Next Article in Journal
Consumption of N2O by Flavobacterium azooxidireducens sp. nov. Isolated from Decomposing Leaf Litter of Phragmites australis (Cav.)
Previous Article in Journal
A Methylotrophic Bacterium Growing with the Antidiabetic Drug Metformin as Its Sole Carbon, Nitrogen and Energy Source
Previous Article in Special Issue
The nsp15 Nuclease as a Good Target to Combat SARS-CoV-2: Mechanism of Action and Its Inactivation with FDA-Approved Drugs
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Review

Developing New Tools to Fight Human Pathogens: A Journey through the Advances in RNA Technologies

Instituto de Tecnologia Química e Biológica António Xavier, Universidade Nova de Lisboa, Avenida da República, 2780-157 Oeiras, Portugal
*
Authors to whom correspondence should be addressed.
Microorganisms 2022, 10(11), 2303; https://doi.org/10.3390/microorganisms10112303
Submission received: 8 October 2022 / Revised: 12 November 2022 / Accepted: 15 November 2022 / Published: 21 November 2022
(This article belongs to the Special Issue Advances in RNA Biology in Pathogenic Microorganisms)

Abstract

:
A long scientific journey has led to prominent technological advances in the RNA field, and several new types of molecules have been discovered, from non-coding RNAs (ncRNAs) to riboswitches, small interfering RNAs (siRNAs) and CRISPR systems. Such findings, together with the recognition of the advantages of RNA in terms of its functional performance, have attracted the attention of synthetic biologists to create potent RNA-based tools for biotechnological and medical applications. In this review, we have gathered the knowledge on the connection between RNA metabolism and pathogenesis in Gram-positive and Gram-negative bacteria. We further discuss how RNA techniques have contributed to the building of this knowledge and the development of new tools in synthetic biology for the diagnosis and treatment of diseases caused by pathogenic microorganisms. Infectious diseases are still a world-leading cause of death and morbidity, and RNA-based therapeutics have arisen as an alternative way to achieve success. There are still obstacles to overcome in its application, but much progress has been made in a fast and effective manner, paving the way for the solid establishment of RNA-based therapies in the future.

1. Introduction

A crucial characteristic of the prokaryotic world is its rapid ability to adjust to a changing environment. In the case of pathogenic organisms, it is also essential that they overcome the host immune system. This implies an extensive and prompt re-adjustment of the gene expression by complex regulatory networks, in which RNA metabolism has a crucial role. In fact, RNA is much more than a messenger as it is able to dynamically coordinate and instruct cellular functions, and it has also emerged as an important feature to be considered for the pathogenesis of microorganisms.
Bacterial infections are associated with a high rate of human morbidity and mortality, and bacterial resistance to antibiotics is an escalating problem worldwide. The widespread use of conventional antibiotics has favored the apperance of drug-resistant pathogens, and there is a growing need for the development of novel antibacterial strategies. The idea of directly targeting RNA is emerging as a new frontier in drug discovery studies, with the ultimate goal of expanding the antibiotic arsenal. The differences between the molecular machinery that governs bacterial and eukaryotic RNA metabolism are fundamental to identify in order to take advantage of this attractive drug target.
The stability of messenger RNA relies on several features and involves numerous players, with ribonucleases (RNases) being among the most important ones. These enzymes are ubiquitous and can perform the RNA degradation alone or in multiprotein complexes. The diversity of RNA molecules with regulatory roles is better understood now, including a wide range of small non-coding RNAs (ncRNAs) and the natural RNA interference (RNAi), CRISPR/Cas (Clustered Regularly Interspaced Short Palindromic Repeats/CRISPR-associated protein) and ERASE (Endogenous Reverse Transcriptase/RNase H-mediated Antiviral System) systems. The ERASE system [1] is a DNA-mediated RNA cleavage mechanism that is parallel to the RNA-guided DNA cleavage of the CRISPR/Cas system and the RNA-guided RNA cleavage of the RNAi pathway. The prospect of using this system to fight pathogenic infections has not yet been explored. All of the other RNA molecules and their therapeutics applications are further explained in the scope of this review.
Altogether, recent advances in RNA studies at a global scale have given us a vast amount of information about the role of the RNA regulation of pathogens. In this context, synthetic biology (SynBio) is emerging as a field that is focused on engineering biomolecular systems for a variety of applications. SynBio devices contribute not only to improve our understanding of the disease mechanisms, but also provide novel diagnostic tools. The developments in this field have created strategies for pathogen characterization, cancer treatment, vaccine development, microbiome engineering, cell therapy, regenerative medicine and the production of new and more affordable drugs. Additionally, the targeting of regulatory RNA-based interactions has broadened the SynBio applications in antimicrobial therapeutics. The inherent modularity and compatibility of RNA-based control components enables them to be independently optimized or exchanged, thus expanding their applications.
In this review, we discuss the connections between RNA metabolism and pathogenesis, uncovering how several techniques have helped to increase the knowledge in the field. Moreover, we cover some of the innovative SynBio systems in the area of the diagnosis and treatment of infectious diseases and the latest research on the usage of antisense antimicrobial therapeutics and CRISPR–Cas as a tool. Lastly, the present applications and the future prospects of mRNA vaccines are also examined. Overall, our main aim is to explore the emerging technologies in the RNA field and their application to current health problems.

2. Ribonucleases (RNases)

Ribonucleases (RNases) are the enzymes that determine the levels of functional RNAs in the cell, validate the quality control of all of the transcripts and allow the recycling of cellular ribonucleotides, which makes them key members of the RNA metabolism machinery [2]. Their diversity, structures, targets, and modes of action can vary significantly, providing multiple solutions for a similar outcome. These enzymes can be divided into endoribonucleases, which cleave the RNA molecules internally, and exoribonucleases, which degrade the RNA from one of its extremities [2,3]. Some of the existing RNases in the cell are essential enzymes, while others have overlapping functions. However, all of them operate according to the requirements of growth in adaptation to a specific environment, and they carry out surveillance. With this involvement in post-transcriptional mechanisms, ribonucleases have been associated with essential bacterial and viral processes (reviewed in [4,5,6]).
Tobe and colleagues showed that the product that was encoded by the gene vacB was required for the expression of several invasion factors in Shigella flexneri, and its deletion affected the bacterial capacity to adhere and spread inside host cells [7] (Figure 1). Later, this vacB gene was demonstrated to code for the exoribonuclease RNase R, and it was renamed rnr [8]. Other works have been published throughout the years, unravelling the impact of RNase R [9,10] and other ribonucleases in the different steps of the bacterial infection process (e.g., the exoribonucleases PNPase [11,12], and RNase AS [13] and the endoribonucleases RNase E [14], RNase III [14], YbeY [15], RNase J [16] and RNase Y [17]). These studies were performed in a plethora of bacterial species, including 10 of the 12 bacterial families that are considered to be ‘priority pathogens’ which pose the greatest threat to human health, according to the World Health Organization (WHO) [18].
RNases are found in all domains of life, and also in viruses. Viruses do not have their own metabolism, so many of them use host proteins during their life cycle, and they rarely code for RNases. When they are present, viral RNases are usually involved in specific steps of viral gene expression, genome replication, shutoff of host cell protein synthesis and host immune evasion, among others [19,20,21,22,23]. An example of viruses that code for RNases is coronaviruses. With the appearance of the coronavirus disease 2019 (COVID-19) pandemic, caused by SARS-CoV-2, viral ribonucleases have gained interest in the scientific community. Coronaviruses are RNA viruses that have in their replication machinery two crucial ribonucleases, nsp14 and nsp15, which are among the strongest interferon antagonists of SARS-CoV-2 [24,25,26] (Figure 2A). Nsp14 is a peculiar enzyme that harbors two distinct enzymatic activities, acting both as an exoribonuclease (ExoN) and as an N7-methyltransferase [27]. SARS-CoV-2 nsp14 ExoN knockout mutants are not viable [28,29]. The ExoN activity is responsible for the proofreading capacity of the viral genome during replication, a feature that has not been previously reported in any other RNA virus [28,30], and this activity is stimulated through the interaction with nsp10 [27]. Nsp15 is a conserved endoribonuclease specific of Nidovirales viruses, which plays fundamental roles in coronavirus pathogenesis and in the evasion of the host’s innate immune system [24,31,32].
Figure 1. Landmarks on RNA technologies. An overview of the most relevant achievements and pioneer experiments around the RNA molecule. The timeline is color-coded for each field (green for synthetic biology; orange for siRNAs; purple for ncRNAs; turquoise for CRISPR/Cas systems; salmon for mRNA vaccines; yellow for RNA-seq technologies; blue for ribonucleases) [7,33,34,35,36,37,38,39,40,41,42,43].
Figure 1. Landmarks on RNA technologies. An overview of the most relevant achievements and pioneer experiments around the RNA molecule. The timeline is color-coded for each field (green for synthetic biology; orange for siRNAs; purple for ncRNAs; turquoise for CRISPR/Cas systems; salmon for mRNA vaccines; yellow for RNA-seq technologies; blue for ribonucleases) [7,33,34,35,36,37,38,39,40,41,42,43].
Microorganisms 10 02303 g001
Taken together, these ribonucleases, which play so many critical roles in both bacterial and viral processes, are very attractive targets for drug designs. The use of small molecules to inhibit the enzymatic activity of these proteins was already reported in Staphylococcus aureus, Escherichia coli, Mycobacterium tuberculosis, and SARS-CoV-2. In 2011, Olson et al. discovered a small molecule inhibitor of the protein component of the S. aureus ribonuclease P, and this inhibitor exhibited antimicrobial activity even against predominant antibiotic-resistant lineages [44]. A few years later, Kenneth McDowall and his team described a method of selecting small molecule inhibitors against RNase E, an essential E. coli endoribonuclease. These inhibitors were also demonstrated to be effective against the endoribonuclease RNase G in vitro (a protein that is homologous to the catalytic domain of RNase E). Additionally, they were shown to bind and inhibit the catalysis of an M. tuberculosis homologue, thus demonstrating a wider application of these inhibitors [45].
Recently, several in silico studies have proposed drug candidates that could inhibit SARS-CoV-2 ribonucleases (Figure 2A). From these, only a minor fraction was tested in vitro regarding their ability to affect the ribonucleolytic activity, and as a consequence, viral replication. For instance, the mycotoxin patulin was described as a specific inhibitor of the SARS-CoV-2 nsp14 ExoN activity, but it only decreased cell viability in vitro when it was used in high concentrations [46]. Disulfiram/Ebselen leads to the inhibition of the ExoN activity of nsp14, and in combination with Remdesivir, it can synergistically inhibit SARS-CoV-2 replication in Vero E6 cells [47]. Tipiracil, which is currently being used in cancer treatment, was shown to inhibit the endonuclease activity of nsp15 in vitro, but an improvement of the compound affinity is needed for it to serve as an antiviral drug in vivo [48]. Dutasteride, Meprednisone and Tasosartan were also able to inhibit nsp15 activity in vitro [49]. A clinical trial using Dutasteride has already shown its beneficial effect in the treatment of COVID-19 [50].

