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Gene expression originates from individual DNA molecules within living cells. Like many single-molecule processes, gene expression and regulation are stochastic, that is, sporadic in time. This leads to heterogeneity in the messenger-RNA and protein copy numbers in a population of cells with identical genomes. With advanced single-cell fluorescence microscopy, it is now possible to quantify transcriptomes and proteomes with single-molecule sensitivity. Dynamic processes such as transcription-factor binding, transcription and translation can be monitored in real time, providing quantitative descriptions of the central dogma of molecular biology and the demonstration that a stochastic single-molecule event can determine the phenotype of a cell.

Transcription factors regulate gene expression through their binding to DNA. In a living Escherichia coli cell, we directly observed specific binding of a lac repressor, labeled with a fluorescent protein, to a chromosomal lac operator. Using single-molecule detection techniques, we measured the kinetics of binding and dissociation of the repressor in response to metabolic signals. Furthermore, we characterized the nonspecific binding to DNA, one-dimensional (1D) diffusion along DNA segments, and 3D translocation among segments through cytoplasm at the single-molecule level. In searching for the operator, a lac repressor spends ~90% of time nonspecifically bound to and diffusing along DNA with a residence time of <5 milliseconds. The methods and findings can be generalized to other nucleic acid binding proteins.

Bacterial chromosomes are confined in submicrometer-sized nucleoids. Chromosome organization is facilitated by nucleoid-associated proteins (NAPs), but the mechanisms of action remain elusive. In this work, we used super-resolution fluorescence microscopy, in combination with a chromosome-conformation capture assay, to study the distributions of major NAPs in live Escherichia coli cells. Four NAPs—HU, Fis, IHF, and StpA—were largely scattered throughout the nucleoid. In contrast, H-NS, a global transcriptional silencer, formed two compact clusters per chromosome, driven by oligomerization of DNA-bound H-NS through interactions mediated by the amino-terminal domain of the protein. H-NS sequestered the regulated operons into these clusters and juxtaposed numerous DNA segments broadly distributed throughout the chromosome. Deleting H-NS led to substantial chromosome reorganization. These observations demonstrate that H-NS plays a key role in global chromosome organization in bacteria.

Tight coupling of 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 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, it remains unclear whether transcription–translation coupling—together with its broad functional consequences—is indeed a fundamental characteristic of bacteria other than Escherichia coli . 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 the diminished role of Rho-dependent transcription termination, as well as the prevalence of mRNA leaders that use riboswitches and RNA-binding proteins. More broadly, we identified widespread genomic signatures of runaway transcription in distinct phyla across the bacterial domain. Our results show 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. In Bacillus subtilis , unlike in Escherichia coli , transcription and translation of genes are not tightly coupled, and pioneering ribosomes lag substantially behind RNA polymerases.

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 large‐scale 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 . Synopsis Accurate proteomic measurements of absolute protein mass fractions in Escherichia coli allowed the characterization of proteome responses under > 60 diverse growth conditions from a coarse (groups of related proteins) to a fine (individual) protein level. The study presents a mass spectrometric workflow based on data‐independent acquisition proteomics and a novel protein inference algorithm (xTop) optimized for absolute protein quantification. The mass spectrometric data was benchmarked and calibrated with absolute protein mass fractions obtained by ribosome profiling. A plethora of novel biological findings are presented, including lack of large‐scale proteome reallocation under stress compared to nutrient limitations, regulation of outer membrane proteins, and effects important for motility and biofilm formation. Graphical Abstract Accurate proteomic measurements of absolute protein mass fractions in Escherichia coli allowed the characterization of proteome responses under > 60 diverse growth conditions from a coarse (groups of related proteins) to a fine (individual) protein level.

Protein and messenger RNA (mRNA) copy numbers vary from cell to cell in isogenic bacterial populations. However, these molecules often exist in low copy numbers and are difficult to detect in single cells. We carried out quantitative system-wide analyses of protein and mRNA expression in individual cells with single-molecule sensitivity using a newly constructed yellow fluorescent protein fusion library for Escherichia coli. We found that almost all protein number distributions can be described by the gamma distribution with two fitting parameters which, at low expression levels, have clear physical interpretations as the transcription rate and protein burst size. At high expression levels, the distributions are dominated by extrinsic noise. We found that a single cell's protein and mRNA copy numbers for any given gene are uncorrelated.

