Engineering signal transduction pathways.

Cells respond to their environment by sensing signals and translating them into changes in gene expression. In recent years, synthetic networks have been designed in both prokaryotic and eukaryotic systems to create new functionalities and for specific applications. In this review, we discuss the challenges associated with engineering signal transduction pathways. Furthermore, we address advantages and disadvantages of engineering signaling pathways in prokaryotic and eukaryotic cells, highlighting recent examples, and discuss how progress in synthetic biology might impact biotechnology and biomedicine.

Comprehensive quantitative modeling of translation efficiency in a genome-reduced bacterium.

Translation efficiency has been mainly studied by ribosome profiling, which only provides an incomplete picture of translation kinetics. Here, we integrated the absolute quantifications of tRNAs, mRNAs, RNA half-lives, proteins, and protein half-lives with ribosome densities and derived the initiation and elongation rates for 475 genes (67% of all genes), 73 with high precision, in the bacterium Mycoplasma pneumoniae (Mpn). We found that, although the initiation rate varied over 160-fold among genes, most of the known factors had little impact on translation efficiency. Local codon elongation rates could not be fully explained by the adaptation to tRNA abundances, which varied over 100-fold among tRNA isoacceptors. We provide a comprehensive quantitative view of translation efficiency, which suggests the existence of unidentified mechanisms of translational regulation in Mpn.

Impact of C-terminal amino acid composition on protein expression in bacteria.

The C-terminal sequence of a protein is involved in processes such as efficiency of translation termination and protein degradation. However, the general relationship between features of this C-terminal sequence and levels of protein expression remains unknown. Here, we identified C-terminal amino acid biases that are ubiquitous across the bacterial taxonomy (1,582 genomes). We showed that the frequency is higher for positively charged amino acids (lysine, arginine), while hydrophobic amino acids and threonine are lower. We then studied the impact of C-terminal composition on protein levels in a library of Mycoplasma pneumoniae mutants, covering all possible combinations of the two last codons. We found that charged and polar residues, in particular lysine, led to higher expression, while hydrophobic and aromatic residues led to lower expression, with a difference in protein levels up to fourfold. We further showed that modulation of protein degradation rate could be one of the main mechanisms driving these differences. Our results demonstrate that the identity of the last amino acids has a strong influence on protein expression levels.

Integration of multi-omics data of a genome-reduced bacterium: Prevalence of post-transcriptional regulation and its correlation with protein abundances.

We developed a comprehensive resource for the genome-reduced bacterium Mycoplasma pneumoniae comprising 1748 consistently generated '-omics' data sets, and used it to quantify the power of antisense non-coding RNAs (ncRNAs), lysine acetylation, and protein phosphorylation in predicting protein abundance (11%, 24% and 8%, respectively). These factors taken together are four times more predictive of the proteome abundance than of mRNA abundance. In bacteria, post-translational modifications (PTMs) and ncRNA transcription were both found to increase with decreasing genomic GC-content and genome size. Thus, the evolutionary forces constraining genome size and GC-content modify the relative contributions of the different regulatory layers to proteome homeostasis, and impact more genomic and genetic features than previously appreciated. Indeed, these scaling principles will enable us to develop more informed approaches when engineering minimal synthetic genomes.

MyMpn: a database for the systems biology model organism Mycoplasma pneumoniae.

MyMpn (http://mympn.crg.eu) is an online resource devoted to studying the human pathogen Mycoplasma pneumoniae, a minimal bacterium causing lower respiratory tract infections. Due to its small size, its ability to grow in vitro, and the amount of data produced over the past decades, M. pneumoniae is an interesting model organisms for the development of systems biology approaches for unicellular organisms. Our database hosts a wealth of omics-scale datasets generated by hundreds of experimental and computational analyses. These include data obtained from gene expression profiling experiments, gene essentiality studies, protein abundance profiling, protein complex analysis, metabolic reactions and network modeling, cell growth experiments, comparative genomics and 3D tomography. In addition, the intuitive web interface provides access to several visualization and analysis tools as well as to different data search options. The availability and--even more relevant--the accessibility of properly structured and organized data are of up-most importance when aiming to understand the biology of an organism on a global scale. Therefore, MyMpn constitutes a unique and valuable new resource for the large systems biology and microbiology community.

