Flies at the Farm: Drosophila at Janelia

On August 1, 2006 the Howard Hughes Medical Institute’s first stand-alone research campus opened at Janelia Farm, near Washington DC. Our mission at Janelia is to do exceptional fundamental research. Our two scientific foci are to understand the function of neural circuits and to develop synergistic imaging technologies. To achieve this we have changed many of the conventions of academic and/or industrial science. The founding director at Janelia is the well-known Drosophilist Gerry Rubin, who has been a central figure in fly molecular, developmental and genomic biology in recent decades. Not coincidentally, we at Janelia fully appreciate the potential of flies to contribute to an understanding of neuronal circuits. Our objectives are ambitious, and in the first ten months of operations at Janelia we have made some good beginnings which I will describe below.     

Janelia Farm: an experiment in scientific culture

Janelia Farm, the new research campus of the Howard Hughes Medical Institute, is an ongoing experiment in the social engineering of research communities.     

Wiring and rewiring of the retinogeniculate synapse

The formation and refinement of synaptic circuits are areas of research that have fascinated neurobiologists for decades. A recurrent theme seen at many CNS synapses is that neuronal connections are at first imprecise, but refine and can be rearranged with time or with experience. Today, with the advent of new technologies to map and monitor neuronal circuits, it is worthwhile to revisit a powerful experimental model for examining the development and plasticity of synaptic circuits--the retinogeniculate synapse.     

Mixed Signal Learning by Spike Correlation Propagation in Feedback Inhibitory Circuits

The brain can learn and detect mixed input signals masked by various types of noise, and spike-timing-dependent plasticity (STDP) is the candidate synaptic level mechanism. Because sensory inputs typically have spike correlation, and local circuits have dense feedback connections, input spikes cause the propagation of spike correlation in lateral circuits; however, it is largely unknown how this secondary correlation generated by lateral circuits influences learning processes through STDP, or whether it is beneficial to achieve efficient spike-based learning from uncertain stimuli. To explore the answers to these questions, we construct models of feedforward networks with lateral inhibitory circuits and study how propagated correlation influences STDP learning, and what kind of learning algorithm such circuits achieve. We derive analytical conditions at which neurons detect minor signals with STDP, and show that depending on the origin of the noise, different correlation timescales are useful for learning. In particular, we show that non-precise spike correlation is beneficial for learning in the presence of cross-talk noise. We also show that by considering excitatory and inhibitory STDP at lateral connections, the circuit can acquire a lateral structure optimal for signal detection. In addition, we demonstrate that the model performs blind source separation in a manner similar to the sequential sampling approximation of the Bayesian independent component analysis algorithm. Our results provide a basic understanding of STDP learning in feedback circuits by integrating analyses from both dynamical systems and information theory.     

From Boolean Network Model to Continuous Model Helps in Design of Functional Circuits

Computational circuit design with desired functions in a living cell is a challenging task in synthetic biology. To achieve this task, numerous methods that either focus on small scale networks or use evolutionary algorithms have been developed. Here, we propose a two-step approach to facilitate the design of functional circuits. In the first step, the search space of possible topologies for target functions is reduced by reverse engineering using a Boolean network model. In the second step, continuous simulation is applied to evaluate the performance of these topologies. We demonstrate the usefulness of this method by designing an example biological function: the SOS response of E. coli. Our numerical results show that the desired function can be faithfully reproduced by candidate networks with different parameters and initial conditions. Possible circuits are ranked according to their robustness against perturbations in parameter and gene expressions. The biological network is among the candidate networks, yet novel designs can be generated. Our method provides a scalable way to design robust circuits that can achieve complex functions, and makes it possible to uncover design principles of biological networks.     

Functional mapping of neurons that control locomotory behavior in Caenorhabditis elegans

One approach to understanding behavior is to define the cellular components of neuronal circuits that control behavior. In the nematode Caenorhabditis elegans, neuronal circuits have been delineated based on patterns of synaptic connectivity derived from ultrastructural analysis. Individual cellular components of these anatomically defined circuits have previously been characterized on the sensory and motor neuron levels. In contrast, interneuron function has only been addressed to a limited extent. We describe here several classes of interneurons (AIY, AIZ, and RIB) that modulate locomotory behavior in C. elegans. Using mutant analysis as well as microsurgical mapping techniques, we found that the AIY neuron class serves to tonically modulate reversal frequency of animals in various sensory environments via the repression of the activity of a bistable switch composed of defined command interneurons. Furthermore, we show that the presentation of defined sensory modalities induces specific alterations in reversal behavior and that the AIY interneuron class mediates this alteration in locomotory behavior. We also found that the AIZ and RIB interneuron classes process odorsensory information in parallel to the AIY interneuron class. AIY, AIZ, and RIB are the first interneurons directly implicated in chemosensory signaling. Our neuronal mapping studies provide the framework for further genetic and functional dissections of neuronal circuits in C. elegans.     

