Summary
Toxin-antitoxin systems are widely distributed genetic modules that regulate growth and persistence in bacteria. Many systems, including E. coli MazEF, include toxins that are endoribonucleases, but the full set of targets for these toxins remains poorly defined. Previous studies on a limited set of transcripts suggested that MazF creates a pool of leaderless mRNAs that are preferentially translated by specialized ribosomes created through MazF cleavage of mature 16S rRNA. Here, using paired-end RNA-Seq and ribosome profiling, we provide a comprehensive, global analysis of MazF cleavage specificity and its targets. We find that MazF cleaves most transcripts at multiple sites within their coding regions, with very few full-length, leaderless mRNAs created. Additionally, our results demonstrate that MazF does not create a large pool of specialized ribosomes, but instead rapidly disrupts ribosome biogenesis by targeting both ribosomal protein transcripts and rRNA precursors, helping to inhibit cell growth.
Introduction
Toxin-antitoxin systems are genetic modules widely found in bacteria and archaea that play important, but incompletely understood roles in regulating cellular growth and proliferation. Originally discovered as modules that promote plasmid inheritance, toxin-antitoxin systems are also commonly found on bacterial chromosomes, with many species encoding dozens of systems that have been categorized into a variety of types (Yamaguchi et al., 2011). The so-called type II systems involve a protein toxin that is bound and inactivated by a cognate antitoxin protein encoded in the same operon. In ways not well understood, antitoxins can be cleared from cells, thereby liberating their cognate toxins to suppress growth. Toxin-antitoxin systems have been suggested to regulate cell growth following a multitude of stresses and have been implicated, at least in some Gram-negative bacteria, in the formation of persisters, cells that survive antibiotic treatment by being in a non-proliferative, dormant state (Balaban et al., 2004; Helaine et al., 2014).
Many type II toxins are endoribonucleases that cleave a variety of RNAs. The RelE family of toxins are ribosome-associated, cleaving mRNAs in the A-site of the ribosome (Pedersen et al., 2003). The VapC and MazF endoribonucleases are not ribosome-associated, and members of these families have been suggested to cleave a variety of mRNAs, rRNAs, and tRNAs (Schifano et al., 2014, 2016; Yamaguchi et al., 2011). However, the precise targets of most endoribonuclease toxins remain poorly defined and how the activities of these toxins ultimately block cell growth remains unclear.
One of the best studied endoribonuclease toxins is Escherichia coli MazF. Early studies, using primarily primer extension assays, demonstrated that MazF cleaves mRNAs at some, though not all, ACA sites (Zhang et al., 2003). Because ACA sites are present in most transcripts, MazF was suggested to suppress the growth of E. coli cells by acting as a general mRNA ‘interferase’ (Zhang et al., 2003). However, a subsequent report argued that E. coli MazF specifically cleaves ACA sites overlapping, or just 5’ of, translational start sites, to produce a pool of leaderless transcripts (Vesper et al., 2011). Further, it was suggested that MazF cleaves an ACA near the 3’ end of the 16S rRNA to eliminate a 43 nt fragment containing the anti-Shine Dalgarno region. These ‘specialized’ ribosomes lacking anti-SD regions were postulated to preferentially translate the leaderless messages also created by MazF, including genes that help cells cope with the inducing stress. Promoting translation through MazF cleavage of leader regions was proposed to be widespread in E. coli, with the MazF regulon suggested to include >300 transcripts (Sauert et al., 2016). Work by a different group also found that MazF triggered production of a 43 nt fragment corresponding to the 3’ end of 16S rRNA, but then provided evidence MazF could be cleaving rRNA precursors in addition (Mets et al., 2017). However, that study did not formally separate or quantify MazF’s effects on rRNA precursors and mature rRNA.
The global cleavage patterns induced by E. coli MazF have not been studied to date. Recent efforts to map the global cleavage patterns of other MazF homologs have revealed a diversity of potential targets. For instance, MazF-mt3 from Mycobacterium tuberculosis was suggested to cleave within a conserved helix/loop of 23S rRNA and to cleave off the anti-SD sequence at the 3’ end of 16S rRNA, as proposed in E. coli, leading to the suggestion that the creation of specialized ribosomes for leaderless messages is a conserved mechanism (Schifano et al., 2014). The method used to map MazF-mt3 targets relied on the sequencing of RNAs having a 5’-OH terminus, which is created by many endoribonuclease toxins (Zhang et al., 2005). However, the cleavage products created by an endoribonuclease can vary widely in stability, complicating analysis and the quantification of cleavage events.
To address these limitations and globally map how E. coli MazF affects cellular RNA levels, we developed a quantitative method that measures changes in paired-end reads across the transcriptome upon induction of MazF. Using this approach, we systematically mapped MazF-dependent cleavages in E. coli and quantified the extent of cleavage at each site. Our results demonstrate that MazF has extended sequence specificity beyond the requisite ACA. Importantly, we also find no evidence that MazF creates a large pool of intact leaderless transcripts. We also performed ribosome profiling and found that MazF inhibits the complete translation of its mRNA targets, with no apparent preferential translation of stress response genes. Additionally, we find that MazF does not produce a substantial pool of specialized ribosomes specifically lacking the anti-SD region of the 16S rRNA. However, quite strikingly, we find that MazF cleaves several sites within rRNA precursors and within the transcripts of many ribosomal proteins. Pulse-chase analyses demonstrate unequivocally that MazF induction rapidly and almost completely inhibits ribosome biogenesis, without significantly affecting the pool of mature ribosomes. Thus, our work supports a model in which the MazF endoribonuclease toxin cleaves a wide range of cellular mRNAs and rRNA precursors to strongly block both translation and the synthesis of new ribosomes.
Results
High-throughput mapping and quantification of MazF-dependent cleavages
To determine the locations and extent of MazF-dependent cleavages in E. coli transcripts, we developed a technique based on the strand-specific dUTP method of paired-end RNA-sequencing (Levin et al., 2010). Briefly, we quantified RNA cleavage by comparing fragment counts at each nucleotide in cells expressing mazF to a control sample (Fig. 1A). Cleavage of an mRNA will lead to fewer paired-end fragments spanning a cleavage site, resulting in lower fragment counts at and near the site. To regulate mazF expression, we placed it under the control of an arabinose-inducible promoter on a low-copy vector in a ΔmazF strain. In the absence of arabinose and presence of glucose, this strain grew at a rate indistinguishable from that of a control strain harboring an empty vector (Fig. S1A). However, upon addition of arabinose, cells harboring Para-mazF showed substantially reduced growth within 10 minutes (Fig. 1B). To maximize the detection of cleavage events driven directly by MazF, rather than any secondary effects, we extracted RNA after inducing MazF for 5 minutes. We treated control cells harboring an empty vector identically. After generating and mapping RNA-sequencing libraries, we counted the number of fragments crossing each nucleotide in the genome to yield fragment counts per nucleotide and then computed the log2 ratio of read counts (log2 MazF:empty vector), hereafter referred to as the cleavage ratio. This ratio measures RNA cleavage while controlling for gene expression differences and region-specific biases in the library generation protocol.
Figure 1. An RNA-seq-based approach for mapping the cleavage targets of MazF.
(A) Schematic overview of the approach for a hypothetical gene of interest with a single cleavage site (red arrowhead). Paired-end RNA-sequencing fragments (top) mapped across each nucleotide position are summed (middle) for cells expressing MazF or carrying an empty vector, and then divided to yield a cleavage ratio profile (bottom).
(B) A representative growth curve for cells expressing MazF or carrying an empty vector. Cells were diluted into media lacking glucose before arabinose was added.
(C) Summed read counts (top) and cleavage ratio profile (bottom) for rplJ and 5’ UTR of rplL. ACA sites are indicated (red arrowheads). Position of primer pairs used in (D) are shown below.
(D-E) Change in RNA abundance, as measured by qRT-PCR and the RNA-Seq-based cleavage ratio, for (D) the two regions of rplJ shown in panel C and (E) the six genes indicated, chosen to span a range of cleavage ratios. Bars show mean ± S.D., n=3. The cleavage ratios plotted are the minimum cleavage ratios within the region amplified by each primer pair, using data from two independent replicates of + MazF and empty vector.
(F) Comparison of the average changes in abundance measured by qRT-PCR and the RNA-Seq-based cleavage ratios for the regions reported in (D-E). Red line is the linear best fit. Data points are mean ± S.D., n=3.
(G) Distribution of the minimum cleavage ratios within expressed coding regions (n=1083) in E. coli when comparing cells expressing MazF to those carrying an empty vector (top) or comparing two independent replicates of cells carrying an empty vector (bottom).
An example of a MazF cleavage profile is shown in Fig. 1C for rplJ, which encodes for a ribosomal protein. After MazF induction, the lowest ratios were observed in an ~50 nucleotide region overlapping the start codon, with a 2–4-fold decrease in fragment counts across the 5’-UTR and the first 30 nucleotides of the coding region of the gene. This region of the rplJ transcript contained three ACA sites, one or all of which may be cleaved by MazF. The middle of the coding region had a cleavage ratio near 0, implying less, or limited, cleavage of the three other ACA sites within rplJ. The cleavage ratio decreased toward the end of the coding region, likely reflecting cleavage at the ACA site in the intergenic region preceding the co-operonic rplL gene, followed by 3’→5’ exonuclease-driven degradation into the rplJ coding region. The overall pattern of cleavage ratios for rplJ suggests that MazF does not cleave all ACA sites equally.
To corroborate our RNA-sequencing results, we conducted qRT-PCR using probes specific for either the 5’ region of rplJ or the middle of the transcript (primer pairs 1 and 2, respectively; Fig. 1C). Consistent with our cleavage ratios, the qRT-PCR analysis also indicated that the 5’ end of rplJ was more strongly cleaved, with an ~4-fold decrease in its abundance compared to the middle region of the transcript (Fig. 1D). We then extended our qRT-PCR analysis to specific regions of six other transcripts, finding a strong correlation between cleavage ratios and qRT-PCR-based ratios (R2=0.92; Fig. 1E–F).
To assess the reproducibility of our method, we compared two independent replicates of the cleavage ratios. We split each transcript’s coding region into windows of 100 nucleotides and then compared the minimum cleavage ratio in each window between the replicates. For this and all subsequent analyses, we chose a threshold of 64 counts in the empty vector sample to eliminate noise associated with low read counts. Using this threshold, the two replicates exhibited a high correlation (Fig. S1B; R2 = 0.91). We also compared cleavage ratios calculated for RNA harvested at 5 min of MazF expression to that harvested at 30 or 60 min. We found a strong, but reduced correlation in each case (Fig. S1C; R2 = 0.74 and R2 = 0.66, respectively), likely a result of indirect effects that arise at later time points. To focus on the primary, direct effects of MazF, we performed our subsequent analyses on the 5 min time point.
Having established the paired-end RNA-Seq method, we probed the global effects of MazF on the E. coli transcriptome by recording the lowest cleavage ratio within each coding region. Of the 1,083 genes above our expression threshold at every nucleotide, we found that 887, or 82%, had a minimum cleavage ratio < −1, i.e. 2-fold down-regulated, after 5 minutes of MazF induction compared to just 4, or 0.4%, genes in a negative control generated by calculating the cleavage ratio of two empty vector replicates (Fig. 1G). Although the majority of transcripts were cleaved after 5 min, MazF had a wide range of effects on relative mRNA levels. The average cleavage ratio minimum was −2.1, with the lowest being −5.6. Examples of cleavage ratio profiles are shown in Fig. S1D with all cleavage ratio minima listed in Table S1. There were 196 genes with a cleavage ratio minimum > −1, including 58 of the 64 transcripts lacking coding ACA sites and hence not expected to be direct MazF targets. Our results indicate that MazF cleavage affects the vast majority of transcripts in E. coli. However, the transcripts with the lowest cleavage ratios had a wide variety of functions, suggesting that MazF does not specifically target a particular set of genes.
Sequencing of 5’-OH-terminated fragments is not a quantitative measure of RNA cleavage
An alternative strategy for mapping the targets of MazF and related endoribonucleases involves the enrichment and sequencing of RNAs with 5’-OH termini (Schifano et al., 2014). To compare our method with this enrichment method, we measured the log2 ratio of 5’-OH ends at single-nucleotide resolution in cells producing MazF relative to cells harboring an empty vector, hereafter referred to as the 5’-OH ratio (Fig. S2A).
