Coexpression of proteins in response to pathway-inducing signals is the founding paradigm of gene regulation. However, it remains unexplored whether the relative abundance of co-regulated proteins requires precise tuning. Here, we present large-scale analyses of protein stoichiometry and corresponding regulatory strategies for 21 pathways and 67-224 operons in divergent bacteria separated by 0.6-2 billion years. Using end-enriched RNA-sequencing (Rend-seq) with single-nucleotide resolution, we found that many bacterial gene clusters encoding conserved pathways have undergone massive divergence in transcript abundance and architectures via remodeling of internal promoters and terminators. Remarkably, these evolutionary changes are compensated post-transcriptionally to maintain preferred stoichiometry of protein synthesis rates. Even more strikingly, in eukaryotic budding yeast, functionally analogous proteins that arose independently from bacterial counterparts also evolved to convergent in-pathway expression. The broad requirement for exact protein stoichiometries despite regulatory divergence provides an unexpected principle for building biological pathways both in nature and for synthetic activities.

Accurate measurements of cellular protein concentrations are invaluable to quantitative studies of gene expression and physiology in living cells. Here, we developed a versatile mass spectrometric workflow based on data-independent acquisition proteomics (DIA/SWATH) together with a novel protein inference algorithm (xTop). We used this workflow to accurately quantify absolute protein abundances in Escherichia coli for > 2,000 proteins over > 60 growth conditions, including nutrient limitations, non-metabolic stresses, and non-planktonic states. The resulting high-quality dataset of protein mass fractions allowed us to characterize proteome responses from a coarse (groups of related proteins) to a fine (individual) protein level. Hereby, a plethora of novel biological findings could be elucidated, including the generic upregulation of low-abundant proteins under various metabolic limitations, the non-specificity of catabolic enzymes upregulated under carbon limitation, the lack of largescale proteome reallocation under stress compared to nutrient limitations, as well as surprising strain-dependent effects important for biofilm formation. These results present valuable resources for the systems biology community and can be used for future multi-omics studies of gene regulation and metabolic control in E. coli.

Coupled transcription and translation is considered a defining feature of bacterial gene expression 1 , 2 . The pioneering ribosome can both physically associate and kinetically coordinate with the RNA polymerase (RNAP) 3 - 11 , forming a signal-integration hub for co-transcriptional regulation that includes translation-based attenuation 12 , 13 and RNA quality control 2 . However, whether transcription-translation coupling – together with its broad functional consequences – is indeed a fundamental characteristic outside the well-studied Escherichia coli remains unresolved. Here we show that RNAPs outpace pioneering ribosomes in the Gram-positive model bacterium Bacillus subtilis , and that this ‘runaway transcription’ creates alternative rules for both global RNA surveillance and translational control of nascent RNA. In particular, uncoupled RNAPs in B. subtilis explain a diminished role of Rho-dependent transcription termination, as well as the prevalence of mRNA leaders that utilize riboswitches and RNA-binding proteins. More broadly, we identified widespread genomic signatures of runaway transcription in distinct phyla across the bacterial domain of life. Our results demonstrate that coupled RNAP-ribosome movement is not a general hallmark of bacteria. Instead, translation-coupled transcription and runaway transcription constitute two principal modes of gene expression that determine genome-specific regulatory mechanisms in prokaryotes.

Many biological networks have to filter out useful information from a vast excess of spurious interactions. In this Letter, we use computational evolution to predict design features of networks processing ligand categorization. The important problem of early immune response is considered as a case study. Rounds of evolution with different constraints uncover elaborations of the same network motif we name "adaptive sorting." Corresponding network substructures can be identified in current models of immune recognition. Our work draws a deep analogy between immune recognition and biochemical adaptation.

