Suppression of Gq and PLC gene expression has a small effect on quantum bumps in vivo in Periplaneta americana

Abstract

Visual signal transmission by Drosophila melanogaster photoreceptors is mediated by a Gq protein that activates a phospholipase C (PLC). Mutations and deficiencies in expression of either of these proteins cause severe defects in phototransduction.Here we investigated whether these proteins are also involved in the cockroach, Periplaneta americana, phototransduction by silencing Gq α-subunit (Gqα) and phosphoinositide-specific phospholipase C (PLC) by RNA interference and observing responses to single photons (quantum bumps, QB). We found (1) non-specific decreases in membrane resistance, membrane capacitance and absolute sensitivity in the photoreceptors of both Gqα and PLC knockdowns, and (2) small changes in QB statistics. Despite significant decreases in expressions of Gq and PLC mRNA, the changes in QB properties were surprisingly modest, with mean latencies increasing by ~ 10%, and without significant decrease in their amplitudes. To better understand our results, we used a mathematical model of the phototransduction cascade. By modifying the Gq and PLC abundances, and diffusion rates for Gq, we found that QB latencies and amplitudes deteriorated noticeably only after large decreases in the protein levels, especially when Gq diffusion was slow. Also, reduction in Gq but not PLC lowered quantum efficiency. These results suggest that expression of the proteins may be redundant.

Speed of phototransduction in the microvillus regulates the accuracy and bandwidth of the rhabdomeric photoreceptor

“…Three factors can contribute to the variability of QBs recorded from the same photoreceptor: the intrinsic stochasticity of the cascade, differences between microvilli, and differences in the functional states of microvilli in the rhabdom. The contributions of the first two factors cannot be easily separated because dispersions of QB amplitudes, durations and latencies arising from simulations of single microvillus responses match very well the dispersions found in recordings from individual photoreceptors [ 29 ]. Furthermore, recordings of QB trains originating from presumably the same microvilli in D .…”

“…melanogaster and modified in the previous study to reproduce P . americana QBs [ 29 ]. All parameters used to produce the “normal” (henceforth “control”) cockroach current bump that deviate from the parameters of the original fly model are listed in S1 Table .…”

“…The parameters were: (1) the time of guanosine diphosphate (GDP) to guanosine-5′-triphosphate (GTP) exchange by Gα, which we varied in 1 ms steps from 1 to 8 ms per event and presented in terms of rate in the remainder of the text; (2) the availability of Gq protein varied in steps from 300 to 10%; (3) the concentration of PLC varied similarly to Gq; (4) phosphatidylinositol 4,5-bisphosphate (PIP 2 ) breakdown time by Gα-PLC mainly varied in 0.2 ms intervals from 0.1 to 2 ms per event and was also converted to rate; and (5) the sensitivity of light-activated channels to DAG, which we varied from 0.15 to 0.8. In this analysis we did not investigate the effects of changes in diffusion rates of Gαβγ, Gα and PIP 2 , because we found that such changes produce only minor effects [ 29 ].…”

“…We therefore hypothesized that analysis of stochasticity using a mathematical model of QB could provide testable insights into the causes of QB parameter dispersions and possible correlations between them. We used a model that was originally developed by Nikolic et al ([31]) for D. melanogaster and modified in the previous study to reproduce P. americana QBs [29]. All parameters used to produce the "normal" (henceforth "control") cockroach current bump that deviate from the parameters of the original fly model are listed in S1 Table. In each experiment the computations were iterated 200 times, eliciting about 190 bumps.…”

“…It was therefore necessary to investigate in the model (1) how latency dispersion PLOS COMPUTATIONAL BIOLOGY depends on the activation parameters of phototransduction and (2) how it relates to another bandwidth-limiting factor, the QB duration. Fig 3A and 3B shows plots for median QB latency and its scatter for: (1) the results of simulations of P. americana current bumps involving changes in five activation parameters ( Fig 3A); (2) P. americana voltage bumps obtained in intracellular recording experiments under three conditions (control, Gαkd and PLCkd [29], Fig 3B); and (3) voltage bumps from the blow fly Protophormia terraenovae ( Fig 3B). Results of the modeling show that: 1) simulations can reproduce the whole range of experimental variability in median QB latency and latency dispersion for P. americana (and also for P. terraenovae, with minor modifications); and 2) changes in the upstream cascade activation parameters are associated with stronger changes in latency dispersion than changes downstream.…”