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RNA Infrastructure and Networks edited by Lesley J. Collins.
©2011 Landes Bioscience and Springer Science+Business Media.
Read this chapter in the Madame Curie Bioscience Database here.

As with eukaryotes, prokaryotes employ a variety of mechanisms to allow the various types of RNA to interact and perform complex functions as a network. This chapter will detail prokaryotic molecular systems, such as riboswitches and CRISPRs, to show how they perform unique functions within the cell. These systems can interact with each other to gain a higher level of control and here we highlight some examples of such interactions including the cleavage of certain riboswitches by RNaseP, and endoribonuclease cleavage of pre-crRNAs in the CRISPR system. Thanks to such insights, we are beginning to get a glimpse of the prokaryotic RNA infrastructure, just as we have done with eukaryotes.


This chapter and the next will look at certain groups and types of RNAs within the bacterial and archaeal cell, with some examples illustrating points and principles for their modes and mechanisms of action. This chapter begins with riboswitches, sequences with untranslated regions that can control the expression of genes and operons through the binding of metabolites and other ligands. Clustered regularly interspersed short palindromic repeats (CRISPRs) are considered next. These are a class of RNA molecules that are key elements of what can be termed 'bacterial immunity'. Complex sequence recognition mechanisms allow the produced and processed RNAs to act in concert with proteins to elicit the response to invading phage. Through the analyses of these systems, and more yet to be discovered, we are beginning to get a glimpse of the prokaryotic RNA infrastructure, just as we have done with the eukaryotic RNA infrastructure described in other chapters in this book.


Riboswitches are RNA elements found in the untranslated regions (UTRs) of bacterial genes, and function to control the expression of those genes by sensing metabolite and other small molecule concentrations within the cell. The mechanism can be regarded as an adaptation of protein biosynthesis to detectable environmental conditions.1 This regulation works by a mutually exclusive conformational change in the secondary structure of the RNA molecule on the binding of a small ligand, of which there is a broad range, for example amino acids, vitamin cofactors, metal ions, purine nucleobases and second messenger molecules (for a review see ref. 2 and references therein). Notable examples of such ligands will be discussed later in this section. There are at least 20 classes of riboswitches that have been identified where the ligand is known,2 but there are also classes that can be regarded as "orphan", as their ligands are as yet undetected. Riboswitches can be regarded as a regulatory mechanism for gene expression, and are involved in bacterial RNA networks.

Riboswitches are now seen as a major prokaryotic gene regulation mechanism, for example they control ~4% of the genes in Bacillus subtilis.3 They are found in the 5′-UTRs of bacteria, and recently have also been found in the 3′-UTRs of some bacterial genes.4 Riboswitches have also been seen in the 3′-UTRs of eukaryotic genes, for example the thiamine pyrophosphate (TPP) riboswitch in the THIC gene in plants.5 A new riboswitch called crcB has been reported in archaea, making it only the second example of a riboswitch found across two domains of life,4 the other example being the TPP riboswitch mentioned above. There is also evidence of riboswitches being found in fungi and algae, for example the three TPP riboswitches in the fungus Neurospora crassa.6 Studies on the NMT1 gene which is a gene involved in TPP metabolism, and known to be repressed by excess thiamine, showed that thiamine caused alternative splicing of this gene. The decrease in expression of the main open reading frame (ORF) and concomitant increase in alternative transcripts are the direct result of thiamine addition to the cells.6

Structurally, riboswitches have two regions, an aptamer domain containing the ligand receptor that can have very complex 3D structures, and an expression platform whose secondary structure regulates the response.7 The aptamer domain is transcribed first, allowing immediate sensing of the cellular environment.2 Most riboswitches exist in two different conformations. In a ligand-bound state adjacent UTR sequence is sequestered into a tightly folded domain. Without the ligand this same portion is involved in transcriptional or translational control, by the use of an intrinsic terminator stem, and changing the availability of the Shine-Dalgarno (SD) sequence respectively. Therefore these regions can be regarded as different structural states of an RNA segment,7 rather than regions. An example of the TPP riboswitch under the conditions of ligand presence and absence is shown in Figure 1. There is a much greater flexibility in the structure of the aptamer than the expression platform, due to the wide variety of ligands for the former, and the structural constraints that nucleic acids provide to the latter.

