Amino acid metabolic origin as an evolutionary influence on protein sequence in yeast

Metabolic rhythms: A framework for coordinating cellular function

Circadian clocks are widespread among eukaryotes and generally involve feedback loops coupled with metabolic processes and redox balance. The organising power of these oscillations has not only allowed organisms to anticipate day-night cycles, but also acts to temporally compartmentalise otherwise incompatible processes, enhance metabolic efficiency, make the system more robust to noise and propagate signals among cells. While daily rhythms and the function of the circadian transcription-translation loop have been the subject of extensive research over the past four decades, cycles of shorter period and respiratory oscillations, with which they are intertwined, have received less attention. Here, we describe features of yeast respiratory oscillations, which share many features with daily and 12 hr cellular oscillations in animal cells. This relatively simple system enables the analysis of dynamic rhythmic changes in metabolism, independent of cellular oscillations that are a product of the circadian transcription-translation feedback loop. Knowledge gained from studying ultradian oscillations in yeast will lead to a better understanding of the basic mechanistic principles and evolutionary origins of oscillatory behaviour among eukaryotes.

The GC Content as a Main Factor Shaping the Amino Acid Usage During Bacterial Evolution Process

Understanding how proteins evolve is important, and the order of amino acids being recruited into the genetic codons was found to be an important factor shaping the amino acid composition of proteins. The latest work about the last universal common ancestor (LUCA) makes it possible to determine the potential factors shaping amino acid compositions during evolution. Those LUCA genes/proteins from Methanococcus maripaludis S2, which is one of the possible LUCA, were investigated. The evolutionary rates of these genes positively correlate with GC contents with P-value significantly lower than 0.05 for 94% homologous genes. Linear regression results showed that compositions of amino acids coded by GC-rich codons positively contribute to the evolutionary rates, while these amino acids tend to be gained in GC-rich organisms according to our results. The first principal component correlates with the GC content very well. The ratios of amino acids of the LUCA proteins coded by GC rich codons positively correlate with the GC content of different bacteria genomes, while the ratios of amino acids coded by AT rich codons negatively correlate with the increase of GC content of genomes. Next, we found that the recruitment order does correlate with the amino acid compositions, but gain and loss in codons showed newly recruited amino acids are not significantly increased along with the evolution. Thus, we conclude that GC content is a primary factor shaping amino acid compositions. GC content shapes amino acid composition to trade off the cost of amino acids with bases, which could be caused by the energy efficiency.

Evolution of initiator tRNAs and selection of methionine as the initiating amino acid

Transfer RNAs (tRNAs) have been important in shaping biomolecular evolution. Initiator tRNAs (tRNAi), a special class of tRNAs, carry methionine (or its derivative, formyl-methionine) to ribosomes to start an enormously energy consuming but a highly regulated process of protein synthesis. The processes of tRNAi evolution, and selection of methionine as the universal initiating amino acid remain an enigmatic problem. We constructed phylogenetic trees using the whole sequence, the acceptor-TψC arm ('minihelix'), and the anticodon-dihydrouridine arm regions of tRNAi from 158 species belonging to all 3 domains of life. All the trees distinctly assembled into 3 domains of life. Large trees, generated using data for all the tRNAs of a vast number of species, fail to reveal the major evolutionary events and identity of the probable elongator tRNA sequences that could be ancestor of tRNAi. Therefore, we constructed trees using the minihelix or the whole sequence of species specific tRNAs, and iterated our analysis on 50 eubacterial species. We identified tRNA(Pro), tRNA(Glu), or tRNA(Thr) (but surprisingly not elongator tRNA(Met)) as probable ancestors of tRNAi. We then determined the factors imposing selection of methionine as the initiating amino acid. Overall frequency of occurrence of methionine, whose metabolic cost of synthesis is the highest among all amino acids, remains almost unchanged across the 3 domains of life. Our correlation analysis shows that its high metabolic cost is independent of many physicochemical properties of the side chain. Our results indicate that selection of methionine, as the initiating amino acid was possibly a consequence of the evolution of one-carbon metabolism, which plays an important role in regulating translation initiation.

Three-dimensional eukaryotic genomic organization is strongly correlated with codon usage expression and function

It has been shown that the distribution of genes in eukaryotic genomes is not random; however, formerly reported relations between gene function and genomic organization were relatively weak. Previous studies have demonstrated that codon usage bias is related to all stages of gene expression and to protein function. Here we apply a novel tool for assessing functional relatedness, codon usage frequency similarity (CUFS), which measures similarity between genes in terms of codon and amino acid usage. By analyzing chromosome conformation capture data, describing the three-dimensional (3D) conformation of the DNA, we show that the functional similarity between genes captured by CUFS is directly and very strongly correlated with their 3D distance in Saccharomyces cerevisiae, Schizosaccharomyces pombe, Arabidopsis thaliana, mouse and human. This emphasizes the importance of three-dimensional genomic localization in eukaryotes and indicates that codon usage is tightly linked to genome architecture.

