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• W4387666721 abstract "Full text Figures and data Side by side Abstract eLife assessment Introduction Results Discussion Materials and methods Data availability References Peer review Author response Article and author information Abstract Flagella are important for bacterial motility as well as for pathogenesis. Synthesis of these structures is energy intensive and, while extensive transcriptional regulation has been described, little is known about the posttranscriptional regulation. Small RNAs (sRNAs) are widespread posttranscriptional regulators, most base pairing with mRNAs to affect their stability and/or translation. Here, we describe four UTR-derived sRNAs (UhpU, MotR, FliX and FlgO) whose expression is controlled by the flagella sigma factor σ28 (fliA) in Escherichia coli. Interestingly, the four sRNAs have varied effects on flagellin protein levels, flagella number and cell motility. UhpU, corresponding to the 3´ UTR of a metabolic gene, likely has hundreds of targets including a transcriptional regulator at the top flagella regulatory cascade connecting metabolism and flagella synthesis. Unlike most sRNAs, MotR and FliX base pair within the coding sequences of target mRNAs and act on ribosomal protein mRNAs connecting ribosome production and flagella synthesis. The study shows how sRNA-mediated regulation can overlay a complex network enabling nuanced control of flagella synthesis. eLife assessment This article provides important findings on how bacteria use small RNAs to regulate flagellar expression with implications for multiple fields. The data supporting the conclusions are convincing with a large amount of data that include results from phenotypic analyses, genomics approaches as well as in-vitro and in-vivo target identification and validation methods. This study on the varied effects of three sRNAs (UhpU, FliX and MotR) is of broad interest to RNA biochemists and microbiologists. https://doi.org/10.7554/eLife.87151.3.sa0 About eLife assessments Introduction Most bacteria are motile and can swim through liquid and semiliquid environments in large part driven by the flagellum. The highly complex bacterial flagellum consists of three major domains: an ion-driven motor, which can provide torque in either direction; a universal joint called the hook-basal body, which transmits motor torque; and a 20-nm-thick hollow filament tube composed of the flagellin subunit, which acts as a propeller (reviewed in Altegoer and Bange, 2015; Nakamura and Minamino, 2019). The complete flagellum is comprised of many proteins, and the flagellar regulon encompasses more than 50 genes. Flagella are costly for the cell to synthesize, requiring up to ~2% of the cell’s biosynthetic energy expenditure and extensive use of ribosomes (reviewed in Soutourina and Bertin, 2003; Guttenplan and Kearns, 2013). To ensure that flagellar components are made in the order in which they are needed, transcription of the genes in the regulon is activated in a sequential manner in Escherichia coli (Kalir et al., 2001) and Salmonella enterica (reviewed in Chevance and Hughes, 2008). The genes can be divided into three groups based on their time of activation: early genes, middle genes, and late genes (Figure 1A). The FlhDC transcription regulators, encoded by the two early genes, activate the transcription of the middle genes (Class 2), which are required for the hook-basal body. FlhDC also activates transcription of fliA, encoding sigma factor σ28 (Fitzgerald et al., 2014). σ28 in turn activates transcription of the late genes responsible for completing the flagellum and the chemotaxis system (Class 3). σ28 additionally increases expression of several of the middle genes (Class 2/3) (Fitzgerald et al., 2014). σ28 activity itself is negatively regulated by the anti-sigma factor, FlgM, which is transported out of the cell, freeing σ28, when the hook-basal body complex is complete (reviewed in Smith and Hoover, 2009; Osterman et al., 2015). Given the numerous components required at different times and in different stoichiometries during flagellum assembly, various factors can be rate limiting under specific conditions (reviewed in Chevance and Hughes, 2008). The dependence of flagella synthesis on FlhDC