3. Small Non-Coding RNAs (ncRNAs or sRNAs)

Small non-coding RNAs are ubiquitous in bacterial species, and they are essential for their adaptation and survival under stress [51]. These transcripts are generally short, being about 50 to 500 nucleotides in length, usually highly structured, and they have the capacity to alter gene expression affecting translation and/or RNA degradation [52].
The first ncRNA to be characterized was MicF (Figure 1) as a regulator of the outer membrane protein OmpF [34]. Since then, with the development and help of several techniques (which are described below), a plethora of new ncRNAs has been identified in several bacteria, mainly in E. coli and Salmonella enterica [53].
Broadly, ncRNAs can be divided into two major classes: (i) cis-acting ncRNAs that are transcribed from the opposing strand of their target mRNAs, with whom they present a perfect complementarity; (ii) trans-acting ncRNAs, which are encoded in a distinct location from their targets, thus they are only partially complementary with them, allowing the recognition of multiple targets by a single ncRNA [54]. In Gram-negative bacteria, the trans-acting ncRNAs often require the aid of a RNA chaperone, such as Hfq and/or ProQ, which act as matchmakers to promote attachment to the targets and to stabilize these RNAs (see section RNA chaperones). In addition, with the discovery of the CRISPR/Cas systems, a new class of ncRNAs has been considered (see also Section The CRISPR System).
Many bacterial ncRNA have been shown to have roles in virulence, and this has been observed both in Gram-negative and -positive bacteria (extensively reviewed in [55]). It was in the early nineties that the first ncRNA was shown to be implicated in pathogenesis—S. aureus RNAIII (Figure 1). This ncRNA is involved in the regulation of the agr quorum-sensing (QS) system, a key regulatory system that is engaged not only in virulence control [37], but also in antibiotic resistance mechanisms, autolysis, and biofilm formation [56,57,58,59]. Later on, additional ncRNAs were found to be involved in S. aureus pathogenicity [60].
Figure 2. (A) Targeting fundamental viral proteins to inhibit SARS-CoV-2. The use of nsp14 and nsp15 ribonucleases as druggable targets may impair SARS-CoV-2 viral replication cycle, and therefore, it can be a good way to tackle infection. (B) Synthetic sRNA expression system. Vector containing the E. coli MicC scaffold, in which a customized seed sequence complementary to the endogenous target transcript is inserted [61]. (C) RNase E mediated thermoregulation. When temperature is low, the RNase E cleavage site (RC) is hybridized with the anti-RNase cleavage site (ARC) forming a hairpin, thus blocking the cleavage by RNase E and allowing gene expression to occur. When temperature increases, the RC is exposed, the mRNA is cleaved by RNase E, and the expression of the gene is impaired (RBS stands for ribosomal binding site and AUG for the initiation codon). This is adapted from [62]. (D) Regulation of the FMN riboswitch by Ribocil. FMN riboswitch in the absence of any compound; it presents a conformation that allows gene expression to occur. Upon binding to the riboswitch, Ribocil induces a rearrangement of its structure that sequesters the RBS, thus preventing translation; this is adapted from [63]. Figure created using BioRender.com (accessed on 11 November 2022).
Figure 2. (A) Targeting fundamental viral proteins to inhibit SARS-CoV-2. The use of nsp14 and nsp15 ribonucleases as druggable targets may impair SARS-CoV-2 viral replication cycle, and therefore, it can be a good way to tackle infection. (B) Synthetic sRNA expression system. Vector containing the E. coli MicC scaffold, in which a customized seed sequence complementary to the endogenous target transcript is inserted [61]. (C) RNase E mediated thermoregulation. When temperature is low, the RNase E cleavage site (RC) is hybridized with the anti-RNase cleavage site (ARC) forming a hairpin, thus blocking the cleavage by RNase E and allowing gene expression to occur. When temperature increases, the RC is exposed, the mRNA is cleaved by RNase E, and the expression of the gene is impaired (RBS stands for ribosomal binding site and AUG for the initiation codon). This is adapted from [62]. (D) Regulation of the FMN riboswitch by Ribocil. FMN riboswitch in the absence of any compound; it presents a conformation that allows gene expression to occur. Upon binding to the riboswitch, Ribocil induces a rearrangement of its structure that sequesters the RBS, thus preventing translation; this is adapted from [63]. Figure created using BioRender.com (accessed on 11 November 2022).
Microorganisms 10 02303 g002
Salmonella has been extensively used as model organism to study ncRNAs. Several ncRNA genes are encoded by the pathogenicity islands of a Salmonella virulent strain, with IsrJ playing a crucial role during the infection process [64]. Another example is the remarkably long cis-acting ncRNA, AmgR, which has been shown to affect Salmonella virulence [65]. In this foodborne bacterium, the OmpD is the most abundant porin, and therefore, its levels need to be tightly regulated to prevent cell lysis [66]. ompD mRNA was demonstrated to be regulated by the ncRNAs InvR, MicC, RybB and SdsR [67,68,69,70]. Interestingly, mutations on ncRNA genes that negatively regulate conserved outer membrane proteins (OMPs) in Salmonella, in combination with a mutation on a transcription regulator, allowed the rationale design of an attenuated vaccine for pigs [71]. Vaccination against Salmonella could improve animal health and reduce antibiotic usage, ultimately increasing food safety.
In the foodborne pathogen Listeria monocytogenes, several ncRNAs have been identified. Some of them are exclusively expressed inside macrophages or in human blood, suggesting an important role of these transcripts for intracellular growth [72,73,74,75]. Interestingly, it was described that two riboswitches (see section RNA riboswitches) could also act as conventional ncRNAs by interacting with the 5′ UTR of the prfA mRNA which encodes a master regulator for Listeria virulence [76].
In Shigella, it was demonstrated that RyhB and RnaG ncRNAs influence pathogenesis [77,78,79]. The Ssr54 ncRNA is important for the tolerance and virulence of Shigella under hyperosmotic pressure [80], and RyfA1, which is under the control of the ncRNA RyfB1 [81], impacts the levels of ompC mRNA that encode an OMP that is related with Shigella virulence.
In Streptococcus pneumoniae, a significant percentage from the identified ncRNAs has important roles in virulence traits [82]. srn157 and F32 were shown to be important for the adhesion/invasion of endothelial or nasopharyngeal cells [83,84], five redundant csRNAs (cis-dependent small RNAs) together with the ncRNA srn206 act to modulate competence [85], and srn135 was demonstrated to be involved in pilus regulation [86].
Native RNA-based interactions of ncRNAs with proteins, RNA transcripts and/or DNA are essential for coordinating gene expression. These interactions, due to their advantages when compared to conventional gene knockouts, are being increasingly targeted in synthetic biology, and in the antimicrobial and therapeutic fields. Engineering strategies involving trans-regulatory ncRNAs fall into two general approaches: (a) altering the expression of well-characterized natural ncRNAs to induce enhanced regulatory effects on protein levels, and (b) designing synthetic ncRNAs to knockdown the expression of individual proteins. The use of these synthetic ncRNAs as a gene-silencing tool mimics the RNA interference system (from eukaryotes) in bacteria. ncRNAs show high modularity, which enables synthetic biologists to decompose and recombine the ncRNA parts to engineer artificial riboregulators with different functions. The basic modular design includes a promoter, an antisense binding domain to target mRNA, a scaffold for stability and/or Hfq binding and a terminator. For instance, a MicC-based synthetic ncRNA was successfully used to fine-tune the gene expression in E. coli [87]. The plasmid-based synthetic ncRNA was easily transferred to other strain backgrounds. A similar construction with “tailor-made synthetic sRNAs” was developed in P. putida where the binding of native Hfq to a MicC scaffold was also demonstrated. It was shown that when these synthetic sRNAs were induced, they could actively control the gene expression [61]. The versatility of this system makes it very useful for different purposes (Figure 2B).
ncRNAs offer an additional suit of tools for engineering metabolic pathways in bacteria with an interest in industrial production, with several examples of successful applications. Despite being a less explored area, recent works also support promising applications in medicine. As mentioned above, the OMPs of Gram-negative bacteria play a main role in mediating bacterial antibiotic resistance and in the virulence of innumerous bacteria. Multiple natural ncRNAs have been found to control OMP expression [51]. Therefore, the use of synthetic sRNAs has been explored as a way to modulate OMP expression and modulate bacterial virulence [88]. There are also examples of synthetic ncRNAs that have been designed to control the virulence of pathogenic bacteria through the modulation of its cellular motility [88], antibiotic sensitivity [89,90] or to downregulate the expression of essential proteins that regulate mRNA turnover [91].

3.1. The Csr System

There are also ncRNAs that bind to proteins to alter their activity, but fewer examples are known in comparison to the antisense ncRNAs. The Csr (carbon storage regulator) system is very important for central metabolism (reviewed in [92]). It is composed of the CsrA (or RsmA) protein, an RNA-binding protein that modulates the expression of several mRNA molecules, and the ncRNAs CsrB and CsrC (or RsmY and RsmZ) that sequester the CsrA protein, thereby inhibiting its activity. A fourth component of this system is the CsrD protein that marks CsrB and CsrC ncRNAs to be degraded by RNase E [93,94,95,96].
In Salmonella, the deletion of csrA caused serious growth deficiencies and defects on invasion [97]. The deletion of both CsrB and CsrC significantly reduced the Salmonella Pathogenicity Island 1 (SPI1) gene expression, and, as a consequence, epithelial cell invasion [98,99]. Additionally, these two ncRNAs were shown to be required for the regulation of the type I fimbrial operon, which contributes to biofilm formation [100]. In S. flexneri, it was determined that CsrA activity is linked to virulence and to the cell membrane structure [101]. In Legionella pneumophila, it was demonstrated that the CsrA protein is crucial for replication inside the macrophages [102], affects the flagellar expression [102,103] and impacts the levels of important regulators of virulence-associated traits [104]. The other two components of the Csr system in Legionella, RsmY and RsmZ, were shown to be expressed depending on the growth phase, and the absence of both ncRNAs impaired the infection and interfered with the replication inside the host [105]. In Vibrio cholerae and in Pseudomonas aeruginosa, the Csr system is important for quorum-sensing regulation [106,107], and, in the plant pathogen Erwinia carotovora ssp. carotovora, it controls the production of extracellular enzymes and secondary metabolites [108].

3.2. RNA Chaperones

RNA chaperones facilitate the proper RNA folding, remodel the RNA structures to expose important regulatory elements, and, in several cases, they can protect the RNA molecules from degradation by ribonucleases. The two RNA chaperones that have been well described until now are Hfq and ProQ. For more information about their mechanism of action and their structural aspects, please see [109].
Hfq is a highly conserved protein from the Sm family, and it has homologues in approximately 50% of all of the sequenced bacteria [110]. This pleiotropic regulator was first described as an essential host factor of the RNA bacteriophage Qβ [111], but several studies have recognized its role in RNA metabolism and in bacterial pathogenesis.
In Salmonella, it was demonstrated that Hfq is important for virulence, considering its role in the motility, membrane composition, invasion, and expression of genes from the SPI1 [112]. In L. pneumophila, Hfq plays a role in the iron uptake and storage system, and mutants lacking this chaperone showed defects during growth and in pigmentation, being slightly less efficient in infecting amoeba and macrophages [113]. In the foodborne pathogen L. monocytogenes, Hfq was proven to be important for the tolerance to osmotic and ethanol stresses, for the long-term survival during amino acid starvation and in the pathogenicity in mice [114]. Similar observations were reported in other common pathogens, namely in V. cholera [115], P. aeruginosa [116], Neisseria gonorrhoeae [117] and Francisella tularensis [118], thereby implicating the Hfq protein in highly relevant pathogen-related mechanisms.
ProQ is a FinO-like protein that is specific to Gram-negative microorganisms. This protein was initially described as a factor that affects the activation of the osmoregulatory transporter ProP, and it has only recently been shown to be an important RNA chaperone that is involved in the regulation of ncRNAs [119]. Contrary to Hfq, ProQ interacts with many cis-acting ncRNAs, which means that they regulate a different series of genes [120]. The involvement of this protein in bacterial virulence has not been fully explored. However, it has already been seen that in Salmonella, the absence of ProQ causes a decrease in the expression of genes that are involved in the motility and chemotaxis pathways, leading to an impaired ability to infect HeLa cells [121]. In L. pneumophilia, two ProQ homologues were described (Lpp1663 and Lpp0148/RocC), and RocC was shown to be involved in natural competence [122]. Furthermore, in the plant pathogens Dickeya dadantii [123] and Erwinia amylovora [124], the loss of ProQ affected different processes, causing a decrease in the virulence rate. Although only a few pieces of evidence have linked ProQ with pathogenesis, we believe that this number will increase in the near future.

4. Regulatory 5′ Untranslated Region (UTR) Elements

Two classes of regulatory elements located at the 5′ UTR of mRNAs have been shown to play important roles in gene expression: RNA thermometers and RNA riboswitches. These RNA elements allow the bacteria to rapidly and efficiently react to environmental stimuli. Taking into consideration the mode of action and simplicity of these regulators, these RNA elements are very appealing for the development of new tools to regulate gene expression, and they can be used for many applications.

4.1. RNA Thermometers

RNA thermometers or thermosensors are molecules that sense temperature shifts, inducing a conformational change of the RNA molecule that will affect the expression of the downstream gene. Regulation by temperature using RNA molecules allows for a more rapid and cost-effective response of the cell. RNA thermometers act by regulating translational initiation: for instance, at lower temperatures, the Shine-Dalgarno (SD) region and/or the initiation codon are masked by a stable secondary structure; when the temperature increases, this region is melted, thus allowing translation to occur. For more information about the mechanism of action of these molecules, please read [125].
Due to their nature, RNA thermometers are not conserved, and this is a challenge for bioinformatic prediction [126]. The first RNA thermometer was discovered more than thirthy years ago, and it controls the development of phage λ by regulating the cIII protein [127]. Contrary to what was described for all of the other RNA thermometers that were later discovered, it allows translation to occur when the temperature decreases [127].
A temperature shift is one of the challenges that a pathogen faces during the infection process. As such, natural RNA thermometers are crucial regulatory elements that are involved in bacterial pathogenesis by controlling the expression of virulence genes. This is the case of the agsA gene in Salmonella, the prfA gene in Listeria, the lcrF and ompA genes in Yersinia, the cssA gene in Neisseria, the toxT gene in Vibrio, and the ompA and shuA genes in Shigella [128,129,130,131,132,133,134,135].
In recent years, a number of synthetic RNA thermometers was developed with success in diverse applications. Contrary to the natural molecules, they were designed to be simpler and more predictable to facilitate their usage [136]. Despite the fact that most of the synthetic RNA thermometers are heat inducible, recently we also assisted to the development of heat-repressible RNA thermometers that use an RNase E-mediated mechanism (Figure 2C) [62].
An interesting example of the use of these regulators in medicine is the development of RNA thermometers for microbial therapeutics in vivo. Two synthetic thermometers were designed to act between 32 °C and 46 °C, which could be used in three different in vivo scenarios to combat microbial infections: (i) the capacity to detect and respond to the host’s fever, (ii) the selective activation of the microbial function at a specific location using focused ultrasound (allowing a local delivery of the therapeutics), and (iii) the restriction of the survival of the administered microbes to the host’s body temperature and self-destruction at room temperatures, thus preventing possible environmental contaminations [137]. Considering that this study was performed with E. coli, further studies may be required to adjust this process to other pathogens.

