosome specific DNA libraries is proceeding as part of a larger effort to construct a physical map of the entire human genome. The robotics and automation section at Los Alamos has been focussed on developing the hardware and software tools required to support this objective. These tools are typically integrated systems that combine an intuitive user interface, a database, as well as the relevant hardware technologies. To date, we have developed a system to automatically grid clones onto nylon filters in high density arrays. We have also developed a hybridization autoradiograph software scoring tool that combines image analysis, databasing, and a user interface.