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Spatio-temporal dynamics of yeast mitochondrial biogenesis: transcriptional and post-transcriptional mRNA oscillatory modules.

Lelandais G, Saint-Georges Y, Geneix C, Al-Shikhley L, Dujardin G, Jacq C - PLoS Comput. Biol. (2009)

Bottom Line: This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors.Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence.More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation.

View Article: PubMed Central - PubMed

Affiliation: Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr

ABSTRACT
Examples of metabolic rhythms have recently emerged from studies of budding yeast. High density microarray analyses have produced a remarkably detailed picture of cycling gene expression that could be clustered according to metabolic functions. We developed a model-based approach for the decomposition of expression to analyze these data and to identify functional modules which, expressed sequentially and periodically, contribute to the complex and intricate mitochondrial architecture. This approach revealed that mitochondrial spatio-temporal modules are expressed during periodic spikes and specific cellular localizations, which cover the entire oscillatory period. For instance, assembly factors (32 genes) and translation regulators (47 genes) are expressed earlier than the components of the amino-acid synthesis pathways (31 genes). In addition, we could correlate the expression modules identified with particular post-transcriptional properties. Thus, mRNAs of modules expressed "early" are mostly translated in the vicinity of mitochondria under the control of the Puf3p mRNA-binding protein. This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors. Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence. More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation.

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Description of the EDPM algorithm.A: Description of the vectors (D,                            M and W) and the                                matrix (P) used by EDPM. The algorithm calculates                                the vector W of ω-values,                                using an optimization procedure (see main text and Figure                                    S1). B: Representation of the 15 model patterns used in                                this study. These models are periodic functions covering three                                consecutive cycles. The color code reflects the metabolic phases                                during which model patterns are maximal                                (R/B = green;                                R/C = blue and                                Ox = red). C: Illustration of EDPM                                results analyzing R/B, R/C and Ox sentinel genes defined in [3]. Initial vectors from the microarray                                data D are plotted in orange; the                                M vector, obtained by multiplying of                                W and P, is plotted in red. The                                ω-values (also referred to as                                ω-footprints in the main text) are                                represented as barplots and model patterns are indicated with a                                color code.
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pcbi-1000409-g001: Description of the EDPM algorithm.A: Description of the vectors (D, M and W) and the matrix (P) used by EDPM. The algorithm calculates the vector W of ω-values, using an optimization procedure (see main text and Figure S1). B: Representation of the 15 model patterns used in this study. These models are periodic functions covering three consecutive cycles. The color code reflects the metabolic phases during which model patterns are maximal (R/B = green; R/C = blue and Ox = red). C: Illustration of EDPM results analyzing R/B, R/C and Ox sentinel genes defined in [3]. Initial vectors from the microarray data D are plotted in orange; the M vector, obtained by multiplying of W and P, is plotted in red. The ω-values (also referred to as ω-footprints in the main text) are represented as barplots and model patterns are indicated with a color code.

Mentions: Our aim was to investigate in more detail the published gene expression profiles obtained from yeast cell cultures displaying highly periodic cycles in the form of respiratory bursts. Starting from previous work [6], we developed the EDPM algorithm (Expression Decomposition based on Periodic Models) to analyze precisely gene expression patterns during yeast metabolic cycles. Overview of the EDPM procedure is presented in Figure S1. The main idea is to decompose each gene expression profile obtained with microarray technology (vector D, Figure 1A), into a mixture of pre-defined model patterns (matrix P, Figure 1A). For that, the algorithm calculates a vector W of ω-values, such that the standard multiplication of vector W and matrix P, forms a vector M that reproduces the initial vector of expression measurements D (eq. 1 below). The ω-values are determine using an optimization procedure (see below and Figure 2 for an illustration) and therefore indicate the contribution of each model pattern to the expression pattern observed for a particular gene. The data vector M matches the vector D exactly if P is a perfect model of the biological:(1)


Spatio-temporal dynamics of yeast mitochondrial biogenesis: transcriptional and post-transcriptional mRNA oscillatory modules.