4.2. RNA Riboswitches

Riboswitches are cis-acting RNA elements that recognize metabolites, thus modulating gene expression in response to specific small molecules. In bacteria, most of the riboswitches are located at the 5’ UTR of a particular transcript, and are composed by two functional domains: the ligand-sensing domain (or the aptamer domain) and the regulatory domain (or the expression platform). In certain conditions, a small molecule binds the aptamer domain, inducing a conformational change that stimulates the expression platform. The expression platform will act over the coding sequence, thus regulating its expression. For more information about the mechanism of action of the riboswitches, please read [138].
Riboswitches were first discovered in 2002 [139,140,141], and since then, they have been acknowledged as crucial contributors for the control of gene expression in many organisms. They can bind to a plethora of small molecules, from vitamins to sugars, amino acids or metals, and they can exert their function in different ways [142]. Additionally, in some pathogens, important genes related with virulence are controlled by riboswitches. This was demonstrated in L. monocytogenes, where the major regulator of virulence, PrfA, was shown to be controlled by two riboswitches, which also function as ncRNAs [76], and in Clostridium difficile, where it was shown that riboswitches are important for growth and infectivity [143].
The existence of riboswitches in pathogenic bacteria presents novel targets for drug development. This has led researchers to start to manipulate how riboswitches bind to their ligands in order to design new molecules that could be used as antimicrobials [144,145,146]. The high-resolution crystal structures of the riboswitches bound to their cognate ligands have helped to design potential inhibitors with improved drug-like properties [147,148,149,150,151,152,153]. From the developed compounds, Ribocil (Figure 2D), which is currently in preclinical development, was shown to inhibit the growth of different bacterial strains, including methicillin-resistant S. aureus and Enterococcus faecalis [63,154,155].
Natural riboswitches combine both the sensory and regulatory functions. This principle of direct RNA-ligand interaction was exploited to synthetically design the aptamer-based conditional gene expression systems. Aptamers are single-stranded RNA or DNA molecules that can self-fold in a unique 3D-spatial conformation to specifically interact with their targets. The selection of aptamers with the capability to bind a plethora of different ligands can be performed in vitro through the so-called Systematic Evolution of Ligands by Exponential Enrichment (SELEX) Technology [156,157,158]. Aptamers targeting pathogenic bacteria and viruses have attracted increasing attention [159]. Such aptamers can be used for the specific recognition of infectious agents or to block their functions [160,161].

5. The CRISPR System

Upon a viral or plasmid invasion, bacteria (and archaea) integrate short fragments of foreign DNA into the host chromosome, namely, at a (variable) number of short repetitive loci (approximately 20–50 base pairs) known as the CRISPR, in a stage called adaptation. These exogenous DNA fragments are inserted by the Cas proteins, Cas 1 and Cas 2, which are the only Cas proteins that are conserved amongst all the CRISPR–Cas systems. The repetitive loci are subsequently transcribed and processed into a library of short CRISPR-derived RNAs (crRNAs) that are complementary to the previous invading nucleic acids. This is the stage of crRNA expression and biogenesis. Then, comes the interference stage, in which each crRNA can guide the effector nucleases to destroy the foreign genetic material through specific cleavage [162,163]. Thus, the integration of invasive DNA constitutes a genetic record of prior encounters with the transgressors, and reflects the surrounding environmental conditions, which change over time.
The CRISPR systems can be divided into two main classes, class 1 and class 2. The class 1 system is found in 90% of the CRISPR loci in bacteria and archaea, whereas the class 2 systems only represent 10% of the CRISPR loci that are found in bacteria. The specific types within each class are defined by the effector endonuclease— the Cas protein—which is responsible for cleavage [164,165].
The Cas effector proteins are, thus, non-specific nucleases that can be programmed by small guide RNAs, the crRNAs, to be directed to target DNAs or RNAs. Great emphasis has been given to these systems due to these RNA-guided programmable enzymes which exhibit remarkable flexibility in targeting. These have encouraged an ever-expanding array of applications. The most explored and used toolbox in genomic engineering is the class 2 (type II) system, which is better known as CRISPR–Cas9. Cas9 is the characteristic effector protein, and it is essential for immune mechanisms in bacteria [166]. Furthermore, CRISPR–Cas9 are also abundant in pathogenic and commensal bacteria. Indeed, the cas9 gene has been reported to play an important role in controlling virulence in various pathogens [166,167,168]. As a virulence regulator, Cas9 is involved in specific steps of the pathogenesis of different bacterial species, as well as in common processes of virulence.
In Streptococcus sp., Cas9 was reported to influence key regulators of virulence traits, such as adhesion and infection [169,170]. The same effect was verified in the knockout strains lacking Cas9 in N. meningitidis [171]. Curiously, cas9 deletion in Campylobacter jejuni highly affects its sensitivity to antibiotics, regulating several genes that promote antimicrobial resistance [172]. This proves the connection of CRISPR with antibiotic resistance mechanisms. Interestingly, in the case of L. pneumophila, Cas2 and not Cas9 is the CRISPR enzyme that is involved in the infection process of macrophages [173]. Both the Cas9 and Cas2 proteins belong to the same CRISPR–Cas type II system. Although they maintain conserved functions regarding their role in the CRISPR bacterial immunity, they appear to have different functions in virulence, depending on the microorganism.
The interest in the relationship between CRISPR and virulence has grown, and it was later discovered that the CRISPR–Cas type I systems also have an important role in the evasion of bacteria from the host. Streptococcus mutans contains a class 1-type I CRISPR, whose effector protein is Cas3. In the absence of the cas3 gene, the strain formed less biofilm, became more sensitive to fluoride, and the expression of the virulence genes was significantly downregulated [174]. Similar observations have been reported with the S. enterica isolate 211 [175]. Additionally, in P. aeruginosa UCBPP-PA14, the cas3 gene has been shown to be involved in the achievement of lower pro-inflammatory host responses in cell and mouse models [176].
Biofilm development and antibiotic resistance are intimately connected since the biofilm matrix can delay the penetration of antimicrobial agents. Biofilm formation is a highly regulated process, and CRISPR has proven to be one of these regulators. Most pathogens involved in nosocomial infections have biofilm-forming abilities. Interestingly, an increased ability to form biofilms has been reported in CRISPR–Cas positive Enterococcus faecalis and P. aeruginosa strains [177]. Additionally, in Acinetobacter baumannii, specific genes that are involved in biofilm formation appear almost exclusively in strains that are enriched with CRISPR–Cas systems [178]. It also appears that CRISPR contributes to a tight control depending on the surrounding environment. The lysogenic infection of P. aeruginosa UCBPP-PA14 by the bacteriophage DMS3 inhibits biofilm formation and swarm motility in a manner that is dependent on the CRISPR regions and cas genes [179]. This strategy, by preventing the infected bacteria from forming biofilms and performing other group behaviors, can limit the effects of bacteriophage spread in bacterial communities.
The existence of group behaviors among the bacteria is indeed extremely important. During biofilm formation, bacteria have the ability to communicate with each other through the process of QS. In Serratia marcescens, it appears that CRISPR–Cas immunity is integrated into the QS circuit, enabling greater defense at higher cell densities [180]. Similarly, P. aeruginosa UCBPP-PA14 also uses the QS process to activate cas gene expression [181]. Thus, bacteria seem to be able to use QS communication to control CRISPR–Cas expression according to the needs of the cell.
In 2011, Charpentier and co-workers [182] reported the existence of a trans-encoded small RNA (tracrRNA) that was transcribed upstream and in the opposite strand of the CRISPR locus, with 24 nucleotides that were complementary to the repeat regions of the crRNA precursor transcripts (pre-crRNA). This tracrRNA is responsible for pre-crRNA maturation by promoting the cleavage of the tracrRNA-pre-crRNA duplex by the very well-known and widely conserved endoribonuclease RNase III [182]. Soon after this, tracrRNA was reported to trigger Cas9 to cleave the target DNA [41]. This discovery enabled the development of a breakthrough method of genome editing, which was later recognized by being awarded the Nobel Prize in Chemistry in 2020 to the scientists, Emmanuelle Charpentier and Jeniffer A. Doudna [41] (Figure 1). There is already evidence that ncRNAs related to the CRISPR systems play a role in bacterial virulence. In Francisella novicida, Cas9 uses a small CRISPR/Cas-associated RNA (scaRNA) to repress an endogenous mRNA transcript encoding a bacterial lipoprotein, which elicits a proinflammatory innate immune response in the host [168]. A CRISPR-associated ncRNA, RliB, has also been shown to play a role in L. monocytogenes pathogenesis [72]. Thus, it appears that ncRNAs constitute an extra layer in CRISPR regulation.
The knowledge of CRISPR has opened avenues to the entire scientific community for the development of genetic engineering tools, namely in the creation of new and improved versions of CRISPR systems that are revolutionizing the world today. As the pieces of the CRISPR puzzle are being discovered, more and more applications are emerging. For instance, in 2014, the use of a type I CRISPR–Cas system in E. coli enabled the successful removal of individual bacterial strains from mixed populations, which share a high homology. This highlights the extraordinary specificity of this tool, and has opened up the possibility of developing smart antibiotics that prevent multidrug resistance and differentiate between the pathogenic and beneficial bacteria [183].
These novel antibacterial strategies can be based on CRISPR–Cas systems, primarily on CRISPR–Cas3 and CRISPR–Cas9, to target DNA, which can be designed to specifically eliminate the plasmids that carry antibiotic resistance genes and chromosomal virulence genes, among others, in order to attack the pathogens (Figure 3A). The tool consists of integrating the CRISPR–Cas sequences into a plasmid vector, allowing the system to target and cut genes of interest. A system that was identified more recently by Feng Zhang’s lab, CRISPR–Cas13 (class 2), brought a new perspective to the CRISPR tool. The RNase Cas13 cleaves single-stranded RNA (ssRNA) molecules in a crRNA-guided manner [184]. CRISPR–Cas13 also exhibits the promiscuous degradation of ssRNAs when it is performing targetted RNA cleavage, thus, limiting the host cell growth by inducing dormancy in the bacteria [185]. Additionally, unlike Cas9-based antimicrobials, the CRISPR–Cas13 system exhibits strong bacterial killing activity, regardless of the target genes’ location (chromosome or plasmid) [186] (Figure 3A). This system has been successfully tested by constructing antibacterial nucleocapsids (CapsidCas13) that are capable of killing carbapenem-resistant E. coli and methicillin-resistant S. aureus through the recognition of the corresponding antimicrobial resistance genes [186].
Nevertheless, these CRISPR–Cas tools are still limited in terms of their clinical application due to their delivery systems. The use of conjugative plasmids [188], phage vectors [189,190], membrane vesicles [191] or their encapsulation into nanomaterials [192] have been explored as delivery systems.
CRISPR has also received substantial attention as a diagnostic tool due to its potential to detect nucleic acids in a quick, sensitive and specific manner [187] (example in Figure 3B). Within the current pandemic context, CRISPR diagnostic technologies were quickly adapted and optimized [193,194,195], being recently highlighted as one of the seven technologies to watch in 2022 [196] (Figure 1).
The role of CRISPR–Cas systems in modulating the genotypes, physiology and ecology of bacteria, plus the implication of CRISPR–Cas in limiting horizontal gene transfer, or in enabling the acquisition of advantageous genes are topics of great interest, as is the development of CRISPR for new applications in the area of treatment of infectious diseases. However, the application of CRISPR–Cas antimicrobials remains at a very preliminary stage and numerous obstacles await to be resolved.

