The Interactive Fly
Genes involved in tissue and organ development
During embryogenesis in insects, the axon-scaffold of the brain is built around the embryonic foregut which separates the anlagen of the brain hemispheres. An investigation of this process was carried out in Drosophila and it appears that the major longitudinal and horizontal tracts of the embryonic brain form superficially near the interface between the foregut and embryonic brain hemispheres. Three types of cellular structures are identified that might be involved in tract formation: rows of glial cells at the medial brain margin, cellular bridges composed of neuronal somata and the epithelial surface of the foregut itself.
The Drosophila central brain is composed of approximately 100 paired lineages, with most lineages comprising 100-150 neurons. Most lineages have a number of important characteristics in common. Typically, neurons of a lineage stay together as a coherent cluster and project their axons into a coherent bundle visible from late embryo to adult. Neurons born during the embryonic period form the primary axon tracts (PATs) that follow stereotyped pathways in the neuropile. Apoptotic cell death removes an average of 30%-40% of primary neurons around the time of hatching. Secondary neurons generated during the larval period form secondary axon tracts (SATs) that typically fasciculate with their corresponding primary axon tract. SATs develop into the long fascicles that interconnect the different compartments of the adult brain. Structurally, this study distinguishs between three types of lineages: (1) PD lineages, characterized by distinct, spatially separate proximal and distal arborizations; (2) C lineages with arborizations distributed continuously along the entire length of their tract; and (3) D lineages that lack proximal arborizations. Arborizations of many lineages, in particular those of the PD type, are restricted to distinct neuropile compartments. It is proposed that compartments are 'scaffolded' by individual lineages, or small groups thereof. Thereby, the relatively small number of primary neurons of each primary lineage set up the compartment map in the late embryo. Compartments grow during the larval period simply by an increase in arbor volume of primary neurons. Arbors of secondary neurons form within or adjacent to the larval compartments, resulting in smaller compartment subdivisions and additional, adult specific compartments (Larsen, 2009).
The peculiar mode of generating fixed lineages of neurons from a small number of stem cell-like neuroblasts, so far found only in insects and crustaceans, has been studied in great detail since many decades. More recent genetic studies on neuroblasts in Drosophila have contributed significantly to the identification of molecular factors involved in the asymmetric distribution of cellular components, or the orientation of the mitotic spindle, during cell division. Less attention was given to the morphological characteristics of the neurons that formed part of the cell lineages derived from individual neuroblasts. This paper has addressed several aspects of the structural development of the lineages forming the Drosophila brain. Using GFP labeled clones, as well lineage specific GFP expression by Gal4 driver lines, the growth of lineages from embryo to adult were followed, focusing on cell number, neurite trajectory and neurite arborization pattern. The main interest was to identify attributes that lineages had in common, or that neurons belonging to a given lineage had in common, rather than emphasizing the diversity of neuronal phenotypes (Larsen, 2009).
Brain neuroblasts segregate from the procephalic (head) neurectoderm during early embryogenesis. They form a layer of approximately 100 cells; within this layer, neuroblasts with a specific genetic identity (i.e., pattern of expression of a certain set of transcription factors) always occupy the same position (Larsen, 2009).
Neuroblasts undergo 5-8 divisions in the embryo, producing that many ganglion mother cells; each ganglion mother cell divides once and forms two neurons or glial cells. It should be mentioned that one should expect exceptions to this general rule; for example, in the ventral nerve cord, atypical neuroblasts like the MP cells derived from the mesectoderm divide only once. One neuroblast of the head, appears to produce only 8 neurons that all express Dilp. However, as observed for the ventral cord, the large majority of brain neuroblasts divide at intervals of 50-60 min after their segregation, and therefore should produce 10-16 labeled cells by the end of embryogenesis. The clone sizes obtained for late embryos were indeed quite uniform, but were consistently smaller than the expected value, most of them ranging between 8 and 12 cells. For example, mesodermal clones that should comprise a total of 8-16 cells (based on four mesodermal mitoses) are only two to six cells in average. The smaller than expected clone size is most likely due to the time interval required for building up a sufficient level of Flipase. For both mesodermal and brain clones, expected and observed clone size differ by about four cells, corresponding to two rounds of mitosis. Assuming a cell cycle length of about 1 h, these data point at a two-hour lag phase required for Flp build-up. In other words, heat-shocking at around 3 h (and one cannot go earlier than that, because it would interfere with gastrulation) will lead to flip-out around 5-6 h, the time when most neuroblasts, or mesodermal cells, have already divided twice (Larsen, 2009).
Aside from rather equal sizes, embryonic clones also behaved quite uniformly in regard to the pattern of axonal projection. Neurons of one lineage invariantly form a tight cluster and send axons in a single bundle that is called the primary axon tract (PAT). PATs were always directed radially away from the surface. Up until stage 15, PATs remained short and unbranched. They entered the minuscule embryonic neuropile at the location closest to their cluster of origin and stopped near the center of the brain; many lineages located dorsally (DPL, DPM) projected towards the commissure connecting the two brain hemispheres. Only during late embryonic stages (late 16 to 17, ~15 h after fertilization) thin neurites with higher order branches became visible. The fact that longer axons (e.g., the pioneer axons establishing the major embryonic brain tracts) are not seen at an earlier stage is most likely due to the fact that the clones did not included the first born neurons. For the ventral nerve cord, most of the pioneer axons (e.g., acc, pcc, RP2) are formed by neurons that are the first born in their lineage. Accordingly, if lineages are visualized by dye injection, they are in most cases comprised of two different types of neurons. One type has larger neurons with long axons that often project in quite different directions (like acc and pcc in the Nb1.1 lineage); these neurons are typically located deep, adjacent to the neuropile. The second type comprises smaller neurons, located more superficially in the cortex, and forming shorter and more uniform projections. The first type represents neurons born first; the second type later born neurons. Using Flip-out induced labeling of lineages, only the later born neurons are seen (Larsen, 2009).
A significant number of primary neurons undergo apoptosis at the embryo-to-larva transition. Cell death in the developing arthropod CNS has been described frequently; the current data, based on both single clone sizes as well as cell counts, put the ratio of cell death occurring at the embryo-to-larva transition at 40%. As a result of this massive amount of cell death, as well as local cell body rearrangements, the cortex thickness shrinks considerably from late embryo to early larva, while the volume of the neuropile increases due to neurite branching. The same phenomenon can be observed during the pupal phase: before onset of pupation, a stage when most neuroblasts have finished or are close to finish dividing and the number of neurons is maximal, the cortex measures 10-12 neuron diameters in thickness. In the adult brain, the cortex is very uneven in thickness. It is stretched out into a thin layer of 1-2 cell diameters thickness over most of the brain surface (VH). At certain locations, in particular in crevices in between compartments that form protrusions at the posterior and anterior brain surface (e.g., calyx, optic tubercle, antennal lobe, ventro-lateral protocerebrum), the cortex is 5-8 cell diameters in thickness. During the same period, the neuropile volume increases dramatically. Precise neuron cell counts do not exist yet for the late larval and adult stages. Based on studies that focus on individual lineages (e.g., BLVa1-3, VH and SH) it is clear that apoptotic cell death eliminates a major fraction of the secondary neurons; whether it amounts to 40%, as in case of primary neurons during the embryo-larval transition, remains to be seen (Larsen, 2009).
The thinning of the brain cortex observed in the embryo-larval and the larval-adult transition is accompanied by rearrangement of neuronal cell bodies. These can be appreciated best when visualizing individual lineages. As might be expected, neuronal cell bodies of a given lineage form radially oriented, wedge- or column shaped clusters in the late embryo (primary lineages) or late larva (secondary lineages). In early larvae, primary neurons of a lineage are more spread out tangentially; the same happens to secondary neurons in the adult brain cortex. That being said, cell bodies of a lineage do stay together as one cluster. There does not appear to be a large scale intermingling of cell bodies of different lineages (Larsen, 2009).
Another aspect of the architecture of the brain cortex that was addressed in this study is the delineation, or absence thereof, of lineages by glial cells. The notion appears in the literature that specialized glial boundaries separate clusters of cells that belong to different lineages. This is definitely not the case in Drosophila, as shown in this study for the cells of the engrailed-positive DPLam lineage. Cortex glia forms a meshwork of processes, called trophospongium, that wrap all neuronal cell bodies individually. The trophospongium at the boundary between cells of different lineages does not appear to be thicker, or specialized in any other way. Only at the larval stage when secondary neurons are being generated, clusters of newly born ganglion mother cells and neurons, located at the surface around the neuroblasts, are enclosed as a group (a sublineage) by cortex glia; as these cells are pushed away from the neuroblast by subsequent divisions, they become individually wrapped by cortex glia (Larsen, 2009).
Anatomical work on insect brains, employing methods such as Golgi silver impregnation, dye backfilling and injection, or antibody labeling, have visualized the arborization patterns of a large number of individual neurons that vary enormously in size and shape. They include giant neurons with arborizations reaching throughout most compartments, as well small neurons with arbors restricted to fractions of a single compartment. To date, no systematic effort was undertaken to investigate how parameters like cell size or cell shape are represented numerically (are there 90% of giant neurons and 10% of dwarfs, or vice versa?) or related to development (are giants always born earlier than dwarfs? Do they come from different lineages?). This paper does not provide a definitive answer to these questions, but presents a step along the way that will, hopefully soon, arrive at these answers (Larsen, 2009).
Neurons of most of the brain lineages visualized by clones or specific Gal4 drivers share a common projection pattern and, most likely, terminal arborization pattern. Three main types of lineages are defined, based on their geometry: PD lineages with well defined proximal and distal arborizations (e.g., MB lineages, BAla1 antennal projection neurons, DALv2 ellipsoid body neurons), C lineages where proximal and distal projections blend into each other (e.g., DPLam), and D lineages which lack proximal arborizations (e.g., BAla3). At both larval and adult stages, the arborization of most lineages is restricted to a minor fraction of the neuropile volume (5%-20%). Many PD lineages and some C lineages outline discrete compartments; aside from the well studied calyx and lobes of the mushroom body, defined by the four MB lineages, one can point at the BA lineages that generate the antennal projection neurons, the primary DALv2 linage whose proximal arbors are restricted to the larval BC compartment, many of the primary BL lineages that outline the BPL compartment, or the BAla3 lineage that is mostly restricted to the BPM. Proximal arborizations of the secondary DPMpm, DPMm, and CM4 lineages define the protocerebral bridge; distal arborizations produce the fan-shaped body and the noduli. Proximal arbors of the secondary DALv2 define the 'bulbs' (formerly called 'lateral triangle'), which represent the input domain of the ellipsoid body. Distal secondary DALv2 neurons generate the ellipsoid body. It is proposed that lineages such as MB, BAla/Bald, DPMm/DPMpm/CM4, or DALv2 act to 'scaffold' these compartments. According to this hypothesis, each compartment, A', has its own 'scaffolding lineage', A (or set of scaffolding lineages). A 'scaffolding lineage' would then be defined in the following manner: (1) during development, the outgrowth of neurites from a lineage A actually creates the compartment A'. If A is deleted, A' also does not form. This has been shown experimentally for the calyx, the compartment scaffolded by the four MB lineages. (2) The arborization of lineage A forms a dense matrix of terminal axons on which synapses of A neurons themselves, as well as extrinsic neurons that enter compartment A' from the outside are made. Again, the calyx provides an example in this case: electron microscopic investigations have shown that well over two thirds of the postsynaptic terminal neurites belong to neurons of the MB lineages (Larsen, 2009).