Figure 1.. An example of a riboswitch in Bacillus subtilis subsp.

Figure 1.

An example of a riboswitch in Bacillus subtilis subsp. subtilis str. 168 (GenBank accession AL009126). The TPP riboswitch structure was retrieved from the RFAM family RF0059 (TPP riboswitch) and drawn with the Java® applet VARNA. A) Riboswitch (more...)

There are some very well characterised riboswitches that will be mentioned briefly. Cobalamin (co-enzyme, B12 ) has been known to repress expression of the cob operon in a variety of bacteria at the level of translation for nearly two decades.8 This operon encodes nearly all 25 genes required for cobalamin de novo synthesis. The cob 5′ UTR is 462 nucleotides (nt) long, and highly structured, containing elements including a ribosomal binding site (RBS).8 It has been shown that in the absence of cobalamin, a long range interaction of RNA element ~200 bp upstream of the initiating AUG suppresses the formation of a short local RNA hairpin that normally sequesters the cob RBS to inhibit the translation of cob mRNA.8 Interestingly, btuB mRNA, needed for extracellular cobalamin import, is controlled by a similar riboswitch mechanism,9 indicating that the control of cellular function goes beyond the level of the operon, and into the RNA network proper.

The co-enzyme S-adenosylmethionine (SAM) is an important cellular metabolite and is also a riboswitch ligand, being found initially in gram-positive bacteria, and consequently controlling the expression of 26 genes involved in sulphur metabolism.10 A high level of discrimination for SAM and its analogues has been shown for the SAM-I riboswitch, with even the change of methyl group accounting for an affinity change of 100-fold. A second structure for a riboswitch binding SAM (SAM-II) has also been found, for example in the metA gene 5′UTR in Agrobacterium tumefaciens.11 Despite a far simpler structure, SAM-I and SAM-II show similar levels of discrimination for SAM and related compounds, albeit with the latter having a lower affiity.11 The SAM-I structure has been solved, and it shows that nearly all functional groups in SAM are recognized by the riboswitch.12

Whilst nearly all riboswitches function through the binding of metabolites or ligands, some do not. Examples include noncoding RNA elements, Mg2+ concentration and temperature. Other riboswitches are also known to act as ribozymes, RNA molecules that are catalysts in RNA cleavage reactions. An example of this, the glmS riboswitch, will be discussed in the next chapter highlighting the way various systems within bacteria work together as a network. Considering tRNAs, T-box riboswitches modulate the expression of amino acid metabolic genes in gram-positive bacteria, and use uncharged tRNAs as their signature molecule.13 They show the classic two conformations depending on ligand binding, with the correct pairing of an uncharged tRNA with the leader sequences promoting the antiterminator structure, and allowing subsequent downstream gene expression.13

The pathogen Salmonella enterica has a variety of genes to control intracellular cation concentrations. The Mg2+ transporter mtgA has been shown to have a riboswitch in its 5′-UTR providing a mechanism for control.14 At high Mg2+ concentrations, the conformation acts as a transcriptional terminator.14 Mg2+ is required for RNA folding, as well as other cellular functions, so its discovery as a determinant in an RNA switch mechanism was important in expanding the variety of ligands riboswitches could use. It has also been shown that a single base mutation in the mtgA riboswitch, in a region not thought to be important in regulation, causes a high level constitutive expression of mgtA.15 The surprising consequence of this expression was an enhanced thermotolerance.15

The agsA gene in Salmonella has been shown to be an 'RNA thermometer'.16 In this case, the conformational changes in this very simple riboswitch are induced by temperature. A small heat shock protein, induced at high temperatures, is encoded by agsA, and a stable hairpin within the 5′-UTR blocks the SD sequence at normal temperatures (e.g., 30°C), but at higher temperatures (e.g., 45°C), the hairpin is open, and a translation initiation complex forms.16