6. RNA Technology

6.1. RNA Sequencing (RNA-Seq)

The development of Next Generation Sequencing (NGS), which is also referred to as deep-sequencing, or high-throughput sequencing, has provided a set of diverse modern technologies with applicability to the study of DNA, RNA and proteins [197]. In particular, RNA-seq methodologies allow for the determination of the sequence of an overwhelming amount of different RNA molecules in a massively parallel way [197,198].
Nowadays, there is a panoply of distinct RNA-seq-based approaches that aim to uncover and characterize the RNA species being expressed at each moment in a cell culture or a single cell. Many fields of study have benefited from such methodologies [199,200,201,202]. In microbiology, RNA-seq derived technologies have been useful as tools for various purposes such as the optimization of bacterial chassis for industrial biotechnology [203] and synthetic biology [61,204], and for the study of both human microbiota [205,206] and human pathogens. In this section, we will present some examples of the contribution of different RNA-seq protocols for the study of pathogenic microorganisms (reviewed in [201,202]).
In a recent study, messenger RNA sequencing (mRNA-seq) was used to elucidate the function of a specific gene which was postulated to be involved in the virulence of the zoonotic bacterial pathogen Streptococcus suis type 2 [207]. In another study, Quant-seq, a variation of mRNA-seq, which is more focused on the 3′-end sequences of polyadenylated RNAs [208], served to demonstrate that human neural progenitor cells infected by Coxsackievirus B3 change their expression patterns, upregulating antiviral innate immunity and inflammatory pathways during infection [209].
As already addressed, ncRNAs are crucial regulators. NGS, and particularly small RNA sequencing (sRNA-seq), has largely contributed for the identification of new ncRNAs species in several pathogenic microorganisms [72,74,82,210].
Moreover, RNA modifications can influence the structure, stability, decoding, and recognition of RNA molecules. They often occur during transcription (e.g., the 5′ NAD cap) or post-transcriptionally (e.g., methylation resulting in N6-methyladenosine, m6A), and they may also play a prominent role both in the bacterial stress response and pathophysiology, and in host adaptation [211,212]. Combining mass spectrometry (MS) with RNA-seq procedures allows for the precise localization of the RNA modifications and the study of their dynamics [213]. Remarkably, specific RNA-seq methodologies have been applied to bacterial pathogens to detect the RNA modifications that are crucial for cytotoxicity and virulence, such as NAD capture-seq which measures the NAD incorporation [214,215], and m6A-seq which identifies the methylated residues in the transcripts [216].
In biology, understanding the network of interactions in the cell is crucial. The RNA interaction by ligation and sequencing (RIL-seq) was designed to identify the RNA–RNA interactions, and this has been particularly useful to elucidate pairs of ncRNAs and their respective mRNA targets. In pathogenic E. coli, this technique was sufficient to determine the global interactome of RNA molecules binding to Hfq, further detecting ncRNAs that had not been previously annotated [217]. In turn, gradient profiling by sequencing (Grad-seq) was developed to analyze the native RNA–protein complexomes in the cellular environment. It combines two approaches (RNA-seq and liquid chromatography-tandem mass spectrometry (LC-MS/MS)) [119], and it can: identify major RNA–protein complexes and RNA binding proteins, cluster ncRNAs according to their biochemical properties, and complement the information regarding the function of domains of uncharacterized proteins [218]. In fact, thanks to this technology, the ProQ was discovered as an important RNA chaperone, which was a missing piece in the puzzle of ncRNA regulation [119].
One of the major breakthroughs in this field was the establishment of single-cell RNA sequencing (scRNA-seq), which allows for the discrimination between RNA species being expressed in different cells belonging to the same population or different populations in the same sample (reviewed in [219]). This technology gained special relevance in enlightening the mechanism of infectious diseases in several pathogens [220,221,222]. Currently, a promising trend in the scRNA-seq approaches is the incorporation of droplet- and microwell-based microfluidics, improving sequencing throughput in an affordable, portable and scalable way [223].
In the last decade, differential RNA-seq emerged with the advantage of distinguishing between the primary and processed transcripts. This way, it has provided an opportunity to map the transcriptional start sites (TSS), and exposed the existence of pervasive transcription and a generally high abundance of ncRNAs in the bacterial genomes [224,225,226,227].
Differential RNA-seq served as an inspiration for dual RNA-seq which has the capability of sequencing RNA molecules of two or more species simultaneously [42] (Figure 4A). The main goal is to get the best possible approximation to the in vivo conditions (reviewed in [201,202]). Although there are still many limitations to overcome, the dual RNA-seq advantages are undeniably evident: it brings the possibility of directly evaluating which genes are differentially expressed in each interacting species which can then be mapped against the known interaction networks or used to predict novel gene regulatory networks [228]. This tool has been very important for unravelling the mechanisms of infection of several pathogens [229,230,231,232,233] (Figure 1). A surprising example of triple RNA-seq enclosed RNA isolation and sequencing starting from a sample containing human immune cells, Aspergillus fumigatus (fungus) and Cytomegalovirus (CMV) [234].
While NGS technologies usually produce short reads, the Third-Generation Sequencing (TGS) has emerged, enabling the sequencing of longer fragments (long reads). As the raw reads can be disclosed in real time, TGS permits data interpretation to occur prior to the samples being fully sequenced [235]. There are two main TGS categories: single-molecule real-time (SMRT) sequencing, and nanopore single-molecule sequencing (Figure 4B). Distinctively, nanopore sequencing relies on registering the changes in the electrical current during the translocation of the template molecule along a protein nanopore, rather than recording the optical or chemical signals that are emitted during the polymerization of a complementary strand, as it commonly happens in other RNA-seq techniques [236]. In the cases where this technology directly uses an RNA molecule as template it may then be called direct RNA-seq. These TGS methods have been of particular relevance for studying pathogenic microorganisms to further disclose the link between post-transcriptional RNA modifications and microorganisms’ mutability and virulence [237,238], as well as to characterize transcript isoforms [239,240,241].
Overall, when they are compared with first-generation sequencing (Sanger sequencing), the NGS and TGS methods are faster, more sensitive and produce a greater amount of data encompassing a wide repertoire of RNA molecules [236]. The employment of NGS and TGS in the meta-transcriptomics through whole-genome or full-length 16S rRNA sequencing has already been shown to accelerate the diagnosis of infectious diseases, namely, by reducing the waiting time, improving the pathogen taxonomic classification and the effectiveness in the detection of RNA viruses, and by extending the spectrum of antibiotic resistance genes that are detected in clinical samples [242,243].
Finally, the above-mentioned RNA-seq strategies might help in the identification of diagnostic biomarkers, the choice of the appropriate treatment for different severity stages of a certain disease, of drug target candidates and potential drugs which can also be repurposed and used for the efficient treatment of specific infectious diseases [244,245].
In fact, independently of the specific RNA-seq method that is employed, it will always require bioinformatic pipelines to process the enormous volume of data. In the past, programming skills were a prerequisite, but many tools with graphical user-friendly interfaces have been progressively developed and made accessible for everyone, as it is the case of the Galaxy platform [246]. Many online resources are also available, namely, several specific transcriptome browsers, or simply, brief explanations of the different techniques, protocols and data.
Figure 4. (A) Simplified workflow of a dual RNA-seq protocol. Host cells are infected in vitro with pathogen cells, lysed and total RNA is extracted. The sequencing library is prepared, and sequencing is performed in a NGS platform, obtaining simultaneously the results for both species. During bioinformatic data analysis, after quality control and data cleaning, the reads from the host and the pathogen are separated in silico in the mapping step. Annotation and quantification are carried out independently for each species, allowing to analyze host and pathogen differential gene expression in parallel, as well as to predict functional correlations between species [230]. (B) Main categories of third-generation sequencing (TGS). (Left panel) Single-molecule real-time (SMRT) sequencing—Sequence is determined through emission of fluorescence due to the incorporation of a fluorescently labelled deoxyribonucleotide (dNTP) by the DNA polymerase in the nascent complementary strand of the cDNA template molecule. The DNA polymerase is anchored to the bottom of a nanowell. (Right panel) Nanopore sequencing—Sequence is obtained without imaging. The template nucleic acid is bound to a motor protein which takes the molecule to a protein nanopore. When the template molecule is translocated through the pore, each nucleotide with its own modifications produces a characteristic current shift that is recorded. Unlike the other methods, direct RNA-seq uses an RNA molecule as template [236]. (C) Antisense oligonucleotides (ASOs) mechanism. (Left panel) General mechanism of ASOs activity. The oligonucleotide binds to the complementary RNA, impairing ribosome progression and/or causing transcript cleavage of a target duplex of mRNA/ASO by RNase H. (Right panel) Targeting of ncRNA–mRNA interaction. In this case, the ASO can be designed to mimic the ncRNA and block its binding to the mRNA (anti-mRNA ASO) or mimic the mRNA sequence to sequester the ncRNA (anti-ncRNA ASO) [247]. (D) mRNA vaccines mechanism. The nucleoside-modified mRNA containing the coding sequence of the protein of interest (SARS-CoV-2 Spike protein) is encapsulated in a lipid nanoparticle (LNP). Upon human vaccination, the LNP is internalized, and the mRNA coding sequence is recognized by the host translation machinery, leading to the production of Spike proteins. This will induce the production of specific antibodies by the host immune system, inducing an immune response cascade [248]. Figure created using BioRender.com (accessed on 11 November 2022).
Figure 4. (A) Simplified workflow of a dual RNA-seq protocol. Host cells are infected in vitro with pathogen cells, lysed and total RNA is extracted. The sequencing library is prepared, and sequencing is performed in a NGS platform, obtaining simultaneously the results for both species. During bioinformatic data analysis, after quality control and data cleaning, the reads from the host and the pathogen are separated in silico in the mapping step. Annotation and quantification are carried out independently for each species, allowing to analyze host and pathogen differential gene expression in parallel, as well as to predict functional correlations between species [230]. (B) Main categories of third-generation sequencing (TGS). (Left panel) Single-molecule real-time (SMRT) sequencing—Sequence is determined through emission of fluorescence due to the incorporation of a fluorescently labelled deoxyribonucleotide (dNTP) by the DNA polymerase in the nascent complementary strand of the cDNA template molecule. The DNA polymerase is anchored to the bottom of a nanowell. (Right panel) Nanopore sequencing—Sequence is obtained without imaging. The template nucleic acid is bound to a motor protein which takes the molecule to a protein nanopore. When the template molecule is translocated through the pore, each nucleotide with its own modifications produces a characteristic current shift that is recorded. Unlike the other methods, direct RNA-seq uses an RNA molecule as template [236]. (C) Antisense oligonucleotides (ASOs) mechanism. (Left panel) General mechanism of ASOs activity. The oligonucleotide binds to the complementary RNA, impairing ribosome progression and/or causing transcript cleavage of a target duplex of mRNA/ASO by RNase H. (Right panel) Targeting of ncRNA–mRNA interaction. In this case, the ASO can be designed to mimic the ncRNA and block its binding to the mRNA (anti-mRNA ASO) or mimic the mRNA sequence to sequester the ncRNA (anti-ncRNA ASO) [247]. (D) mRNA vaccines mechanism. The nucleoside-modified mRNA containing the coding sequence of the protein of interest (SARS-CoV-2 Spike protein) is encapsulated in a lipid nanoparticle (LNP). Upon human vaccination, the LNP is internalized, and the mRNA coding sequence is recognized by the host translation machinery, leading to the production of Spike proteins. This will induce the production of specific antibodies by the host immune system, inducing an immune response cascade [248]. Figure created using BioRender.com (accessed on 11 November 2022).
Microorganisms 10 02303 g004