and σ28 generates a coherent feed-forward loop. In this loop, the first regulator (FlhDC) activates the second regulator (σ28), and they both additively activate their target genes. This results in prolonged flagellar expression, protecting the flagella synthesis from a transient loss of input signal (Kalir et al., 2005). Figure 1 with 2 supplements see all Download asset Open asset σ28-Dependent sRNAs are primarily expressed in log phase. (A) Overview of the flagellar regulon. The early genes initiate the transcription of the middle genes, including fliA which encodes σ28. In turn, σ28 initiates the transcription of the late genes and enhances the transcription of some of the middle genes. For the middle and late genes, only selected operons are shown. The sRNAs analyzed in this study are colored in blue. This model was inspired by Kalir et al., 2005. (B) Browser images showing levels of UhpU, MotR, FliX, and FlgO sRNAs in total RNA (black) and Hfq co-immunoprecipitation (gray) libraries. Normalized read count ranges are shown in the upper right of each frame. Data analyzed is from (RIL-seq experiment 1, Melamed et al., 2020). (C) Northern blot analysis of total RNA from WT (GSO983) or ∆fliA (GSO1068) cells grown to the indicated time points. A full-length transcript (~260 nt) and several processed transcripts, of which one is predominant (UhpU-S,~60 nt), are detected for UhpU, one prominent band (~95 nt) is detected for MotR, one prominent band (~200 nt) is detected for FliX, and two bands close in size (~75 nt) are detected for FlgO. (D) Northern blot analysis of WT (GSO983) cells grown to OD600 ~0.6 and~1.0. RNA was extracted from total lysates as well as samples from co-immunoprecipitation with Hfq, separated on an acrylamide gel, transferred to a membrane, and probed for σ28-dependent sRNAs. A~100 nt FliX band (FliX-S) was revealed immunoprecipitating with Hfq. In (C) and (D), RNAs were probed sequentially on the same membrane, and the 5S RNA served as a loading control. Given flagella are so costly to produce, synthesis is tightly regulated such that flagellar components are only made when motility is beneficial. Thus, flagellar synthesis is strongly impacted by environmental signals. For instance, flagellar gene expression is decreased in the presence of D-glucose, in high temperatures, high salt, and extreme pH, as well as the presence of DNA gyrase inhibitors (Shi et al., 1993; Adler and Templeton, 1967). The flagellar genes are activated under oxygen-limited conditions (Landini and Zehnder, 2002) and at various stages of infection (reviewed in Erhardt, 2016). Consequently, transcription of many genes in the flagellar regulon is regulated in response to a range of environmental signals. For example, the transcription of flhDC is controlled by at least 13 transcription factors, each of them active under different conditions (reviewed in Prüß, 2017). While the activation of flagella synthesis has been examined in some detail, there has been less investigation into the termination of synthesis, which we presume is equally important for the conservation of resources. Additionally, while transcriptional regulation of flagella genes has been studied for many years, the post-transcriptional control of the regulon has only received limited attention. Small RNAs (sRNAs) that can originate from many different genetic loci (reviewed in Adams and Storz, 2020) are key post-transcriptional regulators in bacteria. They usually regulate their targets in trans via limited base-pairing, affecting translation and/or mRNA stability (reviewed in Hör et al., 2020; Papenfort and Melamed, 2023). Many characterized sRNAs are stabilized and their base pairing with targets increased by RNA chaperones, of which the hexameric, ring-shaped Hfq protein has been studied most extensively (reviewed in Updegrove et al., 2016; Holmqvist and Vogel, 2018). The only post-transcriptional control by base pairing sRNAs described for the E. coli flagellar regulon thus far is negative regulation of flhDC by ArcZ, OmrA, OmrB, OxyS (De Lay and Gottesman, 2012), and AsflhD (encoded antisense to flhD)(Lejars et al., 2022), positive regulation of the same mRNA by McaS (Thomason et al., 2012), and negative regulation of flgM by OmrA and OmrB (Romilly et al., 