SRSF3 shapes the structure of miR-17-92 cluster RNA and promotes selective processing of miR-17 and miR-20a.

MicroRNA (miRNA) biogenesis is tightly regulated to maintain distinct miRNA expression patterns. Almost half of mammalian miRNAs are generated from miRNA clusters, but this process is not well understood. We show here that Serine-arginine rich splicing factor 3 (SRSF3) controls the processing of miR-17-92 cluster miRNAs in pluripotent and cancer cells. SRSF3 binding to multiple CNNC motifs downstream of Drosha cleavage sites within miR-17-92 is required for the efficient processing of the cluster. SRSF3 depletion specifically compromises the processing of two paralog miRNAs, miR-17 and miR-20a. In addition to SRSF3 binding to the CNNC sites, the SRSF3 RS-domain is essential for miR-17-92 processing. SHAPE-MaP probing demonstrates that SRSF3 binding disrupts local and distant base pairing, resulting in global changes in miR-17-92 RNA structure. Our data suggest a model where SRSF3 binding, and potentially its RS-domain interactions, may facilitate an RNA structure that promotes miR-17-92 processing. SRSF3-mediated increase in miR-17/20a levels inhibits the cell cycle inhibitor p21, promoting self-renewal in normal and cancer cells. The SRSF3-miR-17-92-p21 pathway operates in colorectal cancer, linking SRSF3-mediated pri-miRNA processing and cancer pathogenesis.

Alteration of DNA supercoiling serves as a trigger of short-term cold shock repressed genes of E. coli.

Cold shock adaptability is a key survival skill of gut bacteria of warm-blooded animals. Escherichia coli cold shock responses are controlled by a complex multi-gene, timely-ordered transcriptional program. We investigated its underlying mechanisms. Having identified short-term, cold shock repressed genes, we show that their responsiveness is unrelated to their transcription factors or global regulators, while their single-cell protein numbers' variability increases after cold shock. We hypothesized that some cold shock repressed genes could be triggered by high propensity for transcription locking due to changes in DNA supercoiling (likely due to DNA relaxation caused by an overall reduction in negative supercoiling). Concomitantly, we found that nearly half of cold shock repressed genes are also highly responsive to gyrase inhibition (albeit most genes responsive to gyrase inhibition are not cold shock responsive). Further, their response strengths to cold shock and gyrase inhibition correlate. Meanwhile, under cold shock, nucleoid density increases, and gyrases and nucleoid become more colocalized. Moreover, the cellular energy decreases, which may hinder positive supercoils resolution. Overall, we conclude that sensitivity to diminished negative supercoiling is a core feature of E. coli's short-term, cold shock transcriptional program, and could be used to regulate the temperature sensitivity of synthetic circuits.

The transcription factor network of E. coli steers global responses to shifts in RNAP concentration.

The robustness and sensitivity of gene networks to environmental changes is critical for cell survival. How gene networks produce specific, chronologically ordered responses to genome-wide perturbations, while robustly maintaining homeostasis, remains an open question. We analysed if short- and mid-term genome-wide responses to shifts in RNA polymerase (RNAP) concentration are influenced by the known topology and logic of the transcription factor network (TFN) of Escherichia coli. We found that, at the gene cohort level, the magnitude of the single-gene, mid-term transcriptional responses to changes in RNAP concentration can be explained by the absolute difference between the gene's numbers of activating and repressing input transcription factors (TFs). Interestingly, this difference is strongly positively correlated with the number of input TFs of the gene. Meanwhile, short-term responses showed only weak influence from the TFN. Our results suggest that the global topological traits of the TFN of E. coli shape which gene cohorts respond to genome-wide stresses.

Analytical kinetic model of native tandem promoters in E. coli.

Closely spaced promoters in tandem formation are abundant in bacteria. We investigated the evolutionary conservation, biological functions, and the RNA and single-cell protein expression of genes regulated by tandem promoters in E. coli. We also studied the sequence (distance between transcription start sites 'dTSS', pause sequences, and distances from oriC) and potential influence of the input transcription factors of these promoters. From this, we propose an analytical model of gene expression based on measured expression dynamics, where RNAP-promoter occupancy times and dTSS are the key regulators of transcription interference due to TSS occlusion by RNAP at one of the promoters (when dTSS ≤ 35 bp) and RNAP occupancy of the downstream promoter (when dTSS > 35 bp). Occlusion and downstream promoter occupancy are modeled as linear functions of occupancy time, while the influence of dTSS is implemented by a continuous step function, fit to in vivo data on mean single-cell protein numbers of 30 natural genes controlled by tandem promoters. The best-fitting step is at 35 bp, matching the length of DNA occupied by RNAP in the open complex formation. This model accurately predicts the squared coefficient of variation and skewness of the natural single-cell protein numbers as a function of dTSS. Additional predictions suggest that promoters in tandem formation can cover a wide range of transcription dynamics within realistic intervals of parameter values. By accurately capturing the dynamics of these promoters, this model can be helpful to predict the dynamics of new promoters and contribute to the expansion of the repertoire of expression dynamics available to synthetic genetic constructs.

Temperature-dependence of the single-cell variability in the kinetics of transcription activation in Escherichia coli.