6.2. ASOS—The Use of Antisense Antimicrobial Therapeutics

An alternative strategy to fight the growing antibiotic resistance phenomena is to design gene-specific oligomers that can specifically target any single pathogen. Antisense antimicrobial therapeutics are a biotechnological form of antibiotic therapy using short, single-stranded oligomers that mimic the structure of DNA or RNA and bind to specific, complementary RNA in a target organism [249,250]. In microorganisms, ASOs (antisense oligonucleotides) bind to their complementary mRNA and inhibit its translation into proteins through the steric blockage of the ribosome progression and/or by promoting the degradation of the targeted mRNA through the RNase degradation of the ASO/mRNA duplex [250].
A key advantage of this antisense approach is that ASOs can be rationally designed to target any microbe through sequence complementation, thus, significantly enlarging the available selection of potential therapeutic targets [249]. A main goal in ASO design is the achievement of high specificity with minimal off-target effects. The sequence specificity and the short length of the antisense antimicrobials pose a minimal risk to human gene expression. Moreover, the specificity of antisense antimicrobials avoids the non-selective killing of the beneficial commensal bacteria by broad-spectrum antibiotics. This overcomes the unintended side-effects that are caused by the dysbiosis of the microbiome, and the consequent medical complications.
The use of antisense therapeutics has been progressively advancing towards clinical use, but in recent years the field has been accelerating. The identification of essential genes and the number of sequenced genomes has largely contributed to this. However, despite the fast advances in the eukaryotic fields [251], the progress in the use of ASOs as antibacterials has been delayed due to the poor uptake efficiency of the antisense molecules by bacteria [249]. This is mainly due to the electrostatic charge or the size barrier that is imposed by the cellular envelope (plasma membrane and cell wall). Other challenges regarding ASO efficiency are its intracellular concentration, oligomer length, nuclease resistance and binding kinetics.
ASOs are typically 10–30 nucleotides in length. The cellular nucleases rapidly attack the unmodified ASOs. Therefore, numerous chemical modifications have been described (e.g., phosphorothioates, locked nucleic acids, peptide nucleic acids, and phosphorodiamidate morpholino oligomers) to confer resistance against nucleases, to improve the stability of the ASO/mRNA hybrid formation and/or to preserve the target specificity.
In the sense of overcoming the challenge of bacterial cellular uptake, the most common strategy for facilitating antisense oligonucleotide delivery is the conjugation of a cell-penetrating peptide (CPP) to the antisense oligonucleotide. The attachment of a compound that can penetrate the bacterial cell wall facilitates the delivery of synthetic antisense oligomers into the bacterial cytoplasm. CPPs are short cationic or amphipathic peptides, which are usually composed of less than 30 amino acids. CPPs have been used with success to deliver modified ASOs in different bacteria ([252] for a review).
Phosphorodiamidate morpholino oligomers (PMOs) are synthetic single-stranded oligomers with a modified backbone which makes them resistant to nucleases [250]. The use of CPP-PMOs has been effective against infections caused by antibiotic resistant bacteria of the genus Acinetobacter (A. lwoffii and A. baumannii) and Klebsiella pneumoniae [253]. Wesolowski et al. described a CPP-PMO conjugate that targeted E. coli gyrA, a highly conserved gene that is found across multiple bacterial species [254]. The authors show that gyrA CPP-PMO reduced the viability of both the Gram-positive and Gram-negative bacterial strains (Enterococcus faecalis, Staphylococcus aureus).
GyrA mRNA was also targeted in S. pyogenes, but it used a CPP-PNA. Peptide nucleic acids (PNAs) are constructed by attaching bases to a modified polyamide backbone. The PNAs are uncharged, which in part accounts for their high affinity for RNA [255]. Successful examples of PNA targeting in different bacteria have been described [256,257]. In the foodborne pathogen C. jejuni, the cmeABC operon encodes a multidrug efflux pump that confers resistance to a broad range of antibiotics [258]. The use of PNAs targeted to different regions of the cmeABC operon restored the antibiotic susceptibility [259].
Locked nucleic acids (LNAs) are oxyphosphorothioate analogues with a 2′-O,4′-C-methylene bridge that locks the ribose ring in the C3′-endo conformation [260]. Both the CPP-PNAs and CPP-LNAs have been used in S. aureus to target the ftsZ mRNA, a gene that is required for cell division [261,262].
As it is mentioned in the previous sections, RNase E is an essential enzyme that is highly conserved in Gram-negative bacteria, and it has no known human orthologue [2]. Thus, the rne gene is a good target for antisense antibiotic development. Using E. coli as a model, Goddard and colleagues have used LNA gapmers, oligonucleotides consisting of a central region of DNA that is flanked by regions of chemically modified LNA nucleotides, to target RNase E [263]. Using this antisense antibiotic strategy, the authors were able to block the translation activity and trigger the RNase H-mediated cleavage of the rne mRNA in vitro, introducing the way to the use of this novel anti-bacterial target in different pathogens (Figure 4C, left panel).
Beyond the targeting of essential genes to reduce the viability of the pathogens, an alternative strategy for using antisense antibiotics is to target non-essential genes, which are required for virulence. Some examples of these are the genes required for invasiveness, biofilm formation [264], and antibiotic resistance genes. In this latter case, the co-administration of the PMO with the antibiotic would restore the susceptibility of the bacteria to its administration [264].
There are also other levels through which ASOs can reprogram the gene expression. For instance, ASOs can target the regulation by ncRNAs over their mRNA targets. In this case, the ASO can be designed to mimic the ncRNA and block its binding to the mRNA target (anti-mRNA ASO) or mimic the mRNA sequence to sequester the ncRNA (anti-ncRNA ASO). In both cases, the ncRNA–mRNA interaction is impaired (Figure 4C, right panel).
Henderson and co-workers [247] designed PNAs to target the ncRNA–mRNA interactions related to a QS system in V. cholerae. The Qrr ncRNAs are composed of four redundant regulators that target, among other genes, the hapR mRNA. At a low cell density, the expression of Qrr ncRNAs represses the master regulator HapR to promote the host colonization and virulence factor production in this human pathogen. At a high cell density, attained at later stages of the infection, the Qrr ncRNAs are no longer expressed, thus reactivating HapR expression and causing the release of the bacterium from the host. The use of two CPP-PNAs designed to sequester the Qrr ncRNAs (anti-Qrr ncRNA ASOs) prevented the Qrr-hapR mRNA interaction. This impaired the HapR downregulation, locking it in the HapR expression state (high cell density profile), with antibacterial implications.
The specific inhibition of a riboswitch by an ASO lead to the inhibition of the growth of S. aureus, L. monocytogenes and E. coli, which widen the lists of possible targets of this antimicrobial alternative system [265]. The potential of the applications of the different types of chemically modified ASOs and the creation of new and improved carrier compounds will expand their uses in multiple pathogenic bacteria.

6.3. RNA Interference (RNAi)

RNA interference (RNAi) is a biological process in which small ncRNAs recognize a specific mRNA, thereby promoting their degradation by Argonaute proteins, thus leading to gene silencing. This eukaryotic mechanism works as an innate defense mechanism against invading viruses [266]. The RNAi system was first described in 1998, and its important role in gene regulation rendered a Nobel Prize to Andrew Fire and Craig Mello [43] (Figure 1). Soon after their discovery, small interfering RNAs (siRNAs) were explored as a tool to treat several diseases, including viral infections [267,268]. The use of siRNA as a therapeutic agent implies the delivery of these molecules into the target cells, thereby activating the RNAi mechanisms in order to silence a specific gene. siRNAs have a high degree of specificity, targeting a unique mRNA, they have reduced toxicity and can reach inaccessible targets. The use of siRNAs to inhibit the replication of SARS-CoV [269], SARS-CoV-2 [270], respiratory syncytial virus (RSV) [271], and hepatitis C virus [272] has already been demonstrated, and this validates the potential of these molecules for the treatment of viral infections. The siRNA molecules target regions of the viral genome that are important for replication, such as mRNA that codes for the spike protein from SARS-CoV-2 [270], or the mRNA that codes for the nucleocapsid protein from RSV [271]. There are still some limitations for the use of siRNA-based therapies, such as siRNA stability, effective carriers, delivery routes and off-target effects. Regardless, clinical trials have already been performed with siRNA-based drugs to treat Ebola and RSV infections ([273], and reviewed in [274]).

6.4. mRNA Vaccines

Vaccination continues to be the most successful and cost-effective public health intervention to control and prevent infectious disease outbreaks. In fact, the conventional application of inactivated, live-attenuated or subunit vaccines had enormous success in the eradication of several infectious diseases, with a classic example being the complete eradication of the smallpox virus; however, many others were not as efficient in treating human immunodeficiency virus (HIV), M. tuberculosis and Plasmodium spp. [275] and other common vaccine-preventable diseases such as influenza [276].
Despite the promising results in the mRNA therapeutics field [36,277], mRNA was seen as too unstable and expensive to be used as a drug or a vaccine for several years [278]. A landmark experience was performed by Robert Malone in 1989 when he discovered the possibility of transfecting mRNA into eukaryotic cells which would induce their intracellular translation, thus recognizing the potential of exploring the RNA molecule for therapeutic purposes [279]. A year after this, the same principle was successfully applied in vivo [36]. In the 1990s, mRNA was tested as a therapeutic agent for the first time using lipid nanoparticles (LPNs) as the delivery method [277,280,281] (Figure 1). At that point, the challenges were to overcome RNA instability, to control the excessive host inflammatory responses and also to improve in vivo delivery systems. Katalin Karikó and Drew Weissman were central players in this context. They unraveled that the incorporation of modified, naturally occurring nucleosides in the mRNA molecules, particularly pseudouridine, prevents the activation of the immune response, reducing the synthetic mRNA immunogenicity in vivo [282] and provides a higher translation capacity [38,283] (Figure 1). More recently, it was demonstrated that N1-methylpseudouridine could provide even better results [284]. In addition, LNPs have become one of the most appealing and commonly used mRNA delivery tools [285].
In face of a sudden new coronavirus pandemic, previous advances in mRNA technology have enabled the rapid release of two highly efficacious mRNA vaccines in the market, BNT162B2 by Pfizer-BioNTech [248] and mRNA-1273 by Moderna [286]. Both of them are LNP-formulated nucleoside-modified RNA vaccines that encode the spike protein of SARS-CoV-2 as the target antigen (Figure 4D). These were the first mRNA-based vaccines to gather an emergency FDA approval, and their success in providing a robust immune response against SARS-CoV-2 was a game changing in the world of immunology and vaccine development (Figure 1). An important point to make is that the speed at which the COVID-19 vaccines were developed was influenced by a global emergency that resulted in an unseen alliance of the scientific community and in a massive funding.
For HIV, since the virus was reported in 1981, many unsuccessful attempts to produce a vaccine were announced [275,287,288,289], but Moderna has currently two mRNA vaccine candidates which are in Phase 1 clinical studies [290]; for tuberculosis and Malaria, the BioNTech company has announced that it is planning to move forward with the clinical trials of mRNA formulations for both of the diseases; for the influenza virus, tremendous effort has been invested in improving the current vaccines, and it is believed that the mRNA platform is well positioned to address the significant unmet need in the season flu [291,292,293]. Finally, the application of mRNA-based therapeutics is also being evaluated for other priority diseases by the CureVac and Moderna companies, such as Rabis, Respiratory Syncytial Virus, Human Cytomegalovirus, Human metapneumovirus and parainfluenza virus, Zika virus, Epstein–Barr Virus, Nipah virus and Chikungunya Virus. For the Ebola Virus and for Streptococcus sp. infections, preliminary mRNA vaccine studies in animal models are already being developed [294,295].
With increased scientific interest in this area, the next-generation mRNA technology will continue to mature both for vaccine development and therapeutics. The field of nucleotide-based vaccines came to the spotlight as a novel, faster and cheaper way to achieve vaccine development when compared with the conventional technologies [296]. Nevertheless, improvements in the storage and stability, production costs, geographic distribution capacity and research alliances are essential to ensure a more effective and prompt response to fight current and future endemic and/or pandemic infectious diseases.

7. Conclusions

RNA is back in the spotlight. The diverse role of RNA in all biological processes, together with the recognition of its important functional properties, have led to its exploitation in a wide range of biotechnological and medical applications. A great contributor to this change of perspective was the validation of the mRNA vaccines at an unpredictable scale and speed at which they fought against the COVID-19 pandemic. As they are natural molecules, RNAs present, in general, low toxicity and immunogenicity. The use of RNA elements presents advantages such as its independent control, tunability, composability and portability which empower their use as genetic tools. However, the advances in the application of these RNA tools have been limited by the rhythm of the progression of the technological advances which have enabled the characterization of new molecules and biological mechanisms. Built upon decades of scientific research, robust and prompt RNA technologies have now emerged, highlighting the importance of fundamental and applied research. For instance, we have testified in recent years, a fast discovery for the new classes of RNA molecules and molecular mechanisms that have transformed our comprehension of RNA metabolism. This review puts together the major discoveries regarding the connection between RNA metabolism and pathogenesis, and how this knowledge has been used to create new strategies to fight microbial pathogenicity. Antibiotic resistance is a serious problem that requires the creation of alternative therapeutics. As such, several RNA tools have surfaced as alternatives to control the virulence of pathogenic bacteria, namely, using synthetic non-coding RNAs, antisense antimicrobial therapeutics with antisense oligonucleotides (ASOs) or CRISPR–Cas antimicrobials. The application of these tools in prokaryotic organisms has been limited by different obstacles. In the case of ASOs, their use has been mostly limited by the development of delivery systems to improve their uptake by the bacterial cells. The same has happened with the CRISPR–Cas tools, and despite the new delivery systems which have been used with success, more research is needed to assure their safety and effectiveness. In the case of the mRNA vaccines, their implementation was possible thanks to the curiosity-driven studies of lipids and experiments with synthetic mRNA. The establishment of mRNA vaccines seems promising because of the speed with which they can be developed and produced, and their flexibility and adaptability to variants.