As expected, the average 5’-OH ratio at ACAs genome-wide was significantly higher than for any other three-nucleotide motif (Fig. S2B). However, 5’-OH ratios and cleavage ratios were not correlated (Fig. 2A; R2 = 0.01). For example, within rplJ (Fig. 1C, 2B), our cleavage ratios and qRT-PCR analysis had indicated that cleavage near the start codon is much stronger than within the coding region, but the highest 5’-OH ratios were within the coding region. Similarly, for all regions queried by qRT-PCR (Fig. 1D–F), we found that the 5’-OH ratio did not correlate with changes in RNA abundance (Fig. 2C; R2=0.09). This discrepancy likely arises because some RNA fragments with 5’-OH ends may be very stable, leading to elevated 5’-OH ratios, even if only a small percentage of a transcript is cleaved at a given ACA. Conversely, some 5’-OH ends may be very unstable or short, leading to a low 5’-OH ratio, even if the majority of the parent molecule is cleaved. We conclude that the 5’-OH ratio is not a quantitative measure of cleavage.
Figure 2. Mapping of 5’-OH termini does not accurately quantify MazF cleavage events.
(A) Scatterplot of the 5’-OH ratio measured at individual ACA sites and the cleavage ratio at the same positions. Red line is the linear best fit. ACA sites in low expressed regions were not included.
(B) Comparison of 5’-OH and cleavage ratio profiles for rplJ. The ratio of 5’-OH signal (+ MazF:empty vector) for cells expressing MazF for 20 minutes or carrying an empty vector is shown (top) and compared to the cleavage ratio profile for rplJ (bottom) also shown in Fig. 1C.
(C) Comparison of the change in abundance measured by qRT-PCR (Fig. 1D–F) and the summed 5’-OH ratios at ACA sites within each amplified region. Red line is the linear best fit. Data points are mean ± S.D., n=3.
See also Figure S2.
MazF has an extended recognition element, including nucleotides flanking a central ACA
Although low cleavage ratios in our method were typically associated with at least one ACA site, not all ACAs produced low cleavage ratios, indicating that additional specificity exists. To better define the primary sequence specificity of MazF, we searched for single MazF cleavage events that likely had minimal additional degradation of the fragments produced. These cleavage events manifest as deep, narrow valleys in cleavage ratio profiles. We identified such regions by finding local minima in the cleavage ratio profiles, and then determined if the cleavage ratio increased by at least 1 (i.e. a relative 2-fold change in fragment density) within 50 nucleotides on each side of the minima. As an example, dnaK has two such local minima (Fig. 3A, regions 1 and 2). We then measured the frequency of all 64 trinucleotide motifs within 195 of these regions (Fig. 3B, S3A). ACA was the only motif present in 100% of these cleaved regions and, after normalizing to frequency in the genome, was substantially more enriched than all other trinucleotides.
Figure 3. MazF has an extended recognition motif with a central ACA trinucleotide.
(A) Cleavage ratio profile for dnaK, indicating two regions identified as cleaved regions, with boundaries defined as the sites where cleavage ratios have increased ≥ 2-fold relative to the local minimum. Local minima are indicated by red dots. The motif scores of each ACA in the transcript, calculated using the scoring matrix in (D), are shown below the cleavage profile.
(B) Plot showing the % of cleaved regions of a maximum width of 100 nucleotides with at least one instance of each possible trinucleotide motif. For % normalized to motif frequency, see Fig. S3A.
(C-D) Sequence logo (C) and position weight matrix (D) for sites associated with MazF cleaved regions of a maximum width of 200 nucleotides. RNA sequences surrounding ACA sites within cleaved regions were aligned and information content in bits calculated compared to the background frequency of nucleotides surrounding ACA sites. Scores were calculated as log likelihoods of observing the nucleotide compared to the background frequency.
(E) (Top) Schematic of 6S RNA reporter, indicating single-stranded region where ACA sites of varying scores were inserted and the locations of primers used to measure cleavage, and the uncleaved region used as a control. Positions in the 6S RNA mutated to eliminate native ACA sites are shown in red. (Bottom) Ratios of + MazF to empty vector, as measured by qRT-PCR of the cleaved region, normalized to abundance of the uncleaved region, 10 minutes after induction of MazF, for reporters harboring the sequence indicated. Data points are mean ± S.D., n=3.
(F) Distribution of scores for all ACAs in coding regions (n= 47,059).
(G) (top) Distribution of the maximum ACA score within regions defined as cleaved by MazF but not used to generate the motif (n=650) compared to (bottom) the distribution of maximum ACA scores associated with randomly sampled coding regions (50 independent samples of n=650) of the same size that had at least one ACA.
See also Figure S3.
To determine if additional nucleotides surrounding ACA affected cleavage by MazF, we examined ACAs in regions where the cleavage ratio increases by 1 within 100 nucleotides of a local minimum. As some regions had multiple ACA motifs, which may not all be cleaved, we only used those with a single ACA site. Using qualifying ACA sites (n = 239), we generated a sequence logo and log-likelihood position weight matrix of the nucleotides flanking the ACA (Fig. 3C–D). There was a clear under-enrichment of C at the two positions preceding the ACA, a near complete lack of G at the position immediately after the ACA, and a modest underenrichment of A and C two positions after the central ACA. We conclude that MazF likely recognizes an ~7 nucleotide region.
To directly probe how the nucleotide sequence flanking an ACA impacts MazF-dependent cleavage, we developed a reporter in which different cleavage sites were inserted within the 5’ single-stranded region of B. subtilis 6S-1 RNA (Fig. 3E, top). To measure cleavage, we co-expressed MazF, or an empty vector, with the reporter molecule and then measured, using qRT-PCR, the abundance of the region containing a given cleavage site relative to a 3’ region lacking an ACA (Fig. 3E, bottom). Using cleavage sites with a range of scores (generated using the position weight matrix in Fig. 3D) from −8 up to 4, we found that scores were positively correlated with the extent of cleavage, confirming a role for the nucleotides flanking an ACA in MazF cleavage specificity.
To test if our inferred MazF recognition motif globally affects RNA cleavage, we scored all ACA sites in E. coli coding regions; these scores ranged from −8 to +4 (Fig. 3F). We then recorded the highest scoring ACA in each region where the cleavage ratio increased by at least 1 (i.e. a 2-fold change in fragment density) within 50 nucleotides on each side of the minima (excluding those used initially to define our motif) (Fig. 3G, top) and, for comparison, in randomly selected coding regions having the same lengths as the set of cleaved regions (Fig. 3G, bottom). The cleaved regions were significantly enriched in high scoring ACA sites (K-S test, p < 10−40). This analysis supports the conclusion that MazF requires more than just an ACA to efficiently cleave RNA. However, 10% of high (i.e. > 1) scoring sites occurred in coding regions with a cleavage ratio ≥ 0. Thus, a high-scoring site is not always sufficient for cleavage, possibly due to secondary structure effects.
Leaderless mRNAs are rare and not protected from MazF cleavage in their coding regions
We next searched for MazF cleavages that produce leaderless mRNAs as prior studies argued that MazF cleaves many ACA sites just upstream of or overlapping translational start sites to produce a large (> 300) pool of leaderless transcripts (Sauert et al., 2016; Vesper et al., 2011). We defined a transcript as leaderless if the cleavage ratio increased ≥ 1 when transitioning from the 15 nucleotides preceding the start codon to the 5’ end of the coding region. In cells producing MazF for 5 minutes, we found only 41 leaderless transcripts among 941 transcripts above our expression threshold of 64 counts across their entire length in the empty vector sample (Fig. 4A, top). We found no leaderless transcripts in a negative control generated by comparing two empty vector samples (Fig. 4A, bottom).
Figure 4. MazF does not produce a large pool of leaderless transcripts.
(A) Distribution of the change in cleavage ratio between the 5’ end of the coding region and the leader region. The distribution calculated for cells expressing mazF compared to cells carrying an empty vector (top) is compared to that for a comparison of two independent replicates of cells carrying an empty vector (bottom), n=941. For cells producing MazF, there are only 41 genes with large (≥ 2-fold) increases in the cleavage ratio across the start codon.
(B) Cleavage ratio profile (top) and ribosome footprint profile (bottom) for groL in cells producing MazF or carrying an empty vector. Summed ribosome footprints are shown in a rolling 30 nt window with Gaussian smoothing. A diagram of the groL transcript, including ACA sites and their scores, and the location of the Northern blot probe shown in panel C, is shown at the bottom.
(C) Northern blot using the probe indicated in (B) at the 5’ end of the coding region of groL. RNA was extracted from cells containing an empty vector or expressing MazF for 5 minutes. RNA lengths were estimated by comparison to a ssRNA ladder run together with RNA samples and visualized prior to membrane transfer.
Leaderless transcripts can only be translated into full-length protein if they are not also cleaved within their coding region. However, of the 41 leaderless transcripts identified, 31 had additional MazF-dependent cleavages within their coding regions, i.e. at least one region with a cleavage ratio < −1 (Fig. S4A). For instance, groL was cleaved to become leaderless, but also had an extended region of low cleavage ratios within its coding region, with a high-scoring ACA site near the local minimum (Fig. 4B). To verify that leaderless groL is also cleaved in the coding region, we performed Northern blotting with a probe to the 5’ end of the groL coding region (Fig. 4C). Full-length, leaderless groL transcript (~1700 nt) was undetectable after inducing MazF, with several smaller fragments accumulating. In total, only 10 leaderless transcripts were identified that also have no other region more than 2-fold downregulated, a finding in sharp contrast to the previously proposed MazF regulon of 330 transcripts (Sauert et al., 2016). A complete list of transcripts and the values we used to determine if they were leaderless and full-length is available in Table S2.
The set of 10 leaderless transcripts identified did not include rpsU or grcA (formerly yfiD) (Fig. S4B)., suggested previously to be leaderless following MazF induction (Vesper et al., 2011). In each case, the ACA just upstream of the start codon had a motif score < −1.5 and there was no valley in the cleavage ratio near the start codon, consistent with MazF not targeting these leaders. To verify that MazF does not create a substantial pool of leaderless grcA, we again used Northern blotting, this time with a probe to the 5’ end of the grcA coding region (Fig. S4C). After 5 minutes of MazF induction, full-length (~450 nt) mRNA was substantially reduced and two major degradation products were detected between 150 and 300 nucleotides in length, likely corresponding to cleavage at positions 152 and 213, respectively. A band of ~400 nt that may represent leaderless grcA was visible, but very faint. Taken all together, our results indicate that MazF does not produce a large pool of abundant, leaderless mRNAs that have complete and intact coding regions.
Leaderless transcripts are not preferentially translated
To test whether any of the leaderless transcripts produced by MazF were preferentially translated and, more generally, to globally profile the effects of MazF on translation, we performed ribosome profiling after inducing MazF for 5 and 25 min. For the 41 leaderless transcripts identified (full-length or not), we found no evidence that MazF induction increased translation. For example, with rsuA, which was leaderless and had little additional cleavage in its coding region, we observed similar or slightly decreased ribosome footprints across the entire coding region following MazF induction (Fig. 5A). For groL, which was leaderless and had additional cleavages within its coding region, we found that MazF induction produced an increase in ribosome footprints within the first ~500 nucleotides of the coding region (Fig. 4B). However, there was a significant decrease in ribosome footprints extending from a cleavage site within groL coding region to the end of the transcript. Thus, MazF likely does not increase the translation of full-length, functional GroL.
Figure 5. MazF does not produce preferentially translated leaderless transcripts, but inhibits translation of targets.
(A) RNA cleavage ratio and ribosome footprinting profiles for rsuA, shown as in Fig. 4B.
(B) Boxplots of the change in ribosome footprints on the 5’-end (nucleotides 10–60) of coding regions between an empty vector sample and a sample expressing mazF for 5 minutes. Full-length transcripts are those < 2-fold downregulated throughout their coding region and leaderless transcripts are defined in the text. Boxplots show the median, lower and upper quartiles, and quartile ± 1.5 interquartile range. ‘n.s.’ indicates no statistically significant difference (p > 0.05, one-sided t-test).
(C) Plot of fluorescence normalized to OD600 in + MazF:empty vector for cells growing in exponential phase. A YFP construct lacking strong coding MazF sites (YFP*) containing a short 5’ UTR either with (red) or without (blue) ACA sites between the Shine-Dalgarno site and the start codon was induced with MazF at t = 0 min. Data points are the mean of three biological replicates ± S.D.
(D) Plot of the distribution of ribosome footprints across coding regions in MazF and empty vector samples. Expressed coding regions were divided into 10 bins in the 5’→3’ direction and the number of ribosome footprints across all genes were summed in each.
(E) Plot of the mean change in 3’ ribosome footprints between a sample expressing mazF for 5 minutes and an empty vector sample is shown at single-nucleotide resolution for the region surrounding coding-region ACAs with scores ≥ 1 (n=6,234). For comparison, the same region is shown for randomly chosen nucleotides (n>80,000). The distances between observed local maxima in ribosome density are shown above the plot.
(F) Plot of the change in ribosome density across uncleaved (blue, n=44) and cleaved (red, n=897) mRNAs after MazF induction. Coding regions were divided into 10 bins running in a 5’→3’ direction and the mean change in ribosome footprints was calculated between a sample expressing mazF for 5 minutes and an empty vector sample. The mean for each bin is shown (line) ± S.D. (shaded region).