The data suggest that a lineage-directed approach may facilitate the analysis of Drosophila brain development and structure considerably. This requires, first and foremost, to identify suitable Gal4 driver lines whose expression is restricted to one or a few lineages, and which then can be used to label, ablate, activate, or otherwise manipulate this lineage. Large scale screens are underway to attain this goal. Lineage-specific driver lines will also be crucial for the next step of the analysis, which looks at individual neurons within lineages. Published data suggest that many lineages can be subdivided 'vertically' into two hemilineages, and 'horizontally' into several sublineages. Neuroblasts produce series of ganglion mother cells (GMCs), each of which divides into an 'a' and a 'b' daughter cell. It has been shown for many lineages of the thoracic ganglia that all neurons of the a-hemilineage share properties that are different from neurons of the b-hemilineage. In some cases, a and b-hemilineages produce different SATs; or one complete hemilineage undergoes apoptosis, whereas the other one survives. Preliminary data suggest that hemilineages also exist for the brain (Larsen, 2009).
Sublineages are groups of neurons born during a defined time interval. For example, the primary neurons represent one significant sublineage for each (hemi)lineage; most likely the primary neurons of most lineages can be further subdivided into smaller subgroups. It has been shown that the lineages scaffolding the fan-shaped body comprise multiple sublineages with different distal arborizations. The fan-shaped body is subdivided into six horizontal layers and eight vertical columns. All neurons of a given lineage (e.g., DPMpm) project to two distinct columns. Within a given lineage, neurons born at different times form sublineages that target different layers within the columns. Preliminary data shows that DALv2 forms sublineages whose distal arbors define the discrete layers within the ellipsoid body. Other lineages may form more overlapping projections; for example, each neuron of one of the MB lineages forms dendritic arbors that spread throughout most of the neuropile volume occupied by the lineage as a whole (Larsen, 2009).
The neurons of the primary lineages formed during embryogenesis form primary axon tracts (PATs) with invariant and characteristic trajectories. Note that, following a widely upheld convention, the unbranched processes that initially grow out from neurons are called 'axons,' irrespective of the fact that eventually, they will form terminal side branches that carry postsynaptic sites, presynaptic sites, or both. For some lineages, PATs can be still recognized in the differentiated larval neuropile. That is particularly true for lineages that form long PATs, like the antenno-protocerebral tract, central anterior protocerebral tract (CAPT), or various commissural tracts. In other cases, the individual axons of one lineage may disperse to a certain extent and form a loose bundle. Once secondary axon tracts (SATs) form, they always extend in close proximity to the PATs of the corresponding lineage. This confirms that, even though several days pass between the time when it has finished producing its primary lineage and starts forming its secondary lineage, a neuroblast remains stationary, in close contact with the primary neurons. As a result, secondary neurons are born in contact with their older, primary siblings; the first primary axons they encounter when growing out their own axons are the ones belonging to these siblings (Larsen, 2009).
In the neuropile, SATs of several lineages form thicker bundles, or fascicles. The term fascicle is used because according to convention it denotes a bundle of nerve fibers with different directionality and endings. In a previous characterization of secondary lineages, the most prominent fascicles have been characterized. This study shows that the larval fascicles, formed by discrete sets of SATs, persist throughout metamorphosis and become the brain fascicles of the adult. In adult brain preparations labeled with markers for synapses, the fascicles (formed by long axons lacking synapses) stand out as signal-negative spaces (Larsen, 2009).
Being able to follow fascicles from the larval period onward will help to unravel the connectivity of the adult brain. At present, unlike for vertebrate brains, knowledge of the 'macro-connectivity' (i.e., fiber bundles connecting different brain compartments) of the insect brain is very rudimentary. Only about a few fiber bundles are known, such as the antenno-protocerebral tract connecting the antennal compartment with the calyx. Other tracts have been tentatively named on section-based maps of the adult brain, but the beginning and ending of these tracts largely remains unclear, and the tract names suggested are not in wide use. The analysis of the secondary axon tracts will allow for a new and systematic effort to unravel macro-connectivity of the brain (Larsen, 2009).
One of the key characteristics of neural development in Drosophila (and probably insects in general) is that neurons of a lineage form a relatively coherent unit, where somata, axons and major parts of their arborizations stay together and define discrete modules of the brain neuropile. In the few cases where experimental studies were done, removal of a particular lineage leads to the absence of the corresponding module; there is little or no regulation. How widespread are these insect-type neural lineages in the animal kingdom? Do they exist in vertebrates (Larsen, 2009)?
The second question can be answered in the negative. A number of fate mapping studies where the birth and migration of neurons was followed were done by the infection of progenitors with reporter-construct carrying viruses or mitotic recombination. These experiments indicate that clones of cells derived from individual neural progenitors do not form structural modules where cell bodies all adhere to each other, and axons form coherent bundles. Vertebrate neural progenitors ('neural stem cells') divide within the ventricular layer, or, in the forebrain, the subventricular zone of the embryonic neural tube. Subsequently, guided by radial glia (specialized neuroepithelial cells that later become astrocytes, neurons migrate preferentially radially. In a mouse study where labeled stem cells were integrated into the 10.5 day anterior neural tube (presumptive forebrain), these cells were found to undergo 9-11 rounds of mitosis every 10 h, producing clones of approximately 600 pyramidal cells. (One might point out that this figure lies in the same ballpark as the number of neurons produced by one insect neuroblast. In Drosophila, most lineages consist of 150-200 neurons; some lineages have more than 500 neurons. The neurons of one clone were relatively close to each other, but left in between them large spaces filled with unlabeled neurons, indicating that cells of many neighboring clones intermingle. More importantly, the dendritic or axonal projections of a clone did not form coherent bundles. Aside from the radial clones of pyramidal cells, clones of tangentially migrating neurons were found. These clones correspond to the interneurons, which are born in a restricted domain of the ventral forebrain (eminence), from where they spread out tangentially to populate the different areas of the cortex (Larsen, 2009).
One can conclude that vertebrate neural lineages, at least up to a certain point in development, appear 'open': Cell bodies of numerous lineages intermingle within a given volume of the brain neuropile, and projections of members of a given lineage do not form distinct bundles or compartments. Outside arthropods and vertebrates, little is known about the relationship between neural architecture and neural development. In various protostome taxa, neuronal cell bodies in the cortex of the central nervous system are clustered around axon bundles (e.g., plathelminthes); whether these clusters of neurons correspond to lineages remains to be shown (Larsen, 2009).
The fact that the Drosophila nervous system is composed of structural modules that are in many cases defined by discrete lineages offers the exciting possibility of getting closer at the link between genes and behavior. In a developmental sense, lineages represent 'units of gene expression'. The expression pattern of more than fifty transcription factors in specific embryonic neuroblasts has been described. In the embryo, a given transcription factor becomes active in one, or a small number of, neuroblasts; a particular neuroblast thereby acquires a 'genetic address,' consisting of specific sets of transcription factors. It is thought that this genetic address will essentially be involved in shaping the morphology and function of that lineage. Lineages also represent to some extent structural modules of the brain. It stands to reason that in many cases, a lineage with its highly restricted
dendritic arborization and axonal pathway, will be involved in a single or a limited number of behaviors, or, probably more accurately, 'behavioral subroutines'. If that is indeed correct, one can manipulate the structural module scaffolded by a given lineage, and thereby address its function, and what aspects of that function is controlled by a given gene expressed in the lineage. For example, completely removing that lineage by driving a cell death-inducing gene, using a lineage specific promoter, would eliminate
the module. Behavioral assays may show, in most cases, the deterioration of certain behavioral subroutines. Using the same driver to modify the expression of genes specifically found in a particular lineage, one might be able to manipulate the genes one at a time, to find that one gene may be simply involved in increasing the cell number in that lineage, or the density of synapses in the scaffolded compartment, etc. By systematically following this approach for each one of the ~100 lineages of the brain the expectation is that a much better understanding of how genes control behavior will be achieved (Larsen, 2009).
Courtship is the best-studied behavior in Drosophila melanogaster, and work on its anatomical basis has concentrated mainly on the functional identification of sexually dimorphic sites in the brain. Much less is known of the more expansive, nondimorphic, but nonetheless essential, neural elements subserving male courtship behavior. Sites in the CNS mediating initiation and early steps of male courtship in Drosophila melanogaster were identified by analyzing the behavior of mosaic flies expressing transgenes designed either to suppress neurotransmission or enhance neuronal excitability. Suppression of neurotransmission was accomplished by means of the dominantly acting, temperature-sensitive dynamin mutation shibirets1, whereas enhanced neuronal excitability was produced by means of a novel, dominantly acting, truncated eag potassium channel. By using a new, landmark-based procedure for aligning diverse expression patterns among the various mosaic strains, a comparison of courtship performance and affected brain sites in strains expressing the transgenes identified a cluster of cells in the posterior lateral protocerebrum that exerts reciprocal effects on the initiation of courtship, suppressing it when they are inactivated and enhancing it when they are hyperactivated, indicative of cells that normally play an excitatory, triggering role. A separate group of nearby cells, slightly more anterior in the lateral protocerebrum, was found to inhibit courtship when its activity is enhanced, indicative of an inhibitory role in courtship. It is concluded that a cluster of cells, some excitatory and some inhibitory, in the lateral protocerebrum regulates courtship initiation in Drosophila. These cells are likely to be an integration center for the multiple sensory inputs that trigger male courtship (Broughton, 2004).
Male courtship is elicited by visual and chemosensory cues, either of which is sufficient to initiate courtship behavior in the presence of a virgin female. Projections from the antennal lobes to the lateral protocerebrum, independent of the mushroom bodies, are essential for courtship initiation. These data, which are consistent with the normal initiation of courtship in mushroom body-ablated and mushroom-body impaired males, suggest that courtship is initiated via a mushroom body-independent mechanism (Broughton, 2004).
In the current study, only those GAL4 lines expressed in a common region of the lateral, posterior protocerebrum had a specific effect on courtship initiation. Of particular significance is the reciprocal effect on initation seen in MJ286 and MJ146 when expressing a transgene suppressing neuronal activity as compared with an enhancing transgene. The implication is that these cells exert an activating effect on courtship initiation. This region has previously been implicated sex specifically in male courtship, physiologically in male courtship, and in mediating the plasticity associated with courtship conditioning. As the recipient of many different kinds of sensory projections, it is likely to carry out a variety of integrative functions, as already suggested by a study of its olfactory inputs (Broughton, 2004).
These lateral protocerebral cells in enhancer trap lines MJ286 and MJ146 lie just ventral to the anatomical neighborhood previously identified as the sex-specific focus for courtship initiation: the dorsal posterior brain. In fact, the marking technique used in the earlier studies detected cell bodies whose neuronal processes may well project into the region identified in the current study. The presence in MJ286 of sexually dimorphic function suggests that its dorsal, lateral, and protocerebral cells may even be part of the sex-specific focus for initiation, as well as being required for its physiological realization. The lack of FRUM expression in these cells may reflect the incomplete overlap in expression patterns between FRUM and the male-specific product of another gene in the sex determination cascade, doublesex (DSXM), each of which distinctively influences male courtship behavior. MJ146 does not show sex-specific function, despite its overlap, albeit limited, with FRUM expression (Broughton, 2004).
In contrast, the one case in which the transgene that enhances neuronal activity exerted a suppressing effect on courtship, MJ63, is suggestive of an inhibitory circuit, though it is not associated with the GABA-ergic marker GAD-dsRED. In this instance, the effect was unidirectional: blocking neuronal activity in the same cells had no effect. One interpretation of this result is that this region normally acts in a modulatory fashion and does not act to continuously inhibit courtship behavior. When MJ63 is used to drive expression of a CaMKII inhibitory peptide during the courtship conditioning assay, memory is disrupted and regions defined by this line have been suggested to be involved in enabling memory of the inhibition by the mated female. These data raise the possibility that the inhibitory regions identified by MJ63 may normally act to mediate experience-dependent inhibition of male courtship behavior and the inappropriate activation of them suppresses courtship, thus mimicking the conditioning paradigm (Broughton, 2004).