Defining a minimal cell: essentiality of small ORFs and ncRNAs in a genome-reduced bacterium.

Identifying all essential genomic components is critical for the assembly of minimal artificial life. In the genome-reduced bacterium Mycoplasma pneumoniae, we found that small ORFs (smORFs; < 100 residues), accounting for 10% of all ORFs, are the most frequently essential genomic components (53%), followed by conventional ORFs (49%). Essentiality of smORFs may be explained by their function as members of protein and/or DNA/RNA complexes. In larger proteins, essentiality applied to individual domains and not entire proteins, a notion we could confirm by expression of truncated domains. The fraction of essential non-coding RNAs (ncRNAs) non-overlapping with essential genes is 5% higher than of non-transcribed regions (0.9%), pointing to the important functions of the former. We found that the minimal essential genome is comprised of 33% (269,410 bp) of the M. pneumoniae genome. Our data highlight an unexpected hidden layer of smORFs with essential functions, as well as non-coding regions, thus changing the focus when aiming to define the minimal essential genome.

Dissecting the energy metabolism in Mycoplasma pneumoniae through genome-scale metabolic modeling.

Mycoplasma pneumoniae, a threatening pathogen with a minimal genome, is a model organism for bacterial systems biology for which substantial experimental information is available. With the goal of understanding the complex interactions underlying its metabolism, we analyzed and characterized the metabolic network of M. pneumoniae in great detail, integrating data from different omics analyses under a range of conditions into a constraint-based model backbone. Iterating model predictions, hypothesis generation, experimental testing, and model refinement, we accurately curated the network and quantitatively explored the energy metabolism. In contrast to other bacteria, M. pneumoniae uses most of its energy for maintenance tasks instead of growth. We show that in highly linear networks the prediction of flux distributions for different growth times allows analysis of time-dependent changes, albeit using a static model. By performing an in silico knock-out study as well as analyzing flux distributions in single and double mutant phenotypes, we demonstrated that the model accurately represents the metabolism of M. pneumoniae. The experimentally validated model provides a solid basis for understanding its metabolic regulatory mechanisms.

Transcription start site associated RNAs in bacteria.

Here, we report the genome-wide identification of small RNAs associated with transcription start sites (TSSs), termed tssRNAs, in Mycoplasma pneumoniae. tssRNAs were also found to be present in a different bacterial phyla, Escherichia coli. Similar to the recently identified promoter-associated tiny RNAs (tiRNAs) in eukaryotes, tssRNAs are associated with active promoters. Evidence suggests that these tssRNAs are distinct from previously described abortive transcription RNAs. ssRNAs have an average size of 45 bases and map exactly to the beginning of cognate full-length transcripts and to cryptic TSSs. Expression of bacterial tssRNAs requires factors other than the standard RNA polymerase holoenzyme. We have found that the RNA polymerase is halted at tssRNA positions in vivo, which may indicate that a pausing mechanism exists to prevent transcription in the absence of genes. These results suggest that small RNAs associated with TSSs could be a universal feature of bacterial transcription.

Cross-talk between phosphorylation and lysine acetylation in a genome-reduced bacterium.

Protein post-translational modifications (PTMs) represent important regulatory states that when combined have been hypothesized to act as molecular codes and to generate a functional diversity beyond genome and transcriptome. We systematically investigate the interplay of protein phosphorylation with other post-transcriptional regulatory mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae. Systematic perturbations by deletion of its only two protein kinases and its unique protein phosphatase identified not only the protein-specific effect on the phosphorylation network, but also a modulation of proteome abundance and lysine acetylation patterns, mostly in the absence of transcriptional changes. Reciprocally, deletion of the two putative N-acetyltransferases affects protein phosphorylation, confirming cross-talk between the two PTMs. The measured M. pneumoniae phosphoproteome and lysine acetylome revealed that both PTMs are very common, that (as in Eukaryotes) they often co-occur within the same protein and that they are frequently observed at interaction interfaces and in multifunctional proteins. The results imply previously unreported hidden layers of post-transcriptional regulation intertwining phosphorylation with lysine acetylation and other mechanisms that define the functional state of a cell.