Most riboswitches exist on their own, but occasionally tandem arrays are found, allowing a higher degree of regulation. The simplest arrangement is a tandem array of the same riboswitch, as can be seen in the glycine riboswitch that controls the gcvT operon that in turn codes for proteins in the glycine cleavage system. Analysis of this riboswitch in B. subtilis showed that the two riboswitch copies (two aptamers and one expression platform) are functionally linked to each other,17 each being able to bind a single molecule of glycine. This arrangement allows for a greater response to ligand concentration changes, as there was co-operative ligand binding observed i.e., the binding of a glycine to one aptamer influenced the binding of another glycine to the other aptamer.17

However, more complex arrangements in tandem riboswitches have also been detected, where expressions can be affected by different metabolites, as is the case for the 5′-UTR of the Bacillus clausii metE gene that contains riboswitches for both SAM and vitamin B12 (also known as adenosylcobalamin, AdoCbl).18 metE and metH both catalyse the formation of methionine from homocysteine, whilst metH requires an AdoCbl derivative for its function. Hence this architecture allows the two ligands to independently repress the metE gene, and for two metabolites to control protein production.18 So in effect, this tandem arrangement allows complex genetic decisions to be made by the RNA without the need for proteins.

It should also be noted that as well as acting in tandem, riboswitches can also interact with other parts of the bacterial RNA network, for example their cleavage by RNase P is described in more detail in the next chapter. It is thus likely that more combinations of riboswitches will be found in the future as more bacterial genomes are sequenced, and computational methodologies to find them improve. As network and systems biology approaches also mature, the interactions between what are now considered to be discrete RNA systems will increase to show that the control of bacterial cellular function is subject to control by a variety of synergistic mechanisms.


Clustered regularly interspersed short palindromic repeats (CRISPRs) are a feature of the bacterial and archaeal genome that were first noticed as genomic repeats nearly a decade ago.19 As a genetic entity, CRISPRs have a longer history, having first been reported in the Escherichia coli genome two decades earlier as part of the 3′ flanking region of the iap gene.20 The locus was shown to have a number of repeats, with nonrepeating sequences (spacers) between them. CRISPRs have had a wide variety of pseudonyms during their short life, but now CRISPR is the acronym by which these features are most commonly known. With the advent of computational searching of bacterial and archaeal genomes, it has become possible to perform large scale analyses to see how many bacteria and archaea have CRISPRs present.21 Current estimates, depending on the software used, put the level at ~45% for bacteria and ~90% for archaea. This frequency discrepancy has been suggested to be due to the sequencing of cultured bacterial strains that may have lost CRISPR arrays from a lack of exposure to phage.22 Software for CRISPR detection is briefly discussed later. It should also be noted however that CRISPRs are absent from both viruses and eukaryotes.

CRISPRs have been thought to be involved in replicon partitioning,23 or to be mobile elements,19 or to be involved in DNA repair.24 However, it was shown independently by three groups in 2005 that the spacer sequences contained plasmid or phage derived DNA.25-27 It was thus proposed that CRISPRs were involved in bacterial immunity against infection, primarily from phage.27 Two years later, the immunity hypothesis was shown to be correct with the addition of new spacers to phage-challenged bacteria, and the resistance to phage upon exposure.28-30 Our understanding of the molecular mechanism behind CRISPR action in still in its infancy. Broadly, there are two stages to the process, as shown in Figure 2. First, there is adaptation or immunization, which is the incorporation of sequences (proto-spacers) from the invading organism into the CRISPR locus through the action of the Cas protein complex. The second stage is interference or immunity, which is the activation of the Cas complex to destroy incoming DNA, and protect the bacteria in the process.

Figure 2.. Description of the CRISPR system.

Figure 2.

Description of the CRISPR system. A) A schematic CRISPR system is shown with cas genes indicated. The direct repeats (DRs) are in black diamonds, and the spacers are in boxes. The Leader sequence (L) is also shown, as is the often mutated terminal DR (more...)

