cis-antisense RNA, another level of gene regulation in bacteria

Abstract

A substantial amount of antisense transcription is a hallmark of gene expression in eukaryotes. However, antisense transcription was first demonstrated in bacteria almost 50 years ago. The transcriptomes of bacteria as different as Helicobacter pylori, Bacillus subtilis, Escherichia coli, Synechocystis sp. strain PCC6803, Mycoplasma pneumoniae, Sinorhizobium meliloti, Geobacter sulfurreducens, Vibrio cholerae, Chlamydia trachomatis, Pseudomonas syringae, and Staphylococcus aureus have now been reported to contain antisense RNA (asRNA) transcripts for a high percentage of genes. Bacterial asRNAs share functional similarities with trans-acting regulatory RNAs, but in addition, they use their own distinct mechanisms. Among their confirmed functional roles are transcription termination, codegradation, control of translation, transcriptional interference, and enhanced stability of their respective target transcripts. Here, we review recent publications indicating that asRNAs occur as frequently in simple unicellular bacteria as they do in higher organisms, and we provide a comprehensive overview of the experimentally confirmed characteristics of asRNA actions and intimately linked quantitative aspects. Emerging functional data suggest that asRNAs in bacteria mediate a plethora of effects and are involved in far more processes than were previously anticipated. Thus, the functional impact of asRNAs should be considered when developing new strategies against pathogenic bacteria and when optimizing bacterial strains for biotechnology.

Fig. 1.

Antisense transcription is a hallmark of gene expression in all three domains of life. The number of reported antisense transcripts is plotted as a percentage of the total number of genes in the selected bacteria (, , , , , , , , , , , –76, 81, 99, 110), various eukaryotes (17, 34, 39, 112), and archaea (91, 107). Dashed boxes indicate that publications with different numbers of asRNAs exist for a distinct organism (e.g., B. subtilis and Mus musculus). In the case of E. coli, the authors speculated that the high incidence of antisense transcription could be representing background transcription throughout the genome (75). The percentages are either directly stated in the respective publications or roughly calculated using the asRNA number and the number of annotated genes. H. sapiens, Homo sapiens.

Fig. 2.

Mechanisms of bacterial asRNAs: codegradation of IsrR together with its target, the mRNA isiA, in the cyanobacterium Synechocystis PCC6803. The asRNA IsrR originates from the central part of the isiA gene from a constitutive promoter (P_cons). The isiA gene is under the control of the inducible promoter P_ind. Under early-stress conditions, isiA transcription becomes activated. Both transcripts are codegraded. The mRNA cannot accumulate as long as IsrR > isiA, and no protein is made. When stressful conditions persist, IsrR is still transcribed, but its turnover is very high, and consequently, it becomes titrated out. The mRNA accumulates, translation occurs, and supercomplexes between IsiA and photosystem I are formed. As a result, IsrR causes a threshold linear response of gene activation and inactivation, with an initial delay and a fast degradation after the stress compared to the expected kinetics of gene expression in the absence of the asRNA (blue dashed line).

Fig. 3.

Two mechanisms for bacterial asRNAs that overlap at the 3′ or the 5′ end of a protein-coding gene. (A) Specific processing of the gadXW transcript through the asRNA GadY. GadY originates from a gene overlapping the 3′ end of the gadX gene that is highly induced during stationary phase and is dependent on the alternative sigma factor RpoS (66). GadY base pairs with the 3′ untranslated region of the gadX mRNA and confers increased stability through posttranscriptional processing, which allows gadX and gadW mRNA accumulation and increased expression levels of the downstream acid resistance genes (97). Protein factors involved include RNase III, other so-far-unknown RNases (65), probably RNase E (90), and possibly Hfq. (B) Inhibition of translation through SymR (40, 41). SymR is complementary over its full length to the symE 5′ UTR, including the ribosome binding site (RBS), and probably causes a block in ribosome binding and, to a lesser extent, enhanced degradation of the untranslated mRNA. GadY and SymR are drawn according to their RNAfold maximum free energy (mfe) secondary structures.

Fig. 4.