The opposing effects of c747/UAS-shits1 and c309/UAS-shits1 on wing extension and vibration, are likely to be due to the fact that the broader expression pattern in c747 disrupts inhibitory sites that are intact in c309 and that c309 affects excitatory sites. If this excitation were due to the mushroom body expression in c309, which would then be couteracted by additional expression in c747, it would be consistent with the previous finding of a sex-specific effect of this structure on the performance of wing extension and vibration. The song itself is controlled in the mesothoracic ganglion. Although the mushroom bodies have been suggested to be involved in mate discrimination, a recent finding that expression of UAS-shits1 in the mushroom bodies did not induce male-male courtship behavior shows that mushroom body activity is not required for the recognition of sex-specific pheromones that inhibit male-male courtship. Mushroom bodies have been implicated, however, in modulating other kinds of motor output (Broughton, 2004).
Mapping the neural elements of male courtship is an essential step in understanding the functional circuitry and neural basis for this evolutionarily critical behavior. The fact that courtship consists of a series of stereotypical steps offers great advantages for assigning roles to particular circuits and will facilitate the merging of findings from studies of the sexual dimorphisms underlying courtship with those of genetic perturbations of physiology (Broughton, 2004).
Courtship is an innate sexually dimorphic behaviour that can be observed in naive animals without previous learning or experience, suggesting that the neural circuits that mediate this behaviour are developmentally programmed. In Drosophila, courtship involves a complex yet stereotyped array of dimorphic behaviours that are regulated by FruM, a male-specific isoform of the fruitless gene. FruM is expressed in about 2,000 neurons in the fly brain, including three subpopulations of olfactory sensory neurons and projection neurons (PNs). One set of Fru+ olfactory neurons expresses the odorant receptor Or67d and responds to the male-specific pheromone cis-vaccenyl acetate (cVA). These neurons converge on the DA1 glomerulus in the antennal lobe. In males, activation of Or67d+ neurons by cVA inhibits courtship of other males, whereas in females their activation promotes receptivity to other males. These observations pose the question of how a single pheromone acting through the same set of sensory neurons can elicit different behaviours in male and female flies. Anatomical or functional dimorphisms in this neural circuit might be responsible for the dimorphic behaviour. This study reports a neural tracing procedure that employs two-photon laser scanning microscopy to activate the photoactivatable green fluorescent protein. Using this technique it was found that the projections from the DA1 glomerulus to the protocerebrum are sexually dimorphic. A male-specific axonal arbor was observed in the lateral horn whose elaboration requires the expression of the transcription factor FruM in DA1 projection neurons and other Fru+ cells. The observation that cVA activates a sexually dimorphic circuit in the protocerebrum suggests a mechanism by which a single pheromone can elicit different behaviours in males and in females (Datta, 2008).
In initial experiments, photoactivatable green fluorescent protein (PA-GFP) was expressed in flies in which the GAL4 enhancer-trap GH146 drives the expression of UAS-PA-GFP in 60% of the PNs that innervate most glomeruli in the antennal lobe. PA-GFP exhibits low-level fluorescence, sufficient to identify individual glomeruli, that is enhanced 100-fold after photoconversion with high-energy light. The PA-GFP was photoactivated with a two-photon laser scanning microscope to localize 710-nm light with submicrometre three-dimensional precision. Photoactivation of the antennal lobe neuropil, encompassing all glomeruli, results in intense labelling of the dendritic arbors of GH146 PNs. Diffusion of PA-GFP from the illuminated dendritic arbors allowed revealation of the cell bodies and axonal projections of the multiple GH146 PNs. Photoactivation of individual glomeruli (VM3 and DA1) reveals the dendritic arbors, cell bodies and projections of the subpopulation of GH146 PNs that innervate a single glomerulus (Datta, 2008).
An approach was devised to allow the tracing of individual PNs that innervate identified glomeruli. The DA1 glomerulus was exposed to low levels of photoconverting light and then the antennal lobe was rapidly imaged to identify the PN cell bodies that show modest increases in fluorescence intensity. Under these limiting conditions of photoactivation, diffusion of PA-GFP into axonal projections was not observed. Next a single weakly labeled PN cell body was strongly photoactivated at higher light intensity to reveal the axonal projections of an individual PN that innervates the DA1 glomerulus. Thus, two-photon laser scanning microscope-mediated activation of PA-GFP provides sufficient spatial resolution and photoconversion energy to reveal the neuronal processes of defined neuronal populations as well as individual neurons in the fly brain (Datta, 2008).
The development of a combined genetic and optical neural tracing method permits comparison of the topography of projections from Fru+ PNs that innervate the cVA-responsive DA1 glomerulus in male and female flies. Flies in which GAL4 is expressed under the control of the P1 fruitless promoter responsible for generating FruM (fruGAL4) were crossed with flies harbouring the UAS-PA-GFP transgene. P1 transcripts from the modified fruGAL4 allele do not undergo the sexually dimorphic splicing observed for the wild-type fru allele, and they therefore allow marking of Fru+ cells in both sexes. Unilateral photoactivation of the fly brain reveals many Fru+ cells, including neurons in the antennal lobe. Specific photoactivation of the DA1 glomerulus reveals six Fru+ PNs in both male and female flies that innervate this glomerulus. The cell bodies of these neurons reside in the lateral PN cluster, not the dorsal cluster as previously suggested (Datta, 2008).
It is possible that the sex-specific behavioural responses to cVA result from different functional responses of the DA1 glomerulus in the two sexes despite there being no apparent difference in the number or location of Fru+ DA1 PNs. Therefore the Ca2+-sensitive fluorescent protein GCaMP was expressed in Fru+ neurons, and two-photon imaging was used to examine increases in Ca2+ in the DA1 glomerulus in response to cVA. Large increases in Ca2+ within the DA1 glomerulus were detected by two-photon imaging after exposure of an intact, behaving fly to cVA. However, no differences were observed between male and female responses over a broad range of cVA concentrations (Datta, 2008).
These imaging experiments report local changes in the concentration of Ca2+ in both the presynaptic and postsynaptic compartments, because both Or67d-expressing neurons and DA1 PNs are Fru+. Therefore whether the electrophysiological properties of Fru+ DA1 PNs were sexually dimorphic was examined. The DA1 glomerulus was photoactivated to identify Fru+ DA1 PNs and the enhanced fluorescence was used to guide a patch electrode to the cell bodies. Recordings were made from Fru+ DA1 PNs in the loose patch configuration in an intact fly preparation and no significant difference was noted in the spike frequency or response kinetics between males and females when tested at several concentrations of cVA. These responses are comparable to those previously observed in whole-cell recordings of female DA1 PNs. This result demonstrates that male and female DA1 PNs show similar electrophysiological responses to cVA despite the previously noted dimorphism in the size of the DA1 glomerulus (Datta, 2008).
Next the projection patterns of Fru+ DA1 PNs were examined in the two sexes. Photoconversion of the DA1 glomerulus allowed the projection patterns of the population of DA1 PNs to be revealed in the lateral horn in living brains. Despite significant similarity in the axonal arbors of DA1 PNs in males and females, an increase was observed in the density of ventral axonal branches in the male. Quantification of differences in branch patterns in multiple individual male and female flies was hampered by variations in the orientation of the live brain during microscopy. Therefore the approach was altered to employ fixed brains stained with the antibody nc82 to label the synaptic neuropil of the lateral horn. An image registration algorithm was used to first 'warp' the nc82 channel of individual brains onto a reference brain and then map the PA-GFP fluorescence onto this reference brain. The registration error averaged less than 2 μm in any dimension when measured at the neuropil edge. It was observed that the projections from the DA1 glomerulus target the anterior ventromedial region of the LH. The projection pattern is triskelion-shaped, with ventral, lateral and dorsal branches. Fru+ DA1 projections from males have additional axonal branches that extend ventromedially. Superposition of the DA1 projections taken from ten male and ten female flies confirms this observation, indicating that information carried by Fru+ DA1 PNs is differentially segregated in the lateral horn of the two sexes. As a control a similar analysis of the PN projections from the Fru- glomerulus VM3, which responds to alcohols and acetates, was performed. Superposition of the projections from VM3 reveals no consistent differences in the pattern of axonal projections in the lateral horn between the two sexes. These observations show that the image alignment procedure does not introduce sex-specific biases in projection patterns and that the dimorphic projection patterns that were observe for the Fru+ glomerulus DA1 are not a general feature of projections from all glomeruli (Datta, 2008).
The anatomical dimorphism observed at the level of the population of axons is also shown by the axons of single identified neurons. Tracing individual Fru+ DA1 neurons after warping revealed that the ventral axonal branches of male PNs define a male-specific region of protocerebral space (about 600 μm3). Each individual male in the data set sends at least one axon branch into this area. This area seems to partly overlap a region of neuropil in the lateral horn that was recently shown to be larger in male flies than in female flies. In addition, the total density of ventrally oriented axonal branches is significantly greater in males than in females. In contrast, the total innervation of the dorsal axonal arbor showed no statistically significant differences between sexes. No similar female-specific area was identified, although there are several smaller areas (particularly laterally) that appear to have an increased density of female axons. The data from single-axon tracing, along with observations from populations of DA1 neurons, indicate that DA1 PN projections are sexually dimorphic (Datta, 2008).
Fru mutant males court other males with high frequency. If the male-specific arbor contributes to the dimorphic behavioural response, it is expected that the DA1 PN projection patterns will be regulated by the fruitless gene. Therefore the axonal projections of single DA1 PNs were made visible in fru mutant males, and it was observed that DA1 PNs lack the characteristic male-specific axonal branches and exhibit a branching pattern more characteristic of wild-type females. However, the feminization is not complete in that the male-specific ventral axonal branches are significantly reduced but not completely eliminated in fru mutant males. Thus, the male pattern of projections of Fru+ DA1 PNs requires the male-specific isoform of fru, FruM (Datta, 2008).
It was also shown that the ectopic expression of FruM in females masculinizes the axonal arbor of their DA1 PNs. Projections of single Fru+ DA1 PNs in female flies that express FruM (fruGAL4/fruUAS-FruM) exhibit a striking increase in axonal projections to the ventral male-enhanced area. Quantitative analysis of these branches reveals that expression of FruM in females renders their ventral axon branch pattern statistically indistinguishable from that of males. The innervation patterns of individual neurons are sufficient for a computational discrimination algorithm to effectively distinguish individual females from FruM-expressing females with 100% accuracy, and individual males from fru mutant males with more than 91% accuracy. Thus, analysis of the PN projections of both single defined neurons and populations of neurons reveal that Fru+ DA1 PNs project to different regions of the protocerebrum in male and female flies. Moreover, this anatomical dimorphism in the neural circuit is controlled by the dimorphic transcription factor, FruM (Datta, 2008).
Next, whether the formation of the male-specific arbor requires the action of FruM in DA1 projection neurons was examined. The enhancer-trap MZ19 drives the expression of GAL4 in six DA1 PNs, about ten additional PNs that innervate two Fru- glomeruli, and 25 extrinsic neurons of the mushroom body. Flies harbouring fruGAL4, MZ19 or MZ19;fruGAL4 all reveal expression of PA-GFP in six DA1 PNs. This suggests that the six lateral DA1 neurons labelled by the MZ19 and fruGAL4 lines are identical. In accord with this observation, male and female DA1 neurons in MZ19 flies have a sexually dimorphic pattern of projections that closely resembles the dimorphic branching observed for Fru+ DA1 PNs. Therefore FruM expression was eliminated in male MZ19 neurons by expression of Tra, which directs the female-specific splicing of fruitless transcripts. Genetic feminization of male DA1 PNs in MZ19/UAS-tra flies results in two anatomical classes of DA1 projection neurons. Half of the genetically feminized DA1 PNs show a reduction in the male-specific arbor and closely resemble male DA1 projection neurons defective for FruM. The remaining genetically feminized neurons exhibit the wild-type male-specific branching patterns. Within a single male MZ19/UAS-tra fly, neurons of both anatomical classes were observed. These data suggest that FruM is required in DA1 PNs to generate a male-specific projection pattern, but its action in this genetic context is partly penetrant (Datta, 2008).