(G) Distributions of summed ACA scores for transcripts that increased in 3’ ribosome footprints (top, n=100) or transcripts that decreased in 3’ ribosome footprints (bottom, n=666). The change in ribosome footprints was measured at positions 3’ of the last ACA with a score ≥ −1.5 in the coding region. To prevent summing negative scores, only motifs with scores ≥ −1.5 were included and 1.5 was added to all scores.
We then expanded our ribosome profiling analysis to all transcripts. To systematically assess changes in ribosome recruitment to mRNAs, we compared the density of ribosome footprints at the 5’ ends of coding regions (nucleotides 10–60) in cells producing MazF for 5 minutes to cells carrying an empty vector (Fig. 5B). For coding regions that met our expression threshold (n=941), there was no trend toward increased or decreased ribosome footprints at their 5’ ends. The full set of leaderless transcripts (n=41) showed no significant increase in 5’ ribosome footprints compared to all considered regions (one-sided t-test, p=0.43). To test if full-length, leaderless transcripts (n=10) were preferentially translated, we compared them to the set of all full-length transcripts (n=168) and found no significant increase in 5’ ribosome footprints on full-length, leaderless messages (one-sided t-test, p=0.22). Similar observations were made using ribosome profiling data for cells that produced MazF for 25 minutes (Fig. S5A). Finally, to confirm that our definition of leaderless mRNAs did not affect these analyses, we also verified that there was no significant increase in 5’ ribosome footprints for mRNAs with a MazF site (score > −1.5) upstream of the start codon (Fig. S5B). These analyses, taken together with the inspection of individual leaderless transcripts, indicate that MazF cleavage does not generally promote ribosome recruitment to the 5’ end of its targets.
To directly test whether MazF cleavages just 5’ of a start codon increase translation, we also measured production of a YFP reporter engineered to lack MazF cleavage sites and produced from a transcript containing a short 5’UTR either with or without MazF sites between the ribosome binding site and the start codon. We found that there was no increase, and if anything a slight decrease, in fluorescence per OD for the construct with MazF sites (Fig. 5C). These results suggest that even if MazF produces leaderless mRNAs, they are not preferentially translated.
MazF directly inhibits the complete translation of its mRNA targets
Although MazF did not, on average, significantly change the density of ribosomes at the 5’ ends of transcript coding regions (Fig. 5B), it did prevent ribosomes from completing the translation of cleaved transcripts. Ribosome footprints progressively decreased across transcripts following MazF induction, with an ~4-fold decrease in ribosome footprints at the 3’ end of transcripts compared to the 5’ end (Fig. 5D), consistent with a prior study indicating a decrease in 35S incorporation following MazF induction (Zhang et al., 2003) and with a later study showing a 5’ increase in ribosome footprints following expression of another RNase toxin, RelE (Hwang and Buskirk, 2017). There was also an ~8-fold increase in ribosome footprints on the mRNA portion of tmRNA, indicating that MazF produces messages without stop codons that are rescued by the ssrA-tagging system (Fig. S5C).
To determine if the drop in ribosome density across transcripts results directly from MazF cleavage, we examined changes in ribosome footprints near all high-scoring MazF motifs regardless of their position within a given transcript (Fig. 5E), finding an ~8-fold enrichment in ribosomes at the −1 position relative to the ACA. Three additional peaks upstream of the ACA, at successive distances of 12, 28, and 26 nucleotides likely correspond to a ‘traffic-jam’ of ribosomes awaiting rescue on MazF-cleaved transcripts. There was an ~2-fold decrease in ribosome footprints immediately after ACA sites (Fig. 5E), supporting the conclusion that MazF is the direct cause of decreased translation in cleaved mRNAs.
Although MazF induction led to a significant reduction in polysomes, they were not completely eliminated (Fig. S5D) suggesting that some translation still occurs. We surmised that the mRNAs that continue to be translated would lack MazF sites and hence be uncleaved. To test this idea, we measured the change in ribosome density following MazF induction for uncleaved transcripts (n=44), i.e. those that had no region with a cleavage ratio below 0. For these uncleaved transcripts, there was little decrease in ribosome footprints across the coding region, in clear contrast to cleaved transcripts (n=897), which dropped significantly (Fig. 5F). These results suggest that MazF prevents the complete translation of cleaved mRNAs and helps drive a redistribution of ribosomes to uncleaved mRNAs.
To generate a list of preferentially translated genes following MazF induction, we calculated the change in ribosome footprint counts at the 3’ ends of all transcripts (Table S3). There were 100 transcripts with increased ribosome footprints at their 3’ ends. As expected, this set of 100 transcripts had fewer high-scoring MazF sites compared to transcripts with lower 3’ ribosome footprints (Fig. 5G) as well as a lower maximum motif score (Fig. S5E). There was, however, no obvious enrichment in the set of transcripts with increased 3’ ribosome footprints for stress-response genes, or any other particular functional process. In sum, our results support the conclusion that MazF does not promote translation of any specific set of messages and instead inhibits the translation of targeted mRNAs.
MazF does not generate specialized ribosomes, but does efficiently inhibit rRNA maturation
The analyses thus far focused on the mRNA targets of MazF. However, a previous model also suggested that MazF cleaves off the 3’ end of the 16S rRNA within mature ribosomes, thereby removing the anti-Shine-Dalgarno sequence to create a pool of specialized ribosomes. To assess cleavage of rRNA, we conducted paired-end RNA-Seq, as above, but without rRNA subtraction, 5, 30, and 60 minutes after inducing MazF. We saw no significant decreases in cleavage ratios anywhere along the 16S rRNA, including near the 3’ end (Fig. 6A). To ensure that our observations were not biased by the inhibition of reverse transcriptase crossing modified m62A bases at positions 1518 and 1519, we also counted the number of fragments crossing the proposed MazF cleavage site, but terminating before position 1518. We found that the difference between + MazF and empty vector samples still did not meet our significance threshold of a 2-fold decrease. In addition, we were able to selectively enrich for fragments which arose from mature, modified ribosomes by counting only fragments with sequencing errors at modified bases, which arise from misincorporation of nucleotides during reverse transcription. Again, we found no significant cleavage of the 3’ end of the 16S rRNA.
Figure 6. MazF does not target mature ribosomes, but does inhibit ribosome maturation.
(A) (Left) Paired-end fragment counts summed across the seven 16S rRNA genes in E. coli. The green arrow outline denotes the extent of the mature rRNA. Below are the RNase III maturation sites (blue arrowheads) and the ACA sites (red arrowheads) that exist in all seven 16S loci. The maximum motif score across 16S loci is plotted above the gene diagram. (Right) Detail of the 3’ end of the 16S rRNA and precursor region indicating the MazF-dependent accumulation of rRNA precursor.
(B) Northern blots of total RNA using probes sensitive to the mature 3’ end of the 16S (1), the precursor region that is 5’ of the RNase III site (2), and the precursor region that is 3’ of the RNase III site (3). The blot for probe 3 was split to enable visualization of two regions requiring different exposures. RNA lengths were estimated by comparison to a ssRNA ladder run together with RNA samples and visualized prior to membrane transfer, except the 43 nt length, which was determined by comparison to a synthesized RNA oligo.
(C) RNA cleavage ratio and ribosome footprinting profiles for the S10 ribosomal protein operon, shown as in Fig. 4B. Regions with lower footprints counts in the MazF + sample are marked with a purple line.
(D) (Left) Timeline of pulse-chase experiment to measure effects of MazF induction on nascent rRNA synthesis indicating MazF induction, pulse, chase, and sampling times. (Right) Measurements of A254 to assess total RNA and 3H c.p.m. to measure nascent RNA across a sucrose gradient. Early and late timepoints were collected for both empty vector and + MazF samples.
See also Figure S6.
Although we found no evidence that mature rRNA is a major MazF target, we did observe a striking increase in fragments arising from immature rRNA in cells expressing MazF. An early step in 16S rRNA maturation is the cleavage of the nascent RNA by RNase III at a hairpin formed between the regions immediately upstream and downstream of the mature ends (Fig. S6A). Near the downstream RNase III cleavage site, we observed an ~64-fold increase in reads after expressing MazF for just 5 min and > 100-fold after 30 min (Fig. 6A, right). We observed a similarly large increase at the 3’ end of the 23S rRNA (Fig. S6B) and a significant increase in reads starting 90 nucleotides upstream of the 5’ end of the 23S rRNA. These results suggest that MazF induction leads to the rapid accumulation of rRNA precursors, which may reflect a disruption in rRNA maturation and lead to an inhibition of ribosome biogenesis.
We also used Northern blotting to probe changes in the 3’ region of the 16S rRNA. First, we used a probe specific to the anti-Shine-Dalgarno region of the mature 16S rRNA (Fig. 6B). If a substantial pool of specialized ribosomes is produced, this probe should result in both the appearance of a major band at 43 nt and a significant loss in signal of the full-length 16S rRNA band. However, we observed very little, if any, signal at 43 nt and only a modest decrease in full-length 16S rRNA, even after 60 min of MazF induction. We directly quantified the 43 nt band by comparison to a synthetic standard (Fig. S6C). There was no detectable 43-nt fragment after 5 min of Maz induction, and only ~50–100 molecules per cell after 60 min, which would represent only ~1% of the initial pool of ribosomes. This calculation assumes that all 43-nt fragment arises from the processing of mature ribosomes, rather than rRNA precursors, so the number of specialized ribosomes is likely even lower. This lack of specialized ribosomes is not the result of insufficient MazF as the levels of expression used here were sufficient to stop growth within ~10 min (Fig. 1B) and to drive substantial amounts of RNA cleavage within 5 min (Fig. 1G).
Although no significant level of 43 nt fragment arose following MazF induction, we did observe significant cleavage products ~70 and ~160 nucleotides in length after 30 min of MazF induction, with additional bands between 150 and 500 nucleotides appearing after 60 minutes. The ~70 and ~160 nucleotide cleavage fragments were also seen using a probe specific to the region between the RNase III site and the mature 3’ end, a region normally degraded during rRNA maturation. The sizes of these fragments are consistent with MazF cleavage of a 16S precursor at ACA sites near nucleotides 1400 and 1500. We also used a probe specific to RNA that is 3’ of the RNase III processing site, using agarose instead of polyacrylamide gels to visualize larger RNA species. In this case, MazF induction resulted in a significant increase in signal for an RNA species between ~1500–2000 nucleotides, including a band larger than the mature 16S rRNA, as well as a species <500 nucleotides. Taken all together, these results contradict a model in which large pools of specialized ribosomes are produced, and instead strongly support the conclusion that MazF (i) directly cleaves rRNA precursors and (ii) prevents the proper maturation of rRNA precursors.
The disruption of rRNA processing may arise from MazF directly cleaving rRNA precursors; we observed several high-scoring MazF sites in precursor regions of the rRNA, including the regions immediately 5’ of both the 16S and 23S rRNAs (Fig. 6A, S6B). Alternatively, or in addition, MazF may indirectly affect rRNA maturation by cleaving the transcripts of ribosomal proteins. Insufficiencies in ribosomal protein levels can prevent the proper maturation of rRNA precursors (Siibak et al., 2011), which are normally bound almost immediately upon transcription by ribosomal proteins. Thus, we inspected the transcripts of ribosomal protein operons for cleavage. For most (11 of 16) operons, we found evidence of strong MazF cleavage and reduced translation, with cleavage ratio minima followed by regions showing significantly reduced ribosome occupancy (Fig. 6C, S6D).
Taken together, our results suggest that a key activity of MazF may be inhibition of rRNA maturation and, consequently, ribosome biogenesis. To directly test this model, we induced the expression of MazF for 5 min, pulse-labeled cells with 3H-uridine for 5 min, and then chased with cold uridine. We took samples 10 and 25 min after chasing, and measured both the 3H-labeled RNA and the total RNA across a sucrose gradient (Fig. 6D). In empty-vector control samples, both the radiolabeled RNA and total RNA (A254) had clear peaks corresponding to 30S, 50S, 70S and polysomes, indicating that the radiolabeled 3H-uridine was incorporated into mature ribosomes. MazF-expressing cells had a similar pattern as the control sample for total RNA. However, in striking contrast to the control, cells expressing MazF had no clear peaks for radiolabeled RNA, with the majority of the signal running as a smear above the position of 30S subunits. These results demonstrate that, upon induction, MazF rapidly and almost completely blocks the production of new ribosomes.
To test if mature ribosomes are also a target of MazF, we again pulse-labeled cells with 3H-uridine (but before producing MazF), chased with cold uridine, and then induced MazF expression. In this case, A254 measurements and radiolabel incorporation were essentially identical for the MazF producing cells and the empty vector control, with clear peaks in each case corresponding to the 70S, 50S, and 30S ribosome subunits (Fig. S6E). Taken all together, our results strongly support a model in which MazF cleaves precursor rRNAs and ribosomal protein transcripts to inhibit new rRNA synthesis and ribosome biogenesis, with no evidence for significant alteration or specialization of mature ribosomes.