Pseudouridine (Ψ) is an ubiquitous RNA modification, present in the tRNAs and rRNAs of species across all domains of life. Conserved pseudouridine synthases modify the mRNAs of diverse eukaryotes, but the modification has yet to be identified in bacterial mRNAs. Here, we report the discovery of pseudouridines in mRNA from E . coli . By testing the mRNA modification capacity of all 11 known pseudouridine synthases, we identify RluA as the predominant mRNA-modifying enzyme. RluA, a known tRNA and 23S rRNA pseudouridine synthase, modifies at least 31 of the 44 high-confidence sites we identified in E . coli mRNAs. Using RNA structure probing data to inform secondary structures, we show that the target sites of RluA occur in a common sequence and structural motif comprised of a ΨURAA sequence located in the loop of a short hairpin. This recognition element is shared with previously identified target sites of RluA in tRNAs and rRNA. Overall, our work identifies pseudouridine in key mRNAs and suggests the capacity of Ψ to regulate the transcripts that contain it.

Bacterial mRNAs are organized into operons consisting of discrete open reading frames (ORFs) in a single polycistronic mRNA. Individual ORFs on the mRNA are differentially translated, with rates varying as much as 100-fold. The signals controlling differential translation are poorly understood. Our genome-wide mRNA secondary structure analysis indicated that operonic mRNAs are comprised of ORF-wide units of secondary structure that vary across ORF boundaries such that adjacent ORFs on the same mRNA molecule are structurally distinct. ORF translation rate is strongly correlated with its mRNA structure in vivo, and correlation persists, albeit in a reduced form, with its structure when translation is inhibited and with that of in vitro refolded mRNA. These data suggest that intrinsic ORF mRNA structure encodes a rough blueprint for translation efficiency. This structure is then amplified by translation, in a self-reinforcing loop, to provide the structure that ultimately specifies the translation of each ORF. Proteins make up much of the biological machinery inside cells and perform the essential tasks needed to keep each cell alive. Cells contain thousands of different proteins and the instructions needed to build each protein are encoded in genes. However, these instructions cannot be used directly to manufacture the proteins. Instead, a messenger molecule called mRNA is needed to carry the information stored within genes to the parts of the cell where proteins are made. In bacteria, one mRNA molecule can include information from several genes. This group of genes is called an operon and produces a set of proteins that perform a shared task. Although these proteins work together, some of them are needed in greater numbers than others. Because they are all made using information from the same mRNA, some instructions on the mRNA must be read more times than others. It is unclear how bacterial cells control how many proteins are produced from each part of one mRNA but it is thought to relate to the three-dimensional shape of the molecule itself. Burkhardt, Rouskin, Zhang et al. have now examined the production of proteins from mRNAs in the commonly studied bacterium, Escherichia coli. The results showed that each set of instructions on the mRNA formed a three-dimensional structure that corresponds to the amount of protein produced from that portion of the mRNA. When this three-dimensional structure is more stable or rigid, the corresponding instructions tended to produce fewer proteins than if the structure was relatively simple and unstable. Further investigation showed that these three-dimensional mRNA structures could form spontaneously outside of cells, suggesting that molecules other than the mRNA itself have a relatively small role in controlling the number of proteins produced. This also suggests that the entire structure of each mRNA is important and is likely to be essential for cell survival. The next step is to understand why bacteria organise their genes in this way and how the different mRNA structures control how proteins are produced. Moreover, because many bacteria are used like biological factories to produce a variety of commercially useful molecules, these new insights have the potential to enhance a number of manufacturing processes.

Proteins seek out binding sites on DNA through diffusion and also by sliding along the strand. Although ‘roadblocks’—other bound proteins on the DNA strand—slow things down, it seems that looping of the DNA aids the search process. DNA-binding proteins control how genomes function. The theory of facilitated diffusion 1 explains how DNA-binding proteins can find targets apparently faster than the diffusion limit by using reduced dimensionality 2 , 3 —combining three-dimensional (3D) diffusion through cytoplasm with 1D sliding along DNA (refs  3 , 4 , 5 , 6 , 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 ). However, it does not include a description of macromolecular crowding on DNA as observed in living cells. Here, we show that such a physical constraint to sliding greatly reduces the search speed, in agreement with single-molecule measurements. Interestingly, the generalized theory also reveals significant insights into the design principles of biology. First, it places a hard constraint on the total number of DNA-binding proteins per cell. Remarkably, the number measured for Escherichia coli fits within the optimal range. Secondly, it defines a new role for DNA looping, a ubiquitous topological motif in genomes. DNA looping can speed up the search process by bypassing proteins that block the sliding track close to the target.

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. In the canonical bacterial transcription, both nascent transcript and polymerase dissociate from template DNA. By employing multi-color single-molecule fluorescence imaging, here the authors show that RNA polymerases remain bound to DNA after the transcript release.