In structure, a typical CRISPR locus displays four key characteristics; CRISPR-associated genes (Cas), an AT-rich leader sequence, and then the array of direct repeats (DRs), and intervening spacer sequences. The CRISPR locus which contains only the spacers and DRs, and thus no ORF, is transcribed from inside the leader sequence.31,32 Approximately half of genomes with CRISPRs have more than one locus,33 and they can thus comprise up to 1% of the genome. Observations of sequences within CRISPRs indicate that there is a fair degree of horizontal gene transfer involving the CRISPR loci.33-35 It has been observed that in a given CRISPR array, the DRs are nearly identical in size and sequence.19 DRs can vary between 24 and 47 bp, and they can be grouped into 12 major groups.36 A large study analysed the secondary structure of the DRs and found them to be heterogeneous, though certain groups contained short palindromes.36 The finding of G:U base pairs also gave a hint at the mechanism of the CRISPR system using an RNA intermediate. Clustering showed that groups with well defined secondary structures clustered together better than those with less well defined structures.36

Whilst being highly divergent, CRISPRs have been defined in 12 groups based on sequence similarity.36 It is also known that spacers will have a homologue in extrachromosomal material. To look at why such spacer sequences are integrated, Mojica et al37 have analysed the sequences around proto-spacers (so-called proto-spacer adjacent motifs; PAMs) with the aim of finding some sequence homology around them.37 This has been found, with two or three nucleotides conserved on the 3′ side of the proto-spacer, as well as a degree of conservation with whether the CRISPR-type is folded or not. For example, CRISPR types 1, 7 and 10, which are unfolded show an NGG motif in their PAM, whereas palindromic CRISPRs such as types 2, 3 and 4 have unique PAM motifs (CWT, GAA and GG respectively).37 Hence the choosing of the proto-spacer sequence for integration is not seen as being random.

The nomenclature surrounding the cas genes is complex. Initially four 'cas' genes were identified, but an extensive genomic study increased the number to six, naming the genes cas1 to cas6.34 There are eight CRISPR/Cas system subtypes defined by Haft et al34 named after the genome in which they were first discovered, a nomenclature which has now been widely adopted. There was also a group of modular genes found within the genome of bacteria/archaea having a CRISPR array, but not always close to the CRISPR locus. Each of these eight subtypes have multiple genes in their arrays,34 however nearly all have cas1 and cas2 present, making these genes universal markers for CRISPR defence mechanisms.35 The Haft et al34 analysis showed that 45 "guilds" of proteins were identifiable, and furthermore, this large gene family encode for proteins carrying different functional domains involved in DNA interaction.34 The reader is directed towards this paper (ref. 34) for a thorough discussion of CRISPR/Cas subtypes.

It has been shown that the CRISPR-Cas system prevents phage infection in Streptococcus thermophilus,28 but nothing similar could be seen in E. coli, which was considered to be a slight oddity for that, the most studied of bacteria. No well-known phage sequences were seen in E. coli CRISPRs, meaning either that the E. coli CRISPR system is nonfunctional, or E. coli have a very large number of phage, most of which are unknown. Recently, it has been shown that the histone-like nucleoid structuring protein (H-NS), a dual regulator of gene expression in Gram-negative bacteria, binds and represses CRISPR arrays, indicating resistance is conferred when H-NS silencing is circumvented.38 In E. coli hns disrupted strains, a protection to phage λ is conferred by phage matching spacers.39 It was also shown that those spacers farthest from the leader sequence, i.e., the oldest, showed no decrease in abundance compared to newer spacers, and therefore were likely to be as functional as the newer spacers.39 This is the current situation in E. coli, but whether it is universal in bacteria with very long spacers remains to be seen. The spacers tend to be unique in a given bacterial or archaeal genome, but show high homology to phage sequence or other extrachromosomal elements,25-27 and can come from either the sense or antisense strand.29 Analyses have shown that only a small fraction of the spacers match to known sequences, highlighting the vast lack of knowledge we have about the potential size of phage sequence space.40 The leader sequence can be over 500 bp long, is upstream of most CRISPR loci, and tends to be AT-rich.19 Leader sequences are conserved within species, but not necessarily between species, and play a key role in the CRISPR system as new repeat-spacer units are introduced between the leader and the previous unit.28