Discussion
Mapping the specificity and global cleavage patterns of endoribonuclease toxins
Toxin-antitoxin systems are abundant genetic modules in bacteria and archaea that play critical roles in regulating cell growth, antibiotic persistence, and phage immunity. Many of the toxins are endoribonucleases, but their global patterns of cleavage and target specificity remain poorly characterized. Here, we described the development of a paired-end RNA-Seq-based method for systematically mapping and quantifying the cleavage of endoribonucleases. These results, along with ribosome profiling data, offer a global and comprehensive view of how the E. coli toxin MazF inhibits cell growth.
Previous efforts to map the cleavage targets and specificity of endoribonuclease toxins have relied on a method involving enrichment and sequencing of the 5’-OH termini created by these toxins (Schifano et al., 2014). We implemented this approach for MazF for comparison to the paired end RNA-Seq method developed here. Although both methods can identify recognition motifs, the 5’-OH method often produced large peaks where there was minimal, if any, cleavage detected by paired-end RNA-Seq (or by qRT-PCR), and there were some clear cleavages detected by RNA-Seq that had no corresponding peak in the 5’-OH data. These differences likely arise from the effects of 5’-OH termini on RNA stability. For instance, a large peak in the 5’-OH method may not reflect extensive cleavage of the parent RNA molecule, but rather high stability of the product containing the 5’-OH terminus. Thus, the 5’-OH method cannot provide reliable, quantitative assessments of the extent of cleavage genome-wide.
A global analysis of RNA cleavage by MazF reveals its specificity and targets
MazEF is one of the most studied toxin-antitoxin systems to date and has, in particular, been a paradigm for understanding the many systems that encode endoribonucleases. MazF is often referred to as specific for ACA sites. Although an ACA is necessary for cleavage, this trinucleotide motif is by no means sufficient. An extended sequence specificity for MazF is consistent with the structure of E. coli MazF in complex with the substrate d(AUACAUA) where the 5 central nucleotides show clear electron density (Zorzini et al., 2016).
Our global study also provides important new insights into the RNA targets of MazF, which have remained poorly defined and controversial. Early studies using model transcripts suggested that MazF cleaves ACA sites that occur in most transcripts to interfere with translation, leading to MazF being dubbed an ‘mRNA interferase’ that inhibits translation by bulk degradation of transcripts (Zhang et al., 2003). However, subsequent studies argued that E. coli MazF reprograms translation by specifically cleaving transcripts with an ACA site near their translational start sites to generate a large pool of leaderless mRNAs that were preferentially translated by specialized ribosomes arising from MazF cleaving a single ACA near the 3’ end of mature 16S rRNA. This model was attractive as it represented a potentially powerful mechanism for cells to precisely tailor their translational program during stress. There has also been significant interest recently in how eukaryotes generate heterogeneous pools of ribosomes with different translational capacities, and MazF-derived ribosomes were a potential prokaryotic instance of such heterogeneity.
Our combined RNA-Seq and ribosome profiling data now delineate the global patterns of cleavage by MazF and the consequences for the cell’s translational program. We find that MazF cleaves a wide range of mRNAs, usually at multiple ACA sites matching the extended specificity noted above. These cleavage events, along with subsequent processing by other nucleases, lead to significant decreases in the abundance of most full-length mRNAs. We found no evidence for a substantial pool of leaderless transcripts capable of being translated into functional proteins. MazF does cleave ~40 transcripts at or just upstream of their translational start sites. However, these transcripts typically had additional, strong cleavage sites within their coding regions. Notably, the previous studies of MazF effectively ignored these additional cleavage events by (i) using primer extension with primers that hybridized upstream of any coding region cleavage sites (Vesper et al., 2011) and (ii) limiting RNA-Seq analysis to the 5’ ends of transcripts (Sauert et al., 2016).
Our ribosome profiling supports a model in which MazF generally inhibits translation by cleaving most mRNAs. For nearly all transcripts, MazF induction led to a significant decrease in ribosome footprints toward their 3’ ends (Fig. 5D, 5F), indicating that MazF leads to decreased translation of full-length proteins. This trend held even when considering just leaderless transcripts, such as groL (Fig. 4B–C). Additionally, the set of transcripts that did show increased ribosome footprints (Fig. 5F–G) were not obviously enriched for any particular function. In sum, we conclude that MazF does not produce a large pool of leaderless mRNAs to drive a translational reprogramming of cells to cope with stress as previously proposed (Sauert et al., 2016; Vesper et al., 2011).
MazF rapidly blocks rRNA maturation and ribosome biogenesis
Our RNA-Seq data revealed rRNA as a major target of MazF. However, we did not find evidence of MazF cleaving off the anti-SD region of the 16S rRNA in mature ribosomes by cutting an ACA site at nucleotide 1500. We did not observe an abundant 43 nucleotide cleavage product corresponding to cleavage at nucleotide 1500 or a robust decrease in signal of the full-length 16S rRNA using a probe specific to the anti-Shine-Dalgarno region (see Fig. 6B, probe 1). In fact, our quantification of the 43 nucleotide fragment indicated no evidence of ribosome specialization after 5 min of MazF induction, despite the extensive cleavage of mRNAs at this time point and the onset of cell growth inhibition (Fig. 1B). Even after 60 min, the abundance of the 43 nt fragment indicates that at most ~1% of ribosomes have been truncated (Fig. S6C). And this estimate may be high as it assumes that the 43 nt fragment arises only from mature ribosomes, a dangerous assumption given MazF’s effects on rRNA maturation (Fig. 6D). Finally, even if a very small fraction of ribosomes are being cleaved by MazF to eliminate the anti-SD region, our ribosome profiling demonstrates that it does not lead to any substantial reprogramming of translation.
Our results indicate that although MazF does not significantly impact mature rRNA, it does have a major effect on rRNA precursors. One recent study of E. coli MazF had suggested that it may cleave precursor rRNAs (Mets et al., 2017) based on 5’-OH mapping that produced a peak in the 16S precursor and several peaks within structured regions of 16S and 23S rRNA. However, these experiments were conducted after MazF was expressed for 2 hours using the 5’-OH method so whether these peaks indicate common products or rare but stable products is unclear. The prior study also reported the formation of aberrant, MazF-dependent rRNA peaks on a sucrose gradient. However, such experiments cannot discern whether those rRNA species arise from MazF targeting mature or immature rRNAs. Additionally, a precursor-specific probe did not yield signal in a Northern blot of RNA from cells expressing MazF. Finally, although this prior study did suggest that rRNA precursors are a target of MazF, they also reported the 43 nt fragment identified by Moll and colleagues (Vesper et al., 2011), leaving unresolved how frequently MazF cleaves mature versus immature rRNA and what impact these cleavage events have on ribosome biogenesis.
Our results now conclusively demonstrate that MazF disrupts rRNA maturation. We observed 50–100 fold increases in RNA past the mature 3’ ends of both the 16S and 23S rRNA, regions that are normally degraded during rRNA maturation and ribosome biogenesis. In E. coli, as in most bacteria, rRNA transcription produces a long rRNA precursor that adopts a complex secondary structure in which the regions immediately upstream and downstream of the 16S and 23S rRNAs hybridize to form dsRNA stems, with the nascent 16S and 23S rRNAs emanating as loops from these stems (Fig. S6A). rRNA maturation initiates through RNase III cleavage of these dsRNA stems followed by a series of additional RNase-based processing and RNA modification steps. The disruption of this maturation process by MazF likely results from both direct cleavage of rRNA transcripts and the cleavage of transcripts encoding ribosomal proteins, which normally bind rRNA to promote their proper maturation. The net result is that MazF almost completely blocks the biogenesis of ribosomes (Fig. 6D). Our pulse-chase analysis of ribosome biogenesis indicated a rapid and nearly complete loss of 3H-uridine incorporation into 30S, 50S, and 70S ribosomes after inducing MazF. An inability to synthesize new ribosomes may be a key mechanism by which MazF inhibits cell growth (Fig. 1B). The cleavage of many different cellular mRNAs will also generally slow translation, but our findings suggest that the massive disruption of rRNA maturation and ribosome biogenesis is likely a major facet of the growth inhibition following MazF induction.
Concluding remarks
In sum, our work indicates that E. coli MazF does not create a large pool of leaderless mRNAs, nor does it create specialized ribosomes lacking the anti-SD region that preferentially translate leaderless mRNAs. Instead, our results demonstrate that MazF efficiently blocks ribosome biogenesis, probably through the cleavage of rRNA precursors and ribosomal protein transcripts, which together will contribute significantly to a suppression of cell growth. Disrupting rRNA biogenesis is a well-known and powerful mechanism for blocking translation and cell growth in E. coli. One of the best studied growth regulators in E. coli is guanosine tetraphosphate (ppGpp), which accumulates following amino acid starvation (Potrykus and Cashel, 2008). By binding directly to RNA polymerase, ppGpp directly shuts down rRNA transcription, thereby slowing ribosome biogenesis, translation, and cell growth. The inhibition of ribosome synthesis by MazF without degrading or altering mature ribosomes may represent a similar strategy for reversibly blocking cell growth following the onset of stressful conditions, or potentially as a mechanism of inducing growth rate heterogeneity in a clonal population.
The RNA-Seq-based method developed here enabled a global and quantitative assessment of the RNA cleavages triggered by MazF in E. coli and can now be applied to other ribonucleases. MazF homologs are found in a wide range of bacteria with some species encoding several paralogs that may have diverse targets or that may target different regions of rRNA precursors. Additionally, there are other families of toxins, including the RelE, HigB, and VapC toxins that cleave RNAs. The systematic mapping of their cleavage patterns and specificities promises to provide new insight into the biological roles and mechanisms of toxin-antitoxin systems as regulators of bacterial growth and persistence.
STAR Methods
Contact for Reagent and Resource Sharing
Questions or requests for methods, strains, and resources generated in this study can be directed to the Lead Contact, Michael T. Laub (laub@mit.edu).
Experimental Model and Subject Details
Growth conditions
Escherichia coli was grown in M9 (10x stock made with 64 g/L Na2HPO4-7H2O, 15 g/L KH2PO4, 2.5 g/L NaCl, 5.0 g/L NH4Cl) medium supplemented with 0.1% casamino acids, 0.4% glycerol, 2 mM MgSO4, and 0.1 mM CaCl2. Glucose at 0.4% was used to prevent leaky expression from the arabinose promoter and 0.2% arabinose was used to induce expression. Cells were grown at 37 °C and 200 rpm in an orbital shaker. Prior to liquid growth, individual colonies were selected by growth overnight on LB (10 g/L NaCl, 10 g/L tryptone, 5 g/L yeast extract) agar plates. Antibiotics were used at the following concentrations (liquid/plates): carbenicillin (50 μg mL−1 / 100 μg mL−1), chloramphenicol (20 μg mL−1 / 30 μg mL−1).
Strain construction
MazF deletion strain MG1655 strain was courtesy of Kenn Gerdes (Maisonneuve et al., 2011). MazF induction, empty vector, and promoter strains were constructed by transformation of plasmids into this strain. The pKVS45 vector was courtesy of Kristala Prather. For a list of strains and plasmids used in this work see Table S4 and S5.
Plasmid construction
Modified pBAD30 and pBAD33 plasmids were used for expression of MazF (Guzman et al., 1995). A sequence containing a ribosome binding site (AGGAGGGATT) was added between the EcoRI and SacI sites in the MCS of the pBAD plasmids. MazF was inserted by amplification of MazF from MG1655 genomic DNA inserted into pBAD30:mazF and pBAD33:mazF using the SacI and HindIII sites. Bacillus subtilis 6S-1 RNA with mutated ACA sites (see Fig. 3E) was purchased as a gBlock (Integrated DNA Technologies) and was inserted into pKVS45 (modified to include a sc101 origin from pSB4K5) using Gibson assembly. MazF cleavage sites of varying scores were then inserted using site directed mutagenesis. The YFP* reporter constructs were constructed using Gibson assembly of a YFP* gBlock (Integrated DNA Technologies), primers generating the 5’UTR, and the pKVS45 plasmid. They YFP* gene itself is a translational fusion of the first 28 amino acids of the rne gene and a codon-optimized YFP gene with MazF cleavage sites removed. For a list of primers used for strain construction, see Table S6.
Experimental Method Details
MazF induction
For MazF induction, E. coli cells were grown with glucose until just prior to induction to prevent loss of toxicity. Single colonies were grown overnight in glucose. Overnight cultures were back-diluted and grown to ~0.35 OD600 in fresh media with 0.4% glucose at 37 °C in an orbital shaker at 200 rpm. Cells were pelleted by centrifugation at 4 °C and 4000 g for 5 minutes. Pellets were washed, centrifuged, and resuspended in fresh medium without glucose. OD600 was normalized across all samples by dilution into fresh medium to an OD600 of ~0.15, and cells were allowed to recover at 37 °C for at least 30 minutes, after which they were induced with 0.2% arabinose at OD600 ~0.2. RNA extraction times vary and are as noted for each experiment.