Also, whether the expression of FruM in female DA1 PNs masculinizes the DA1 axon arbor was examined. DA1 PNs in female MZ19; fruUAS-FruM flies do not significantly innervate the male-specific area, although most send minor branches into the ventral region of the lateral horn. This is in contrast with observations with fruGAL4/fruUAS-FruM strains that exhibit a transformation of the female DA1 PN branching pattern into a complete male-specific arbor. Taken together, these results suggest that FruM is required in both DA1 PNs and in other Fru+ neurons to generate the male-specific pattern of ventral axon arborization in the lateral horn (Datta, 2008).
In Drosophila, courtship behaviour is governed by pheromonal excitation of peripheral olfactory pathways that ultimately activate behavioural circuits in higher brain centres. One pheromone elaborated by the male, cVA, suppresses male-male courtship but in females enhances receptivity to courting males. cVA activates the DA1 glomerulus, which is innervated by PNs that have sexually dimorphic projections in the lateral horn. This dimorphic circuit is under control of the transcription factor FruM, a male-specific isoform of fruitless. Moreover, the dimorphism in this circuit correlates with behaviour. In males mutant for FruM, cVA no longer suppresses male-male courtship and males exhibit a feminized pattern of DA1 projections. In females that express FruM, DA1 PNs exhibit a male pattern of axonal arbors in the lateral horn, and these females show reduced sexual receptivity. These observations are in accord with a mechanism in which the anatomical differences observed in Fru+ DA1 projection neurons contribute to the distinct behaviours elicited by cVA in the two sexes. In Drosophila, dimorphism in the Fru+ SP2 and mAL neurons has been observed, but the behavioural function of these circuits is unknown (Datta, 2008).
The anatomical dimorphism observed may be translated into a behavioural dimorphism if the connections between DA1 PNs and third-order neurons differ between the sexes. Third-order neurons whose dendrites innervate the ventral lateral horn may either receive greater input from male PNs or may restrict their synapses to the male-specific region of the DA1 axon arbor. The relatively small size of the male-specific arbor, about the volume of a glomerulus, implies a precision of connectivity in higher processing centres in the fly brain. The stereotyped and local precision of synaptic connections is an organizing principle in the antennal lobe and may be a common feature of invertebrate nervous systems (Datta, 2008).
Characterization of specific neural circuits that may mediate behaviour, as described in this study for the pheromone-responsive DA1 pathway, requires the development of tracing approaches that label defined populations of neurons. The distinction between genetic approaches -- including MARCM, Flp-Out and PA-GFP-based tracing -- and the histological approaches of Golgi and Cajal 100 years ago is the ability to use genetic markers to identify partners in the neural circuit more precisely. The targeted illumination of PA-GFP permits non-random, optically guided labelling of individual neurons from either anatomically or genetically defined subsets of neurons. Moreover, PA-GFP can be photoactivated in neurons in the living brain and allows electrophysiological recordings of labelled cells. This approach to neural tracing and recording in a defined circuit can be readily adapted to other brain regions in both the fly and mouse (Datta, 2008).
How does the sensory environment shape circuit organization in higher brain centers? This study has addressed the dependence on activity of a defined circuit within the mushroom body of adult Drosophila. This is a brain region receiving olfactory information and involved in long-term associative memory formation. The main mushroom body input region, named the calyx, undergoes volumetric changes correlated with alterations of experience. However, the underlying modifications at the cellular level remained unclear. Within the calyx, the clawed dendritic endings of mushroom body Kenyon cells form microglomeruli, distinct synaptic complexes with the presynaptic boutons of olfactory projection neurons. Tools were developed for high-resolution imaging of pre- and postsynaptic compartments of defined calycal microglomeruli. This study shows that preventing firing of action potentials or synaptic transmission in a small, identified fraction of projection neurons causes alterations in the size, number, and active zone density of the microglomeruli formed by these neurons. These data provide clear evidence for activity-dependent organization of a circuit within the adult brain of the fly (Kremer, 2010).
Odors encountered in the environment and detected by olfactory sensory neurons are initially processed in a first olfactory center, the antennal lobe in insects or the olfactory bulb in mammals. This olfactory information is then conveyed by insect antennal lobe projection neurons or mammalian mitral/tufted cells to secondary centers for odor recognition and the formation of olfactory memories. These two functions appear to be accomplished by two regions in the fly brain, the lateral horn and the mushroom body, respectively. Changes in the olfactory environment are reflected by changes in activity at the mushroom body input synapses. Furthermore, because projection neurons can house an appetitive memory trace, the mushroom body input synapses might be potentially involved in olfactory memory formation. It is unknown, though, whether alterations of presynaptic activity or formation of memories induce structural changes in the mushroom body (Kremer, 2010).
In the Drosophila brain, most antennal lobe projection neurons send axonal projections terminating with bulbous boutons into the mushroom body calyx. Here they form specialized synaptic complexes, called microglomeruli (Yasuyama, 2002; Leiss, 2009), with the dendrites of mushroom body Kenyon cells, which are essential for the formation and retrieval of olfactory memories. Within a microglomerulus, a projection neuron bouton is enwrapped by actin-rich, claw-like, dendritic endings of more than one Kenyon cell and forms multiple synapses with these Kenyon cells' claws, each including a presynaptic active zone and a postsynaptic density. In social insects, the size and number of microglomeruli are modified in correlation with changes in the sensory environment. This study asked directly whether silencing olfactory projection neuron presynaptic activity or blocking their synaptic transmission alters the organization of calycal microglomeruli of Drosophila (Kremer, 2010).
To this end, genetic tools were generated to identify the microglomeruli and the sites of synaptic contact within them. Projection neurons are the only reported cholinergic input to the mushroom body calyx. Therefore, a fusion of the MB247 fragment of the D-mef2 promoter, active in a large subset of Kenyon cells, and the Dα7 subunit of the acetylcholine receptor tagged with eGFP were constructed (MB247-Dα7-GFP) to visualize the postsynaptic rim formed by claw-like dendritic endings of multiple Kenyon cells around each projection neuron bouton. The localization of Dα7-GFP within the calyx appeared to be specific for the postsynaptic densities of the Kenyon cell claws, and it closely matched the active zone labeling in the projection neuron boutons. Importantly, expressing this construct did not affect the active zone number in the calyx (Kremer, 2010).
Attempts were made to label the presynaptic active zones associated with postsynaptic densities. The active zone protein Bruchpilot (BRP) shapes the presynaptic active zone T bar and is essential for proper active zone function. A fluorescently tagged fragment of BRP, which depends on endogenous BRP for localization (UAS-brp-shortcherry), represents a reliable marker for active zones. Upon specific expression of UAS-brp-shortcherry in projection neurons, discrete BRP-shortcherry dots lined the inner rim of the Kenyon cell claw, closely matching the Dα7-GFP signal at putative sites of synaptic contact (Mz19-Gal4). The number of active zones is not affected by the expression of UAS-brp-shortcherry (using Mz19-Gal4) (Kremer, 2010).
Previous data suggested that simple complete sensory deprivation experiments did not elicit detectable changes in the calyx. Therefore, a competitive situation in the calyx was constructed between silenced and nonsilenced projection neurons and among dendrite claws of the same Kenyon cell receiving normal or no presynaptic input. Thus a defined subset of microglomeruli was manipulated and differentially labeled, highlighted by the Mz19-Gal4 driver. Mz19-Gal4 is expressed after 18 hr after puparium formation in 10-13 projection neurons whose dendrites are restricted to three glomeruli in the antennal lobe (DA1, VA1d, and DC3; and form boutons in a confined area of the calyx. Mz19-Gal4-driven UAS-brp-shortcherry signal was used to identify the subset of microglomeruli formed by these projection neurons. Whereas calycal microglomeruli were highlighted with MB247-Dα7-GFP, the Mz19-positive subpopulation was identified by BRP-shortcherry and MB247-Dα7-GFP (Kremer, 2010).
Within each calyx, the Mz19-positive microglomeruli were compared with those in which no Mz19-Gal4-driven expression of brp-shortcherry was observed. This experimental setup also allowed the problems posed by the large variability of overall brain volume and calycal size among animals, to be obviated independently of their genotype (in these experiments, approximately 10% of the calycal volume), and by potential differences in image acquisition and calycal labeling among animals. These factors could, in principle, hamper the detection of small morphological changes (Kremer, 2010).
It was reasoned that the structurally repetitive organization of the calyx, the introduction of a competitive situation within the calyx, and the specificity of the developed markers might facilitate revealing alterations induced by changes in presynaptic activity (Kremer, 2010).
To address whether the size and number of microglomeruli and the active zone distribution in adult calyces depend on presynaptic activity, attempts were made to silence or at least drastically reduce firing of the Mz19-positive projection neuron population. Using the Mz19-Gal4 driver, UAS-dORK1.ΔC, which functionally acts as a constitutively open K+ selective pore or leak and should lead to hyperpolarization of the resting membrane potential, was expressed; UAS-dORK1.ΔNC, a nonconducting version of the same channel, served as a control. Whole-cell current-clamp recordings from the somata were performed in an isolated, intact brain preparation to analyze the intrinsic firing properties of the projection neurons. Seven-day-old adult males were used, and the recorded neurons were labeled with biocytin to confirm their identity. Mz19-positive projection neurons of both genotypes did not show spontaneous activity in the cell-attached configuration or in the whole-cell configuration (Kremer, 2010).
Next, it was asked whether the microglomeruli formed by boutons of the silenced Mz19-positive projection neurons were altered (Kremer, 2010).
For every experimental group, the two calyces of at least six 7-day-old adult males weew analyzed, and 60-100 confocal optical sections were obtained per calyx. To obtain an unbiased identification of microglomeruli in high numbers of single optical sections, software was developed for the automated detection of microglomeruli. In every optical section, microglomerular rings were identified based on the intensity of the Dα7-GFP signal, the size and shape of the structure, and whether the Dα7-GFP-positive structure surrounded a darker lumen. A microglomerulus was defined as the sum of a Dα7-GFP-positive ring object and the lumen it contained. The software detected more than 30% of the manually identified microglomeruli, including only 3% false positives. Importantly, the overall size distribution of the microglomeruli was not significantly different between manual and software-based identification, suggesting that the software detection is unbiased. Furthermore, by using this approach, it was possible to detect alterations in the number of Mz19-positive microglomeruli obtained by overexpression of PI3K, a manipulation that induced bouton sprouting of ellipsoid body projection neurons and served as a positive control (Kremer, 2010).
Thus the Mz19-positive neurons were silenced by expressing dORK1.ΔC. It was found that the fraction of Mz19-positive microglomeruli per calyx was significantly increased compared to the nonsilenced dORK1.ΔNC control. It should be noted that, in motorneurons, hyperactivation -- and not suppression of activity -- leads to bigger axonal elaborations (Kremer, 2010).
Moreover, it was observed that the relative size of the microglomeruli was increased. This general enlargement of microglomerular size upon silencing correlated with an increase of the relative size of the Dα7-GFP-positive ring, which was, however, not significant (Kremer, 2010).
Hence, reducing the activity of the Mz19-positive projection neurons led to an increase in the number of the microglomeruli formed by those neurons. Additionally, the relative size of the microglomeruli increased (Kremer, 2010).