Associative and sensorimotor cortico‐basal ganglia circuit roles in effects of abused drugs

The mammalian forebrain is characterized by the presence of several parallel cortico‐basal ganglia circuits that shape the learning and control of actions. Among these are the associative, limbic and sensorimotor circuits. The function of all of these circuits has now been implicated in responses to drugs of abuse, as well as drug seeking and drug taking. While the limbic circuit has been most widely examined, key roles for the other two circuits in control of goal‐directed and habitual instrumental actions related to drugs of abuse have been shown. In this review we describe the three circuits and effects of acute and chronic drug exposure on circuit physiology. Our main emphasis is on drug actions in dorsal striatal components of the associative and sensorimotor circuits. We then review key findings that have implicated these circuits in drug seeking and taking behaviors, as well as drug use disorders. Finally, we consider different models describing how the three cortico‐basal ganglia circuits become involved in drug‐related behaviors. This topic has implications for drug use disorders and addiction, as treatments that target the balance between the different circuits may be useful for reducing excessive substance use.     

A description of dynamical graphs associated to elementary regulatory circuits

The biological and dynamical importance of feedback circuits in regulatory graphs has often been emphasized. The work presented here aims at completely describing the dynamics of isolated elementary regulatory circuits. Our analytical approach is based on a discrete formal framework, built upon the logical approach of R. Thomas. Given a regulatory circuit, we show that the structure of synchronous and asynchronous dynamical graphs depends only on the length of the circuit (number of genes) and on its sign (which depends on the parity of the number of negative interactions). This work constitutes a first step towards the analytical characterisation of discrete dynamical graphs for more complex regulatory networks in terms of contributions corresponding to their embedded elementary circuits.     

Studying transcriptional interactions in single cells at sufficient resolution

Our ability to dissect and understand the principles of gene regulatory circuits is partly limited by the resolution of our experimental assays. In this brief review, we discuss aspects of gene expression in microbial organisms apparent only when increasing the experimental resolution from populations to single cells and sub-cellular structures, from snap-shots to high-speed time-lapse movies and from molecular ensembles to single molecules.     

A cell type annotation Jamboree—Revival of а communal science forum

Cell Atlases are currently being constructed for human tissues as well as several model organisms. New technologies make creation of vast datasets in many species possible, but the value of such data crucially depends on the quality of annotation. The tools of annotating single cell data and creating knowledge representations comparable across organisms have been lagging. We argue that successfully creating Cell Atlases will require a revival of a boot‐camp style forum for communal annotation combined with an intensive learning workshop, dubbed a “Jamboree”. We report on our experience of successfully developing a structure and curriculum and running such a Jamboree for Xenopus Embryonic Cell Types at the Janelia Farms campus of the Howard Hughes Medical Institute.     

Long-term plasticity at inhibitory synapses

Experience-dependent modifications of neural circuits and function are believed to heavily depend on changes in synaptic efficacy such as LTP/LTD. Hence, much effort has been devoted to elucidating the mechanisms underlying these forms of synaptic plasticity. Although most of this work has focused on excitatory synapses, it is now clear that diverse mechanisms of long-term inhibitory plasticity have evolved to provide additional flexibility to neural circuits. By changing the excitatory/inhibitory balance, GABAergic plasticity can regulate excitability, neural circuit function and ultimately, contribute to learning and memory, and neural circuit refinement. Here we discuss recent advancements in our understanding of the mechanisms and functional relevance of GABAergic inhibitory synaptic plasticity.     

Proposed mechanisms for coincidence detection in the auditory brainstem

Sound localization in mammals uses two distinct neural circuits, one for low- and one for high-frequency bands. Recent experiments call for revision of the theory explaining how the direction of incoming sound is calculated. We propose such a revised theory. Our theory is based on probabilistic spiking and probabilistic delay of spikes from both sides. We have applied the mechanism originally proposed as an operation on spike trains resulting in multiplication of firing rates. We have adapted this mechanism for the case of synchronous spike trains. The mechanism has to detect spikes from both sides within a short time window. Therefore, in both circuits neurons act as coincidence detectors. In the excitatory low-frequency circuit we call the mechanism the excitatory coincidence detection, to distinguish it from the mechanism of the inhibitory coincidence detection in the high-frequency circuit. The times to first spike and gains of the two mechanisms are calculated. We show how the output gains of the mechanisms predict the dip within the human frequency sensitivity range. This dip has been described in human psychophysical experiments.     

Aggression and conflict management at fusion in spider monkeys

In social systems characterized by a high degree of fission-fusion dynamics, members of a large community are rarely all together, spending most of their time in smaller subgroups with flexible membership. Although fissioning into smaller subgroups is believed to reduce conflict among community members, fusions may create conflict among individuals from joining subgroups. Here, we present evidence for aggressive escalation at fusion and its mitigation by the use of embraces in wild spider monkeys (Ateles geoffroyi). Our findings provide the first systematic evidence for conflict management at fusion and may have implications for the function of human greetings.     