Because of their occurrence within a large proportion of bacterial genomes, and the increasing relative use of sequencing bacterial genomes with high-throughput sequencing methodologies, software for detecting CRISPRs is an area of active research. Software dedicated to CRISPRs has only been relatively recently developed, and are available for users either to download, e.g., PILER-CR,41 CRISPR Recognition Tool,42 to use on websites e.g., CRISPRFinder as part of CRISPRdb,43 including precomputed databases to search against,43-45 or as part of larger sequence motif detection tools.46 Different researchers have employed slightly different methodologies in their software, resulting for example in a different frequency of occurrence amongst the bacteria. Recently, it has been suggested that a combinatorial approach of using CRISPRFinder and CRISPI has its advantages to produce a thorough analysis of a given genome,47 and in so doing, partially overcomes some of these differences.

It is becoming clear that CRISPR spacers can also be from the host's genome. One immediate consequence of this was that the CRISPR system had some role in gene regulation,48 thereby adding complexity to the network. However, a review of self-targeting CRISPR spacers in bacterial genomes has shown that the explanation is more likely to be leaky incorporation of self nucleic acids leading to autoimmunity,49 i.e., the inability of an organism to distinguish between what is self and foreign, thereby resulting in a response against self. Approximately 0.4% of spacers are self-targeting, but 18% of organisms with CRISPRs have at least one self-targeting spacer, none of which were the same.49 About half of these spacers came from sequences of possible exogenous origin, but the other half did not. Moreover, these spacers were significantly likely to be the most recently incorporated spacers into the array. Incorporation would require shutting down of the host's CRISPR system, potentially by a variety of mechanisms. An alternative hypothesis for the low self-targeting fraction being due to autoimmunity is that phage could occasionally capture their host's DNA, and use it to hijack that same host's CRISPR system. There have been examples seen of CRISPR loci being found on prophages within bacterial genomes, such as in Clostridium difficile,50 thereby suggesting the acquisition of CRISPR loci by phage.

For any organism autoimmunity is something to be avoided. In the case of CRISPRs, the CRISPR genomic locus and proto-spacer in the invading phage will be the same sequence, and detectable through the crRNA (small RNAs from the CRISPR locus). Using Staphylococcus epidermis, it has been shown that the detection of mismatches 5′ to the spacer marks the foreign DNA for degradation, and is thus the discriminatory factor, sparing the bacterial chromosome from any interference in the process.51

A more specific example of host interaction concerns the interference of his-tRNA synthetase (hisS) in Pelobacter carbinolicus,52 and the role this had has in the evolution of the species. P. carbinolicus is a member of the Geobacter genus and it cannot reduce Fe(III) directly, unlike other members of the genus. It has been hypothesised that this observation is due to the fact that the evolution of P. carbinolicus has been influenced by a spacer within the bacteria that matches a proto-spacer within hisS, that has in turn resulted in the loss of ancestral genes that contain multiple histidines.52

An early prediction linked CRISPRs to RNAi35 meant that the RNA from the system was of prime interest to study. Analysis of archaeal noncoding RNAs showed homology to the CRISPR locus,32 providing the first evidence that crRNAs came from a larger CRISPR transcript. Tang et al31 went on to show that crRNAs had approximately half a DR, the spacer and another half DR. The mechanisms around this process have started to be investigated in E. coli, showing that a protein complex called Cascade (CRISPR-associated complex for antiviral defence) cleaves the long CRISPR transcript into crRNAs.53 It has been commented by many authors that while it is useful to consider the CRISPR/Cas system as being analogous to eukaryotic RNAi, it is becoming clear that there are differences in the two systems, i.e., they are not homologous.22 For example, the two systems have distinct protein machineries,35 and the CRISPR-Cas complex binds DNA, suggesting little phylogenetic relationship between the two systems.37 Also, no spacers from RNA viruses have been found, again adding weight to the CRISPR system recognising DNA.37

It is thus of great interest that recent discoveries in archaea add another dimension to this apparent duality. Archaea show morphological similarity to bacteria, but also show genetic similarity to eukaryotes. A study of a large number of archaeal genomes has shown that some species have genes involved in eukaryotic RNAi pathways, which is extremely interesting given that nearly all archaea have CRISPR systems present.54