From in vivo single-cell, single-RNA measurements of the activation times and subsequent steady-state active transcription kinetics of a single-copy Lac-ara-1 promoter in Escherichia coli, we characterize the intake kinetics of the inducer (IPTG) from the media, following temperature shifts. For this, for temperature shifts of various degrees, we obtain the distributions of transcription activation times as well as the distributions of intervals between consecutive RNA productions following activation in individual cells. We then propose a novel methodology that makes use of deconvolution techniques to extract the mean and the variability of the distribution of intake times. We find that cells, following shifts to low temperatures, have higher intake times, although, counter-intuitively, the cell-to-cell variability of these times is lower. We validate the results using a new methodology for direct estimation of mean intake times from measurements of activation times at various inducer concentrations. The results confirm that E. coli's inducer intake times from the environment are significantly higher following a shift to a sub-optimal temperature. Finally, we provide evidence that this is likely due to the emergence of additional rate-limiting steps in the intake process at low temperatures, explaining the reduced cell-to-cell variability in intake times.

The precision of the symmetry in Z-ring placement in Escherichia coli is hampered at critical temperatures.

Cell division in Escherichia coli is morphologically symmetric due to, among other things, the ability of these cells to place the Z-ring at midcell. Studies have reported that, at sub-optimal temperatures, this symmetry decreases at the single-cell level, but the causes remain unclear. Using fluorescence microscopy, we observe FtsZ-GFP and DAPI-stained nucleoids to assess the robustness of the symmetry of Z-ring formation and positioning in individual cells under sub-optimal and critical temperatures. We find the Z-ring formation and positioning to be robust at sub-optimal temperatures, as the Z-ring's mean width, density and displacement from midcell maintain similar levels of correlation to one another as at optimal temperatures. However, at critical temperatures, the Z-ring displacement from midcell is greatly increased. We present evidence showing that this is due to enhanced distance between the replicated nucleoids and, thus, reduced Z-ring density, which explains the weaker precision in setting a morphologically symmetric division site. This also occurs in rich media and is cumulative, i.e. combining richer media and critically high temperatures enhances the asymmetries in division, which is evidence that the causes are biophysical. To further support this, we show that the effects are reversible, i.e. shifting cells from optimal to critical, and then to optimal again, reduces and then enhances the symmetry in Z-ring positioning, respectively, as the width and density of the Z-ring return to normal values. Overall, our findings show that the Z-ring positioning in E. coli is a robust biophysical process under sub-optimal temperatures, and that critical temperatures cause significant asymmetries in division.

Sequence-dependent model of genes with dual σ factor preference.

Escherichia coli uses σ factors to quickly control large gene cohorts during stress conditions. While most of its genes respond to a single σ factor, approximately 5% of them have dual σ factor preference. The most common are those responsive to both σ70, which controls housekeeping genes, and σ38, which activates genes during stationary growth and stresses. Using RNA-seq and flow-cytometry measurements, we show that 'σ70+38 genes' are nearly as upregulated in stationary growth as 'σ38 genes'. Moreover, we find a clear quantitative relationship between their promoter sequence and their response strength to changes in σ38 levels. We then propose and validate a sequence dependent model of σ70+38 genes, with dual sensitivity to σ38 and σ70, that is applicable in the exponential and stationary growth phases, as well in the transient period in between. We further propose a general model, applicable to other stresses and σ factor combinations. Given this, promoters controlling σ70+38 genes (and variants) could become important building blocks of synthetic circuits with predictable, sequence-dependent sensitivity to transitions between the exponential and stationary growth phases.

Dissecting the in vivo dynamics of transcription locking due to positive supercoiling buildup.

Positive supercoiling buildup (PSB) is a pervasive phenomenon in the transcriptional programs of Escherichia coli. After finding a range of Gyrase concentrations where the inverse of the transcription rate of a chromosome-integrated gene changes linearly with the inverse of Gyrase concentration, we apply a LineWeaver-Burk plot to dissect the expected in vivo transcription rate in absence of PSB. We validate the estimation by time-lapse microscopy of single-RNA production kinetics of the same gene when single-copy plasmid-borne, shown to be impervious to Gyrase inhibition. Next, we estimate the fraction of time in locked states and number of transcription events prior to locking, which we validate by measurements under Gyrase inhibition. Replacing the gene of interest by one with slower transcription rate decreases the fraction of time in locked states due to PSB. Finally, we combine data from both constructs to infer a range of possible transcription initiation locking kinetics in a chromosomal location, obtainable by tuning the transcription rate. We validate with measurements of transcription activity at different induction levels. This strategy for dissecting transcription initiation locking kinetics due to PSB can contribute to resolve the transcriptional programs of E. coli and in the engineering of synthetic genetic circuits.

Estimating RNA numbers in single cells by RNA fluorescent tagging and flow cytometry.

Estimating the statistics of single-cell RNA numbers has become a key source of information on gene expression dynamics. One of the most informative methods of in vivo single-RNA detection is MS2d-GFP tagging. So far, it requires microscopy and laborious semi-manual image analysis, which hampers the amount of collectable data. To overcome this limitation, we present a new methodology for quantifying the mean, standard deviation, and skewness of single-cell distributions of RNA numbers, from flow cytometry data on cells expressing RNA tagged with MS2d-GFP. The quantification method, based on scaling flow-cytometry data from microscopy single-cell data on integer-valued RNA numbers, is shown to readily produce precise, big data on in vivo single-cell distributions of RNA numbers and, thus, can assist in studies of transcription dynamics.