Determination of the Gene Regulatory Network of a Genome-Reduced Bacterium Highlights Alternative Regulation Independent of Transcription Factors.

Here, we determined the relative importance of different transcriptional mechanisms in the genome-reduced bacterium Mycoplasma pneumoniae, by employing an array of experimental techniques under multiple genetic and environmental perturbations. Of the 143 genes tested (21% of the bacterium's annotated proteins), only 55% showed an altered phenotype, highlighting the robustness of biological systems. We identified nine transcription factors (TFs) and their targets, representing 43% of the genome, and 16 regulators that indirectly affect transcription. Only 20% of transcriptional regulation is mediated by canonical TFs when responding to perturbations. Using a Random Forest, we quantified the non-redundant contribution of different mechanisms such as supercoiling, metabolic control, RNA degradation, and chromosome topology to transcriptional changes. Model-predicted gene changes correlate well with experimental data in 95% of the tested perturbations, explaining up to 70% of the total variance when also considering noise. This analysis highlights the importance of considering non-TF-mediated regulation when engineering bacteria.

A reporter system coupled with high-throughput sequencing unveils key bacterial transcription and translation determinants.

Quantitative analysis of the sequence determinants of transcription and translation regulation is relevant for systems and synthetic biology. To identify these determinants, researchers have developed different methods of screening random libraries using fluorescent reporters or antibiotic resistance genes. Here, we have implemented a generic approach called ELM-seq (expression level monitoring by DNA methylation) that overcomes the technical limitations of such classic reporters. ELM-seq uses DamID (Escherichia coli DNA adenine methylase as a reporter coupled with methylation-sensitive restriction enzyme digestion and high-throughput sequencing) to enable in vivo quantitative analyses of upstream regulatory sequences. Using the genome-reduced bacterium Mycoplasma pneumoniae, we show that ELM-seq has a large dynamic range and causes minimal toxicity. We use ELM-seq to determine key sequences (known and putatively novel) of promoter and untranslated regions that influence transcription and translation efficiency. Applying ELM-seq to other organisms will help us to further understand gene expression and guide synthetic biology.Quantitative analysis of how DNA sequence determines transcription and translation regulation is of interest to systems and synthetic biologists. Here the authors present ELM-seq, which uses Dam activity as reporter for high-throughput analysis of promoter and 5'-UTR regions.

Defined chromosome structure in the genome-reduced bacterium Mycoplasma pneumoniae.

DNA-binding proteins are central regulators of chromosome organization; however, in genome-reduced bacteria their diversity is largely diminished. Whether the chromosomes of such bacteria adopt defined three-dimensional structures remains unexplored. Here we combine Hi-C and super-resolution microscopy to determine the structure of the Mycoplasma pneumoniae chromosome at a 10 kb resolution. We find a defined structure, with a global symmetry between two arms that connect opposite poles, one bearing the chromosomal Ori and the other the midpoint. Analysis of local structures at a 3 kb resolution indicates that the chromosome is organized into domains ranging from 15 to 33 kb. We provide evidence that genes within the same domain tend to be co-regulated, suggesting that chromosome organization influences transcriptional regulation, and that supercoiling regulates local organization. This study extends the current understanding of bacterial genome organization and demonstrates that a defined chromosomal structure is a universal feature of living systems.

Insights into the Mechanisms of Basal Coordination of Transcription Using a Genome-Reduced Bacterium.

