Mecanismos de expressão gênica em Eucariotos.

Com raras exceções, as células de eucariotos pluricelulares apresentam o mesmo material genético. Porém, com o decorrer das fases de desenvolvimento do organismo ou em diferentes tecidos, as exigências metabólicas são diferenciadas, e diferentes genes são ligados e desligados, expressando um conjunto distinto de proteínas. Existem vários mecanismos responsáveis por controlar a ativação e desativação de genes (controle da expressão gênica), em diferentes momentos da vida celular. Apresentamos nesta revisão alguns passos que são passíveis de controle, bem como uma breve descrição e exemplos ilustrativos de mecanismos de regulação de expressão gênica.With rare exceptions, all cells of multicellular eukaryotes have the same genetic material. However, metabolic requirements are different over the stages of their development or in different tissues. These requirements are satisfied by gene expression control in these organisms. In the present review we discuss some steps that are likely to be controlled, and a brief description and examples of mechanisms of gene expression

Axenic Leishmania amazonensis promastigotes sense both the external and internal arginine pool distinctly regulating the two transporter-coding genes.

Leishmania (L.) amazonensis uses arginine to synthesize polyamines to support its growth and survival. Here we describe the presence of two gene copies, arranged in tandem, that code for the arginine transporter. Both copies show similar Open Reading Frames (ORFs), which are 93% similar to the L. (L.) donovani AAP3 gene, but their 5' and 3' UTR's have distinct regions. According to quantitative RT-PCR, the 5.1 AAP3 mRNA amount was increased more than 3 times that of the 4.7 AAP3 mRNA along the promastigote growth curve. Nutrient deprivation for 4 hours and then supplemented or not with arginine (400 µM) resulted in similar 4.7 AAP3 mRNA copy-numbers compared to the starved and control parasites. Conversely, the 5.1 AAP3 mRNA copy-numbers increased in the starved parasites but not in ones supplemented with arginine (p<0.05). These results correlate with increases in amino acid uptake. Both Meta1 and arginase mRNAs remained constant with or without supplementation. The same starvation experiment was performed using a L. (L.) amazonensis null knockout for arginase (arg(-)) and two other mutants containing the arginase ORF with (arg(-)/ARG) or without the glycosomal addressing signal (arg(-)/argΔSKL). The arg(-) and the arg(-)/argΔSKL mutants did not show the same behavior as the wild-type (WT) parasite or the arg(-)/ARG mutant. This can be an indicative that the internal pool of arginine is also important for controlling transporter expression and function. By inhibiting mRNA transcription or/and mRNA maturation, we showed that the 5.1 AAP3 mRNA did not decay after 180 min, but the 4.7 AAP3 mRNA presented a half-life decay of 32.6 +/- 5.0 min. In conclusion, parasites can regulate amino acid uptake by increasing the amount of transporter-coding mRNA, possibly by regulating the mRNA half-life in an environment where the amino acid is not present or is in low amounts

<i>Leishmania infantum</i> altered metabolic pathways in R <i>vs</i> SNT.

<p><i>Leishmania infantum</i> metabolic pathways with the higher divergence among the groups of parasites studied (R <i>vs</i> SNT strains). Variation of the metabolites inside the metabolic pathways are represented in green (increase), red (decrease) or black (lack of statistical significance). Those that incorporates ¹³C appeared underlined.</p

PCA models for ¹³C.

<p>PCA models for the whole data set filtered according to their presence in at leasts 50% of the QCs for the ¹³C arginine experiment. Panels: A LC-MS. 3 components. R² = 0.428. Q² = 0.107. B.- CE-MS. 2 components. R² = 0.577. Q² = 0.424.</p

Venn diagram.

<p>Venn diagram for the number of compounds identified in each technique.</p

<i>Leishmania infantum</i> altered metabolic pathways in ST <i>vs</i> SNT.

<p><i>Leishmania infantum</i> metabolic pathways with the higher divergence among the groups of parasites studied (ST <i>vs</i> SNT strains). Variation of the metabolites inside the metabolic pathways are represented in green (increase), red (decrease) or black (lack of statistical significance). Those that incorporates ¹³C appeared underlined.</p

Biochemical classification.

<p>Biochemical classification of the identified compounds per each technique expressed as percentage. Green: amines. Cyan: amino acids, peptides and conjugates. Yellow: carbohydrates. Orange: fatty acids. Light blue: glycerophospholipids. Red: ketones and aldehydes. Ochre: organic acids. Purple: purines, pyrimidines and conjugates. Pink: sphingolipids and spingoid bases. Brown: sterol and prenol lipids.</p

PCA models.

<p>PCA models for the whole data set filtered according to their presence in at leasts 50% of the QCs. Panels: A.- LC-MS. 2 components. R² = 0.62. Q² = -0.029. B.- CE-MS. 2 components. R² = 0.872. Q² = 0.694. C.- GC-MS. 2 components. R² = 0.515. Q² = 0.235. Each group is obtained from four samples, except R in CE-MS that consisted of three due to some problems during the sample treatment.</p

Compounds identified by LC-MS/MS and their characteristic fragments.

<p>Compounds identified by LC-MS/MS and their characteristic fragments.</p