2020). These sRNAs and a few other sRNAs also were shown to affect motility and biofilm formation (Bak et al., 2015). In this study, we characterized four σ28-dependent sRNAs, which were detected with their targets on Hfq through RIL-seq methodology that captures the sRNA-target interactome (Melamed et al., 2016; Melamed et al., 2020 and reviewed in Silverman and Melamed, 2023). These sRNAs originate from the untranslated regions (UTRs) of mRNAs, three of which belong to the flagellar regulon. We identified a wide range of targets for the sRNAs, including genes related to flagella and ribosome synthesis and observed that the sRNAs act on some of these targets by unique modes of action. We also found that three of these sRNAs regulate flagella number and bacterial motility, possibly imposing temporal control on flagella synthesis and integrating metabolic signals into this complex regulatory network. Results σ28-dependent sRNAs are expressed sequentially in log phase cells Analysis of several different RNA-seq data sets suggested the expression of four σ28-dependent sRNAs in E. coli. σ28-dependent expression of the sRNAs was detected using ChIP-seq and RNA-seq in a comprehensive analysis of the σ28 regulon (Fitzgerald et al., 2014), while the position and nature of the 5´ ends were revealed by a 5´ end mapping study (Thomason et al., 2015). Regulatory roles were indicated by binding to other RNAs in RIL-seq data (Melamed et al., 2016; Melamed et al., 2020; Bar et al., 2021). The four sRNAs originate from the UTRs of protein coding genes (Figure 1B and Figure 1—figure supplement 1A). UhpU corresponds to the 3´ UTR of uhpT, which encodes a hexose phosphate transporter (Marger and Saier, 1993). UhpU is transcribed from its own promoter inside the coding sequence (CDS) of uhpT (Thomason et al., 2015). The other three σ28-dependent sRNAs correspond to the UTRs of the late genes in the flagellar regulon. MotR originates from the 5´ UTR of motA, which encodes part of the flagellar motor complex. Based on previous transcription start site analysis, the promoter for motR is within the flhC CDS and is also the promoter of the downstream motAB-cheAW operon (Thomason et al., 2015; Fitzgerald et al., 2014). FliX originates from the 3´ UTR of fliC, which encodes flagellin, the core component of the flagellar filament (reviewed in Thomson et al., 2018). FlgO originates from the 3´ UTR of flgL, a gene that encodes a junction protein shown to connect the flagella to the hook in S. enterica (Ikeda et al., 1987). The observation that FliX and FlgO levels decline substantially in RNA-seq libraries treated with 5´ phosphate-dependent exonuclease to deplete processed RNAs (Thomason et al., 2015), indicates that both of these sRNAs are processed from their parental mRNAs. Northern blot analysis confirmed σ28-dependent synthesis of these sRNAs since expression was significantly decreased in a mutant lacking σ28 (ΔfliA) (Figure 1C). Given that most σ28-dependent mRNAs encode flagella components, the regulation suggests the sRNAs impact flagella synthesis. The northern analysis also showed that the levels of the four σ28-dependent sRNAs are highest in the transition from mid-exponential to stationary phase growth, though there are some differences with UhpU and MotR peaking before FliX and FlgO (Figure 1C and Figure 1—figure supplement 2). Since flagellar components are expressed at precise times, the difference in the UhpU and MotR peak times compared to the FliX and FlgO peak times hints at different roles for each of these sRNAs. For UhpU, two predominant bands were observed, a long transcript and a shorter transcript processed from UhpU (denoted UhpU-S), which corresponds to the higher peak in the sequencing data (Figure 1B). One prominent band was detected for MotR and for FliX, while a doublet was observed for FlgO. Additional higher bands detected by the MotR probe could be explained by RNA polymerase readthrough of the MotR terminator into the downstream motAB-cheAW operon, while the additional bands seen for FliX could be explained by alternative processing of the fliC mRNA. We also examined the levels of the four sRNAs in minimal media (M63) supplemented with different carbon sources (Figure 1—figure supplement 1B). Generally, the sRNAs levels