Lelandais G, Saint-Georges Y, Geneix C, Al-Shikhley L, Dujardin G, Jacq C - PLoS Comput. Biol. (2009)

Description of the EDPM algorithm.A: Description of the vectors (D,                            M and W) and the                                matrix (P) used by EDPM. The algorithm calculates                                the vector W of ω-values,                                using an optimization procedure (see main text and Figure                                    S1). B: Representation of the 15 model patterns used in                                this study. These models are periodic functions covering three                                consecutive cycles. The color code reflects the metabolic phases                                during which model patterns are maximal                                (R/B = green;                                R/C = blue and                                Ox = red). C: Illustration of EDPM                                results analyzing R/B, R/C and Ox sentinel genes defined in [3]. Initial vectors from the microarray                                data D are plotted in orange; the                                M vector, obtained by multiplying of                                W and P, is plotted in red. The                                ω-values (also referred to as                                ω-footprints in the main text) are                                represented as barplots and model patterns are indicated with a                                color code.
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Related In: Results  -  Collection

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getmorefigures.php?uid=PMC2690403&req=5

pcbi-1000409-g001: Description of the EDPM algorithm.A: Description of the vectors (D, M and W) and the matrix (P) used by EDPM. The algorithm calculates the vector W of ω-values, using an optimization procedure (see main text and Figure S1). B: Representation of the 15 model patterns used in this study. These models are periodic functions covering three consecutive cycles. The color code reflects the metabolic phases during which model patterns are maximal (R/B = green; R/C = blue and Ox = red). C: Illustration of EDPM results analyzing R/B, R/C and Ox sentinel genes defined in [3]. Initial vectors from the microarray data D are plotted in orange; the M vector, obtained by multiplying of W and P, is plotted in red. The ω-values (also referred to as ω-footprints in the main text) are represented as barplots and model patterns are indicated with a color code.
Mentions: Our aim was to investigate in more detail the published gene expression profiles obtained from yeast cell cultures displaying highly periodic cycles in the form of respiratory bursts. Starting from previous work [6], we developed the EDPM algorithm (Expression Decomposition based on Periodic Models) to analyze precisely gene expression patterns during yeast metabolic cycles. Overview of the EDPM procedure is presented in Figure S1. The main idea is to decompose each gene expression profile obtained with microarray technology (vector D, Figure 1A), into a mixture of pre-defined model patterns (matrix P, Figure 1A). For that, the algorithm calculates a vector W of ω-values, such that the standard multiplication of vector W and matrix P, forms a vector M that reproduces the initial vector of expression measurements D (eq. 1 below). The ω-values are determine using an optimization procedure (see below and Figure 2 for an illustration) and therefore indicate the contribution of each model pattern to the expression pattern observed for a particular gene. The data vector M matches the vector D exactly if P is a perfect model of the biological:(1)

Bottom Line: This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors.Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence.More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation.

View Article: PubMed Central - PubMed

Affiliation: Dynamique des Structures et Interactions des Macromolécules Biologiques (DSIMB), INSERM UMR-S 665, Université Paris Diderot, Paris, France. gaelle.lelandais@univ-paris-diderot.fr

ABSTRACT
Examples of metabolic rhythms have recently emerged from studies of budding yeast. High density microarray analyses have produced a remarkably detailed picture of cycling gene expression that could be clustered according to metabolic functions. We developed a model-based approach for the decomposition of expression to analyze these data and to identify functional modules which, expressed sequentially and periodically, contribute to the complex and intricate mitochondrial architecture. This approach revealed that mitochondrial spatio-temporal modules are expressed during periodic spikes and specific cellular localizations, which cover the entire oscillatory period. For instance, assembly factors (32 genes) and translation regulators (47 genes) are expressed earlier than the components of the amino-acid synthesis pathways (31 genes). In addition, we could correlate the expression modules identified with particular post-transcriptional properties. Thus, mRNAs of modules expressed "early" are mostly translated in the vicinity of mitochondria under the control of the Puf3p mRNA-binding protein. This last spatio-temporal module concerns mostly mRNAs coding for basic elements of mitochondrial construction: assembly and regulatory factors. Prediction that unknown genes from this module code for important elements of mitochondrial biogenesis is supported by experimental evidence. More generally, these observations underscore the importance of post-transcriptional processes in mitochondrial biogenesis, highlighting close connections between nuclear transcription and cytoplasmic site-specific translation.

Show MeSH