RNA extraction
Cells were pelleted by harvesting 1 mL of cell culture, with 110 μL of an ice cold stop solution (95% ethanol, 5% acid-buffered phenol) and spun at 13000 rpm for 30 seconds in a bench-top centrifuge. After removing supernatant, cells were flash frozen in liquid nitrogen and stored at −80 °C. Trizol (Invitrogen) was pre-heated to 65 °C and added directly to cell pellets. The mixture was shaken for 10 minutes at 65 °C and 2000 rpm in a thermomixer (Eppendorf) to lyse cells. Lysed cells were frozen at −80 °C for at least 10 minutes, thawed, and centrifuged for 5 minutes at max speed at 4 °C. Trizol supernatant was mixed with 400 μL of ethanol, avoiding the pellet of cell debris. Samples were passed over a Direct-zol miniprep column (Zymo). Columns were pre-washed twice with 400 μL of provided pre-wash buffer, washed once with 700 μL of provided wash buffer, and dried for 2 minutes by centrifuging at 13000 rpm. Samples were eluted in 90 μL DEPC water. RNA was then treated with 2 μL Turbo DNase (Invitrogen) in 100 μL using provided 10x buffer. After incubating for 20 minutes at 37 °C, an additional 2 μL of DNase was added, followed by another 20 minutes at 37 °C. Reaction volume was brought to 200 μL with DEPC water and vortexed with 200 μL of acid-phenol:chloroform IAA, pH 4.5 (Invitrogen). Samples were centrifuged 10 minutes at 4 °C and top layer was extracted and ethanol precipitated with 20 μL of 3M NaOAc, 2 μL GlycoBlue (Invitrogen), and 600 μL of ice cold ethanol. Samples were incubated at −80 °C for at least 4 hours and then spun at max speed at 4 °C for 30 minutes. Samples were washed with 500 μL of ice-cold 70% ethanol, recentrifuged for 5 minutes, air dried, and resuspended in 30 μL of DEPC water. Chemical purity and yield was quantified by NanoDrop spectrophotometer and RNA integrity was verified by running out on a Novex 6% TBE-Urea gel (Invitrogen).
Paired-end library preparation
The library generation protocol was a modified version of the paired-end strand-specific dUTP method using random hexamer priming (Levin et al., 2010). For libraries without rRNA removal, 500 ng of total RNA was used in the fragmentation step, skipping rRNA removal. For libraries with rRNA removal, 2–3 μg of input RNA was used in the rRNA removal step.
rRNA removal:
rRNA removal was conducted using the Ribo-Zero rRNA Removal Kit for Bacteria (Illumina). Provided magnetic beads were prepared individually by adding 225 μL of beads to a 1.5 mL tube, left to stand on a magnetic rack for 1 minute, washed twice with 225 μL of water, and resuspended in 65 μL of provided resuspension solution with 1 μL of provided RNase inhibitor. Samples were prepared using provided reagents with 4 μL of reaction buffer, 2–3 μg of total RNA, 10 μL of rRNA removal solution in a total reaction volume of 40 μL. Samples were incubated at 68 °C for 10 minutes and at room temperature for 5 minutes. Samples were added directly to the resuspended magnetic beads, mixed by pipetting, incubated for 5 minutes at room temperature, and then incubated for 5 minutes at 50 °C. After incubation, samples were placed on magnetic rack and the supernatant was transferred to a new tube, discarding the beads. Samples were ethanol precipitated as above with a 1 hour incubation at −20 °C and resuspended in 9 μL of water.
Fragmentation:
RNA fragmentation was conducted using stop solution and fragmentation reagent provided with RNA Fragmentation Reagents (Invitrogen). Samples were mixed with 1 μL of 10x fragmentation reagent in a final volume of 10 μL, incubated at 70 °C for 8 minutes, placed on an ice block, and mixed with 1 μL of stop solution. Reactions were brought to 20 μL with DEPC water and ethanol precipitated using 2 μL of 3M NaOAc, 2 μL of GlycoBlue (Invitrogen), and 60 μL of ice-cold ethanol. Samples were ethanol precipitated as above with a 1 hour incubation at −20 °C and resuspended in in 6 μL of DEPC water.
cDNA synthesis:
1 μL of random primers at 3 μg/μL (Invitrogen) were added to fragmented RNA. Samples were incubated at 65 °C for 5 minutes and placed on ice for at least 1 minute. First strand synthesis was conducted by adding 4 μL of 5x first-strand buffer (Invitrogen), 2 μL of 100 mM DTT, 1 μL of 10 mM dNTPs, 1 μL of SUPERase-In (Invitrogen), and 4 μL of DEPC water. Reactions were incubated at room temperature for 2 minutes and 1 μL of Superscript III (Invitrogen) was then added. Reactions were placed on a thermocycler and incubated for 10 minutes at 25 °C, 1 hour at 50 °C, and 15 minutes at 70 °C. Reactions were brought to 200 μL with 180 μL of DEPC water and vortexed with neutral phenol-chloroform isoamyl alcohol. Layers were separated by centrifugation for 10 minutes at maximum speed at 4 °C. The aqueous top layer was extracted and ethanol precipitated by adding 18.5 μL 3M NaOAc, 2 μL GlycoBlue, and 600 μL of ice-cold ethanol. Samples were incubated for 1 hour at −20 °C, centrifuged at maximum speed for 30 minutes at 4 °C, washed twice with ice-cold 70% ethanol with 5 minute centrifugations, air-dried, and resuspended in 104 μL of DEPC water. Second strand synthesis was conducted by adding 30 μL 5x second strand buffer (Invitrogen), 4 μL 10 mM dNTPs (using dUTP instead of dTTP), 4 μL 5x first strand buffer (Invitrogen), and 2 μL 100 mM DTT. Samples were mixed by pipetting and placed on ice for 5 minutes. Reactions were started by adding 1 μL RNase H (NEB), 1 μL E. coli DNA Ligase (NEB), and 4 μL E. coli DNA Polymerase I (NEB), mixing by pipetting, and incubating at 16 °C for 2.5 hours. Reactions could be frozen at −20 °C at this stage.
End-repair and adapter ligation:
Cleanup for subsequent reactions was conducted by Agencourt AMPure XP magnetic beads (Beckman Coulter). Note that unless otherwise stated, beads were left in the reaction to be reused in future reactions. For each sample, 100 μL of AMPure beads were added to 1.5 mL tubes and placed on the magnetic rack for ~5 minutes. Supernatent was removed and replaced with 450 μL of 20% (w/v) PEG 8000 in 2.5 M NaCl. Second strand synthesis reactions were added directly to resuspended beads and allowed to incubate at room temperature for 10 minutes. Samples were placed on the magnetic rack and left until beads formed a diffuse pellet (about 10 minutes). Beads were washed twice with 80% ethanol, leaving the tubes on the magnetic rack during washes. Residual ethanol was removed and beads were allowed to dry for 5 minutes. Beads were resuspended in 50 μL of elution buffer (Qiagen). End repair was conducted for each sample by adding 10 μL of 10x T4 DNA ligase reaction buffer (NEB), 4 μL 10 mM dNTPs, 25 μL water, 5 μL T4 DNA polymerase (NEB), 1 μL Klenow DNA polymerase (NEB), and 5 μL T4 PNK. Reactions were incubated for 30 minutes at 25 °C. To clean up reactions, 300 μL of PEG-NaCl solution was added to each reaction. After incubation at room temperature for 10 minutes, samples were placed on the magnetic rack until the beads pelleted, about 5 minutes. Beads were washed twice with 80% ethanol, dried for 5 minutes, and resuspended in 32 μL of elution buffer (Qiagen). 3’-adenylation was conducted by adding 5 μL NEB buffer 2 (NEB), 9 μL of water, 1 μL 10 mM dATP, and 3 μL Klenow Fragment (3’→5’ exo-) (NEB) and incubated for 30 minutes at 37 °C. To clean up reactions, 150 μL of PEG-NaCl solution was added to each reaction. After incubation at room temperature for 10 minutes, samples were placed on the magnetic rack until the beads pelleted, about 5 minutes. Beads were washed twice with 80% ethanol, dried for 5 minutes, and resuspended in 23 μL of elution buffer (Qiagen). After 5 minutes of incubation, tubes were returned to the magnetic rack and eluted DNA was moved to a new tube and beads were discarded. To ligate adapters, 1 μL annealed adapter mix, 25 μL 2x quick ligase buffer (NEB), and 1 μL quick DNA ligase (NEB) was added to each sample and incubated at 25 °C for 15 minutes. Annealed adapter mix was made by mixing 25 μL of a 200 μM solution of each paired-end adapter together, heating to 90 °C for 2 minutes, cooling at 2 °C/minute for 30 minutes on a thermocycler, placing on ice, adding 50 μL of water, and storing aliquots at −20 °C. Ligation reactions were cleaned up by adding 75 μL resuspended AMPure beads (made by resuspending 100 μL of AMPure beads in 75 μL of PEG-NaCl solution). After incubation at room temperature for 10 minutes, samples were placed on the magnetic rack until the beads pelleted, about 5 minutes. Beads were washed twice with 80% ethanol, dried for 5 minutes, and resuspended in 23 μL of elution buffer (Qiagen). After 5 minutes of incubation, tubes were returned to the magnetic rack and eluted DNA was moved to a new tube and beads were discarded. The dUTP-containing second strand was digested by adding 6 μL of Phusion 5x high fidelity buffer (NEB) and 1 μL of USER enzyme (NEB) and incubating at 37 °C for 15 minutes, followed by 95 °C for 5 minutes to inactivate the enzyme.
Library amplification:
Full PCR reactions were prepared by adding 13.3 μL 3M betaine, 3 μL 10 mM dNTPs, 14 μL 5x high fidelity buffer (NEB), 2 μL 25 μM global primer, 2 μL 25 μM barcoded primer, 34.7 μL water, 1 μL Phusion (NEB) in a final volume of 100 μL. The following thermocycler program was used: 98 °C/30 seconds, 98 °C/10 seconds, 65 °C/30 seconds, 72 °C/30 seconds, 72 °C/5 minutes. Steps 2–4 were repeated for 9–12 cycles. The cycle number was optimized prior to final amplification using 10 μL reactions. Primers were removed by adding 300 μL resuspended AMPure beads (made by resuspending 100 μL of AMPure beads in 300 μL of PEG-NaCl solution). After incubation at room temperature for 10 minutes, samples were placed in the magnetic rack until the beads were pelleted, about 5 minutes. Beads were washed twice with 80% ethanol, dried for 5 minutes, and resuspended in 20 μL of elution buffer (Qiagen). Elutions were run on an 8% TBE polyacrylamide gel (Invitrogen) for 30 minutes at 180 V. The region from 200 to 350 bp was excised, crushed, soaked in 500 μL 10 mM Tris 8.0, and extracted using a Spin-X 0.22 μm cellulose acetate column (Costar). Samples were precipitated by adding 32 μL 5M NaCl, 2 μL of GlycoBlue (Invitrogen), and 550 μL of ice-cold isopropanol. Samples were incubated at −20 °C for 1 hour, centrifuged at 4 °C at maximum speed for 30 minutes, washed twice with 500 μL of ice-cold 70% ethanol and 5 minutes of recentrifugation, air dried, and resuspended in 11 μL of water. Paired-end sequencing was performed on an Illumina NextSeq500 at the MIT BioMicroCenter.