Mechanisms of transcription termination by bacterial asRNAs. (A) Organization of the Vibrio anguillarum iron transport-biosynthesis operon. The asRNA RNAβ induces transcription termination at a predicted stem-loop after the fatABCD part of the mRNA (89). (B) Schematic representation of the virA-rnaG-icsA (virG) locus of the Shigella flexneri pVIN plasmid and visualization of the proposed transcription termination mechanism (28). The 5′ region of the newly transcribed icsA message forms the stem-loop structure AH1 (1), and, without binding to RnaG, another stem-loop (AH2) is formed. This 5′ structure resembles an antiterminator structure (2a), and the full-length mRNA could be transcribed (3a). When RnaG is present, it forms a heteroduplex with the growing icsA message. This inhibits the formation of the antiterminator structure, and a terminator hairpin is formed (2b). Subsequently, transcription is attenuated, and a ∼100-nt abortion RNA is released (3b).

Fig. 5.

Transcriptional interference: asRNAs as a by-product of interfering promoters. (A) Proposed collision mechanism for the ubiG-mccAB-as_mccA system (as_mccA stands for mccA antisense RNA). The two divergently elongating RNA polymerases, transcribing the asRNA and the ubiG-mccAB operon, collide and give rise to the 1,000-nt fragment for as_mccA, which represents the sole known mechanism of termination. Short fragments for the mRNA were not detected, indicating a rapid degradation of the prematurely terminated transcript. (B) Promoter occlusion. (C) The sitting-duck mechanism of transcriptional interference.

Fig. 6.

Quantitative effects of asRNAs on the modulation of gene expression in the threshold linear response model. (A) In the threshold linear response, the mRNA and its asRNA regulator interact in a stoichiometric way with each other. The transcription rates (α) and the individual degradation rates (β) define the concentrations of mRNA ([mRNA]) and asRNA ([asRNA]) that are available for interaction with the rate (k) to be sequestered or codegraded (also see Fig. 2 for the special case of IsrR/isiA codegradation that follows this model) (50). (B) Graphical representation of the threshold linear response caused by the presence of an asRNA. The threshold is set by the ratio of mRNA/asRNA (52). The black line illustrates the theoretical behavior if the asRNA and target interact completely and instantly. In reality, there is no sharp transition point, and the actual response depends on the interaction rate between the regulator and target (illustrated by the gray line). (C) The expression of genes belonging to one and the same regulon is temporally shifted by the presence of an asRNA. Without an asRNA regulator, a gene is expressed directly upon the onset of a stimulus, and when the stimulus disappears, the mRNA level declines relatively slowly via its intrinsic turnover rate (blue line, middle). The asRNA facilitates a temporal delay of gene expression and a faster expression cutoff due to codegradation with its target (red line, middle). If a stimulus is only of a transient nature, e.g., because of short-term environmental changes or noise in upstream regulatory loops, it is filtered by the function of the asRNA (right). A.U., arbitrary units. (The two plots are adapted from reference with permission of Elsevier.)

Fig. 7.

Dynamic effects of asRNAs on the regulation of gene expression. (A) The speed of a regulatory response to environmental stress depends on the level at which control is exerted. The plot illustrates an example where the regulators have to be newly synthesized upon stress. (Adapted from reference with permission of Macmillan Publishers Ltd. Copyright 2007.) In the time window soon after the onset of the downregulation, posttranscriptional regulation by RNAs is the fastest (gray region). (B) Schematic visualization of an asRNA-regulated, uncoordinated expression of genes within an operon, thereby tuning the amounts of gene products made from the different genes. Thus far, this mechanism has been described only qualitatively (66, 89, 97).

Fig. 8.

Predicted effects of asRNAs on the level of biological noise in gene expression. The noise properties of transcription factor (TF)- and asRNA (RNA)-based regulation depend on the relative output protein level. For a low protein output (repressed regime), the noise of RNA-based posttranscriptional regulation is lower (gray region). For an intermediate-to-high protein output, the noise of transcriptional regulation is clearly lower. (Adapted from reference with permission of Macmillan Publishers Ltd., copyright 2008.)