Cancer Evolution and the Limits of Predictability in Precision Cancer Medicine.

The ability to predict the future behavior of an individual cancer is crucial for precision cancer medicine. The discovery of extensive intratumor heterogeneity and ongoing clonal adaptation in human tumors substantiated the notion of cancer as an evolutionary process. Random events are inherent in evolution and tumor spatial structures hinder the efficacy of selection, which is the only deterministic evolutionary force. This review outlines how the interaction of these stochastic and deterministic processes, which have been extensively studied in evolutionary biology, limits cancer predictability and develops evolutionary strategies to improve predictions. Understanding and advancing the cancer predictability horizon is crucial to improve precision medicine outcomes.

Revisiting the yeast PPR proteins--application of an Iterative Hidden Markov Model algorithm reveals new members of the rapidly evolving family.

Pentatricopeptide repeat (PPR) proteins are the largest known RNA-binding protein family, and are found in all eukaryotes, being particularly abundant in higher plants. PPR proteins localize mostly to mitochondria and chloroplasts, and many were shown to modulate organellar genome expression on the posttranscriptional level. Although the genomes of land plants encode hundreds of PPR proteins, only a few have been identified in Fungi and Metazoa. As the current PPR motif profiles are built mainly on the basis of the predominant plant sequences, they are unlikely to be optimal for detecting fungal and animal members of the family, and many putative PPR proteins in these genomes may remain undetected. In order to verify this hypothesis, we designed a hidden Markov model-based bioinformatic tool called Supervised Clustering-based Iterative Phylogenetic Hidden Markov Model algorithm for the Evaluation of tandem Repeat motif families (SCIPHER) using sequence data from orthologous clusters from available yeast genomes. This approach allowed us to assign 12 new proteins in Saccharomyces cerevisiae to the PPR family. Similarly, in other yeast species, we obtained a 5-fold increase in the detection of PPR motifs, compared with the previous tools. All the newly identified S. cerevisiae PPR proteins localize in the mitochondrion and are a part of the RNA processing interaction network. Furthermore, the yeast PPR proteins seem to undergo an accelerated divergent evolution. Analysis of single and double amino acid substitutions in the Dmr1 protein of S. cerevisiae suggests that cooperative interactions between motifs and pseudoreversion could be the force driving this rapid evolution.

DMR1 (CCM1/YGR150C) of Saccharomyces cerevisiae encodes an RNA-binding protein from the pentatricopeptide repeat family required for the maintenance of the mitochondrial 15S ribosomal RNA.

Pentatricopeptide repeat (PPR) proteins form the largest known RNA-binding protein family and are found in all eukaryotes, being particularly abundant in higher plants. PPR proteins localize mostly in mitochondria and chloroplasts, where they modulate organellar genome expression on the post-transcriptional level. The Saccharomyces cerevisiae DMR1 (CCM1, YGR150C) encodes a PPR protein that localizes to mitochondria. Deletion of DMR1 results in a complete and irreversible loss of respiratory capacity and loss of wild-type mtDNA by conversion to rho(-)/rho(0) petites, regardless of the presence of introns in mtDNA. The phenotype of the dmr1Delta mitochondria is characterized by fragmentation of the small subunit mitochondrial rRNA (15S rRNA), that can be reversed by wild-type Dmr1p. Other mitochondrial transcripts, including the large subunit mitochondrial rRNA (21S rRNA), are not affected by the lack of Dmr1p. The purified Dmr1 protein specifically binds to different regions of 15S rRNA in vitro, consistent with the deletion phenotype. Dmr1p is therefore the first yeast PPR protein, which has an rRNA target and is probably involved in the biogenesis of mitochondrial ribosomes and translation.

Maintenance and expression of the S. cerevisiae mitochondrial genome--from genetics to evolution and systems biology.

As a legacy of their endosymbiotic eubacterial origin, mitochondria possess a residual genome, encoding only a few proteins and dependent on a variety of factors encoded by the nuclear genome for its maintenance and expression. As a facultative anaerobe with well understood genetics and molecular biology, Saccharomyces cerevisiae is the model system of choice for studying nucleo-mitochondrial genetic interactions. Maintenance of the mitochondrial genome is controlled by a set of nuclear-coded factors forming intricately interconnected circuits responsible for replication, recombination, repair and transmission to buds. Expression of the yeast mitochondrial genome is regulated mostly at the post-transcriptional level, and involves many general and gene-specific factors regulating splicing, RNA processing and stability and translation. A very interesting aspect of the yeast mitochondrial system is the relationship between genome maintenance and gene expression. Deletions of genes involved in many different aspects of mitochondrial gene expression, notably translation, result in an irreversible loss of functional mtDNA. The mitochondrial genetic system viewed from the systems biology perspective is therefore very fragile and lacks robustness compared to the remaining systems of the cell. This lack of robustness could be a legacy of the reductive evolution of the mitochondrial genome, but explanations involving selective advantages of increased evolvability have also been postulated.

A toolkit for high-throughput, cross-species gene engineering in Drosophila.

We generated two complementary genomic fosmid libraries for Drosophila melanogaster and Drosophila pseudoobscura that permit seamless modification of large genomic clones by high-throughput recombineering and direct transgenesis. The fosmid transgenes recapitulated endogenous gene expression patterns. These libraries, in combination with recombineering technology, will be useful to rescue mutant phenotypes, allow imaging of gene products in living flies and enable systematic analysis and manipulation of gene activity across species.