5’-OH library preparation
The protocol for generating 5’-OH libraries was a modified version of the MORE RNA-seq protocol for sequencing of 5’-OH ends (Schifano et al., 2014). RNA was extracted from wild type MG1655 cells containing either pBAD33-empty or pBAD33-mazF (ML2902 and ML2903). 5’-P terminated RNA was degraded by adding 2 μL 10x Terminator exonuclease buffer A, 1 μL SUPERase-In (Invitrogen), and 1 μL Terminator exonuclease (Epicentre) to a 20 μL reaction with 1–2 μg of total RNA. Reactions were incubated 1 hour at 30 °C. Reactions were brought to 200 μL of acid-phenol:chloroform, pH 4.5 (Invitrogen). Samples were spun 10 minutes at 4 °C and the top layer was extracted and ethanol precipitated with a 4 hour incubation at −80 °C and resuspended in 34 μL of DEPC water. 5’-OH ends were phosphorylated by adding 5 μL 10x Optikinase buffer (USB), 5 μL 10 mM ATP, 1 μL SUPERase-In (Invitrogen), and 5 μL Optikinase (USB). Reactions were incubated 1 hour at 37 °C. Reactions were phenol extracted and ethanol precipitated as above, resuspending in 14.5 μL of DEPC water. 5’ RNA adapters were ligated by adding 7.5 μL of 10 pmol/μL 5’ RNA adapter, 3 μL of 10x ligase buffer (NEB), 3 μL of 10 mM ATP, 1 μL SUPERase-In (Invitrogen), and 1 μL of T4 RNA Ligase 1 (NEB). Reactions were incubated for 16 hours at 16 °C. Reactions were then purified on a 6% TBE-Urea (Invitrogen) gel using 2x Novex TBE-Urea sample buffer (Invitrogen). The gel was pre-run for at least 30 minutes, and samples were run 20 minutes at 200 V. The entire region above the free-adapter band was excised from the gel. Gel slices were split into four 0.5 mL tubes, centrifuged through a hole pieced in the bottom, and eluted in 600 μL 1x TE/0.3M NaCl per tube. The gel was filtered using Spin-X 0.22 μm cellulose acetate columns (Costar) and ethanol precipitations were conducted. The multiple precipitations for each sample were mixed after pelleting by resuspending in a total of 21 μL of water per sample. 10 μL from each sample was set aside in case downstream steps failed. First strand synthesis was conducted with a primer with both a random region and adapter region. 1 μL of 30 pmol/μL RT primer and 1 μL of 10 mM dNTPs were added to 10 μL of gel elutions and incubated for 5 minutes at 65 °C. On ice, 4 μL of 5x first strand buffer (Invitrogen), 1 μL of 100 mM DTT, 1 μL SUPERase-In (Invitrogen), and 1 μL of Superscript II was added to each reaction. Reactions were placed on a thermocycler and incubated for 10 minutes at 25 °C, 50 minutes at 42 °C, and 15 minutes at 70 °C. 1 μL of RNase H (NEB) was added and reactions were incubated at 37 °C for 20 minutes. Reactions were then purified on a 6% TBE-Urea gel using the 2x loading buffer as above. The region from 110 – 550 nucleotides was excised by comparison with an ssRNA ladder. Each excised region was split into two 0.5 mL tubes, centrifuged through a hole pieced in the bottom, and eluted in 400 μL of 1x TE/0.3M NaCl per tube. The gel was filtered using Spin-X 0.22 μm cellulose acetate columns (Costar) and isopropanol precipitations were conducted. The multiple precipitations for each sample were mixed after pelleting by resuspending in a total of 10 μL of water per sample. Libraries were amplified by adding 18 μL of 5x Phusion HF buffer (NEB), 10 μL of 2.5 μM global 5’-OH primer, 10 μL of 2.5 μM indexed 5’-OH primer, 2 μL of 10 mM dNTP mix, and 1 μL of Phusion polymerase (NEB) to 10 μL of cDNA sample then conducting the amplification protocol following amplification protocol: 98 °C/30 seconds, 98 °C/10 seconds, 60 °C/30 seconds, 72 °C/15 seconds, 72 °C/10 minutes. Steps 2–4 were repeated for 12 cycles. The entire PCR reaction was loaded onto a 2% agarose gel and the library smear above the primer bands was extracted using the MinElute kit (Qiagen). Single-end sequencing was performed on an Illumina HiSeq2000 at the MIT BioMicroCenter.
Ribosome profiling library preparation
The ribosome profiling protocol was adapted from (Oh et al., 2011). Cell growth outlined in the MazF induction section was scaled up to 250 mL final culture size in 1 L flasks. Cells were harvested by filtration over a 90 mm 0.2 μm filter attached to a vacuum flask pre-heated to 37 °C. After filtration, cells were scraped off the filter and immediately frozen in liquid nitrogen. To lyse cells, 650 μL of lysis buffer was prepared and flash frozen: 20 μM Tris pH 8.0, 100 mM NH4Cl, 10 mM MgCl2, 0.4% Triton X-100, 0.1% NP-40, 1 mM chloramphenicol, 15 μL of Turbo DNase (Invitrogen). Frozen lysis buffer and cells were added to liquid nitrogen cooled stainless steel grinding jars (Qiagen) and lysed on a TissueLyser II (Qiagen) instrument 5 times at 15 Hz x 3 minutes, re-cooling jars in between. Lysate was thawed and centrifuged at 20,000 rpm at 4 °C on a tabletop centrifuge. A portion of the lysate from this stage was saved and run on sucrose gradients (see below) without MNase treatment to verify that polysomes were present. To separate monosomes ~0.5 mg of RNA was mixed with 750 U of MNase, 100 U of SUPERase-In (Invitrogen), and 5 mM CaCl2, adding additional lysis buffer to achieve a final volume of 200 μL. Reactions were incubated for 1 hour at 25 °C and then were quenched by adding 2.4 μL of 500 mM EGTA. Monosomes were isolated using a 10–55% sucrose gradient generated on a Gradient Master (BioComp) in a buffer of 20 mM Tris 8.0, 100 mM NH4Cl, 10 mM MgCl and 1 mM chloramphenicol. Sampleos were centrifuged in an SW41 rotor at 35000 rpm for 2.5 hours. Gradients were fractionated and the monosome fraction was collected. To isolate monosome RNA, SDS was added to 1% and acid phenol chloroform IAA (Invitrogen) pre-warmed to 65 °C was added 1:1. Samples were shaken at 1400 rpm at 65 °C on a thermomixer for 5 minutes and then chilled on ice for 5 minutes. The aqueous layer was extracted and mixed with acid phenol chloroform a second time. After the second extraction, samples were isopropanol precipitated and resuspended in 11 μL of 10 mM Tris 7. Then, 20 μg of RNA was loaded onto a Novex 15% TBE-Urea (Invitrogen) gel using 2x TBE-urea sample buffer (Invitrogen) and run for 65 minutes at 200 V. The region between 15–45 bases was excised by comparison with a 10 bp DNA ladder. Each excised region was centrifuged through a hole pieced in the bottom of a 0.5 mL tube, and eluted in 500 μL of 10 mM Tris 7. The gel was filtered using Spin-X 0.22 μm cellulose acetate columns (Costar) and isopropanol precipitations were conducted. RNA was resuspended in 15 μL of 10 mM Tris 7. To prepare for ligation of the linker, RNA was dephosphorylated by adding 2 μL of T4 PNK buffer, 1 μL of SUPERase-In (Invitrogen), and 2 μL of T4 PNK (NEB) and incubating for 1 hour at 37 °C. The enzyme was heat inactivated by incubating for 10 minutes at 75 °C. Samples were purified by isopropanol precipitation and resuspended in 11 μL of 10 mM Tris 7. Linker was ligated by diluting 30 ng of RNA in 5 μL of 10 mM Tris 7 and adding 10 μL of 50% PEG 8000 (NEB), 2 μL of 10x T4 RNA Ligase 2 buffer (NEB), 1 μL of water, 1 μL of 100 μM linker, and 1 μL of T4 ligase 2, truncated (NEB). Reactions were incubated at 25 °C for 2.5 hours, purified by isopropanol precipitation, and resuspended in 6 μL of 10 mM Tris 7. For size selection, samples were run on a Novex 10% TBE-Urea gel (Invitrogen) for 50 minutes at 200 V using 2x sample buffer (Invitrogen). The region between 35–65 bases was excised, eluted and purified as above. Samples were resuspended in 10 μL of 10 mM Tris 7. Reverse transcription was conducted by adding 1 μL of 10 mM dNTPs, 0.5 μL of 25 μM RT oligo oCJ485, and 1.5 μL of DEPC water. Mixture was denatured at 65 °C for 5 minutes and then placed on ice before adding 4 μL of 5x first strand buffer (Invitrogen), 1 μL of SUPERase-In (Invitrogen), 1 μL of 100 mM DTT, and 1 μL of Superscript III (Invitrogen). Reactions were incubated for 30 minutes at 50 °C and quenched by adding 2.3 μL of 1 M NaOH. RNA was degraded by incubating at 95 °C for 15 minutes. Samples were then mixed with 2x TBE-Urea loading buffer (Invitrogen) and run (2 lanes per sample) on a Novex 10% TBE-Urea gel at 200V for 80 minutes. The cDNA region excluding the free RT primer was excised, eluted and purified as above except that 500 μL of 10 mM Tris 8 was used for elution rather than Tris 7. The sample was resuspended in 15 μL of 10 mM Tris 8. The cDNA was circularized by adding 1 μL of 1 mM ATP, 2 μL of 10x CircLigase buffer, 1 μL of 50 mM MnCl2, and 1 μL of CircLigase (Epicentre). The reaction was incubated at 60 °C for 1 hour, after which an additional 1 μL of CircLigase was added before incubating for another hour. The enzyme was deactivated by incubating the reaction for 10 minutes at 80 °C. A 5 μL aliquot of circularized cDNA was used for rRNA subtraction. A subtraction oligo mix was prepared by mixing 77 μL of o1055, 4 μL of o1056, 17 μL of o1057, and 2 μL of o1058 using 100 μM stocks. Next, 5 μL of cDNA was mixed with 1 μL of subtraction oligo mix, 1 μL of 20x SSC (Invitrogen), and 3 μL of DEPC water. Using a thermocycler, reactions were incubated at 98 °C for 75 seconds. Then the temperature was linearly decreased from 98 °C to 37 °C over 1 hour and finally the temperature was held at 37 °C for 20 minutes for hybridization. In parallel, 25 μL of MyOne streptavidin C1 Dynabeads (Invitrogen) were prepared by washing 3 times with 1x B&W buffer and resuspending in 10 μL of 2x B&W buffer; 2x B&W buffer was 10 mM Tris 7.5, 1 mM EDTA, 2 M NaCl, and 0.01% Tween. Beads were heated to 37 °C and mixed 1:1 with the hybridization reaction and incubated at 37 °C for 15 minutes. The supernatant was recovered using a magnetic rack and was isopropanol precipitated and resuspended in 10 μL of 10 mM Tris 8. Libraries were PCR amplified in a reaction with 1x high fidelity buffer (NEB), 200 μM dNTPs, 500 nM o231, 500 nM indexing primer, 0.6 μL of Phusion (NEB) in a 60 μL final reaction volume. The following amplification protocol was used: 98 °C/30 seconds, 98 °C/10 seconds, 60 °C/10 seconds, 72 °C/5 seconds. Steps 2–4 were repeated for 12 cycles. PCR reactions were purified on a Novex 8% TBE (Invitrogen) gel run at 180 V for 50 minutes. The library region was excised, eluted and purified as above using 500 μL of 10 mM Tris 8. Samples were isopropanol precipitated, resuspended in 11 μL of 10 mM Tris 8, and submitted for sequencing. Single-end sequencing was performed on an Illumina NextSeq500 at the MIT BioMicroCenter.
qRT-PCR acquisition and analysis
Reverse transcriptase reactions were conducted by mixing 100 ng Random Primers (Invitrogen), 250 ng total RNA, and 10 nmol dNTPs in 13 μL nuclease-free water. Reactions were incubated at 65 °C for 5 minutes and placed on ice. After cooling, reactions were mixed with first strand buffer (Invitrogen) at 1X, 100 nmol DTT, and 20 U SUPERase-In (Invitrogen). After allowing the reactions to come to room temperature, 200 U of SuperScript III (Invitrogen) was added to yield a final reaction volume of 20 μL. Reactions were incubated with the following thermocycler program: 25 °C/5 minutes, 50 °C/1 hour, 70 °C/15 minutes. 5 U of RNase H (NEB) was then added and reactions were incubated for 20 minutes at 37 °C. qPCR reactions were prepared with 2x SYBR FAST Master Mix (Roche) and 300 nM of each qPCR primer in a 10 μL final volume. cDNA from reverse transcription reactions was diluted with nuclease-free water. All experimental samples and standard curves were loaded onto a 384-well plate in triplicate for qPCR. qPCR was conducted in a LightCycler 480 system (Roche) using the following thermocycler program: 95 °C/10 minutes, 95 °C/15 seconds, 60 °C/30 seconds, 72°C/30 seconds with 40 cycles of steps 2–4. Cp values were calculated using the LightCycler 480 software at the second derivative maximum. Technical replicates were averaged to yield a final Cp value for each sample and standard curve point. On each plate, relative quantities of cDNA in a given sample were calculated by comparison to a least-square fit on a 2-fold dilution standard curve (Cp vs. log-transformed standard fold dilution). Target region quantities were normalized to control region quantities and normalized change from + MazF to empty vector was calculated. Error across three biological replicates was propagated and reported in the final value. For a complete list of control and target region primers, see Table S5.
6S RNA reporter
To use the B. subtilis 6S RNA reporter, + MazF and empty vector plasmid containing strains (ML2883 and ML2884) were transformed with reporter expression plasmids (purified from ML2885-ML2891). Cells were then grown as in the ‘MazF induction’ section with the addition of 100 ng/mL anhydrotetracycline in the wash and final MazF induction media to induce expression of the reporter construct. qRT-PCR was performed as described above using the 5’ end containing the MazF site as the target region and the 3’ end of the reporter as the control region. RNA was extracted 10 minutes after induction of MazF.
