The Journal of experimental biology.
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Fig. 4. Schematic drawing of the interactions between identified interneurones, sensory neurones and motor networks of the stomatogastric ganglion (STG). (Left) In the crab Cancer borealis, three pairs of proctolin (Proc)-like immunoreactive neurones are present (coloured in different shades of grey), which each elicit a different motor pattern. The two modulatory proctolin neurones (MPN) are located in the oesophageal ganglion (OG) or the oesophageal nerve and elicit a pyloric motor pattern (pyloric patterns coloured in different shades of orange) via excitatory synapses (symbolised by triangles). MPN inhibits, via the release of {{gamma}}-aminobutyric acid (GABA; inhibitory synapses symbolised by small circles), two pairs of modulatory neurones located in the commissural ganglia, which are called commissural projection neurones 2 (CPN2) and modulatory commissural neurones 1 (MCN1), thereby preventing a gastric mill rhythm, which the latter neurones normally initiate. Stimulating MCN1 (containing proctolin, Cancer borealis tachykinin-related peptide, CabTRP, and GABA) alone elicits a gastropyloric motor pattern (gastric mill motor patterns are coloured in different shades of green, gastropyloric motor patterns are drawn in stripes of orange and green). After blocking the action of CabTRP, MCN1 does not elicit a gastric mill rhythm and the pyloric rhythm it initiates is more similar but still not identical to that elicited by MPN. Co-stimulation of the MCN1 and CPN2 elicits a different type of gastropyloric pattern. MCN1 receives rhythmic inhibition from the lateral gastric neurone (LG) in the STG. This does not influence the MCN1 synapses in the commissural ganglia (CoGs), demonstrating that activity of synapses can vary with the output region. Modulatory commissural neurones 7 (MCN7) also elicit a pyloric motor pattern that differs from that elicited by the MPNs. (Right) In the lobster Homarus gammarus, the anterior gastric receptor (AGR) excites two pairs of modulatory interneurones in the CoGs: the commissural gastric (CG) neurones and the gastric inhibitor (GI) neurones. AGR, which is a mechanoreceptor activated by the movements of the gastric mill muscle 1 (gm1), has its soma in the dorsal ventricular nerve (dvn) and projects through the STG without any arborization to innervate the CoGs. When AGR fires weakly, one gastric mill pattern is elicited. When AGR fires strongly, a second gastric mill pattern is elicited, demonstrating that the activity of a feedback loop is able to select different motor patterns (modified from Blitz et al., 1999; Blitz and Nusbaum, 1997; Coleman and Nusbaum, 1994; Coleman et al., 1995; Combes et al., 1999a; Combes et al., 1999b).
- That neurones containing the same peptide can elicit a different motor pattern was shown by investigating three pairs of proctolin-like immunoreactive neurones in Cancer borealis (Fig.4; Blitz et al., 1999): the modulatory proctolin neurones (MPNs) with cell bodies located either in the OG or in the on, and the modulatory commissural neurones 1 and 7 (MCN1 and MCN7) with cell bodies located in the CoGs.
- Both MPN (showing proctolin- and GABA-like immunoreactivity) (Nusbaum and Marder, 1989a; Blitz et al., 1999) and MCN7 (showing proctolin-like immunoreactivity) stimulation elicit distinct pyloric rhythms (Fig.4; Blitz et al., 1999).
- In contrast, MCN1 (showing proctolin-, GABA- and tachykinin-like immunoreactivity) activates both the pyloric and the gastric mill rhythms (Fig.4; Coleman and Nusbaum, 1994; Bartos and Nusbaum, 1997).
- Investigation of MPN also showed that motor pattern selection occurs not only through direct modulation of the network but also via the inhibition of a competing pathway (Fig.4; Blitz and Nusbaum, 1997).
- Meyrand, unpublished data), and the gastric inhibitor neurone (GI) are excited by the anterior gastric receptor (AGR, Fig.4) (Combes et al., 1999a; Combes et al., 1999b).
- A second example of this is MCN1, which elicits a different gastric mill motor pattern when co-activated with CPN2 (Fig.4; Blitz and Nusbaum, 1997).
- Another peptidergic influence on a mechanoreceptor was demonstrated in Homarus gammarus, in which bath application of an FLRFamide-related peptide to the dendritic membrane of AGR, but not to its cell body or axon, switches its firing pattern from a tonic to a bursting one (Fig.4; Combes et al., 1997).
