The flux of precursors determines JH synthesis rates
The rate of JH synthesis, expressed in our studies as fmol per pair of glands per hour, refers to the number of molecules that transit the synthetic pathway from the time they are taken up by the first enzyme as the initial substrate (Acetyl-CoA) until they are released by the last enzyme as the end product (JH III) (). The rate of JH synthesis is controlled by the rate of flux of isoprenoids in the pathway, which is the outcome of a complex interplay of changes in precursor pools, enzyme levels and external regulators (). It has previously described that the modulation of the flux of isoprenoid precursors throughout the synthetic pathway changes the levels of JH synthesis (Schooley and Baker, 1985
). These changes in biosynthetic rates are always initiated by an external alteration which sets into motion changes in some enzymes and fluxes (Cascante et al., 1995
). Discussion on “control” or “regulation” of biosynthetic pathways normally focuses on the question of which individual enzymes are controlling the flux in a pathway (Kacser and Burns, 1973
). Flux is a systemic property, and questions of its control cannot be answered by looking at the different enzymatic steps in isolation. If we would like to understand how regulators modify JH synthesis, it is important to know their effect on the changes in the levels of all enzymes and precursor pool sizes.
A schematic representation of our working model for the control of the flux of precursors in the JH biosynthetic pathway
The JH synthetic pathway involves 13 discrete enzymatic steps organized in an obligatory sequence. Each product represents the substrate for the next “downstream” enzyme. Enzymes are connected by metabolite pools that are common to them, for example farnesol is the product of the FPP-pyrophosphatase activity and the substrate for farnesol dehydrogenase. The pools are in fact the links in the system interactions, therefore pool concentrations and fluxes (which are flows into and out of pools) are critical variables in JH regulation. Experimental manipulation of individual precursor pool concentrations differentially affected the rates of JH synthesis. The experimental results showed that the effect of addition of the five tested precursors was progressive, namely the closer the precursor to the end of the pathway (JH III), the greater the stimulatory effect observed. The “progressive” effect can be due to many factors; such as the rate of penetration into the CA cells, the rate of degradation of GPP and FPP and subsequent re-phosphorylation, the size of the endogenous pool, etc.
The spontaneous synthesis of JH in CA dissected from both sugar-fed and blood-fed females was always markedly stimulated by the addition of precursors to the medium, demonstrating that the supply of these precursors and not the activity of the last 6 enzymes in the pathway is rate limiting in these glands. Exogenous late precursors were efficiently utilized by the mosquito CA to nullify the effect of rate-limiting factors at earlier steps in JH synthesis.
The system sensitivity
to changes in the size of a precursor pool indicates the control importance of this enzymatic step in the final flux and can be experimentally tested. If the level of farnesol dehydrogenase is low but still most of the farnesol is present in the enzyme-bound pool, the addition of exogenous precursor might not have a significant effect on the rate of JH synthesis. We observed the contrary; an increase in the farnesol pool size resulted in up to a 6 fold stimulation in the rates of MF + JH synthesis. This information can be used to understand how elastic
this particular enzymatic step is in its response to a pool change. In a non-stimulated CA the free-farnesol pool appears to be small and most of the mass of farnesol could be present as part of the pool bound to farnesol dehydrogenase. Increasing the farnesol pool to 40 μM apparently was enough to saturate the farnesol dehydrogenase; because further increasing the pool size to 200 μM mostly increased the size of the free farnesol pool and had limited additional stimulatory effect on JH synthesis (Supplementary Fig. 1
Unfortunately, the effect of increasing the farnesol pool could not be evaluated directly by looking at changes in the farnesal pool, but only by changes in pool sizes for two compounds (MF and JH III) upstream in the pathway. We recently reported a Direct Analysis in Real Time (DART) mass spectrometry approach that allows the rapid simultaneous evaluation of the levels of the last 5 metabolites in the JH pathway (Navare et al., 2010
). This technique could be used in the future to evaluate more accurately changes in individual pool sizes. Adding farnesal to the incubation media had also limited stimulatory effect when compared with the addition of FA, suggesting that the levels of farnesal dehydrogenase enzymatic activity might also be low.
Although control of fluxes tends to be distributed among all enzymes in a pathway rather than confined to a single rate-limiting enzyme, the extent of control can differ widely between enzymes of a synthetic pathway (Kacser and Burns, 1973
). In glands with low synthetic activity, the flux of isoprenoids might become sensitive
to minimal thresholds of enzymes with low levels of expression such as acetoacetyl-CoA thiolase, phosphomevalonate kinase and farnesol dehydrogenase. Under these conditions any of these enzymes could become rate limiting or “bottleneck”.