Therefore, it was next asked whether the number of individual presynaptic active zones per microglomerulus would increase as well or whether only size changes in the postsynaptic densities were taking place (Kremer, 2010).
Individual synaptic release sites are characterized by a presynaptic active zone, identifiable by BRP. Thus, the BRP-shortcherry puncta weew analyzed in calyces of flies expressing dORK1.ΔNC or dORK1.ΔC and brp-shortcherry under the control of Mz19-Gal4. The BRP-shortcherry puncta were counted using software for semiautomated detection applied to 3D reconstructions of the whole calyx (Kremer, 2010).
Strikingly, silencing the presynaptic neurons with dORK1.ΔC induced a clear increase in the number of BRP-shortcherry puncta per calyx compared to the control. This increase could simply be due to the above-described higher number of Mz19-positive microglomeruli obtained upon silencing. Therefore the active zone density in the Mz19-positive terminals was determined. Silencing those projection neurons resulted in a total increase in synaptic density in the Mz19-positive terminals; no significant increase was seen in the total area of the presynaptic terminals. The size of single active zones was not modified in silenced projection neurons with respect to the control. Hence, silencing or strongly reducing the generation of action potentials in projection neurons induced increased active zone density (Kremer, 2010).
In summary, the microglomeruli formed by silenced projection neurons were more numerous compared to the control. Additionally, the postsynaptic domain was larger and the density of presynaptic active zones was higher in the silenced rather than in the unaffected microglomeruli (Kremer, 2010).
The overexpression of dORK.1ΔC in projection neurons led to hyperpolarization, decreased input resistance, and subsequent inhibition of action potential firing, and thus, presumably, suppression of action potential evoked synaptic transmission. To dissect the contribution of these components, synaptic vesicle fusion was specifically suppressed using tetanus toxin (UAS-TNT) under the control of Mz19-Gal4. As a consequence, the relative size of the microglomeruli was significantly increased. Because this result was similar to the effect of silencing the presynaptic neurons with dORK1.ΔC, increase of the synaptic complex size might be caused by the loss of synaptic transmission in both situations. In contrast to the effect caused by dORK1.ΔC expression, however, the fraction of Mz19-positive microglomeruli was decreased upon expression of TNT. Also, the number and density of active zones were clearly diminished upon TNT expression. Thus, the number of microglomeruli and the active zone density are distinctly regulated depending on the manipulation (Kremer, 2010).
It is suggested that antagonistic mechanistic components might confront each other here. First, a mechanism seems to sense activity within projection neurons. If neuronal activity is suppressed, a coherent 'compensatory' response is triggered, increasing bouton size and number, as well as the density of active zones at the affected terminals. In mammals, neuronal activity was found to effectively control neuronal gene transcription and translation. Second, there appears to be a homeostatic compensation within the microglomerular microcircuit of the loss of synaptic transmission, leading to increased bouton and postsynaptic ring size. Finally, loss of transmission per se induces a reduction in the active zone density and in the number of microglomeruli. How these phenomena interact throughout physiological adaptations will be interesting to address in the future (Kremer, 2010).
This study has described changes in the number of calycal microglomeruli, as well as in their pre- and postsynaptic composition, that depend on the activity state of the presynaptic neuron and on transmission. Thus, this study has revealed that the structural and synaptic organization of the adult mushroom body calyx of Drosophila requires appropriate presynaptic activity and synaptic transmission (Kremer, 2010).
Microglomeruli are more ill defined in calyces of just-eclosed males, suggesting a reorganization of the circuit during early adult life. In line with this hypothesis, the microglomerular circuit might be refined after eclosion in Apis. It is thus possible that microglomeruli form normally but that projection neuron input is required during a hypothetical refinement phase. Alternatively, the initial formation of microglomeruli may be affected by the absence of appropriate presynaptic activity and/or synaptic transmission. In support of this second scenario, modification of synaptic input alters the dendritic differentiation of a motor neuron in fly embryos (Tripodi, 2008). At this point, these two possibilities cannot be distinguished (Kremer, 2010).
Previous evidence indicated that, in the adult fly brain, the establishment of correct connectivity is largely independent of activity. Nonetheless, the activity-dependent component of circuit organization might be difficult to detect above interanimal variability. Thus, it is proposed that the type of approach described in this study, including internal controls, high-resolution imaging of pre- and postsynaptic elements, and software-based analysis, will be necessary to reveal similar phenomena in other regions of the fly brain. In the calyx, this analysis was facilitated by the organization in microglomeruli, recognizable repetitive structural elements (Kremer, 2010).
In addition, it is reckoned that the effect of activity on circuit organization might be best revealed by unbalancing the circuit as this study did by silencing only a defined fraction of olfactory projection neurons. As an example, monocular deprivation experiments, rather than binocular elimination of visual input, were instrumental to the understanding of the role of activity in shaping the visual circuit in mammals (Kremer, 2010).
Projection neuron activity delivers a representation of the olfactory environment to the calyx. The effect of the manipulations of projection neuron activity in this study suggests that olfactory experience modulates the calycal circuit. In line with this hypothesis, sensory experience modifies properties of microglomeruli in the honeybee and ant. The functional outcome of these adaptations remains to be investigated. Importantly, in Drosophila, alterations of olfactory experience determine volumetric changes of adult antennal lobes. Furthermore, because projection neurons can house an appetitive memory trace, the mushroom body input synapses might be potentially involved in olfactory memory formation. Given the high resolution of the system that this study has established, it is envisaged that the next challenge will be to address directly whether the structure of defined microglomeruli can be modulated upon the establishment of long-term appetitive memories (Kremer, 2010).
Drosophila show innate olfactory-driven behaviours that are observed in naive animals without previous learning or experience, suggesting that the neural circuits that mediate these behaviours are genetically programmed. Despite the numerical simplicity of the fly nervous system, features of the anatomical organization of the fly brain often confound the delineation of these circuits. This study identified a neural circuit responsive to cVA, a pheromone that elicits sexually dimorphic behaviours. Neural tracing using an improved photoactivatable green fluorescent protein (PA-GFP) was combined with electrophysiology, optical imaging and laser-mediated microlesioning to map this circuit from the activation of sensory neurons in the antennae to the excitation of descending neurons in the ventral nerve cord. This circuit is concise and minimally comprises four neurons, connected by three synapses. Three of these neurons are overtly dimorphic and identify a male-specific neuropil that integrates inputs from multiple sensory systems and sends outputs to the ventral nerve cord. This neural pathway suggests a means by which a single pheromone can elicit different behaviours in the two sexes (Ruta, 2010).
The male pheromone 11-cis-vaccenyl acetate (cVA) elicits male-male aggression and suppresses male courtship towards females as well as males. A single class of olfactory neurons mediates behavioural responses to a Drosophila sex pheromone. In females, cVA activates the same sensory neurons to promote receptivity to males. cVA-induced aggregation behaviour is shown by both sexes. What neural circuits permit a single pheromone acting through the same set of sensory neurons to elicit several distinct and sexually dimorphic behavioural responses? (Ruta, 2010).
The sensory neurons that express the odorant receptor Or67d respond to cVA, and these neurons converge on the DA1 glomerulus in the antennal lobe. Projection neurons (PNs) that innervate the DA1 glomerulus terminate in the lateral horn of the protocerebrum. Comprehensive maps of Drosophila higher olfactory centers: spatially segregated fruit and pheromone representation. Previous experiments showed that the DA1 axons are sexually dimorphic and reveal a male-specific ventral axonal arborization in the lateral horn (Datta, 2008). This dimorphism by itself might explain the sexually dimorphic behaviours or, alternatively, it might presage iterative anatomical dimorphisms at each stage in the circuit to descending output. Therefore, a neural circuit was characterized that transmits information from the DA1 PNs to the ventral nerve cord (see Photoactivation identifies dimorphic lateral horn neurons). The analysis was restricted to neurons that express the sexually dimorphic transcription factor fruitless (FruM). FruM is expressed in both Or67d-expressing sensory neurons and DA1 PNs and governs the development of dimorphic neural circuitry including the male-specific axonal arborization of DA1 PNs. In addition FruM specifies many male-specific behaviours, including those that are mediated by cVA (Ruta, 2010).
In initial experiments PA-GFP, a photoactivatable GFP, was used to identify Fru+ third-order neurons whose dendritic processes are closely apposed to DA1 axon termini. A strategy was developed in which two-photon photoactivation is restricted to a small, circumscribed region of a neuron's axonal arborization with the expectation that this would label the postsynaptic cells by photoconversion of PA-GFP in their dendrites. To ensure that this limited activation could produce sufficient signal from the photoconverted fluorophore to illuminate third-order neurons and their most distal processes, two new enhanced PA-GFPs were generated, namely C3PA-GFP and SPA-GFP (Ruta, 2010).
Photoconversion of the DA1 glomerulus in flies expressing C3PA-GFP or SPA-GFP under the control of fruGAL4 readily identified the axonal arborizations of the DA1 PNs. Then the volume of neuropil circumscribing the DA1 axon termini was photoactivated and four clusters of presumptive third-order neurons were reproducibly labelled in the lateral horn of male flies. Labelling of the two dorsal clusters, DC1 and DC2, was observed only in males; the clusters were either absent in the female or lacked projections into the ventral lateral horn. The lateral cluster LC1 was present in the two sexes but was dimorphic in both number and projection pattern. LC2 did not show an apparent numeric or anatomical dimorphism. Photoactivation of DA1 axon terminals in male flies that express C3PA-GFP pan-neuronally labelled few additional neurons and suggests that these four Fru+ clusters constitute the major potential recipients of DA1 input (Ruta, 2010).
These photoactivation experiments identify clusters of third-order neurons in the lateral horn that are anatomically poised to propagate dimorphic responses to cVA. However, anatomical proximity does not ensure functional connectivity. Therefore a method was developed to specifically activate individual glomeruli and simultaneously record from presumptive downstream neurons to determine whether the lateral horn clusters that were identified receive excitatory input from DA1 PNs. DA1 PNs were selectively stimulated by positioning a fine glass electrode in the centre of the DA1 glomerulus and iontophoresing acetylcholine, the neurotransmitter that excites PNs, into the glomerular neuropil. Varying the iontophoretic voltage allowed variation of the frequency of elicited action potentials systematically in DA1 PNs up to 250, a value close to the upper limit of cVA-elicited responses measured in these PNs (Datta, 2008; Schlief, 2007). Activation of the DA1 glomerulus over this voltage range excited DA1 PNs specifically and elicited no response in PNs innervating other glomeruli in the antennal lobe. Stimulation of the neighbouring glomeruli, VA1d and VA1lm, similarly elicited the specific excitation of their cognate PNs but did not activate DA1 PNs (Ruta, 2010).
Next, whether stimulation of the DA1 glomerulus would result in the excitation of neurons within the four clusters in the lateral horn that were identified, a result indicative of functional synaptic connections with DA1 PNs, was examined. The genetically encoded calcium indicator GCaMP3 was examressed in Fru+ neurons in male flies and two-photon imaging was used to monitor increases in Ca2+ concentration in the lateral horn clusters in response to DA1 excitation. Stimulation of the DA1 glomerulus elicited large increases in Ca2+ in neurons within the DC1 and LC1 clusters, with a far weaker response being observed in LC2. The small DC2 cluster is difficult to identify reliably because of the low basal fluorescence of GCaMP3; it was therefore not examined by optical imaging. The Ca2+ response in DC1 was specific for DA1 activation and was not observed when the stimulating electrode was repositioned in two neighbouring glomeruli, VA1d and VA1lm. These optical imaging experiments demonstrate that neurons within the DC1 and LC1 clusters extend processes in anatomical proximity to the DA1 axons and receive excitatory input from DA1 PNs. Immunostaining indicated that neurons within the LC1 cluster produce the inhibitory neurotransmitter GABA (γ-aminobutyric acid). Electrophysiological experiments suggested that DC1 neurons are excitatory but the neurotransmitter remains unknown (Ruta, 2010).