in minimal medium are comparable to or slightly higher to the levels in rich media (LB) except in medium with glucose-6-phosphate (G6P), where the levels of UhpU-S are significantly elevated while the levels of full-length UhpU transcript and the other σ28-dependent sRNAs are decreased. These observations suggest an alternative means for UhpU-S generation from the uhpT mRNA known to be induced by G6P (Postma et al., 2001). We also observe more FliX products, particularly for cells grown in minimal medium with ribose or galactose. The predicted structures for the four σ28-dependent sRNAs (Figure 1—figure supplement 1C), with strong stem-loops at the 3´ ends, are consistent with the structures of known Hfq-binding sRNAs and the association with Hfq observed in the RIL-seq data (Melamed et al., 2016). To confirm Hfq binding, we probed RNA that co-immunoprecipitated with Hfq (Figure 1D). Strong enrichment and fewer background bands were observed for all of the sRNAs; ~260 nt and ~60 nt bands for UhpU and UhpU-S, respectively, a~95 nt band for MotR, a ~200 nt band for FliX and a doublet of ~75 nt bands for FlgO. For FliX, we also detected a second ~100 nt FliX band (denoted FliX-S; Figure 1—figure supplement 1A) that corresponds to the 3´ peak in the sequencing data (Figure 1B) and includes one of the repetitive extragenic palindromic (REP) sequences downstream of fliC. σ28-dependent sRNAs impact flagella number and bacterial motility To begin to decipher the roles of the four σ28-dependent sRNAs, we constructed plasmids for overexpression of the sRNAs (Figure 2—figure supplement 1A). Given that it was challenging to obtain constructs constitutively overexpressing UhpU because all clones had mutations, this sRNA could only be expressed from a plasmid when controlled by an IPTG-inducible Plac promoter (Guo et al., 2014), hinting at a critical UhpU role in E. coli vitality. The other sRNAs were expressed from a plasmid with the constitutive PLlacO-1 promoter (Urban and Vogel, 2007). We also obtained a plasmid constitutively overexpressing MotR*, a more abundant derivative of MotR identified by chance (TGC at positions 6–8 mutated to GAG; Figure 1—figure supplement 1A). We tested the effects of overexpressing the sRNAs on flagellar synthesis by determining the number of flagella by electron microscopy (EM) and on bacterial motility by assaying the spread of cells on 0.3% agar plates. The WT E. coli strain used throughout the paper is highly motile due to an IS1 insertion in the crl gene (crl-), thus eliminating expression of a protein that promotes σS binding to the RNA polymerase core enzyme (Typas et al., 2007), and resulting in higher expression of the flagellar regulatory cascade (Pesavento et al., 2008). However, we also assayed a less motile strain with the restored crl+ gene for UhpU and MotR effects on motility, given that no effects were observed with the highly motile crl- strain. Intriguingly, overexpression of the individual sRNAs had different consequences. UhpU overexpression caused a slight increase in flagella number (Figure 2A) and a marked increase in motility (Figure 2B). Overexpression of MotR, particularly MotR*, led to a dramatic increase in the flagella number (Figure 2C and Figure 2—figure supplement 2A) and MotR but not MotR* had a slight effect on motility (Figure 2D and Figure 2—figure supplement 2B). It has been suggested that the run/tumble behavior of bacteria, which affect their swimming, is only weakly dependent on number of flagella (Mears et al., 2014), possibly explaining these somewhat contradictory effects on flagella number and motility. In contrast to UhpU and MotR, FliX overexpression led to a reduction in the number of flagella (Figure 2E), an effect that was even more pronounced in a strain overexpressing FliX-S (Figure 2—figure supplement 2C). Overexpression of FliX-S but not FliX also reduced bacterial motility (Figure 2F and Figure 2—figure supplement 2D). While FliX-S overexpression seems to lead to aflagellated bacteria, we hypothesize that the sRNA is delaying but not eliminating flagella gene expression, explaining why the bacteria are still moderately motile. Some motility phenotypes can be explained by differences in growth rate, but we do not think that this is the case for MotR and