ANCAC: amino acid, nucleotide, and codon analysis of COGs--a tool for sequence bias analysis in microbial orthologs

BACKGROUND

The COG database is the most popular collection of orthologous proteins from many different completely sequenced microbial genomes. Per definition, a cluster of orthologous groups (COG) within this database exclusively contains proteins that most likely achieve the same cellular function. Recently, the COG database was extended by assigning to every protein both the corresponding amino acid and its encoding nucleotide sequence resulting in the NUCOCOG database. This extended version of the COG database is a valuable resource connecting sequence features with the functionality of the respective proteins.

RESULTS

Here we present ANCAC, a web tool and MySQL database for the analysis of amino acid, nucleotide, and codon frequencies in COGs on the basis of freely definable phylogenetic patterns. We demonstrate the usefulness of ANCAC by analyzing amino acid frequencies, codon usage, and GC-content in a species- or function-specific context. With respect to amino acids we, at least in part, confirm the cognate bias hypothesis by using ANCAC's NUCOCOG dataset as the largest one available for that purpose thus far.

CONCLUSIONS

Using the NUCOCOG datasets, ANCAC connects taxonomic, amino acid, and nucleotide sequence information with the functional classification via COGs and provides a GUI for flexible mining for sequence-bias. Thereby, to our knowledge, it is the only tool for the analysis of sequence composition in the light of physiological roles and phylogenetic context without requirement of substantial programming-skills.

Elemental economy: microbial strategies for optimizing growth in the face of nutrient limitation

Microorganisms play a dominant role in the biogeochemical cycling of nutrients. They are rightly praised for their facility for fixing both carbon and nitrogen into organic matter, and microbial driven processes have tangibly altered the chemical composition of the biosphere and its surrounding atmosphere. Despite their prodigious capacity for molecular transformations, microorganisms are powerless in the face of the immutability of the elements. Limitations for specific elements, either fleeting or persisting over eons, have left an indelible trace on microbial genomes, physiology, and their very atomic composition. We here review the impact of elemental limitation on microbes, with a focus on selected genetic model systems and representative microbes from the ocean ecosystem. Evolutionary adaptations that enhance growth in the face of persistent or recurrent elemental limitations are evident from genome and proteome analyses. These range from the extreme (such as dispensing with a requirement for a hard to obtain element) to the extremely subtle (changes in protein amino acid sequences that slightly, but significantly, reduce cellular carbon, nitrogen, or sulfur demand). One near-universal adaptation is the development of sophisticated acclimation programs by which cells adjust their chemical composition in response to a changing environment. When specific elements become limiting, acclimation typically begins with an increased commitment to acquisition and a concomitant mobilization of stored resources. If elemental limitation persists, the cell implements austerity measures including elemental sparing and elemental recycling. Insights into these fundamental cellular properties have emerged from studies at many different levels, including ecology, biological oceanography, biogeochemistry, molecular genetics, genomics, and microbial physiology. Here, we present a synthesis of these diverse studies and attempt to discern some overarching themes.

Economical evolution: microbes reduce the synthetic cost of extracellular proteins

Protein evolution is not simply a race toward improved function. Because organisms compete for limited resources, fitness is also affected by the relative economy of an organism's proteome. Indeed, many abundant proteins contain relatively high percentages of amino acids that are metabolically less taxing for the cell to make, thus reducing cellular cost. However, not all abundant proteins are economical, and many economical proteins are not particularly abundant. Here we examined protein composition and found that the relative synthetic cost of amino acids constrains the composition of microbial extracellular proteins. In Escherichia coli, extracellular proteins contain, on average, fewer energetically expensive amino acids independent of their abundance, length, function, or structure. Economic pressures have strategically shaped the amino acid composition of multicomponent surface appendages, such as flagella, curli, and type I pili, and extracellular enzymes, including type III effector proteins and secreted serine proteases. Furthermore, in silico analysis of Pseudomonas syringae, Mycobacterium tuberculosis, Saccharomyces cerevisiae, and over 25 other microbes spanning a wide range of GC content revealed a broad bias toward more economical amino acids in extracellular proteins. The synthesis of any protein, especially those rich in expensive aromatic amino acids, represents a significant investment. Because extracellular proteins are lost to the environment and not recycled like other cellular proteins, they present a greater burden on the cell, as their amino acids cannot be reutilized during translation. We hypothesize that evolution has optimized extracellular proteins to reduce their synthetic burden on the cell.

Metabolic cycling in single yeast cells from unsynchronized steady-state populations limited on glucose or phosphate

Oscillations in patterns of expression of a large fraction of yeast genes are associated with the "metabolic cycle," usually seen only in prestarved, continuous cultures of yeast. We used FISH of mRNA in individual cells to test the hypothesis that these oscillations happen in single cells drawn from unsynchronized cultures growing exponentially in chemostats. Gene-expression data from synchronized cultures were used to predict coincident appearance of mRNAs from pairs of genes in the unsynchronized cells. Quantitative analysis of the FISH results shows that individual unsynchronized cells growing slowly because of glucose limitation or phosphate limitation show the predicted oscillations. We conclude that the yeast metabolic cycle is an intrinsic property of yeast metabolism and does not depend on either synchronization or external limitation of growth by the carbon source.