Author Contributions

Conceptualization, S.C.V. and R.G.M.; writing—original draft preparation and review and editing, S.C.V., V.G.C., M.S., M.V.C., C.M.A., S.M.C. and R.G.M.; supervision, S.C.V. and R.G.M. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by FCT—Fundação para a Ciência e a Tecnologia, I.P.—through the MOSTMICRO-ITQB R&D Unit (UIDB/04612/2020, UIDP/04612/2020) and the LS4FUTURE Associated Laboratory (LA/P/0087/2020). FCT also funded the project PTDC/BIA-BQM/28479/2017 for R.G.M. R.G.M was also financed by an FCT contract (ref. CEECIND/02065/2017). M.S. was financed by an FCT contract according to DL57/2016: SFRH/BPD/109464/2015. V.G.C. and S.M.C were recipients of a doctoral grant which was funded by FCT (ref. 2021.05169.BD and 2022.11492.BD, respectively).

Data Availability Statement

Not applicable.

Acknowledgments

There is a vast amount of literature on the topics addressed in this review article, and inevitably, only a fraction of the relevant work could be cited. We are aware of the existence of many relevant publications that we did not have the opportunity to cite. We sincerely apologize to all colleagues whose important contributions are not cited due to space constraints and acknowledge their important contribute for these topics.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Wu, J.; Wu, C.; Xing, F.; Cao, L.; Zeng, W.; Guo, L.; Li, P.; Zhong, Y.; Jiang, H.; Luo, M.; et al. Endogenous reverse transcriptase and RNase H-mediated antiviral mechanism in embryonic stem cells. Cell Res. 2021, 31, 998–1010. [Google Scholar] [CrossRef]
  2. Arraiano, C.M.; Andrade, J.M.; Domingues, S.; Guinote, I.B.; Malecki, M.; Matos, R.G.; Moreira, R.N.; Pobre, V.; Reis, F.P.; Saramago, M.; et al. The critical role of RNA processing and degradation in the control of gene expression. FEMS Microbiol. Rev. 2010, 34, 883–923. [Google Scholar] [CrossRef]
  3. Arraiano, C.M.; Mauxion, F.; Viegas, S.C.; Matos, R.G.; Seraphin, B. Intracellular ribonucleases involved in transcript processing and decay: Precision tools for RNA. Biochim. Biophys. Acta 2013, 1829, 491–513. [Google Scholar] [CrossRef] [PubMed]
  4. Matos, R.G.; Barria, C.; Pobre, V.; Andrade, J.M.; Arraiano, C.M. Exoribonucleases as modulators of virulence in pathogenic bacteria. Front. Cell Infect Microbiol. 2012, 2, 65. [Google Scholar] [CrossRef]
  5. Lawal, A.; Jejelowo, O.; Chopra, A.K.; Rosenzweig, J.A. Ribonucleases and bacterial virulence. Microb. Biotechnol. 2011, 4, 558–571. [Google Scholar] [CrossRef] [PubMed]
  6. Arraiano, C.M.; Matos, R.G.; Barbas, A. RNase II: The finer details of the modus operandi of a molecular killer. RNA Biol. 2010, 7, 276–278. [Google Scholar] [CrossRef]
  7. Tobe, T.; Sasakawa, C.; Okada, N.; Honma, Y.; Yoshikawa, M. Vacb, a novel chromosomal gene required for expression of virulence genes on the large plasmid of Shigella flexneri. J. Bacteriol. 1992, 174, 6359–6367. [Google Scholar] [CrossRef] [PubMed]
  8. Cheng, Z.F.; Zuo, Y.; Li, Z.; Rudd, K.E.; Deutscher, M.P. The vacb gene required for virulence in Shigella flexneri and Escherichia coli encodes the exoribonuclease RNase R. J. Biol. Chem. 1998, 273, 14077–14080. [Google Scholar] [CrossRef]
  9. Tsao, M.Y.; Lin, T.L.; Hsieh, P.F.; Wang, J.T. The 3′-to-5′ exoribonuclease (encoded by HP1248) of Helicobacter pylori regulates motility and apoptosis-inducing genes. J. Bacteriol. 2009, 191, 2691–2702. [Google Scholar] [CrossRef]
  10. Barria, C.; Mil-Homens, D.; Pinto, S.N.; Fialho, A.M.; Arraiano, C.M.; Domingues, S. RNase R, a new virulence determinant of Streptococcus pneumoniae. Microorganisms 2022, 10, 317. [Google Scholar] [CrossRef]
  11. Haddad, N.; Tresse, O.; Rivoal, K.; Chevret, D.; Nonglaton, Q.; Burns, C.M.; Prévost, H.; Cappelier, J.M. Polynucleotide phosphorylase has an impact on cell biology of Campylobacter jejuni. Front. Cell. Inf. Microbio. 2012, 2, 30. [Google Scholar] [CrossRef] [PubMed]
  12. Engman, J.; Negrea, A.; Sigurlasdottir, S.; Georg, M.; Eriksson, J.; Eriksson, O.S.; Kuwae, A.; Sjolinder, H.; Jonsson, A.B. Neisseria meningitidis polynucleotide phosphorylase affects aggregation, adhesion, and virulence. Infect. Immun. 2016, 84, 1501–1513. [Google Scholar] [CrossRef] [PubMed]
  13. Romano, M.; van de Weerd, R.; Brouwer, F.C.C.; Roviello, G.N.; Lacroix, R.; Sparrius, M.; van den Brink-van Stempvoort, G.; Appelmelk, B.J.; Geurtsen, J.J.; Berisio, R. Structure and function of RNase AS, a polyadenylate-specific exoribonuclease affecting mycobacterial virulence in vivo. Structure 2014, 22, 719–730. [Google Scholar] [CrossRef]
  14. Viegas, S.C.; Mil-Homens, D.; Fialho, A.M.; Arraiano, C.M. The virulence of Salmonella enterica serovar typhimurium in the insect model Galleria mellonella is impaired by mutations in RNase E and RNase III. Appl. Environ. Microbiol. 2013, 79, 6124–6133. [Google Scholar] [CrossRef]
  15. Xia, Y.S.; Weng, Y.D.; Xu, C.J.; Wang, D.; Pan, X.L.; Tian, Z.Y.; Xia, B.; Li, H.Z.; Chen, R.H.; Liu, C.; et al. Endoribonuclease YbeY is essential for RNA processing and virulence in Pseudomonas aeruginosa. MBio 2020, 11, e00659-20. [Google Scholar] [CrossRef] [PubMed]
  16. Gao, P.; Pinkston, K.L.; Bourgogne, A.; Murray, B.E.; van Hoof, A.; Harvey, B.R. Functional studies of E. faecalis RNase J2 and its role in virulence and fitness. PLoS ONE 2017, 12, e0175212. [Google Scholar] [CrossRef]
  17. Marincola, G.; Schafer, T.; Behler, J.; Bernhardt, J.; Ohlsen, K.; Goerke, C.; Wolz, C. RNase Y of Staphylococcus aureus and its role in the activation of virulence genes. Mol. Microbiol. 2012, 85, 817–832. [Google Scholar] [CrossRef]
  18. World Health Organization. Available online: Www.Who.Int (accessed on 23 September 2022).
  19. Beilhartz, G.L.; Gotte, M. HIV-1 ribonuclease H: Structure, catalytic mechanism and inhibitors. Viruses 2010, 2, 900–926. [Google Scholar] [CrossRef]
  20. Everly, D.N., Jr.; Feng, P.; Mian, I.S.; Read, G.S. mRNA degradation by the virion host shutoff (Vhs) protein of herpes simplex virus: Genetic and biochemical evidence that Vhs is a nuclease. J. Virol. 2002, 76, 8560–8571. [Google Scholar] [CrossRef]
  21. Smiley, J.R. Herpes simplex virus virion host shutoff protein: Immune evasion mediated by a viral RNase? J. Virol. 2004, 78, 1063–1068. [Google Scholar] [CrossRef]
  22. Taddeo, B.; Roizman, B. The virion host shutoff protein (Ul41) of herpes simplex virus 1 is an endoribonuclease with a substrate specificity similar to that of RNase A. J. Virol. 2006, 80, 9341–9345. [Google Scholar] [CrossRef] [PubMed]
  23. Meyers, G.; Rümenapf, T.; Ziebuhr, J. Viral RNase Involvement in Strategies of Infection. In Ribonucleases; Nicholson, A., Ed.; Springer: Berlin/Heidelberg, Germany, 2011. [Google Scholar] [CrossRef]
  24. Deng, X.; Hackbart, M.; Mettelman, R.C.; O’Brien, A.; Mielech, A.M.; Yi, G.; Kao, C.C.; Baker, S.C. Coronavirus nonstructural protein 15 mediates evasion of dsRNA sensors and limits apoptosis in macrophages. Proc. Natl. Acad. Sci. USA 2017, 114, E4251–E4260. [Google Scholar] [CrossRef] [PubMed]
  25. Kindler, E.; Gil-Cruz, C.; Spanier, J.; Li, Y.; Wilhelm, J.; Rabouw, H.H.; Zust, R.; Hwang, M.; V’Kovski, P.; Stalder, H.; et al. Early endonuclease-mediated evasion of RNA sensing ensures efficient coronavirus replication. PLoS Pathog. 2017, 13, e1006195. [Google Scholar] [CrossRef] [PubMed]
  26. Hackbart, M.; Deng, X.; Baker, S.C. Coronavirus endoribonuclease targets viral polyuridine sequences to evade activating host sensors. Proc. Natl. Acad. Sci. USA 2020, 117, 8094–8103. [Google Scholar] [CrossRef] [PubMed]
  27. Saramago, M.; Barria, C.; Costa, V.G.; Souza, C.S.; Viegas, S.C.; Domingues, S.; Lousa, D.; Soares, C.M.; Arraiano, C.M.; Matos, R.G. New targets for drug design: Importance of nsp14/nsp10 complex formation for the 3′-5′ exoribonucleolytic activity on SARS-CoV-2. FEBS J. 2021, 288, 5130–5147. [Google Scholar] [CrossRef] [PubMed]
  28. Bouvet, M.; Debarnot, C.; Imbert, I.; Selisko, B.; Snijder, E.J.; Canard, B.; Decroly, E. In vitro reconstitution of SARS-coronavirus mRNA cap methylation. PLoS Pathog. 2010, 6, e1000863. [Google Scholar] [CrossRef]
  29. Ogando, N.S.; Zevenhoven-Dobbe, J.C.; van der Meer, Y.; Bredenbeek, P.J.; Posthuma, C.C.; Snijder, E.J. The enzymatic activity of the nsp14 exoribonuclease is critical for replication of MERS-CoV and SARS-CoV-2. J Virol 2020, 94, e01246-20. [Google Scholar] [CrossRef]
  30. Almazan, F.; Dediego, M.L.; Galan, C.; Escors, D.; Alvarez, E.; Ortego, J.; Sola, I.; Zuniga, S.; Alonso, S.; Moreno, J.L.; et al. Construction of a severe acute respiratory syndrome coronavirus infectious cDNA clone and a replicon to study coronavirus RNA synthesis. J. Virol. 2006, 80, 10900–10906. [Google Scholar] [CrossRef]
  31. Snijder, E.J.; Bredenbeek, P.J.; Dobbe, J.C.; Thiel, V.; Ziebuhr, J.; Poon, L.L.; Guan, Y.; Rozanov, M.; Spaan, W.J.; Gorbalenya, A.E. Unique and conserved features of genome and proteome of SARS-coronavirus, an early split-off from the coronavirus group 2 lineage. J. Mol. Biol. 2003, 331, 991–1004. [Google Scholar] [CrossRef]
  32. Ivanov, K.A.; Hertzig, T.; Rozanov, M.; Bayer, S.; Thiel, V.; Gorbalenya, A.E.; Ziebuhr, J. Major genetic marker of nidoviruses encodes a replicative endoribonuclease. Proc. Natl. Acad. Sci. USA 2004, 101, 12694–12699. [Google Scholar] [CrossRef]
  33. Jayaraman, K.; McParland, K.; Miller, P.; Ts’o, P.O. Selective inhibition of Escherichia coli protein synthesis and growth by nonionic oligonucleotides complementary to the 3′ end of 16s rRNA. Proc. Natl. Acad. Sci. USA 1981, 78, 1537–1541. [Google Scholar] [CrossRef] [PubMed]
  34. Mizuno, T.; Chou, M.Y.; Inouye, M. A unique mechanism regulating gene expression: Translational inhibition by a complementary RNA transcript (micRNA). Proc. Natl. Acad. Sci. USA 1984, 81, 1966–1970. [Google Scholar] [CrossRef] [PubMed]