FliX as we observed only slight effects on growth upon MotR, MotR*, FliX and FliX-S overexpression (Figure 2—figure supplement 1B). FlgO overexpression did not result in detectable changes in our assays (Figure 2G and Figure 2H). Together, these results show that the σ28-dependent sRNAs have a range of effects on flagella number and motility, with UhpU and MotR, which are expressed first, increasing both phenotypes and FliX, which is expressed later, decreasing both. Given that MotR* and FliX-S have stronger effects for some phenotypes and provide a bigger dynamic range, these derivatives were included in subsequent assays. Figure 2 with 2 supplements see all Download asset Open asset Overexpression of the σ28-dependent sRNAs leads to differences in flagella number and motility. (A) Moderate increase in flagella number with UhpU overexpression based on EM analysis for WT (crl-) cells carrying an empty vector or overexpressing UhpU. (B) Increased motility with UhpU overexpression based on motility in 0.3% agar for WT (crl+) cells carrying an empty vector or overexpressing UhpU. (C) Increase in flagella number with MotR overexpression based on EM analysis for WT (crl-) cells carrying an empty vector or overexpressing MotR. (D) Slight increase in motility with MotR overexpression based on motility in 0.3% agar for WT (crl+) cells carrying an empty vector or overexpressing MotR. (E) Reduction in flagella number with FliX overexpression based on EM analysis for WT (crl-) cells carrying an empty vector or overexpressing FliX. (F) Reduced motility with FliX overexpression based on motility in 0.3% agar for WT (crl-) cells carrying an empty vector or overexpressing FliX. (G) No change in flagella number with FlgO overexpression based on EM analysis for WT (crl-) cells carrying an empty vector or overexpressing FlgO. (H) No change in motility with FlgO overexpression based on motility in 0.3% agar for WT (crl-) cells carrying an empty vector or overexpressing FlgO. Cells in (A) and (B) were induced with 1 mM IPTG. Quantification for all the assays is shown on the right. For (A), (C), (E) and (G) quantification of the number of flagella per cell was done by counting the flagella for 20 cells (black dots), and a one-way ANOVA comparison was performed to calculate the significance of the change in flagella number (ns = not significant, **=p < 0.01, ****=p < 0.0001). Each experiment was repeated three times, and one representative experiment is shown. The bottom and top of the box are the 25th and 75th percentiles, the line inside the box is the median, the lower and the upper whiskers represent the minimum and the maximum values of the dataset, respectively. While some differences in cells size and width were observed in the EM analysis, they were not statistically significant. The experiments presented in (C) and (E) were carried out on same day, and the same pZE sample is shown. Graphs for (B), (D), (F) and (H) show the average of nine biological repeats. Error bars represent one SD, and a one-way ANOVA comparison was performed to calculate the significance of the change in motility (ns = not significant, *=p < 0.05, ****=p < 0.0001). The scales given in (A) and (B) are the same for all EM images and all motility plates, respectively. σ28-dependent sRNAs have wide range of potential targets based on RIL-seq analysis To understand the phenotypes associated with overexpression of the σ28-dependent sRNAs, we took advantage of the sRNA-target interactome data obtained by RIL-seq (Melamed et al., 2020; Melamed et al., 2016). We analyzed the data (Supplementary file 1) generated from 18 samples representing six different growth conditions, which included different stages of bacterial growth in rich medium as well as growth in minimal medium and iron-limiting conditions. We selected targets for further characterization if they were detected in the datasets for least four different conditions. The sRNAs differ significantly in their target sets (Figure 3—figure supplement 1A). In general, UhpU is a hub with hundreds of RIL-seq targets. Its target set comprises a wide range of genes, including multiple genes that have roles in flagella synthesis and carbon metabolism. MotR and FliX were associated with fewer targets, but intriguingly, both