Coordination of transcription in bacteria occurs at supra-operonic scales, but the extent, specificity, and mechanisms of such regulation are poorly understood. Here, we tackle this problem by profiling the transcriptome of the model organism Mycoplasma pneumoniae across 115 growth conditions. We identify three qualitatively different levels of co-expression corresponding to distinct relative orientations and intergenic properties of adjacent genes. We reveal that the degree of co-expression between co-directional adjacent operons, and more generally between genes, is tightly related to their capacity to be transcribed en bloc into the same mRNA. We further show that this genome-wide pervasive transcription of adjacent genes and operons is specifically repressed by DNA regions preferentially bound by RNA polymerases, by intrinsic terminators, and by large intergenic distances. Taken together, our findings suggest that the basal coordination of transcription is mediated by the physical entities and mechanical properties of the transcription process itself, and that operon-like behaviors may strongly vary from condition to condition.

Bacterial transcriptomics: what is beyond the RNA horiz-ome?

Over the past 3 years, bacterial transcriptomics has undergone a massive revolution. Increased sequencing capacity and novel tools have made it possible to explore the bacterial transcriptome to an unprecedented depth, which has revealed that the transcriptome is more complex and dynamic than expected. Alternative transcripts within operons challenge the classic operon definition, and many small RNAs involved in the regulation of transcription, translation and pathogenesis have been discovered. Furthermore, mRNAs may localize to specific areas in the cell, and the spatial organization and dynamics of the chromosome have been shown to be important for transcription. Epigenetic modifications of DNA also affect transcription, and RNA processing affects translation. Therefore, transcription in bacteria resembles that in eukaryotes in terms of complexity more closely than was previously thought. Here we will discuss the contribution of 'omics' approaches to these discoveries as well as the possible impact that they are expected to have in the future.

Transcriptome complexity in a genome-reduced bacterium.

To study basic principles of transcriptome organization in bacteria, we analyzed one of the smallest self-replicating organisms, Mycoplasma pneumoniae. We combined strand-specific tiling arrays, complemented by transcriptome sequencing, with more than 252 spotted arrays. We detected 117 previously undescribed, mostly noncoding transcripts, 89 of them in antisense configuration to known genes. We identified 341 operons, of which 139 are polycistronic; almost half of the latter show decaying expression in a staircase-like manner. Under various conditions, operons could be divided into 447 smaller transcriptional units, resulting in many alternative transcripts. Frequent antisense transcripts, alternative transcripts, and multiple regulators per gene imply a highly dynamic transcriptome, more similar to that of eukaryotes than previously thought.

Proteome organization in a genome-reduced bacterium.

The genome of Mycoplasma pneumoniae is among the smallest found in self-replicating organisms. To study the basic principles of bacterial proteome organization, we used tandem affinity purification-mass spectrometry (TAP-MS) in a proteome-wide screen. The analysis revealed 62 homomultimeric and 116 heteromultimeric soluble protein complexes, of which the majority are novel. About a third of the heteromultimeric complexes show higher levels of proteome organization, including assembly into larger, multiprotein complex entities, suggesting sequential steps in biological processes, and extensive sharing of components, implying protein multifunctionality. Incorporation of structural models for 484 proteins, single-particle electron microscopy, and cellular electron tomograms provided supporting structural details for this proteome organization. The data set provides a blueprint of the minimal cellular machinery required for life.

Impact of genome reduction on bacterial metabolism and its regulation.

To understand basic principles of bacterial metabolism organization and regulation, but also the impact of genome size, we systematically studied one of the smallest bacteria, Mycoplasma pneumoniae. A manually curated metabolic network of 189 reactions catalyzed by 129 enzymes allowed the design of a defined, minimal medium with 19 essential nutrients. More than 1300 growth curves were recorded in the presence of various nutrient concentrations. Measurements of biomass indicators, metabolites, and 13C-glucose experiments provided information on directionality, fluxes, and energetics; integration with transcription profiling enabled the global analysis of metabolic regulation. Compared with more complex bacteria, the M. pneumoniae metabolic network has a more linear topology and contains a higher fraction of multifunctional enzymes; general features such as metabolite concentrations, cellular energetics, adaptability, and global gene expression responses are similar, however.