Genome Biology
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Modularity of gene interactions. The 298 HU-selected strains were perturbed with other drugs, and GI values were analyzed by hierarchical clustering. The color intensity represents the magnitude of the GI, green being negative (synergistic effect of gene deletion), but note that the range of color intensity may be different for each perturbation (see Figure 2j and Additional data file 3) because the phenotypic noise, determined for replicates of the reference strain, is measured uniquely for each perturbation (see Figure 2i). Gene clusters were given numbers (on right) for ease of referral, based subjectively on their appearance with respect to the dendrogram branches (see also Additional data file 10). GI values are reported in Additional data file 9. The first two columns (C) indicate the GI for unperturbed deletion strains (synthetic complete media, no drug). '_gen' indicates data from the original genomic screen. Otherwise, data are from a single retest of selected strains. The other columns indicate drugs used for perturbation as follows (numbers following the abbreviation indicate the concentration): miconaz, miconazole (nM); TBHP, t-butyl hydroperoxide (mM); cyclohex, cycloheximide (ng/ml); HU, hydroxyurea (mM); cisplat, cisplatin (μM). The drug perturbations and the growth phenotypes for the reference strain under each perturbation are given in Additional data file 1. Gene names are from SGD and descriptions can be found in Additional data file 10 [47].
- In contrast, correlation between cisplatin and HU was higher (R2 = 0.13) (Figure 4, and Additional data file 5).
- We refer to 'bio-modules' as sets of strains within a clustered phenotypic profile, indicating modular effects of the respective genes in responding to various growth perturbations (Figures 3, 4, 5, 6, 7).
- GI data for the 298 HU-selected deletion strains, under all perturbation conditions, were clustered together (Figure 4, and Additional data file 10).
- HU and cisplatin perturbations clustered together with respect to the other perturbations, but separately with respect to each other (Figures 4, 5, 6, and Additional data file 6), reflecting the related but distinguishable biology of these two perturbations.
- The strains in cluster 2 (Figure 4) indicate strong synergistic effects, selective for HU and cisplatin perturbations.
- Within cluster 9a, five of six genes involved in sensing DNA damage (RAD24, RAD17, RAD9, DDC1 and MRC1) form a module, while MEC3 appears distinct, not interacting with cisplatin, and interacting antagonistically with other perturbations (Figure 4, cluster 9c, and Figure 6b).
- The lst4 and lst7 (lethal with sec13) deletion strains, which clustered together, were phenotypically 'modular' with rtg2 as well (Figure 4, cluster 9a).
- A different bio-module was suggested by the broad phenotypic profile of interactions involving vesicular trafficking and vacuolar protein sorting genes [40,61], and the strong synergism with cycloheximide (Figures 4 (cluster 3), 5b).
- The following broad conclusions drawn from the entire dataset (Figure 4) were confirmed.
- The pathway-oriented sub-analysis also highlighted clustering features that are less obvious when the entire dataset is analyzed (Figure 4).
- For example, Figure 6a recapitulates clusters 3 and 5 (from Figure 4), both composed of vesicular trafficking genes, while Figure 6b recapitulates clusters 2 and 9a, composed of genes required for DNA damage repair (Figure 6).
- Clustering of GI data was useful for identifying biomodules, as were gene annotations for interpreting their relatedness (see Figures 4, 5, 6, 7).
- Sixth, the respective studies found overlapping sets of genes required to tolerate HU and camptothecin [29], or HU and cisplatin (Figure 4).
- By using a continuous scale for quantifying interactions, we are able to distinguish relative strength and specificity of interaction (Figure 4, clusters 7 and 9b, and see Additional data file 4), which should enhance capabilities for computational modeling of gene interaction networks.
- (type:XLS, size:)A table showing identity and annotation of genes depicted in Figure 4
- strains, under growth inhibition with other drugs (Additional data file 6); tables showing AUGC and GI data from the genome wide screen for HU interactions (Additional data file 7); comparison of HU interactions found in different genome-wide screens (Additional data file 8); AUGC and GI data from the retest of HU-interacting strains for growth on HU, cisplatin, miconazole, cycloheximide, and t-butyl hydrogen peroxide (Additional data file 9); identity and annotation of genes depicted in Figure 4 (Additional data file 10); detailed classification of HU-selected strains (Additional data file 11); interaction index values for all HU-selected deletion strains (Additional data file 12); AUGC and GI data from the genome wide HU screen in the homozygous diploid deletion set (Additional data file 13); a comparison of the MATa haploid and homozygous diploid HU 150 screens (Additional data file 14).