sets were enriched for genes encoding ribosomal proteins. We also noted that the fliC gene encoding flagellin was present in the target sets for UhpU, MotR, and FliX. Although FlgO is one of the most strongly enriched sRNAs upon Hfq purification (ranked fourth in Melamed et al., 2020), it had the smallest set of targets. Almost none of the targets were found in more than two conditions and only gatC was detected in four conditions, hinting FlgO might not act as a conventional Hfq-dependent base-pairing sRNA. Unlike for most characterized sRNA targets, the RIL-seq signal for the sRNA interactions with fliC and the ribosomal protein genes is internal to the CDSs (Supplementary file 1 and Figure 3—figure supplement 1B). Before turning our attention to these unique targets, we first examined the UhpU interaction with a canonical target. UhpU represses expression of the LrhA transcriptional repressor of flhDC We were intrigued to find that the mRNA encoding the transcription factor LrhA, which represses flhDC transcription, was among the top RIL-seq interactors for UhpU (Supplementary file 1). The signals that activate this LysR-type transcription factor (Lehnen et al., 2002), are not known, but the lrhA mRNA has an unusually long 371 nt 5´ UTR (Figure 3A), a feature that has been found to correlate with post-transcriptional regulation (reviewed in Adams and Storz, 2020). The predicted base pairing between UhpU and the lrhA 5´-UTR (Figure 3B) corresponds to the seed sequence suggested for UhpU (Melamed et al., 2016). Figure 3 with 1 supplement see all Download asset Open asset Multiple sRNAs repress LrhA synthesis. (A) Browser image showing chimeras (in red) for UhpU, ArcZ, RprA and McaS, at the 5´ UTR region of lrhA. Blue highlighting indicates position of sRNA-lrhA base pairing. Data analyzed is from Melamed et al., 2020. (B) Base-pairing between lrhA and UhpU with sequences of mutants assayed. Seed sequence predicted by Melamed et al., 2016 is underlined. Numbering is from AUG of lrhA mRNA and +1 of UhpU sRNA. (C) UhpU represses lrhA-lacZ fusion based on β-galactosidase assay detecting the levels of lrhA-lacZ and lrhA-M1-lacZ translational fusions in response to UhpU and UhpU-M1 overexpression. (D) UhpU does not affect motility when LrhA is absent, based on motility in 0.3% agar for WT (crl+) cells or ΔlrhA cells (GSO1179) carrying an empty vector or overexpressing UhpU. Graph shows the average of three biological repeats, and error bars represent one SD. One-way ANOVA comparison was performed to calculate the significance of the change in motility (ns = not significant, ****=p < 0.0001). (E) Predicted base-pairing between lrhA and ArcZ, RprA or McaS. Numbering is from AUG of lrhA mRNA and +1 of indicated sRNAs. (F) Down regulation of lrhA by ArcZ and RprA but not McaS based on β-galactosidase assay detecting the levels of lrhA-lacZ translational fusions in response to ArcZ, RprA and McaS overexpression. For (C) and (F), graphs show the average of three biological repeats, and error bars represent one SD. One-way ANOVA comparison was performed to calculate the significance of the change in β-galactosidase activity (ns = not significant, ****=p < 0.0001). To test the effects of UhpU on this target, we fused the 5´ UTR of lrhA, which includes the region of the RIL-seq lrhA-UhpU chimeras and the predicted base-pairing region, to a lacZ reporter (Mandin and Gottesman, 2009). UhpU overexpression reduced expression of the chromosomally-encoded PBAD-lrhA-lacZ reporter (Figure 3C). A single nucleotide mutation in the base pairing region of uhpU (uhpU-M1) eliminated UhpU repression of lrhA-lacZ, while a complementary mutation introduced into the chromosomal lrhA-lacZ fusion (lrhA-M1) restored the repression providing direct evidence for UhpU base pairing to lrhA leading to repression. Down-regulation of LrhA by UhpU, which is expected to lead to increased FlhDC levels, is in accord with the positive impact of UhpU on motility (Figure 2). To test this model, we monitored the effect of UhpU on bacterial motility in a lrhA deletion strain compared to a WT strain (Figure 3D). With UhpU overexpression, motility was increased in the WT background as expected. In contrast, while the ∆lrhA strain was more motile, likely due to flhDC de-repression, motility