Zebrafish forebrain and temporal conditioning

The rise of zebrafish as a neuroscience research model organism, in conjunction with recent progress in single-cell resolution whole-brain imaging of larval zebrafish, opens a new window of opportunity for research on interval timing. In this article, we review zebrafish neuroanatomy and neuromodulatory systems, with particular focus on identifying homologies between the zebrafish forebrain and the mammalian forebrain. The neuroanatomical and neurochemical basis of interval timing is summarized with emphasis on the potential of using zebrafish to reveal the neural circuits for interval timing. The behavioural repertoire of larval zebrafish is reviewed and we demonstrate that larval zebrafish are capable of expecting a stimulus at a precise time point with minimal training. In conclusion, we propose that interval timing research using zebrafish and whole-brain calcium imaging at single-cell resolution will contribute to our understanding of how timing and time perception originate in the vertebrate brain from the level of single cells to circuits.     

Force measurements of Myosin II waves at the yolk surface during Drosophila dorsal closure

The mechanical properties and the forces involved during tissue morphogenesis have been the focus of much research in the last years. Absolute values of forces during tissue closure events have not yet been measured. This is also true for a common force-producing mechanism involving Myosin II waves that results in pulsed cell surface contractions. Our patented magnetic tweezer, CAARMA, integrated into a spinning disk confocal microscope, provides a powerful explorative tool for quantitatively measuring forces during tissue morphogenesis. Here, we used this tool to quantify the in vivo force production of Myosin II waves that we observed at the dorsal surface of the yolk cell in stage 13 Drosophila melanogaster embryos. In addition to providing for the first time to our knowledge quantitative values on an active Myosin-driven force, we elucidated the dynamics of the Myosin II waves by measuring their periodicity in both absence and presence of external perturbations, and we characterized the mechanical properties of the dorsal yolk cell surface.     

Design and implementation of a genomics field trip program aimed at secondary school students

With the rapid pace of advancements in biological research brought about by the application of computer science and information technology, we believe the time is right for introducing genomics and bioinformatics tools and concepts to secondary school students. Our approach has been to offer a full-day field trip in our research facility where secondary school students carry out experiments at the laboratory bench and on a laptop computer. This experience offers benefits for students, teachers, and field trip instructors. In delivering a wide variety of science outreach and education programs, we have learned that a number of factors contribute to designing a successful experience for secondary school students. First, it is important to engage students with authentic and fun activities that are linked to real-world applications and/or research questions. Second, connecting with a local high school teacher to pilot programs and linking to curricula taught in secondary schools will enrich the field trip experience. Whether or not programs are linked directly to local teachers, it is important to be flexible and build in mechanisms for collecting feedback in field trip programs. Finally, graduate students can be very powerful mentors for students and should be encouraged to share their enthusiasm for science and to talk about career paths. Our experiences suggest a real need for effective science outreach programs at the secondary school level and that genomics and bioinformatics are ideal areas to explore.     

Sources of Variability in a Synthetic Gene Oscillator

Synthetic gene oscillators are small, engineered genetic circuits that produce periodic variations in target protein expression. Like other gene circuits, synthetic gene oscillators are noisy and exhibit fluctuations in amplitude and period. Understanding the origins of such variability is key to building predictive models that can guide the rational design of synthetic circuits. Here, we developed a method for determining the impact of different sources of noise in genetic oscillators by measuring the variability in oscillation amplitude and correlations between sister cells. We first used a combination of microfluidic devices and time-lapse fluorescence microscopy to track oscillations in cell lineages across many generations. We found that oscillation amplitude exhibited high cell-to-cell variability, while sister cells remained strongly correlated for many minutes after cell division. To understand how such variability arises, we constructed a computational model that identified the impact of various noise sources across the lineage of an initial cell. When each source of noise was appropriately tuned the model reproduced the experimentally observed amplitude variability and correlations, and accurately predicted outcomes under novel experimental conditions. Our combination of computational modeling and time-lapse data analysis provides a general way to examine the sources of variability in dynamic gene circuits.     

The Evolution of Your Success Lies at the Centre of Your Co-Authorship Network

Collaboration among scholars and institutions is progressively becoming essential to the success of research grant procurement and to allow the emergence and evolution of scientific disciplines. Our work focuses on analysing if the volume of collaborations of one author together with the relevance of his collaborators is somewhat related to his research performance over time. In order to prove this relation we collected the temporal distributions of scholars’ publications and citations from the Google Scholar platform and the co-authorship network (of Computer Scientists) underlying the well-known DBLP bibliographic database. By the application of time series clustering, social network analysis and non-parametric statistics, we observe that scholars with similar publications (citations) patterns also tend to have a similar centrality in the co-authorship network. To our knowledge, this is the first work that considers success evolution with respect to co-authorship.