Endonucleolytic cleavage within polycistronic mRNAs can lead to differential stability, and thus discordant abundance, among cotranscribed genes. RNase Y, the major endonuclease for mRNA decay in , was originally identified for its cleavage activity toward the operon, an event that differentiates the synthesis of a glycolytic enzyme from its transcriptional regulator. A three-protein Y-complex (YlbF, YmcA, and YaaT) was recently identified as also being required for this cleavage in vivo, raising the possibility that it is an accessory factor acting to regulate RNase Y. However, whether the Y-complex is broadly required for RNase Y activity is unknown. Here, we used end-enrichment RNA sequencing (Rend-seq) to globally identify operon mRNAs that undergo maturation posttranscriptionally by RNase Y and the Y-complex. We found that the Y-complex is required for the majority of RNase Y-mediated mRNA maturation events and also affects riboswitch abundance in In contrast, noncoding RNA maturation by RNase Y often does not require the Y-complex. Furthermore, deletion of RNase Y has more pleiotropic effects on the transcriptome and cell growth than deletions of the Y-complex. We propose that the Y-complex is a specificity factor for RNase Y, with evidence that its role is conserved in.

RNA polymerases (RNAPs) transcribe genes through a cycle of recruitment to promoter DNA, initiation, elongation, and termination. After termination, RNAP is thought to initiate the next round of transcription by detaching from DNA and rebinding a new promoter. Here we use single-molecule fluorescence microscopy to observe individual RNAP molecules after transcript release at a terminator. Following termination, RNAP almost always remains bound to DNA and sometimes exhibits one-dimensional sliding over thousands of basepairs. Unexpectedly, the DNA-bound RNAP often restarts transcription, usually in reverse direction, thus producing an antisense transcript. Furthermore, we report evidence of this secondary initiation in live cells, using genome-wide RNA sequencing. These findings reveal an alternative transcription cycle that allows RNAP to reinitiate without dissociating from DNA, which is likely to have important implications for gene regulation.

Highlights d Bacteria produce just enough aaRSs to support the amino acid fluxes for translation d tRNA charging is not maximized at growth-optimized levels of aaRS production d Native levels of uncharged tRNAs have limited impacts on cell fitness d Stringent response alleviates fitness defects of aaRS underproduction in rich media

Variability in the chemical composition of the extracellular environment can significantly degrade the ability of cells to detect rare cognate ligands. Using concepts from statistical detection theory, we formalize the generic problem of detection of small concentrations of ligands in a fluctuating background of biochemically similar ligands binding to the same receptors. We discover that in contrast with expectations arising from considerations of signal amplification, inhibitory interactions between receptors can improve detection performance in the presence of substantial environmental variability, providing an adaptive interpretation to the phenomenon of ligand antagonism. Our results suggest that the structure of signaling pathways responsible for chemodetection in fluctuating and heterogeneous environments might be optimized with respect to the statistics and dynamics of environmental composition. The developed formalism stresses the importance of characterizing nonspecific interactions to understand function in signaling pathways.I nformation transmission within biological networks has recently been subject to intense scrutiny. Quantities such as mutual information appear to be biologically relevant and optimized in many contexts (1), such as neural coding (2) and development (3, 4). In these situations, the nature of the signal is unambiguous: only uncertainty in the value of the input limits information content. In other realistic biological problems, the input consists of a complex mixture, with the signal of interest buried in a sea of nonspecific interactions. For instance, multiple different molecules could bind to a cellular receptor, in which case the signaling pathway downstream needs to find a way to discriminate between correct and spurious signals. An example is immune ligand detection: T cells need to detect foreign ligands at the surface of antigen presenting cells (APC) but there are many other nonagonist ligands interacting with receptors in charge of detection (5).The consideration of heterogeneous environments, with multiple ligand types binding to a receptor, corresponds to a departure from past theoretical analyses of bounds on the performance of cellular measurements (6, 7) and requires specific treatment (8). Predefined mixtures of ligands were previously considered in ref. 9 with an emphasis on optimum decision time for given ligand compositions. Here, we use statistical detection theory to formalize the general problem of detection of a chemical signal in a time-varying mixture. We compare the detection performance of optimal proofreading networks of independent receptors to receptors with inhibitory coupling whose strength increases with the input. We find that despite antagonism and signal attenuation, coupled receptors outperform independent receptors in strongly varying environments. Intuitively, a negative feedback growing with the input size damps rare large fluctuations in the spurious ligand concentration, while retaining sensitivity to situations where few correct ligands ...