Focused was placed on the male-specific DC1 neurons to define a cVA-responsive circuit. The DC1 cluster consists of ~19.7 cell bodies (n = 10) in a spatially stereotyped location in the dorsal aspect of the anterior protocerebrum. Double labelling experiments revealed that the DC1 processes interdigitate richly with DA1 axons in the lateral horn. Photoactivation of single DC1 cell bodies indicated that the cluster is composed of several anatomical classes of neurons characterized by distinct branch patterns within the protocerebrum that are likely to receive and integrate inputs from both olfactory and non-olfactory brain centres (Ruta, 2010).
Electrophysiological recordings were performed to examine the response of DC1 neurons to both DA1 stimulation and cVA exposure. Selective stimulation of the DA1 glomerulus evoked action potentials in 66% of male-specific DC1 neurons recorded in the loose patch configuration. Among responsive DC1 neurons, it was observed that the sensitivity to DA1 stimulation differed. This functional heterogeneity within the DC1 cluster observed by both electrical and optical recording was consistent with the anatomical heterogeneity of dendritic fields in the lateral horn observed for single DC1 neurons (Ruta, 2010).
In accord with the imaging experiments, the electrophysiological response of DC1 neurons is selectively tuned to DA1 input. After recording the response of a DC1 neuron to DA1 stimulation, the stimulating electrode was repositioned into 6-11 other superficial glomeruli located throughout the antennal lobe. DC1 neurons activated by minimal DA1 stimulation were either weakly excited or unresponsive to strong stimulation of other glomeruli. Stimulation of the Fru+ VA1lm glomerulus failed to excite DC1 neurons despite the close proximity of DA1 and VA1lm axons (Jefferis, 2007). These observations demonstrate the specificity of glomerular excitation and reveal that olfactory input to DC1 is mediated largely by the DA1 glomerulus and not by the activation of at least 11 other glomeruli, suggesting that DC1 neurons receive olfactory stimulation only from cVA. Next cVA-evoked responses from DC1 neurons were recorded in an intact fly preparation. It was observed that 62% of DC1 neurons were responsive to cVA over a range of concentrations. The input-output relationship of DC1 neurons was similar whether action potentials were evoked in DA1 PNs through direct glomerular stimulation or by pheromonal excitation of the antenna, suggesting that DC1 neurons are excited primarily by means of DA1 input. Both Or67d-expressing sensory neurons and DA1 PNs have been shown to be selectively tuned to cVA. DC1 neurons showed similar odorant selectivity and fired only weakly in response to stimulation of the antenna with a cocktail of ten fruit-derived odorants that excite a majority of glomeruli. Thus, DC1 neurons are likely to receive direct excitatory feedforward input from DA1 PNs and respond selectively to cVA (Ruta, 2010).
Photoactivation of PA-GFP in presynaptic DA1 axonal arborizations, in concert with electrophysiology, has identified postsynaptic third-order neurons in the lateral horn that are responsive to cVA. The iterative use of this strategy could allow definition of the complete cVA circuit from sensory input to descending output. Tracing of photoactivated DC1 axons revealed that they terminate proximally within a triangular neuropil in the lateral protocerebrum (the lateral triangle) and extend distal processes to a previously uncharacterized tract within the superior medial protocerebrum (the SMP tract). The lateral triangle and SMP tract are sexually dimorphic neuropils that are absent in females (Ruta, 2010).
Photoactivation of the terminal arborizations of DC1 axons was performed to identify neurons innervating the lateral triangle and SMP tract. Dense labelling was observed in these structures arising from the rich male-specific projections of multiple classes of Fru+ neurons. Dimorphic LC1 neurons that receive direct innervation from DA1 PNs send inhibitory projections to the lateral triangle and SMP tract. Dimorphic mAL neurons were also observed extending from the suboesophageal ganglion (SOG) and terminating within these neuropils. In addition, these neuropils are innervated by male-specific P1 interneurons implicated in the initiation of male courtship behaviour. Thus, the lateral triangle and SMP tract receive dimorphic projections from several brain regions including other sensory processing areas, suggesting that these neuropils may integrate sex-specific information from multiple sensory systems (Ruta, 2010).
Several neurons that innervate the lateral triangle and SMP tract also extend processes that descend into the ventral nerve cord, suggesting that these potential fourth-order descending neurons may transmit information from cVA-responsive sensory neurons to the ganglia of the ventral nerve cord. Descending neurons that innervate the lateral triangle and SMP tract were characterized by photoactivation of the cervical connectives conveying neural signals from the brain to the ventral nerve cord. In the brain, the processes of these descending neurons showed a marked dimorphism that was apparent in their extensive innervation of the male-specific SMP tract and lateral triangle. A descending neuron, DN1, absent in females, was observed in the ventral posterior aspect of the male brain, at the midline. Labelling of this male-specific cell body revealed short processes terminating within the lateral triangle and SMP tract, and a long descending process entering the ventral nerve cord and terminating within the thoracic and abdominal ganglia. Electroporation of DN1 with Texas Red dextran, followed by photoactivation of the DC1 cluster, revealed extensive intermingling of the green DC1 axons with the red dendrites of the descending neuron. This suggests that this descending neuron is anatomically poised to make direct synaptic contacts with third-order, cVA-responsive DC1 neurons (Ruta, 2010).
Whole-cell patch clamp recordings were performed on DN1 to discern whether it transmits pheromonal information to the ventral nerve cord. In response to either exposure of the antenna to cVA or direct stimulation of the DA1 glomerulus, DN1 received a barrage of excitatory postsynaptic potentials (EPSPs) bringing its membrane potential close to or past threshold. To determine whether this response was mediated by DC1 neurons, a microlesion technique was devised exploiting the spatial precision of a two-photon laser to effectively sever DC1 inputs into the lateral triangle and SMP tract. Optical recordings revealed that microlesioning of DC1 dendrites resulted in the immediate and selective loss of DC1 responses to DA1 stimulation without affecting the excitation of neighbouring LC1 dendrites and cell bodies. Severing the connections between DA1 and DC1 resulted in an almost complete loss of the response of DN1 to stimulation of DA1. The response of this descending neuron was far weaker than the response of early neural participants in this circuit. However, the observation that two-photon-mediated microlesions in DC1 resulted in a decrease of more than 70% in the DN1 response to stimulation of DA1 suggests that, despite its weak excitation, DN1 is a component of this circuit. A more potent response may require a more natural setting that integrates pheromonal input with other sensory signals. Taken together, these experiments suggest that male-specific DC1 neurons excite the male-specific DN1 through synaptic connections within the dimorphic lateral triangle and SMP tract. Thus, olfactory information may be processed by as few as three synapses within the brain before descending to initiate motor programs within the ganglia of the ventral nerve cord. Although a behaviour elicited by this circuit cannot yet be defined, it is presumed that it mediates a component of the innate behavioural repertoire initiated by cVA (Ruta, 2010).
This cVA-responsive circuit provides insights into the mechanism by which sensory information received by the antenna may be translated into motor output. First, the circuit is concise: as few as four neuronal clusters and three synapses bring pheromonal signals from the periphery to the ganglia of the nerve cord. This minimal circuit assumes monosynaptic connections between the neurons that that were identified. This circuit is shallow but seems to include adequate synaptic connections to permit the integration of olfactory and non-olfactory information. Third-order lateral horn neurons reveal a capacity for multisensory integration with inputs to the DC1 cluster from the SOG and from the optic lobe. The lateral triangle and SMP tract also integrate sensory inputs from DC1 and LC1 as well as inhibitory projections from the SOG. This integration provides the opportunity for other sensory signals emanating from a cVA-scented fly to modulate the response to the pheromone (Ruta, 2010).
Second, multiple neural components within the circuit are anatomically dimorphic, and this could explain the different behaviours elicited by cVA in males and females. The initial neural components of the circuit, Or67d-expressing sensory neurons and DA1 PNs, are dedicated to the receipt of a singular olfactory stimulus, cVA, and are equally responsive to the pheromone in the two sexes. However, dimorphisms are observed in the synaptic connections between the PNs and the third-order lateral horn neurons and define a node from which sex-specific neural pathways emanate. The DA1 PNs reveal dimorphic axon arborizations, but this dimorphism is only one component of a highly dimorphic circuit. These dimorphic arborizations synapse with male-specific DC1 neurons that send axons to a male-specific neuropil (the lateral triangle and SMP tract). One output of this neuropil is a male-specific descending neuron, DN1. This circuit is likely to participate in the generation of cVA-elicited behaviours observed only in males. The identification of a sex-specific circuit including extensive neuropils present only in males suggests pathways for dimorphic behaviours that differ from earlier proposals that invoke the differential activation of circuits that are common to the two sexes. DA1 PNs also synapse onto the cluster of LC1 neurons that are present in both sexes but are numerically and anatomically dimorphic. The multiple dimorphic targets of a singular olfactory input could explain how a pheromone acting through the same sensory inputs may elicit different behaviours in the two sexes (Ruta, 2010).
An animal's state of arousal is fundamental to all of its behavior. Arousal is generally ascertained by measures of movement complemented by brain activity recordings, which can provide signatures independently of movement activity. The relationships were examined among movement, arousal state, and local field potential (LFP) activity in the Drosophila brain. This study measured the correlation between local field potentials (LFPs) in the brain and overt movements of the fruit fly during different states of arousal, such as spontaneous daytime waking movement, visual arousal, spontaneous night-time movement, and stimulus-induced movement. The correlation strength between brain LFP activity and movement was found to be dependent on behavioral state and, to some extent, on LFP frequency range. Brain activity and movement are uncoupled during the presentation of visual stimuli and also in the course of overnight experiments in the dark. Epochs of low correlation or uncoupling are predictive of increased arousal thresholds even in moving flies and thus define a distinct state of arousal intermediate between sleep and waking in the fruit fly.
These experiments indicate that the relationship between brain LFPs and movement in the fruit fly is dynamic and that the degree of coupling between these two measures of activity defines distinct states of arousal (van Swinderen, 2004).
Sleep in fruit flies shares key characteristics with sleep in all other animals. In Drosophila, sleep is homeostatically regulated and is defined by increased arousal thresholds, and molecular changes correlated with sleep mirror similar changes occurring in mammals. Sleep measures, which include rest/activity data, arousal thresholds, and sleep rebound following deprivation, are most often quantified behaviorally by locomotor activity; an awake fly shows a high probability of walking within a 5 min period. Sleep in Drosophila is accompanied by decreased brain activity (10-100 Hz), as measured by local field potentials (LFPs) in the medial protocerebrum (mpc). In the preparation developed for these studies, sleep is defined by lack of fly movement for periods of more than 5 min and an increased arousal threshold. In this study movement was not monitored in freely moving flies. Instead, flies were tethered by their head and thorax, and movement was monitored by an infrared beam directed across their legs. Alternatively, a wire implanted into their thorax served as a movement detector. By these techniques, gross movements from the fly's wings, legs, and abdomen were monitored continuously to determine sleep states and arousal thresholds, and these were correlated with simultaneous brain activity recordings. A central finding (Nitz, 2002) is that that sleep in Drosophila is correlated with significantly decreased brain LFP activity, and by the same token, that waking is correlated with increased brain LFP activity in the medial protocerebrum (mpc). However, waking LFP activity is not well correlated with fly movement on a short time scale; moment-to-moment correlation between brain activity and movement potentials is insignificant and increases only moderately for longer (5 s) correlation bins. This observation is important because it uncouples the waking levels of brain activity from every movement and suggests that increased brain activity is truly a correlate of waking rather than a correlate of just the movement that accompanies most waking states. Similarly, van Swinderen (2003) showed that 20-30 Hz brain activity in response to visual salience (noticable visual stimulation) can be uncoupled from flight or movement behavior in the fruit fly. Increased arousal, as measured by increased responsiveness to a visual or mechanical stimulus, can therefore be manifested in the fly brain without necessarily being accompanied by gross behavioral changes. Behavior is usually correlated with states of arousal, especially over circadian time scales, but changes in arousal, as evidenced by neural signatures in the brain, can occur without changes in behavior. In the current study, the dynamic relationship between brain activity, movement, and arousal has been explore more closely in Drosophila. This study seeks to define how arousal is manifested over short time scales by examining the ongoing correlation between two parameters central to describing arousal: brain activity and movement (van Swinderen, 2004).