  35. Ishino, Y.; Shinagawa, H.; Makino, K.; Amemura, M.; Nakata, A. Nucleotide sequence of the iap gene, responsible for alkaline phosphatase isozyme conversion in Escherichia coli, and identification of the gene product. J. Bacteriol. 1987, 169, 5429–5433. [Google Scholar] [CrossRef] [PubMed]
  36. Wolff, J.A.; Malone, R.W.; Williams, P.; Chong, W.; Acsadi, G.; Jani, A.; Felgner, P.L. Direct gene transfer into mouse muscle in vivo. Science 1990, 247, 1465–1468. [Google Scholar] [CrossRef]
  37. Novick, R.P.; Ross, H.F.; Projan, S.J.; Kornblum, J.; Kreiswirth, B.; Moghazeh, S. Synthesis of staphylococcal virulence factors is controlled by a regulatory RNA molecule. EMBO J. 1993, 12, 3967–3975. [Google Scholar] [CrossRef]
  38. Kariko, K.; Buckstein, M.; Ni, H.; Weissman, D. Suppression of RNA recognition by toll-like receptors: The impact of nucleoside modification and the evolutionary origin of RNA. Immunity 2005, 23, 165–175. [Google Scholar] [CrossRef]
  39. Cheung, F.; Haas, B.J.; Goldberg, S.M.; May, G.D.; Xiao, Y.; Town, C.D. Sequencing Medicago truncatula expressed sequenced tags using 454 life sciences technology. BMC Genom. 2006, 7, 272. [Google Scholar] [CrossRef]
  40. Bainbridge, M.N.; Warren, R.L.; Hirst, M.; Romanuik, T.; Zeng, T.; Go, A.; Delaney, A.; Griffith, M.; Hickenbotham, M.; Magrini, V.; et al. Analysis of the prostate cancer cell line lncap transcriptome using a sequencing-by-synthesis approach. BMC Genom. 2006, 7, 246. [Google Scholar] [CrossRef]
  41. Jinek, M.; Chylinski, K.; Fonfara, I.; Hauer, M.; Doudna, J.A.; Charpentier, E. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 2012, 337, 816–821. [Google Scholar] [CrossRef]
  42. Westermann, A.J.; Gorski, S.A.; Vogel, J. Dual RNA-seq of pathogen and host. Nat. Rev. Microbiol. 2012, 10, 618–630. [Google Scholar] [CrossRef]
  43. Fire, A.; Xu, S.; Montgomery, M.K.; Kostas, S.A.; Driver, S.E.; Mello, C.C. Potent and specific genetic interference by double-stranded RNA in Caenorhabditis elegans. Nature 1998, 391, 806–811. [Google Scholar] [CrossRef] [PubMed]
  44. Olson, P.D.; Kuechenmeister, L.J.; Anderson, K.L.; Daily, S.; Beenken, K.E.; Roux, C.M.; Reniere, M.L.; Lewis, T.L.; Weiss, W.J.; Pulse, M.; et al. Small molecule inhibitors of Staphylococcus aureus RnpA alter cellular mRNA turnover, exhibit antimicrobial activity, and attenuate pathogenesis. PLoS Pathog. 2011, 7, e1001287. [Google Scholar] [CrossRef] [PubMed]
  45. Kime, L.; Vincent, H.A.; Gendoo, D.M.; Jourdan, S.S.; Fishwick, C.W.; Callaghan, A.J.; McDowall, K.J. The first small-molecule inhibitors of members of the ribonuclease E family. Sci. Rep. 2015, 5, 8028. [Google Scholar] [CrossRef] [PubMed]
  46. Canal, B.; McClure, A.W.; Curran, J.F.; Wu, M.; Ulferts, R.; Weissmann, F.; Zeng, J.; Bertolin, A.P.; Milligan, J.C.; Basu, S.; et al. Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of nsp14/nsp10 exoribonuclease. Biochem. J. 2021, 478, 2445–2464. [Google Scholar] [CrossRef]
  47. Chen, T.; Fei, C.Y.; Chen, Y.P.; Sargsyan, K.; Liang, J.J.; Liao, C.C.; Lin, Y.L.; Chang, C.P.; Yuan, H.S.; Lim, C. Synergistic inhibition of SARS-CoV-2 replication using disulfiram/ebselen and remdesivir (vol 4, pg 898, 2021). Acs Pharm. Transl. 2021, 4, 1246. [Google Scholar] [CrossRef]
  48. Kim, Y.; Wower, J.; Maltseva, N.; Chang, C.; Jedrzejczak, R.; Wilamowski, M.; Kang, S.; Nicolaescu, V.; Randall, G.; Michalska, K.; et al. Tipiracil binds to uridine site and inhibits nsp15 endoribonuclease NendoU from SARS-CoV-2. Commun. Biol. 2021, 4, 193. [Google Scholar] [CrossRef]
  49. Saramago, M.; Costa, V.G.; Souza, C.S.; Barria, C.; Domingues, S.; Viegas, S.C.; Lousa, D.; Soares, C.M.; Arraiano, C.M.; Matos, R.G. The nsp15 nuclease as a good target to combat SARS-CoV-2: Mechanism of action and its inactivation with FDA-approved drugs. Microorganisms 2022, 10, 342. [Google Scholar] [CrossRef]
  50. Cadegiani, F.A.; McCoy, J.; Gustavo Wambier, C.; Goren, A. Early antiandrogen therapy with dutasteride reduces viral shedding, inflammatory responses, and time-to-remission in males with COVID-19: A randomized, double-blind, placebo-controlled interventional trial (eat-duta androcov trial—biochemical). Cureus 2021, 13, e13047. [Google Scholar] [CrossRef]
  51. Hor, J.; Matera, G.; Vogel, J.; Gottesman, S.; Storz, G. Trans-acting small RNAs and their effects on gene expression in Escherichia coli and Salmonella enterica. EcoSal. Plus 2020, 9. [Google Scholar] [CrossRef]
  52. Waters, L.S.; Storz, G. Regulatory RNAs in bacteria. Cell 2009, 136, 615–628. [Google Scholar] [CrossRef]
  53. Boutet, E.; Djerroud, S.; Perreault, J. Small RNAs beyond model organisms: Have we only scratched the surface? Int. J. Mol. Sci. 2022, 23, 4448. [Google Scholar] [CrossRef] [PubMed]
  54. Storz, G.; Vogel, J.; Wassarman, K.M. Regulation by small RNAs in bacteria: Expanding frontiers. Mol. Cell 2011, 43, 880–891. [Google Scholar] [CrossRef] [PubMed]
  55. Caldelari, I.; Chao, Y.; Romby, P.; Vogel, J. RNA-mediated regulation in pathogenic bacteria. Cold Spring Harb Perspect Med. 2013, 3, a010298. [Google Scholar] [CrossRef] [PubMed]
  56. Boisset, S.; Geissmann, T.; Huntzinger, E.; Fechter, P.; Bendridi, N.; Possedko, M.; Chevalier, C.; Helfer, A.C.; Benito, Y.; Jacquier, A.; et al. Staphylococcus aureus RNAIII coordinately represses the synthesis of virulence factors and the transcription regulator Rot by an antisense mechanism. Genes Dev. 2007, 21, 1353–1366. [Google Scholar] [CrossRef]
  57. Geisinger, E.; Adhikari, R.P.; Jin, R.; Ross, H.F.; Novick, R.P. Inhibition of Rot translation by RNAIII, a key feature of Agr function. Mol. Microbiol. 2006, 61, 1038–1048. [Google Scholar] [CrossRef]
  58. Gupta, R.K.; Luong, T.T.; Lee, C.Y. RNAIII of the Staphylococcus aureus Agr system activates global regulator MgrA by stabilizing mRNA. Proc. Natl. Acad. Sci. USA 2015, 112, 14036–14041. [Google Scholar] [CrossRef]
  59. Luong, T.T.; Newell, S.W.; Lee, C.Y. Mgr, a novel global regulator in Staphylococcus aureus. J. Bacteriol. 2003, 185, 3703–3710. [Google Scholar] [CrossRef]
  60. Pichon, C.; Felden, B. Small RNA genes expressed from Staphylococcus aureus genomic and pathogenicity islands with specific expression among pathogenic strains. Proc. Natl. Acad. Sci. USA 2005, 102, 14249–14254. [Google Scholar] [CrossRef]
  61. Apura, P.; Saramago, M.; Peregrina, A.; Viegas, S.C.; Carvalho, S.M.; Saraiva, L.M.; Arraiano, C.M.; Domingues, S. Tailor-made sRNAs: A plasmid tool to control the expression of target mRNAs in Pseudomonas putida. Plasmid 2020, 109, 102503. [Google Scholar] [CrossRef]
  62. Hoynes-O’Connor, A.; Hinman, K.; Kirchner, L.; Moon, T.S. De novo design of heat-repressible RNA thermosensors in E. coli. Nucleic Acids Res. 2015, 43, 6166–6179. [Google Scholar] [CrossRef]
  63. Wang, H.; Mann, P.A.; Xiao, L.; Gill, C.; Galgoci, A.M.; Howe, J.A.; Villafania, A.; Barbieri, C.M.; Malinverni, J.C.; Sher, X.; et al. Dual-targeting small-molecule inhibitors of the Staphylococcus aureus FMN riboswitch disrupt riboflavin homeostasis in an infectious setting. Cell Chem. Biol. 2017, 24, 576–588.e6. [Google Scholar] [CrossRef] [PubMed]
  64. Padalon-Brauch, G.; Hershberg, R.; Elgrably-Weiss, M.; Baruch, K.; Rosenshine, I.; Margalit, H.; Altuvia, S. Small RNAs encoded within genetic islands of Salmonella typhimurium show host-induced expression and role in virulence. Nucleic Acids Res. 2008, 36, 1913–1927. [Google Scholar] [CrossRef] [PubMed]
  65. Lee, E.J.; Groisman, E.A. An antisense RNA that governs the expression kinetics of a multifunctional virulence gene. Mol. Microbiol. 2010, 76, 1020–1033. [Google Scholar] [CrossRef] [PubMed]
  66. Pfeiffer, V.; Sittka, A.; Tomer, R.; Tedin, K.; Brinkmann, V.; Vogel, J. A small non-coding RNA of the invasion gene island (SPI-1) represses outer membrane protein synthesis from the Salmonella core genome. Mol. Microbiol. 2007, 66, 1174–1191. [Google Scholar] [CrossRef] [PubMed]
  67. Pfeiffer, V.; Papenfort, K.; Lucchini, S.; Hinton, J.C.; Vogel, J. Coding sequence targeting by MicC RNA reveals bacterial mRNA silencing downstream of translational initiation. Nat. Struct. Mol. Biol. 2009, 16, 840–846. [Google Scholar] [CrossRef] [PubMed]
  68. Papenfort, K.; Pfeiffer, V.; Mika, F.; Lucchini, S.; Hinton, J.C.; Vogel, J. Sigmae-dependent small RNAs of Salmonella respond to membrane stress by accelerating global Omp mRNA decay. Mol. Microbiol. 2006, 62, 1674–1688. [Google Scholar] [CrossRef]
  69. Balbontin, R.; Fiorini, F.; Figueroa-Bossi, N.; Casadesus, J.; Bossi, L. Recognition of heptameric seed sequence underlies multi-target regulation by RybB small RNA in Salmonella enterica. Mol. Microbiol. 2010, 78, 380–394. [Google Scholar] [CrossRef]
  70. Frohlich, K.S.; Papenfort, K.; Berger, A.A.; Vogel, J. A conserved RpoS-dependent small RNA controls the synthesis of major porin OmpD. Nucleic Acids Res. 2012, 40, 3623–3640. [Google Scholar] [CrossRef]
  71. Bearson, B.L.; Bearson, S.M.; Kich, J.D. A DIVA vaccine for cross-protection against Salmonella. Vaccine 2016, 34, 1241–1246. [Google Scholar] [CrossRef]
  72. Mraheil, M.A.; Billion, A.; Mohamed, W.; Mukherjee, K.; Kuenne, C.; Pischimarov, J.; Krawitz, C.; Retey, J.; Hartsch, T.; Chakraborty, T.; et al. The intracellular sRNA transcriptome of Listeria monocytogenes during growth in macrophages. Nucleic Acids Res. 2011, 39, 4235–4248. [Google Scholar] [CrossRef]
  73. Thorsing, M.; Dos Santos, P.T.; Kallipolitis, B.H. Small RNAs in major foodborne pathogens: From novel regulatory activities to future applications. Curr. Opin Biotechnol. 2018, 49, 120–128. [Google Scholar] [CrossRef] [PubMed]
  74. Toledo-Arana, A.; Dussurget, O.; Nikitas, G.; Sesto, N.; Guet-Revillet, H.; Balestrino, D.; Loh, E.; Gripenland, J.; Tiensuu, T.; Vaitkevicius, K.; et al. The Listeria transcriptional landscape from saprophytism to virulence. Nature 2009, 459, 950–956. [Google Scholar] [CrossRef] [PubMed]