YFP* translation reporter construct
To use the B. subtilis 6S RNA reporter, + MazF and empty vector plasmid containing strains (ML2902 and ML2903) were transformed with reporter YFP* expression systems with or without ACA sites between the Shine-Dalgarno site and the start codon (purified from ML2902 and ML2903). Cultures were grown as in the ‘MazF induction’ section, but 100 ng/mL of anhydrotetracycline was added at the same time as arabinose induction of MazF or the empty vector. Cultures were plated in triplicate on a Synergy H1 plate reader (BioTek) at 37°C with orbital shaking at 237 rpm. OD600 and YFP fluorescence were recorded every 5 minutes for 2 hours and triplicate samples were averaged. YFP signal was normalized to blanked OD600 and the ratio of the + MazF to empty vector sample was calculated. In Fig. 5C, we report the average and S.D. of 3 biological replicates.
Northern blotting
For Northern blots, induction and RNA extraction were conducted as above. For all blots except Fig. 6B probe 3, 200–1000 ng of total RNA and low range ssRNA ladder was loaded onto Novex 6% TBE-Urea gels (Invitrogen) using 2x sample buffer (Invitrogen) and run for 40–60 minutes at 100 V. Ladder positions relative to rRNA bands were recorded using SYBR Gold (Invitrogen). RNA was transferred onto Amersham Hybond-N+ nylon membrane (GE) using a Trans-Blot Turbo semi-dry transfer apparatus (BioRad) for 90 minutes at 0.4 A. For Fig. 6B probe 3, 800 ng of RNA was loaded onto a denaturing 1% agarose gel with formaldehyde load dye (Invitrogen) and run for 3 hours at 100 V. ssRNA ladder (NEB) was used for size comparison. RNA was transferred onto Amersham Hybond-N+ nylon membrane (GE) using capillary transfer overnight. RNA was crosslinked to the membrane using the autocrosslink setting on a UV Stratalinker 1800 (Stratagene). Oligonucleotide probes were radiolabeled in a 25 μL reaction by mixing 1 μL of 10 μM oligo, 2.5 μL of 10x T4 PNK buffer (NEB), 7.5 μL of [γ−32P] ATP (PerkinElmer), and 1 μL of T4 PNK (NEB). Reactions were incubated at 37 °C for 30 minutes and the enzyme was inactivated by incubating at 65 °C for 20 minutes. Free ATP was removed using a NucAway spin columns (Invitrogen). Membranes were pre-hybridized by adding 10 mL of pre-heated ULTRAhyb-Oligo (Invitrogen) to the membrane and incubating at 42 °C for 30 minutes with rotation in a hybridization oven. 5–20 μL of radiolabeled probe was added and hybridization was allowed to proceed overnight. After hybridization, membranes were washed twice with 2x SSC (Invitrogen) / 0.5% SDS, sealed in plastic bags and incubated at room temperature with a storage phosphor screen for 4–16 hours. Images were recorded with a Typhoon FLA 9500 (GE) instrument. ImageJ was used to crop images and lower the upper limit of the display range to make bands visible for figures.
Quantification of 43 nt fragment and rRNA cleavage estimate
Northern blots were run as above. The concentration of synthetic 43 nt marker (IDT) and total RNA loaded were measured by Qubit hsRNA assay (Invitrogen) before loading on gel. After imaging, ImageJ was used to quantify signal from the marker standard curve and the total RNA samples. Amount of RNA at the 43 nt band was quantified by linear interpolation from the standard curve. We estimated the fraction of cleaved ribosomes by first calculating the fraction of the ribosome which would be cleaved off (~0.01). Then, we determined the expected ng of 43 nt fragment we would observe if 100% of ribosomes were cleaved using the amount of total RNA we loaded in each lane assuming that 85% of total RNA is rRNA. Finally, we compared our observed 43 nt fragment in each lane to the expected value to estimate the percentage of ribosomes that may be cleaved. The molecules of 43 nt fragment per cell calculation is based on an estimate of ~10,000 ribosomes per cell.
Isotopic labeling of mature and nascent rRNA
Cells were grown as above in 40 mL final culture volume with a pulse of 5 μCi of [5, 6-3H] uridine (PerkinElmer) and 1000-fold excess chase of cold uridine at times indicated. Cells were harvested by centrifugation at 10000 g for 1 minute at 4 °C. Cell pellets were placed on ice and resuspended in 300 μL of lysis buffer: 20 mM Tris 8, 100 mM NH4Cl, 10 mM MgCl2, 0.5 mM EDTA, and 6 mM β-mercaptoethanol with 1 μL of Ready-Lyse (Epicentre), 5 μL of SUPERase-In (Invitrogen), and 2 μL of TURBO DNase (Invitrogen) added directly to each resuspension. Lysis reactions were incubated on ice for 5 minutes. Reactions were then incubated at −80 °C for 10 minutes and incubated at 4 °C for 30 minutes. This freeze-thaw cycle was repeated for a total of 3 freeze-thaws to lyse the cells. Cell debris was then removed by centrifugation for 20 minutes at 4 °C at maximum speed on a tabletop centrifuge. The supernatant was loaded onto a 5–30% linear sucrose gradient generated on a Gradient Master (BioComp) instrument in a buffer of 20 mM Tris 8.0, 100 mM NH4Cl, and 10 mM MgCl. Samples were centrifuged in an SW41 rotor at 35000 rpm for 4 hours. Gradients were fractionated by poking a hole in the bottom of the centrifuge tube and collecting 40–50 ~200 μL fractions in a 96-well plate. A portion of each fraction was back-diluted in water and A254 was measured. 100 μL of each fraction was added to 4 mL of Ecoscint H (National Diagnostics) and 3H cpm was measured on a TRI-CARB 4910 TR liquid scintillation counter (PerkinElmer).
Data Analysis Details
Sequencing read mapping and normalization
FASTQ files for each barcode were mapped to the MG1655 genome (NC_000913.2) using bowtie2 (version 2.1.0) with the following arguments: -D 20 -R 3 -N 0 -L 20 -i S,1,0.50 -p 6 -I 40 -X 300 (Langmead and Salzberg, 2012). The samtools (version 0.1.19) suite (Li et al., 2009) was used via the pysam library (version 0.9.1.4) for interconversion of BAM and SAM file formats and conducting indexing. Adapter sequences were trimmed from ribosome profiling reads. Gene names, coding region positions, gene ontology categories were extracted from ecocyc.org.
Paired-end sequencing, coding regions:
For each uniquely mapped paired fragment, one count was added for all positions between and including the 5’ and 3’ ends of the forward and reverse strand reads. To correct for variability in sequencing depth, counts at each position were divided by a sample size factor. Briefly, counts recorded in each coding region were summed for all samples and then the geometric mean was taken across samples to yield a reference sample. The size factor for a given sample was the median counts in coding regions after normalizing counts to the reference sample. Except in figures where replicates were compared, reported counts were the average of the log2 of two replicates after adding a pseudocount to all positions and normalizing to the sample size factor. The cleavage ratio at each nucleotide was then calculated as the log2 transformed + MazF:empty vector ratio.
Paired-end sequencing, rRNA loci:
For all paired fragments, one count was added for all positions between and including the 5’ and 3’ ends of the forward and reverse strand reads. To correct for variability in sequencing depth, counts at each position were normalized by calculating counts per million counts. Prior to normalization, a pseudocount was added at each position. To determine the number of counts mapping across conserved regions of the different rRNA loci, we made alignments of the 16S and 23S genes including surrounding immature rRNA regions using Clustal Omega. Using the alignment, we made a consensus map of the mature regions of the 16S and 23S genes. For each position in the consensus map, the counts occurring at the corresponding positions in the genome were summed. Consensus positions which did not exist in all loci (i.e. insertions) were left undefined and appear as blank regions on plots. Consensus positions with mismatches at one or more loci were allowed. The summed counts for each sample were log2 transformed and two replicates were averaged before plotting.
5’-OH sequencing:
For all reads, a single count was added at the position corresponding to the 5’ end. To correct for variability in sequencing depth, counts at each position were normalized by calculating counts per million reads uniquely mapped. Prior to normalization, a pseudocount was added at each position. The 5’-OH ratio was the log2 transformed + MazF:empty vector ratio.
Ribosome profiling:
For uniquely mapped reads, a single count was added at the position corresponding to the 5’ or 3’ end of the read, depending on the analysis. To correct for variability in sequencing depth, reads at each position were normalized by calculating reads per million reads uniquely mapped. For visualization of ribosome position on gene plots, a rolling 30 nucleotide window was used to sum read counts from the 3’ ends of reads, adding a single pseudo-count to enable log2 transformation. Gaussian smoothing (σ=20 nucleotides, filter truncation at 4σ) was also conducted on the rolling sum to enable easy visual comparison of + MazF and empty vector samples.
Comparison of qRT-PCR data to sequencing data
To compare RNA-Seq and qRT-PCR data, we compared the RNA abundance measured by qRT-PCR to the set of RNA-Seq values across the entire region assayed by qRT-PCR. In Fig. 1D–E, the minimum cleavage ratio value in the region was compared to the measured RNA abundance. The four dots correspond to cleavage ratios calculated using all possible pairings of two + MazF replicates and two empty vector replicates. In Fig. 1F, the minimum cleavage ratio was calculated by averaging all of the replicate cleavage ratios. In Fig. 2C, the sum of 5’-OH values at ACA sites within the amplified region was compared to the measured RNA abundance.
Assessing the reproducibility of the cleavage ratio
Most analyses with the cleavage ratio involved taking the minimum cleavage ratio in a gene or region. Thus, if any position in this region had few reads, it would reduce the certainty in measurements of the entire region. To simulate measurements of this type, we split coding regions into non-overlapping windows of 100 nucleotides. Windows were generated by combining all contiguous coding regions and stepping the maximum number of 100 nucleotide windows in a left to right direction across each contiguous region. To assess the reproducibility of the cleavage ratio at 5 minutes (Fig. S1B), any regions which had, at nucleotide position, fewer counts in the empty vector sample than the expression cutoff of 64 counts were discarded, leaving 15,926 regions. The minimum cleavage ratios in these regions were compared. This protocol was also used to compare 5 minute, 30 minute, and 60 minute cleavage ratios in Fig. S1C, leaving 1,868 regions. Note that these cleavage ratios were calculated using 30 minute empty vector data for all samples in Fig. S1C.
Identifying cleaved regions and the MazF motif
To determine additional sequence specificity beyond ACA, we set out to find a set of ACAs that were very likely to be MazF targets to compare against the general set of ACAs. To do this, we looked for deep and narrow valleys in the cleavage ratio that had single ACA sites in them, as these were likely to be the recognition site for MazF. To find local minima, we conducted Gaussian smoothing of the cleavage ratio using σ = 40 nucleotides, truncating the filter at 4σ. Next, we found local minima on the smoothed cleavage ratio and searched the region ±25 nucleotides from the identified local minima for the minimum value on the unsmoothed cleavage ratio. To ensure that the valley was relatively narrow, we next looked 100 nucleotides upstream and downstream and found the first position on both sides that was ≥1 larger in the cleavage ratio, equivalent to a 2-fold increase in relative RNA abundance; these left and right nucleotides defined the cleaved region. If the cleavage ratio did not increase by 1 within 100 nucleotides on either side, the region was removed from consideration. To ensure that all cleaved regions were transcribed and of high certainty, any region that had any position that was not in a coding region or was below the expression cutoff of 64 counts was removed. The above algorithm was also used to define regions to test the frequency of tri-nucleotide motifs with the exception that 50 nucleotides, rather than 100, was the maximum distance allowed for an increase of 1 in the cleavage ratio. To determine the motif, we recorded the nucleotides ±3 from ACAs that were the only ACA in the cleaved region. The surrounding nucleotides were also recorded for all ACA sites occurring in coding regions. The frequency of nucleotides at cleaved ACAs and background (all coding) ACAs were compared to generate a sequence logo (Fig. 3C) and position weight matrix (Fig. 3D) for the three upstream/downstream positions relative to the ACA.
Verification of the motif
To determine if high scoring motifs were enriched in cleaved regions (Fig. 3G), we used the same algorithm and settings to find regions as we used to find motifs with the exception that we did not filter the regions based on how many ACA sites they had. To ensure that the motif does not change significantly with different algorithm settings, we varied the minima search distance (10, 25, 50, or 100), the minimum change in cleavage ratio (0.75, 1, 1.25, or 1.5), and the maximum region half-width (50, 100, 150, or 200), resulting in the 64 different motifs (Fig. S3B). The preferences for particular nucleotides were stable and all calculated position weight matrices correlated well (mean R2 = 0.92, minimum R2 = 0.74). The motif finding algorithm used above relies on the formation of stable MazF cleavage products (the edges of the ‘valley’). To ensure our motif was not strongly affected by this, we verified that high scoring MazF sites were enriched in cleaved regions regardless of the stability of the fragments generated by MazF cleavage. To do this, we classified as cleaved a region of any size with a cleavage ratio value ≤ −1 after median-normalizing the cleavage ratio across each coding region. By this metric, 7.5% of all positions were cleaved. Then, for each score class of motif and all 3-nt motifs apart from ACA, we recorded the fraction of these sites which occurred in cleaved or uncleaved regions of the genome (Fig. S3C). Cleaved regions accounted for 31.5, 16.5 and 9.4% of high (score ≥ 1), medium (1 > score ≥ −1.5) and low (−1.5 > score) scoring sites, respectively. The 3-nt motifs had a mean of 7.5% occurring in the background region, the same as the percent of positions classified as cleaved in this analysis. Based on this analysis, we conclude that higher scoring motifs are more enriched in cleaved regions regardless of the stability of the degradation products.