Spontaneous fly movement was monitored in 5 s bins with an electrode implanted into the thorax and brain activity was simultaneously recorded from electrodes inserted 75-100 μm into the medial protocerebrum with a reference electrode in the eye. Dye released from the mpc electrode tip showed that this brain-recording position in adult CS females is level with the base of the mushroom bodies, above the esophagus and in the vicinity of the central complex. The simultaneous recordings of spontaneous movement from the thoracic electrode and brain activity from the mpc revealed a correlation profile for this recording position. The correlation level is not equal for all frequencies (1-100 Hz) of brain activity. The higher frequencies (60-100 Hz) are more strongly correlated to movement than the lower frequencies in the 10-50 Hz range. The very lowest frequency range examined, 1-10 Hz, also shows a stronger correlation to movement than the 10-50 Hz bracket does. Among the lower frequencies, the 20-30 Hz bracket shows the lowest correlation to movement during spontaneous, daytime waking activity at this recording position (van Swinderen, 2004).
In a study of Drosophila LFP responses to visual stimuli, it has been shown that 20-30 Hz brain activity is associated with salience effects evoked by novelty, conditioning, and selective discrimination of visual stimuli (van Swinderen, 2003). In that study, the 20-30 Hz effects were found to be independent of spontaneous, gross movement. Such movement-independent changes in 20-30 Hz activity may account for some of the 10-50 Hz trough in the profile correlating brain activity and movement. Therefore two distinct frequency ranges emerge from these results: the lower range centered around 20-30 Hz (this is less correlated with unstimulated, waking movement but is associated with salience-related arousal), and the higher frequencies, which are more strongly correlated with unstimulated, waking movement but less associated with salience effects (van Swinderen, 2004).
Both visual and movement paradigms were combined in order to test the effect of visually induced arousal (van Swinderen, 2003) on the correlation profile coupling brain activity and ongoing movement. Introducing a visual stimulus (a rotating dark bar layered onto an unchanged lit background) to the fly uncouples brain activity from movement. That this uncoupling was most significant in the higher frequency range is surprising because these higher frequencies are not coupled to the visual response either. Neither low (10-50 Hz) nor high (60-100 Hz) frequencies by themselves change significantly in average power for the duration of the experiment in comparison to the imageless control, and average movement was unchanged as well. Rather, it appears that visual salience (which has a characteristic 20-30 Hz response (van Swinderen, 2003) uncouples most brain LFP activity (at this medial recording position) from ongoing movement activity. The correlation level between movement and brain LFP activity appears to depend on the fly's arousal state as well as on the frequency bracket examined. In the following experiments the relationship between the correlation phenotype and arousal was examined more closely by focusing on movement activity and two LFP frequency ranges: 20-30 Hz because of its association to salience effects and 80-90 Hz as a contrasting range that is more correlated to movement (van Swinderen, 2004).
These correlation studies were all performed for short time periods (200 s, or 40 five-second bins) during the day. In the absence of salient, rotating, visual stimuli, the correlation between brain LFP activity and movement was consistent for these daytime experiments. Whether such consistency persists throughout much longer recording sessions (12 hr) extending through the animal's night time, when characteristic changes in arousal state are endogenously generated, was examined. Epochs without movement more than 5 min long are associated with decreased power for all frequencies in the brain. However, such immobile epochs do not constitute the majority of a tethered fly's night time behavior, in contrast to the behavior of a freely walking fly. In fact, tethered flies move most of the time, even at night, and will be rendered immobile by sleep for only about 20% of the night, not necessarily contiguously. Whether the correlation profile (between movement and brain LFP activity) changed during spontaneous night time movement was investigated (van Swinderen, 2004).
The correlation was analyzed for six flies kept in sealed and humidified chambers during overnight (12 hr) experiments performed in complete darkness. All animals were still alive and moving in the morning after lights were turned back on. Average movement activity during the first daylight hour after the experiments was not significantly different from pre-experiment levels. For each hour of the night, the correlation coefficient between brain activity (20-30 Hz, 80-90 Hz) and movement was calculated from averages of 5 s activity data. In all six flies, the correlation between brain activity and movement decreased during several consecutive hours of the night compared to the first two hours of the night. Both frequency ranges showed a proportionally similar decrease in correlation to movement. These decreases did not necessarily occur during the same contiguous hours in all animals. This 'correlation trough' was maximal in hours 6-7 after dark for four flies and hours 3-4 for two flies. Average correlation levels increased later in the night) to pre-trough levels, before the lights were turned back on (van Swinderen, 2004).
Average hourly movement and average LFP amplitude at both 20-30 and 80-90 Hz also decrease during the night, but the decrease of either is not significant during the respective 'correlation trough' hours compared to the first two hours of the experiments. Thus, the loss of correlation between brain activity and movement cannot be accounted for by any significant changes in the hourly averages of either brain activity or movement. The epoch in which both average hourly movement and LFP power do attenuate significantly, during the last hours of the night, exhibits a correlation between the two statistics that is as high as pre-trough levels (van Swinderen, 2004).
Closer inspection of hourly averages through the night reveals that average movement can increase while average brain activity does not. Indeed, combined data from all six flies show that the variance in 20-30 Hz activity decreases significantly during the respective trough hours compared to the first hours of the night. Variance in 80-90 Hz brain activity was also significantly decreased during the 'correlation trough' hour. In comparison, the variance of movement activity was not significantly decreased during the trough hours compared to hours 1-2. Such unmatched changes in variance may partially explain why a decreased correlation with brain activity is seen during consecutive hours of the night (van Swinderen, 2004).
Because the records also show evidence of sleep, the relationship between the LFP/movement correlation dynamics and epochs of extended immobility embedded throughout the overnight records was investigated. Long bouts of quiescence (>5 min) were immediately preceded by significantly lower levels of correlation to movement (for both 20-30 Hz and 80-90 Hz), compared to the correlation levels seen immediately after the resumption of movement. Brain activity and movement are thus more uncoupled immediately before quiescence as well as during contiguous hours of the night (van Swinderen, 2004).
Sleep is typically associated with immobility, but determining sleep in an animal is also contingent on testing arousal thresholds by measuring behavioral responsiveness to a stimulus. Because the average correlation between movement and brain activity is dynamic during the night and because sleep is preceded by uncoupling, it was questioned whether the loss of correlation between brain and body was similarly associated with altered behavioral responsiveness to a test stimulus, as was shown for sleep (van Swinderen, 2004).
Six additional flies were prepared for testing arousal thresholds throughout the night. Responsiveness to arousing stimuli (measured by increased movement following mechanical taps or light flashes) was analyzed in terms of the preceding level of correlation between movement and brain activity. Using an automated online paradigm, the thoracic channel was periodically scanned for brief epochs (5 s) of immobility before delivering a stimulus, so that all subsequent behavioral responses were compared with this baseline immobility. Responsive animals displayed, on average, a greater correlation between movement and 20-30 Hz brain activity during the 3 min preceding the test stimulus. The level of correlation between 80-90 Hz brain activity and movement was also predictive of responsiveness to the test stimulus. By the same token, unresponsive flies displayed a significantly decreased correlation between brain activity at both frequencies and ongoing movement in the 3 min preceding the test stimulus (van Swinderen, 2004).
As in the overnight 'correlation troughs', correlation level in these arousal experiments was not dependent on the amount of movement displayed by the animal. Different levels of movement showed similar levels of correlation to brain activity when considered irrespective of responsiveness to stimuli. Unresponsiveness to a test stimulus is therefore predicted by a decreased correlation between brain LFPs and movement as well as by prolonged immobility in these tethered preparations. These predictors of arousal level are distinct but complementary. As in Nitz (2002), unresponsiveness was also associated with less average movement in the minutes preceding a test stimulus because these cases included instances of extended (> 5 min) immobility. The predictive value for arousal level of the correlation between movement and LFPs was significant, however, even when these few cases were removed from the analysis (van Swinderen, 2004).
In summary, the correspondence between movement and brain LFP activity in the mpc decreases significantly during overnight recordings, and such uncoupling is characterized by increased arousal thresholds. These results demonstrate that ongoing changes in arousal levels in the fly do not necessarily parallel spontaneous movement activity. Rather, changes in arousal are marked by changes in the coupling dynamics between brain activity and movement (van Swinderen, 2004).
These studies demonstrate, by simultaneously monitoring brain LFPs and gross movement in a tethered Drosophila preparation, that brain activity can be uncoupled from the body activity typically used as the measure of arousal state in nonhuman animals. It was thus possible to examine arousal in terms of the correlation between two relevant yet distinct measures of fly activity. The results suggest that ongoing changes in arousal in the fly can be effectively studied as a function of the degree of coupling between brain LFP activity and movement (van Swinderen, 2004).
In humans and other mammals, most states of heightened arousal (waking, attention), as well as 'paradoxical' (REM) sleep, are accompanied by increased high-frequency (40-80 Hz) field activity in the brain, whereas deep sleep is associated with slow activity. Such brain signatures can be uncorrelated to bodily movement, as in paradoxical sleep and in sleep disorders such as narcolepsy/catalepsy or somnambulism, although most sleep is indeed accompanied by quiescence. In fruit flies, extended immobility also correlates with sleep and associated changes in brain activity. Yet, changes in fly brain LFP activity are not always associated with movement on shorter time scales. Because behavioral changes, evidenced by movement of some kind, are the primary way of ascertaining arousal states in nonhuman animals, the relationship between arousal and movement can be difficult to disentangle. Brain activity may be closer to reflecting ongoing changes in arousal in the fruit fly, and the uncoupling between brain activity and movement appears to be a useful indicator of a change in arousal state (van Swinderen, 2004).
20-30 Hz brain activity plays a crucial role in visually directed arousal (van Swinderen, 2003). In the current study, 20-30 Hz brain activity is less coupled to spontaneous, waking movement than are other frequencies, including the 80-90 Hz range contrasted throughout this study. The higher frequencies (of which 80-90 Hz is just representative) may represent a variety of stimuli coming from the body, whereas the 20-30 Hz signature might represent the fly's version of a 'spotlight.' In support of this idea, the level of correlation between movement and 20-30 Hz brain activity increases up to 80-90 Hz correlation levels during the initial hours of the overnight experiments, immediately after epochs of extended quiescence, and also throughout overnight arousal-testing experiments. This contrasts with the lower correlation (approximately 0.2) found during the day for the 20-30 Hz range in spontaneously moving flies. 20-30 Hz activity can be selectively correlated with visual stimuli (van Swinderen, 2003). For an awake fly in complete darkness at night, when visual (as well as auditory and vibrational) stimuli are lacking, this signal may associate with a different set of stimuli, such as those engendered by the fly's own movement (van Swinderen, 2004).