Having the last 6 enzymes of the JH synthetic pathway readily available all the time might be critical for rapid dynamic changes in JH synthesis in response to nutritional changes or blood feeding. Evidence for the dynamic regulation comes from the observation that spontaneous and stimulated rates of CA activity were very different. The addition of FA resulted in a 7.5 and 16.1 fold induction of MF + JH synthesis in gland dissected from sugar fed females at 0h and 72h respectively; as well as a 15 fold increase in CA dissected 24h after a blood meal. It has been postulated that in a synthetic pathway containing numerous enzymes, almost all the enzymes will appear to be “in excess”, in the sense that individual quantities or activities can be considerably reduced without appreciable effect on the flux (Kacser and Burns, 1973
). Stimulation with exogenous precursors has been reported for the CA of many insect species and it seems that having an excess of enzymes is common in most insects studied (Feyereisen et al., 1984
; Gadot and Applebaum, 1986
). In the CA of the cockroach Diploptera punctata
3-hydroxy-3-methyl-glutaryl-CoA reductase and 3-hydroxy-3-methyl-glutaryl-CoA synthase activities were not always closely linked to the rate of spontaneous JH synthesis (Feyereisen and Farnsworth, 1987
; Couillaud and Feyereisen, 1991
). Sutherland and Feyereisen (1992) showed in D. punctata
that inhibiting the 3-HMG reductase activity by a third has a moderate inhibition of JH synthesis (less than 15%), indicating that this enzyme is in excess and has a low control coefficient on JH synthesis.
There was a coordinated expression of JH biosynthetic enzymes in female pupae and adult mosquito. A comprehensive analysis a several of the JH biosynthetic enzymes has only been done in B. mori (Kinjoh, et al., 2007, Ueda et al., 2009); their studies showed that transcripts levels for 8 enzymes of the mevalonic pathway and juvenile hormone acid methyl transferase are expressed in a highly coordinated manner during the 4th and 5th instar larvae as well as in pupae and adult. It seems that evolution has selected mechanisms that regulate transcription of JH biosynthetic enzymes in insects by affecting the entire synthetic pathway rather than individual pathway components. Positive correlations between JH synthesis and transcripts levels for the JH biosynthetic enzymes suggest that a coordinated regulation in the transcription of the genes encoding JH biosynthetic enzymes is at least partially responsible for the changes of JH biosynthesis in the CA of mosquitoes; that suggest the existence of common transcription factors regulating the enzymes of the entire pathway and stress the need to search for similar regulatory regions in the promoters of the genes encoding all these enzymes.
We are aware that transcript levels might not exactly reflect the levels of enzymatic activities. For example, in the synthesis of cholesterol, the enzyme 3-hydroxy-3-methyl-glutaryl-CoA reductase is regulated at 3 levels by addition of the inhibitor mevinolin: an 8-fold increase in transcription, a 5-fold increase in translation and a 5-fold decrease in degradation speed; that gives a total increase in 200-fold (Goldstein and Brown, 1990
). Nevertheless, we would like to propose that transcripts levels need to surpass a minimal threshold to ensure a significant flux of precursors to sustain a sensible rate of JH synthesis. We observed that when all enzyme concentrations simultaneously increased or decreased by a factor, JH synthesis (or the flux) increased or decreased by a similar factor (Supplementary Fig. 2
). The changes in the transcript levels of the enzymes we described seem to be enough to modify the flux of precursors and therefore to modify the rate of JH synthesis.
These variations in enzyme levels during cycles of CA activity are responsible for the constitutive responses
previously described for the control of JH synthesis (Unnithan et al., 1998
). Additional regulatory mechanisms are most likely in place. Flux of metabolites into other synthetic pathways cannot be ruled out, especially in the early steps (mevalonate pathway); other aspects such as compartmentalization of the enzymatic steps might add an additional level of complexity. Experiments performed by Sutherland and Feyereisen (1996)
provided strong evidence that D. punctata
CA glands inhibited with allatostatin-A (AS-A) were prevented from using glucose or amino acids to synthesize JH, but free to utilize acetate, i.e., AS-A was inhibiting steps in the glucose or amino acid (mitochondrial) incorporation pathway but not the acetate (cytoplasmic) incorporation pathway. Results from the D. punctata
-AS-A model confirm that compartmentalization of the precursor pools and enzymatic steps is important and suggest that a major target of AS-A is either the transport of citrate across the mitochondrial membrane and/or the cleavage of citrate to yield cytoplasmic acetyl-CoA (Sutherland and Feyereisen, 1996
). Quantitative proteomics, with the development of new mass spectrometry (MS)-based techniques to detect, identify and quantify minute amounts of proteins, should open the opportunity to fill the current gap of knowledge between transcriptional studies and enzymatic activities (Walther and Mann, 2010
; Ning et al., 2011