Identification of leaderless transcripts
To determine if genes were leaderless and/or cleaved in their coding region, we only considered genes that met our expression threshold both across their entire coding region and in the 15 nucleotides just upstream of the translation start site (n=941). The amount of possible leaderless transcript was estimated by comparing each of the 15 positions upstream of the transcription start site to the position 15 nucleotides ahead (for a total of 15 comparisons). We define the maximum of these 15 values as an upper-bound estimate on the amount of leaderless transcript relative to unprocessed transcript.
Observation of ribosome footprints near MazF motifs
To generate single-nucleotide-level plots of the change in 3’ ribosome footprints near MazF motifs, we collected the regions surrounding a category of ACA sites for which the ±100 nucleotides were all in coding regions. Random regions were also selected with the same requirement. Then, for each nucleotide position within all regions, the log2 change in footprints was calculated after expression of MazF for 5 minutes. Finally, the average was calculated across the regions to generate the plotted data. Any nucleotide positions which were undefined due to having no footprints in either the empty vector of MazF treatment were ignored.
Calculation of changes in 3’ ribosome footprints
The number of 3’ ribosome footprints in a given gene was calculated by summing ribosome footprints in the nucleotides following the last MazF motif (score ≥ −1.5). This avoided inflation of ribosome counts in MazF-cleaved samples by ribosome ‘traffic-jams’ upstream of cleaved sites. To be included in this analysis, genes had to be expressed (as defined above) in their leader region and across their entire length (n=941) and also had to have at least 30 nucleotides following the last MazF motif (n=766). If there was no motif, footprints in the entire coding region were summed. These values were then used to calculate the change in ribosome footprints after MazF induction (Fig. 5F, Table S3). Though not included in the above analyses, in genes where there were less than 30 nucleotides after the last MazF motif, the summed footprints in the last 50 nucleotides were included in Table S3 for reference.
Data and Software Availability
Sequencing data
Processed data used in analyses is available in Table S1 (minimum cleavage ratios in expressed genes), Table S2 (identification of leaderless and full-length, leaderless genes), and Table S3 (changes in ribosome footprint counts at the 5’ and 3’ ends of genes). The raw sequencing files and nucleotide-resolution counts and cleavage ratios have been deposited on GEO database under the ID code GSE107330.
Supplementary Material
Table S2. Identification of leaderless transcripts, Related to Figure 4A.
Table S1. Cleavage ratio minima for all coding regions, Related to Figure 1G.
Table S3. Change in ribosome footprints in transcripts, Related to Figure 5G.
Table S4. Strains, Related to STAR Methods.
Table S5. Plasmids, Related to STAR Methods.
Table S6. Primers, Related to STAR Methods.
Figure S1, Related to Figure 1. Analysis of replicates and examples of MazF cleavage profiles.
Figure S2, Related to Figure 2. Overview of 5’-OH sequencing.
Figure S3, Related to Figure 3. MazF has an extended recognition motif.
Figure S4, Related to Figure 4. MazF does not produce a large pool of leaderless transcripts.
Figure S5, Related to Figure 5. MazF does not drive the preferential translation of leaderless transcripts.
Figure S6, Related to Figure 6. MazF does not target mature ribosomes, but does inhibit ribosome maturation.
KEY RESOURCES TABLE.
| REAGENT or RESOURCE | SOURCE | IDENTIFIER |
|---|---|---|
| Antibodies | ||
| Bacterial and Virus Strains | ||
| MG1655 ΔmazF | (Maisonneuve et al., 2011) | N/A |
| DH5α | Invitrogen | N/A |
| MG1655 ΔmazF pBAD30-mazF | This study | ML2881 |
| MG1655 ΔmazF pBAD30 | This study | ML2882 |
| MG1655 ΔmazF pBAD33-mazF | This study | ML2883 |
| MG1655 ΔmazF pBAD33 | This study | ML2884 |
| DH5α pKVS45-6S score 4 | This study | ML2885 |
| DH5α pKVS45-6S score 1.5 | This study | ML2886 |
| DH5α pKVS45-6S score −0.5 | This study | ML2887 |
| DH5α pKVS45-6S score −2.1 | This study | ML2888 |
| DH5α pKVS45-6S score −4.5 | This study | ML2889 |
| DH5α pKVS45-6S score −8 | This study | ML2890 |
| DH5α pKVS45-6S ACC | This study | ML2891 |
| DH5α pKVS45-5’UTR with ACA-yfp* | This study | ML2900 |
| DH5α pKVS45-5’UTR without ACA-yfp* | This study | ML2901 |
| MG1655 pBAD33-mazF | This study | ML2902 |
| MG1655 pBAD33 | This study | ML2903 |
| Chemicals, Peptides, and Recombinant Proteins | ||
| Trizol | Invitrogen | 15596018 |
| Turbo DNase | Invitrogen | AM2238 |
| GlycoBlue | Invitrogen | AM9515 |
| Random Primers (3 μg/μL) | Invitrogen | 48190011 |
| RNA Fragmentation Reagents | Invitrogen | AM8740 |
| SUPERase-In | Invitrogen | AM2694 |
| Superscript III Reverse Transcriptase | Invitrogen | 18080044 |
| Second Strand Buffer | Invitrogen | 10812014 |
| RNase H | NEB | M0297 |
| E. coli DNA Ligase | NEB | M0205 |
| E. coli DNA Polymerase I | NEB | M0209 |
| Elution Buffer (Buffer EB) | Qiagen | 19086 |
| T4 DNA Ligase Buffer | NEB | B0202 |
| T4 DNA Polymerase | NEB | M0203 |
| Klenow DNA Polymerase | NEB | M0210 |
| T4 PNK | NEB | M0201 |
| NEB Buffer 2 | NEB | B7002 |
| Klenow Fragment (3’→5’ exo-) | NEB | M0212 |
| Quick Ligase | NEB | M2200 |
| USER Enzyme | NEB | M5505 |
| Phusion Polymerase | NEB | M0530 |
| acid-phenol:chloroform IAA, pH 4.5 | Invitrogen | AM9720 |
| Terminator Exonuclease | Epicentre | TER51020 |
| Optikinase | USB | E78334 |
| T4 RNA Ligase 1 | NEB | M0204 |
| 2x Novex TBE-Urea sample buffer | Invitrogen | LC6876 |
| Superscript II | Invitrogen | 18064014 |
| MNase | Gene-Wei Li | N/A |
| T4 ligase 2, truncated | NEB | M0242 |
| Circligase | Epicentre | CL4111K |
| MyOne Streptavidin C1 Dynabeads | Invitrogen | 65001 |
| KAPA SYBR Fast qPCR Master Mix (2X) | Roche | 07959494001 |
| SYBR Gold Stain | Invitrogen | S11494 |
| [γ-32P] ATP | PerkinElmer | NEG002A100UC |
| ULTRAhyb-Oligo | Invitrogen | AM8663 |
| [5, 6-3H] uridine | PerkinElmer | NET367250UC |
| Ready-Lyse | Epicentre | R1810M |
| Ecoscint H | National Diagnostics | LS-275 |
| Critical Commercial Assays | ||
| Direct-zol RNA MiniPrep | Zymo | R2050 |
| Ribo-Zero rRNA Removal Kit | Illumina | MRZB12424 |
| MinElute Kit | Qiagen | 28604 |
| Deposited Data | ||
| RNA-Sequencing | This study | GSE107330 |
| Oligonucleotides | ||
| See Table S6 for primers used in strain construction. | This study | N/A |
| See Table S6 for primers used for qRT-PCR. | This study | N/A |
| See Table S6 for primers used for library construction. | Illumina | N/A |
| Recombinant DNA | ||
| pKVS45 | Kristala Prather | N/A |
| pBAD30 | (Guzman et al., 1995) | CGSC#:12524 |
| pBAD33 | (Guzman et al., 1995) | CGSC#:12525 |
| pBAD30-mazF | This study | N/A |
| pBAD33-mazF | This study | N/A |
| DH5α pKVS45-6S score 4 | This study | N/A |
| DH5α pKVS45-6S score 1.5 | This study | N/A |
| DH5α pKVS45-6S score −0.5 | This study | N/A |
| DH5α pKVS45-6S score −2.1 | This study | N/A |
| DH5α pKVS45-6S score −4.5 | This study | N/A |
| DH5α pKVS45-6S score −8 | This study | N/A |
| DH5α pKVS45-6S ACC | This study | N/A |
| Software and Algorithms | ||
| ImageJ (v1.48) | NIH | https://imagej.nih.gov/ij/ |
| bowtie2 (v2.1.0) | Langmead and Salzberg, 2012 | http://bowtie-bio.sourceforge.net/bowtie2/index.shtml |
| pysam (v0.9.1.4) | N/A | https://github.com/pysam-developers/pysam |
| samtools (v0.1.19) | Li et al., 2009 | http://samtools.sourceforge.net/ |
| numpy (v1.13.1) | N/A | https://github.com/numpy/numpy |
| biopython (v1.65) | N/A | https://github.com/biopython/biopython |
| scipy (v0.18.1) | N/A | https://github.com/scipy/scipy |
| jupyter notebook | N/A | https://github.com/jupyter |
| Other | ||
| Thermomixer C | Eppendorf | 5382000015 |
| TissueLyser II | Qiagen | |
| Stainless Steel Grinding Jars | Qiagen | |
| SW41 Ultracentrifuge Rotor | Beckman Coulter | |
| Novex 15% TBE-Urea gel | Invitrogen | EC6885BOX |
| Novex 10% TBE-Urea gel | Invitrogen | EC6875BOX |
| Novex 6% TBE-Urea gel | Invitrogen | EC6865BOX |
| Novex 8% TBE gel | Invitrogen | EC6215BOX |
| Agencourt AMPure XP | Beckman Coulter | A63880 |
| Gradient Master | Biocomp | |
| Corning Costar Spin-X centrifuge tube filters, 0.22 um | Sigma-Aldrich | CLS8160 |
| LightCycler 480 instrument | Roche | |
| Amersham Hybond-N+ nylon membrane | GE | RPN119B |
| Trans-Blot Turbo Transfer System | BioRad | 1704150 |
| UV Stratalinker 1800 | Stratagene | N/A |
| NucAway spin columns | Invitrogen | AM10070 |
| Typhoon FLA 9500 | GE | 28996943 |
| TRI-CARB 4910 TR liquid scintillation counter | PerkinElmer | A491000 |
| Synergy H1 plate reader | BioTek | |
Acknowledgements
We thank M. LeRoux, M. Guo, and J. Davis for comments on the manuscript. M.T.L. is an Investigator of the Howard Hughes Medical Institute (HHMI). This work also supported by an NSF predoctoral graduate research fellowship to P.H.C.
Footnotes
Declaration of Interests
The authors declare no competing interests.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S2. Identification of leaderless transcripts, Related to Figure 4A.
Table S1. Cleavage ratio minima for all coding regions, Related to Figure 1G.
Table S3. Change in ribosome footprints in transcripts, Related to Figure 5G.
Table S4. Strains, Related to STAR Methods.
Table S5. Plasmids, Related to STAR Methods.
Table S6. Primers, Related to STAR Methods.
Figure S1, Related to Figure 1. Analysis of replicates and examples of MazF cleavage profiles.
Figure S2, Related to Figure 2. Overview of 5’-OH sequencing.
Figure S3, Related to Figure 3. MazF has an extended recognition motif.
Figure S4, Related to Figure 4. MazF does not produce a large pool of leaderless transcripts.
Figure S5, Related to Figure 5. MazF does not drive the preferential translation of leaderless transcripts.
Figure S6, Related to Figure 6. MazF does not target mature ribosomes, but does inhibit ribosome maturation.
Data Availability Statement
Sequencing data
Processed data used in analyses is available in Table S1 (minimum cleavage ratios in expressed genes), Table S2 (identification of leaderless and full-length, leaderless genes), and Table S3 (changes in ribosome footprint counts at the 5’ and 3’ ends of genes). The raw sequencing files and nucleotide-resolution counts and cleavage ratios have been deposited on GEO database under the ID code GSE107330.