The most surprising outcome of overnight studies is the finding that fruit flies display a distinct behavioral state intermediate between sleep and waking; this state is defined by heightened arousal thresholds and is characterized by the loss of correlation between ongoing movement and LFP activity. In unperturbed flies during the course of overnight experiments, such loss of correlation is consolidated during several contiguous hours of the night. Additionally, periods of low correlation between brain activity and movement immediately precede epochs of extended quiescence. During sleep, already well characterized in this organism, animals become immobile, and all brain frequencies attenuate to equal extents (Nitz, 2002). The uncoupled state in moving animals may enable subsequent sleep or may itself accomplish certain key sleep functions. Beyond increased arousal thresholds, both behavioral states are also similar in the uniformity of their effects on the different frequency ranges. In the low-arousal, moving state, correlation to movement is decreased proportionally for both 20-30 Hz and 80-90 Hz frequency ranges, and during sleep, both frequency ranges decrease proportionally in terms of overall power. In contrast, in awake flies, frequencies between 1 and 100 Hz are partitioned by salience effects in the 20-30 Hz range (van Swinderen, 2003) and movement effects in the higher frequencies (e.g., 80-90 Hz). When flies are in either of the two states characterized by increased arousal threshold, there is a corresponding decrease in the variance or amount of information in the entire LFP signal (van Swinderen, 2004).
Experiments with visual stimuli show that a form of arousal directed to salient images (van Swinderen, 2003) also uncouples brain activity from movement, even at the higher frequencies not associated with visual salience. This brings up the possibility that during the uncoupled state at night flies may still be partially aroused (as suggested, after all, by their ongoing movement), despite their higher arousal thresholds. This paradox may be partially understood if one considers some common features between sleep and selective attention, both arousal states with behavioral and neural correlates in the fruit fly. Although humans perceive sleep and attention as clearly different states of arousal, both are defined to a certain extent by uncoupling. During sleep, most external stimuli are rendered less accessible, thereby uncoupling the brain from those sensory modalities. During selective attention, an animal may be seen as having partitioned its arousal between a high level directed at the salient stimulus and a low level directed at everything else. The current demonstration of uncoupling between brain activity and movement is consistent with Drosophila's ability to suppress brain responses to simultaneous unattended stimuli (van Swinderen, 2003). Similarly, responses to visual stimuli persist in the optic lobes during sleep, whereas the 20-30 Hz response in the medial brain is attenuated (van Swinderen, 2003). These ideas are extended, in this study, to propose that such uncoupling is a common feature of different arousal states and that fly brain activity might be uncorrelated from movement at night by a similar mechanism as that which suppresses visual stimuli. Altogether, these findings suggest that arousal states in the fly are a function of the degree of coupling within the nervous system and that changes in arousal can be defined more accurately by such criteria in the fly when considered in conjunction with the standard behavioral measures of responsiveness (van Swinderen, 2004).
Arousal in Drosophila, like consciousness in humans, is unlikely to be localized to a unique set of cells in the brain. Rather, arousal probably recruits dynamic networks extending throughout the brain, a phenomenon that may be accessible to a combined genetic and electrophysiological approach in Drosophila (van Swinderen, 2004).
Sleep is one of the few major whole-organ phenomena for which no function and no underlying mechanism have been conclusively demonstrated. Sleep could result from global changes in the brain during wakefulness or it could be regulated by specific loci that recruit the rest of the brain into the electrical and metabolic states characteristic of sleep. This study addresses this issue by exploiting the genetic tractability Drosophila, which exhibits the hallmarks of vertebrate sleep. Large changes in sleep are achieved by spatial and temporal enhancement of cyclic-AMP-dependent protein kinase (PKA) activity specifically in the adult mushroom bodies of Drosophila. Other manipulations of the mushroom bodies, such as electrical silencing, increasing excitation or ablation, also alter sleep. These results link sleep regulation to an anatomical locus known to be involved in learning and memory (Joiner, 2006).
To determine whether specific brain loci regulate sleep, the GAL4/UAS (upstream activating sequence) system was used to express a catalytic subunit of PKA in various regions of the fly brain. PKA was first expressed under the control of the RU486-inducible pan-neuronal driver elavGeneSwitch. Restricting the expression of PKA to adult neurons decreased daily sleep, supporting earlier studies with mutants such as dunce that increase PKA levels, and showing that PKA directly regulates sleep rather than a developmental process that might affect sleep. PKA was expressed under the control of different GAL4 drivers, and the changes in total daily sleep were examined in the different driver/transgene combinations relative to driver/background and background/transgene controls. When both controls were taken into account, the expression of PKA by only two drivers led to changes in sleep that exceeded 2 s.d. These were 201Y, which increased sleep by 75 +/- 3% and 93 +/- 4% respectively, and c309, which decreased sleep by 46 +/- 11% and 43 +/- 14% per day compared with the two sets of controls. Changes in sleep caused by all other GAL4 drivers remained within 1 s.d. of the mean (Joiner, 2006).
Next, whether activity levels during wake periods were affected by the 201Y and c309 drivers was examined. Many GAL4 driver/UAS-PKA lines were hypoactive, but line 201Y had normal waking activity. Similarly, activity normalized to waking time in c309 was not significantly higher in PKA-driven animals than in either control, indicating that c309 was not hyperactive. It is concluded that the sleep phenotypes of animals expressing PKA under control of the 201Y and c309 drivers are not associated with abnormal waking activity. Interestingly, both these drivers are known to be expressed in the mushroom bodies (MBs), a brain region implicated in associative learning (Joiner, 2006).
Given the strong, yet opposite, effects that 201Y and c309 had on sleep, their expression patterns in the fly brain were further characterized by crossing them into animals bearing a UAS transgene for green fluorescent protein (GFP). It was found that 201Y is expressed largely in the γ lobes and the core region of the α/β lobes of the MBs, whereas c309 is expressed in the α/β and γ lobes but not in the core region of the α/β; lobes. This differential expression pattern within the MBs indicates that PKA might affect the regulation of sleep by the MBs in both a positive and a negative fashion by using anatomically distinct classes of neurons. Consistent with this notion of heterogeneous cell types within the MBs, some MB drivers, such as 30Y and 238Y, promoted sleep during the day but inhibited sleep during the night, leading to only marginal overall changes in daily sleep. This effect was not observed with any driver that was expressed exclusively outside the MBs. A small increase in daytime sleep was also frequently produced by the pan-neuronal elavGeneSwitch driver, which decreased overall sleep. The expression patterns of 238Y and 30Y overlap those of 201Y and c309, supporting the idea that 238Y and 30Y are expressed in both sleep-promoting and sleep-inhibiting areas (Joiner, 2006).
To test the hypothesis that PKA expression in MBs regulates adult sleep, the PKA transgene was expressed under the control of an RU486-activatable MB GAL4 driver, P{MB-Switch}. It was confirmed selective expression of this driver in the MBs by coupling it to a GFP reporter, and inducible expression was found in the MBs. Sleep was significantly reduced in response to RU486 in MB-Switch/PKA animals but was unaffected by the drug in control animals harbouring either the driver or the transgene alone. Thus, PKA overexpressed preferentially in specific neurons of adult MBs is sufficient to reduce sleep (Joiner, 2006).
Next sleep structure in the hyposomnolent animals was compared with that of controls. In both MB-Switch/PKA animals and c309/PKA animals, loss of sleep was caused by a shortened sleep bout duration without a concomitant increase in the sleep bout number. The underlying cause of reduced sleep in both sets of animals therefore seems to be impaired sleep need, because the alternative-normal sleep need, but an inability to maintain the sleep state-would be expected to produce an increase in sleep bout number. In contrast, in 201Y sleep bout duration remained unchanged (Joiner, 2006).
It was then asked whether the reduction of sleep in MB-Switch/PKA animals was due to an impaired accrual of a sleep-inducing signal. If this were so, then a hallmark of sleep, homeostatic rebound-sleep that exceeds baseline to compensate for lost sleep-should not occur on relief of induced PKA expression. However, when RU486 was withdrawn after about three days of sleep deprivation, an average rebound of 156 +/- 38 min was observed. This is a robust rebound, comparable to that produced when genetically identical but uninduced flies were submitted to a standard 12 h of mechanical deprivation (137 +/- 26 min). Behavioural rebound was also observed in animals expressing elavGeneSwitch-driven PKA, after withdrawal of RU486, and was accompanied by a decrease in PKA activity in fly heads. Rebound after withdrawal of RU486 indicates that PKA might not prevent the accrual of sleep-promoting signals but might suppress homeostatic output (Joiner, 2006).
To determine whether PKA affects sleep by regulating synaptic output in MB neurons, either of two K+ channels, Kir2.1 or EKO, were inducibly expressed under the control of the MB-Switch driver. Such transgenic expression should suppress action-potential firing by hyperpolarizing neurons and decreasing membrane resistance, thus leading to reduced synaptic transmission. It was found that induction of either Kir2.1 or EKO caused a significant increase in sleep. Because the opposite was observed with PKA expression in the same neurons, it indicates that PKA might decrease sleep by increasing either excitability or synaptic transmission. To address this issue further, a sodium channel (NaChBac), which depolarizes neurons and increases excitability, was inducibly expressed. When expressed under the control of the MB-Switch driver, the sodium channel caused a decrease in sleep, similar to that produced by PKA, confirming that PKA increases the output of these neurons (Joiner, 2006).
The MB-Switch driver is expressed in a subpopulation of MB neurons similar to those labelled by c309, and both drivers had sleep-inhibiting effects. As noted above, this pattern of expression differed from that of other drivers, which had sleep-promoting or bidirectional effects on sleep, thus leading to a proposal that the MBs contain sleep-inhibiting and sleep-promoting neurons. To determine the overall effect of MBs on sleep, they were ablated with hydroxyurea, and sleep and activity were examined in adult flies. An overall increase in activity was observed. However, normalization of this activity to waking time indicates that the phenotype derives less from hyperactivity than from a reduction in sleep. Even so, the reduction in sleep was much less than that seen with other manipulations of the MBs or in short-sleep mutants such as minisleep. This supports the conclusion that MBs exert both positive and negative influences on sleep that are integrated to produce the overt behavioural state. A model takes into account these results; notably the integrator downstream of the MBs promotes activity in the default state. Thus, when MBs are ablated the overall effect is increased wakefulness (Joiner, 2006).
Opposing effects of the c309 and 201Y drivers are also observed in a different behavioural model. They parallel MB-dependent changes in brain activity during the sleep/wake cycle that are associated with salience, a behavioural trait that may correspond to arousal. Consistent with the data was the observation that reducing synaptic transmission using the c309 driver inhibited salience, whereas the 201Y driver in the same type of experiment yielded no change. Increased arousal wouldbe predicted with 201Y, but in those experiments the animals were already awake (Joiner, 2006).
Because MBs receive and transduce considerable sensory, particularly olfactory, input to the fly brain, it is speculate that they promote arousal or sleep by allowing or inhibiting the throughput of sensory information. In addition, given the major function that MBs have in regulating plasticity in the fly brain, it is likely that this is linked to their role in sleep. In mammals, sleep deprivation suppresses the performance of learned tasks, and sleep permits memory consolidation. Sleep and sleep deprivation also differentially affect cortical synaptic plasticity. In Drosophila, MBs participate in the consolidation or retrieval of memories involving olfactory cues, courtship conditioning and context-dependent visual cues by mechanisms that include cAMP signalling. Distinct anatomical regions of the MBs have been shown to be important for at least some forms of memory, as has now also been shown for sleep. Thus, memory and sleep may involve similar molecular pathways (cAMP signalling) and anatomical regulatory loci (MBs) (Joiner, 2006).
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Separate sections of The Interactive Fly group genes according to their involvement in glia morphogenesis and axonogenesis.
genes expressed in brain morphogenesis
Genes involved in organ development
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