was unaltered by high levels of UhpU indicating that significant UhpU effects on motility are mediated by LrhA. Interestingly, the RIL-seq data also suggested that lrhA directly interacts with other sRNAs such as ArcZ, RprA and McaS (Figure 3A). Regions of predicted base pairing overlap known seed regions for these sRNAs (Figure 3E). In translational reporter assays using the lrhA-lacZ fusion, both RprA and ArcZ reduced expression, while McaS, despite having the most chimeras, had no effect (Figure 3F). Possibly the McaS-lrhA interaction has other regulatory consequences such as McaS inhibition. Intriguingly, ArcZ, RprA, and LrhA form a complex regulatory network with the general stress response sigma factor σS encoded by rpoS, as previous studies showed that LrhA represses the expression of rprA and rpoS (Peterson et al., 2006), while ArcZ and RprA increase rpoS expression (reviewed in Mika and Hengge, 2014). UhpU, MotR and FliX modulate flagellin levels The high numbers of chimeras between UhpU, MotR or FliX with the fliC mRNA encoding flagellin were striking, particularly between the 3´ end of fliC corresponding to FliX (blue) and the 5´ end of fliC (red) (Figure 4A). As mentioned above, it was also noteworthy that most of the chimeras were internal to the fliC CDS. When we examined the consequences of overexpressing UhpU, MotR, MotR*, FliX or FliX-S on the levels of the flagellin protein, we observed somewhat increased levels of flagellin, both as cytosolic monomers (Figure 4B) and de-polymerized flagella (Figure 4—figure supplement 1A) with UhpU and MotR* overexpression and reduced levels with FliX or FliX-S overexpression. These differences are reflected in increased levels of the fliC mRNA with overexpression of UhpU, particularly in a crl+ background, or MotR or MotR*, particularly at OD600~0.2 (Figure 4C and Figure 4—figure supplement 1B). In contrast, fliC mRNA levels decreased with FliX and FliX-S overexpression (Figure 4C and Figure 4—figure supplement 1B). In general, the impacts of the sRNAs on flagellin protein and fliC mRNA levels are consistent with the increased flagella number and/or motility upon UhpU or MotR overexpression and decreased flagella number upon FliX overexpression. Comparatively, the effects of MotR and MotR* on flagella number and fliC mRNA levels were stronger than the effects on the flagellin protein; possibly increases in flagellin levels are masked by the abundance of the protein. Figure 4 with 2 supplements see all Download asset Open asset Multiple sRNAs regulate flagellin synthesis. (A) Browser image showing chimeras (red and blue) for UhpU, MotR, and FliX at the fliCX region. Data analyzed is from (RIL-seq experiment 1, Melamed et al., 2020). Red and blue lines indicate the RNA in the region is first or second RNA in the chimera, respectively. Blue highlighting indicates position of sRNA-fliC base pairing. (B) Immunoblot analysis showing UhpU and MotR overexpression leads to increased flagellin levels and FliX overexpression leads to reduced flagellin levels in the cytosol. Flagellin levels were determined by immunoblot analysis using α-FliC antibody. A sample from a ∆fliC strain was included as a control given the detection of a cross-reacting band slightly larger than flagellin. The Ponceau S-stained membrane serves as a loading control. Cells were grown with shaking at 180 rpm to OD600 ~1.0, and cell fractions were separated by a series of centrifugation steps as detailed in Materials and Methods. (C) Northern blot analysis showing UhpU and MotR overexpression increases fliC mRNA levels and FliX overexpression reduces fliC levels across growth. The 5S RNA served as a loading control. The variation in fliC levels in the pBR* and pZE control samples is due to the different strain backgrounds (crl + versus crl-) and the length of membrane exposure to film. (D) Predicted base-pairing between fliC and UhpU, MotR, or FliX. Seed sequences predicted by Melamed et al., 2016 or by this study are underlined. Numbering is from AUG of fliC mRNA a" @default.
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• W4387666721 title "Reviewer #2 (Public Review):: σ28-dependent small RNA regulation of flagella biosynthesis" @default.
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