It has already been noted that the production of crRNAs from the CRISPR locus is central to the CRISPR immunity system. Recently, an endoribonuclease called Csy4 has been found that is responsible for pre-crRNA processing in Pseudomonas aeruginosa.55 Csy4 is a member of the Ypest subtype.34 The structure shows interactions within the major group of the crRNA DR stem loop, allowing cleavage of the pre-crRNA at the downstream ssRNA-dsRNA junction.55 Mutational analysis also showed that there is a requirement for there to be a C-G pair at the base of the stem loop structure. Csy4 has two other homologues in other subtypes, again indicating that co-evolution has occurred in shaping CRISPR recognition mechanisms.55

It has been realised that CRISPRs can be used to study epidemiological and co-evolutionary dynamics in microbial communities. Indeed, CRISPRs may provide the molecular record of co-evolution of host and phage pathogens in their natural environments.56 Along with restriction modification and abortive infective systems, CRISPRs could therefore provide a record of what has happened in the recently termed "phage-host arms race", and how these have shaped microbial evolution.57 As phage-derived spacers are integrated at the CRISPR 5′ leader sequence, the order of spacers gives a temporal record of the infection history, and as such is unparalleled in host-pathogen systems.56 It might be that phage from certain environments are likely to co-exist in that environment, and so bacterial CRISPRs to those phage would be far more efficient if they were arranged in a way that kept the same phage cohort exposures together. Again, considering the microbial community of an environment, one outcome of metagenomics is that CRISPR-mediated co-evolution can be studied in noncultivable bacteria, important given how few bacteria (~1%) are currently cultivable. However, CRISPR incorporation might have a price for bacteria. For example, spacer incorporation would take longer to replicate, and result in a reduced growth rate. Finally, there might also be mutation accumulation on the spacers themselves, resulting in lower fitness for the organism that has the CRISPRs.56 However, as it is at present unknown how many CRISPRs are expressed during infection, the actual organismal cost could be hard to determine.

A recent analysis of the two CRISPR loci in 51 genomes from Escherichia and Salmonella showed one locus was specialised in plasmid-based genes.58 In addition, relatively recently diverged species had almost identical CRISPRs, suggesting contrary to recent studies that the use of the CRISPR locus as an epidemiological tool may be of limited value, as its rate of evolution for an immune system is quite slow.58 It was also proposed that one of the CRISPR loci could be an anti-CRISPR, i.e., activation of this locus by native cas genes could lead to protection from any mobile elements or plasmids that might themselves harbour other cas genes. In eukaryotes we see a host-parasite war of mechanism and anti-mechanism so the discovery of such antagonism in bacteria is perhaps not so surprising. However, this recent discovery indicates that there is still much to learn about the fascinating CRISPR system, and its mode of action.


In this chapter, we have given some examples of how bacteria and archaea use RNA in various ways to provide a wealth of functions to the cell, often acting in conjunction with other RNAs, and therefore working in a true network of RNAs. These functions are diverse, and show just how diverse a molecule of RNA can be. We have described in some detail riboswitches and CRISPRs. The expression of gene control amenable through riboswitch action is immense; complete multi-gene operons can be controlled by the sensing of certain metabolites. CRISPRs have been shown to be a very powerful method for bacteria to combat the continual onslaught of bacteriophages that are present in the environment. The mode of action is not completely understood, but what we know shows a remarkable system relying on reasonably short sequence to elicit a major response.

As both the sequencing of bacterial genomes becomes a more routine activity, out of the purview of large sequencing centres, and computer algorithms continue to improve, the ability to find other regulatory or important RNA motifs outside of bacterial genes continues apace. It is thus a very exciting time for bacterial genomics, and no doubt, more players in the bacterial RNA infrastructure will be revealed in the not-too-distant future, providing even greater insight into how sophisticated bacteria really are.


LJC would like to thank Prof. David Penny for continued support, financial and intellectual and stimulating discussions around this topic. PJB would like to thank Prof. Peter Lockhart for his support, and is part funded by the Royal Society of New Zealand Marsden Fund (08-MAU-099).


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