  75. Quereda, J.J.; Ortega, A.D.; Pucciarelli, M.G.; Garcia-Del Portillo, F. The Listeria small RNA Rli27 regulates a cell wall protein inside eukaryotic cells by targeting a long 5′-UTR variant. PLoS Genet. 2014, 10, e1004765. [Google Scholar] [CrossRef] [PubMed]
  76. Loh, E.; Dussurget, O.; Gripenland, J.; Vaitkevicius, K.; Tiensuu, T.; Mandin, P.; Repoila, F.; Buchrieser, C.; Cossart, P.; Johansson, J. A trans-acting riboswitch controls expression of the virulence regulator PrfA in Listeria monocytogenes. Cell 2009, 139, 770–779. [Google Scholar] [CrossRef] [PubMed]
  77. Murphy, E.R.; Payne, S.M. Ryhb, an iron-responsive small RNA molecule, regulates Shigella dysenteriae virulence. Infect. Immun. 2007, 75, 3470–3477. [Google Scholar] [CrossRef]
  78. Oglesby, A.G.; Murphy, E.R.; Iyer, V.R.; Payne, S.M. Fur regulates acid resistance in Shigella flexneri via Ryhb and YdeP. Mol. Microbiol. 2005, 58, 1354–1367. [Google Scholar] [CrossRef]
  79. Giangrossi, M.; Prosseda, G.; Tran, C.N.; Brandi, A.; Colonna, B.; Falconi, M. A novel antisense RNA regulates at transcriptional level the virulence gene icsa of Shigella flexneri. Nucleic Acids Res. 2010, 38, 3362–3375. [Google Scholar] [CrossRef]
  80. Yang, G.; Li, B.; Jia, L.; Qiu, H.; Yang, M.; Zhu, B.; Xie, J.; Qiu, S.; Li, P.; Ma, H.; et al. A novel sRNA in Shigella flexneri that regulates tolerance and virulence under hyperosmotic pressure. Front. Cell Infect. Microbiol. 2020, 10, 483. [Google Scholar] [CrossRef]
  81. Fris, M.E.; Broach, W.H.; Klim, S.E.; Coschigano, P.W.; Carroll, R.K.; Caswell, C.C.; Murphy, E.R. Sibling sRNA RyfA1 influences Shigella dysenteriae pathogenesis. Genes 2017, 8, 50. [Google Scholar] [CrossRef]
  82. Mann, B.; van Opijnen, T.; Wang, J.; Obert, C.; Wang, Y.D.; Carter, R.; McGoldrick, D.J.; Ridout, G.; Camilli, A.; Tuomanen, E.I.; et al. Control of virulence by small RNAs in Streptococcus pneumoniae. PLoS Pathog. 2012, 8, e1002788. [Google Scholar] [CrossRef]
  83. Acebo, P.; Martin-Galiano, A.J.; Navarro, S.; Zaballos, A.; Amblar, M. Identification of 88 regulatory small RNAs in the TIGR4 strain of the human pathogen Streptococcus pneumoniae. RNA 2012, 18, 530–546. [Google Scholar] [CrossRef] [PubMed]
  84. Kumar, R.; Shah, P.; Swiatlo, E.; Burgess, S.C.; Lawrence, M.L.; Nanduri, B. Identification of novel non-coding small RNAs from Streptococcus pneumoniae TIGR4 using high-resolution genome tiling arrays. BMC Genom. 2010, 11, 350. [Google Scholar] [CrossRef] [PubMed]
  85. Marx, P.; Nuhn, M.; Kovacs, M.; Hakenbeck, R.; Bruckner, R. Identification of genes for small non-coding RNAs that belong to the regulon of the two-component regulatory system CiaRH in Streptococcus. BMC Genom. 2010, 11, 661. [Google Scholar] [CrossRef] [PubMed]
  86. Acebo, P.; Herranz, C.; Espenberger, L.B.; Gomez-Sanz, A.; Terron, M.C.; Luque, D.; Amblar, M. A small non-coding RNA modulates expression of pilus-1 type in Streptococcus pneumoniae. Microorganisms 2021, 9, 1883. [Google Scholar] [CrossRef]
  87. Na, D.; Yoo, S.M.; Chung, H.; Park, H.; Park, J.H.; Lee, S.Y. Metabolic engineering of Escherichia coli using synthetic small regulatory RNAs. Nat. Biotechnol. 2013, 31, 170–174. [Google Scholar] [CrossRef] [PubMed]
  88. Sharma, V.; Yamamura, A.; Yokobayashi, Y. Engineering artificial small RNAs for conditional gene silencing in Escherichia coli. ACS Synth. Biol. 2012, 1, 6–13. [Google Scholar] [CrossRef]
  89. Libis, V.K.; Bernheim, A.G.; Basier, C.; Jaramillo-Riveri, S.; Deyell, M.; Aghoghogbe, I.; Atanaskovic, I.; Bencherif, A.C.; Benony, M.; Koutsoubelis, N.; et al. Silencing of antibiotic resistance in E. coli with engineered phage bearing small regulatory RNAs. ACS Synth. Biol. 2014, 3, 1003–1006. [Google Scholar] [CrossRef]
  90. Sharma, V.; Sakai, Y.; Smythe, K.A.; Yokobayashi, Y. Knockdown of recA gene expression by artificial small RNAs in Escherichia coli. Biochem. Biophys. Res. Commun. 2013, 430, 256–259. [Google Scholar] [CrossRef]
  91. Kemmer, C.; Neubauer, P. Antisense RNA based down-regulation of RNase E in E. coli. Microb. Cell Factories 2006, 5, 38. [Google Scholar] [CrossRef]
  92. Vakulskas, C.A.; Potts, A.H.; Babitzke, P.; Ahmer, B.M.; Romeo, T. Regulation of bacterial virulence by Csr (Rsm) systems. Microbiol. Mol. Biol. Rev. MMBR 2015, 79, 193–224. [Google Scholar] [CrossRef]
  93. Liu, M.Y.; Gui, G.; Wei, B.; Preston, J.F., 3rd; Oakford, L.; Yuksel, U.; Giedroc, D.P.; Romeo, T. The RNA molecule CsrB binds to the global regulatory protein CsrA and antagonizes its activity in Escherichia coli. J. Biol. Chem. 1997, 272, 17502–17510. [Google Scholar] [CrossRef] [PubMed]
  94. Romeo, T.; Gong, M.; Liu, M.Y.; Brun-Zinkernagel, A.M. Identification and molecular characterization of CsrA, a pleiotropic gene from Escherichia coli that affects glycogen biosynthesis, gluconeogenesis, cell size, and surface properties. J. Bacteriol. 1993, 175, 4744–4755. [Google Scholar] [CrossRef] [PubMed]
  95. Weilbacher, T.; Suzuki, K.; Dubey, A.K.; Wang, X.; Gudapaty, S.; Morozov, I.; Baker, C.S.; Georgellis, D.; Babitzke, P.; Romeo, T. A novel sRNA component of the carbon storage regulatory system of Escherichia coli. Mol. Microbiol. 2003, 48, 657–670. [Google Scholar] [CrossRef] [PubMed]
  96. Suzuki, K.; Babitzke, P.; Kushner, S.R.; Romeo, T. Identification of a novel regulatory protein (CsrD) that targets the global regulatory RNAs CsrB and CsrC for degradation by RNase E. Genes Dev. 2006, 20, 2605–2617. [Google Scholar] [CrossRef] [PubMed]
  97. Altier, C.; Suyemoto, M.; Lawhon, S.D. Regulation of Salmonella enterica serovar typhimurium invasion genes by CsrA. Infect. Immun. 2000, 68, 6790–6797. [Google Scholar] [CrossRef]
  98. Altier, C.; Suyemoto, M.; Ruiz, A.I.; Burnham, K.D.; Maurer, R. Characterization of two novel regulatory genes affecting Salmonella invasion gene expression. Mol. Microbiol. 2000, 35, 635–646. [Google Scholar] [CrossRef]
  99. Fortune, D.R.; Suyemoto, M.; Altier, C. Identification of CsrC and characterization of its role in epithelial cell invasion in Salmonella enterica serovar typhimurium. Infect. Immun. 2006, 74, 331–339. [Google Scholar] [CrossRef]
  100. Teplitski, M.; Al-Agely, A.; Ahmer, B.M.M. Contribution of the SirA regulon to biofilm formation in Salmonella enterica serovar typhimurium. Microbiology 2006, 152, 3411–3424. [Google Scholar] [CrossRef]
  101. Gore, A.L.; Payne, S.M. CsrA and Cra influence Shigella flexneri pathogenesis. Infect. Immun. 2010, 78, 4674–4682. [Google Scholar] [CrossRef]
  102. Forsbach-Birk, V.; McNealy, T.; Shi, C.; Lynch, D.; Marre, R. Reduced expression of the global regulator protein CsrA in Legionella pneumophila affects virulence-associated regulators and growth in Acanthamoeba castellanii. Int. J. Med. Microbiol. 2004, 294, 15–25. [Google Scholar] [CrossRef]
  103. Fettes, P.S.; Forsbach-Birk, V.; Lynch, D.; Marre, R. Overexpresssion of a Legionella pneumophila homologue of the E. coli regulator CsrA affects cell size, flagellation, and pigmentation. Int. J. Med. Microbiol. 2001, 291, 353–360. [Google Scholar] [CrossRef] [PubMed]
  104. Hammer, B.K.; Tateda, E.S.; Swanson, M.S. A two-component regulator induces the transmission phenotype of stationary-phase Legionella pneumophila. Mol. Microbiol. 2002, 44, 107–118. [Google Scholar] [CrossRef] [PubMed]
  105. Sahr, T.; Bruggemann, H.; Jules, M.; Lomma, M.; Albert-Weissenberger, C.; Cazalet, C.; Buchrieser, C. Two small ncRNAs jointly govern virulence and transmission in Legionella pneumophila. Mol. Microbiol. 2009, 72, 741–762. [Google Scholar] [CrossRef] [PubMed]
  106. Kay, E.; Humair, B.; Denervaud, V.; Riedel, K.; Spahr, S.; Eberl, L.; Valverde, C.; Haas, D. Two gaca-dependent small RNAs modulate the quorum-sensing response in Pseudomonas aeruginosa. J. Bacteriol. 2006, 188, 6026–6033. [Google Scholar] [CrossRef] [PubMed]
  107. Lenz, D.H.; Miller, M.B.; Zhu, J.; Kulkarni, R.V.; Bassler, B.L. CsrA and three redundant small RNAs regulate quorum sensing in Vibrio cholerae. Mol. Microbiol. 2005, 58, 1186–1202. [Google Scholar] [CrossRef] [PubMed]
  108. Liu, Y.; Cui, Y.; Mukherjee, A.; Chatterjee, A.K. Characterization of a novel RNA regulator of Erwinia carotovora ssp. carotovora that controls production of extracellular enzymes and secondary metabolites. Mol. Microbiol. 1998, 29, 219–234. [Google Scholar] [CrossRef]
  109. Katsuya-Gaviria, K.; Paris, G.; Dendooven, T.; Bandyra, K.J. Bacterial RNA chaperones and chaperone-like riboregulators: Behind the scenes of RNA-mediated regulation of cellular metabolism. RNA Biol. 2022, 19, 419–436. [Google Scholar] [CrossRef]
  110. Sun, X.; Zhulin, I.; Wartell, R.M. Predicted structure and phyletic distribution of the RNA-binding protein Hfq. Nucleic Acids Res. 2002, 30, 3662–3671. [Google Scholar] [CrossRef]
  111. Franze de Fernandez, M.T.; Eoyang, L.; August, J.T. Factor fraction required for the synthesis of bacteriophage Qβ-RNA. Nature 1968, 219, 588–590. [Google Scholar] [CrossRef]
  112. Sittka, A.; Pfeiffer, V.; Tedin, K.; Vogel, J. The RNA chaperone Hfq is essential for the virulence of Salmonella typhimurium. Mol. Microbiol. 2007, 63, 193–217. [Google Scholar] [CrossRef]
  113. McNealy, T.L.; Forsbach-Birk, V.; Shi, C.; Marre, R. The Hfq homolog in Legionella pneumophila demonstrates regulation by LetA and RpoS and interacts with the global regulator CsrA. J. Bacteriol. 2005, 187, 1527–1532. [Google Scholar] [CrossRef] [PubMed]
  114. Christiansen, J.K.; Larsen, M.H.; Ingmer, H.; Sogaard-Andersen, L.; Kallipolitis, B.H. The RNA-binding protein Hfq of Listeria monocytogenes: Role in stress tolerance and virulence. J. Bacteriol. 2004, 186, 3355–3362. [Google Scholar] [CrossRef] [PubMed]
  115. Ding, Y.; Davis, B.M.; Waldor, M.K. Hfq is essential for Vibrio cholerae virulence and downregulates sigma expression. Mol. Microbiol. 2004, 53, 345–354. [Google Scholar] [CrossRef] [PubMed]
  116. Sonnleitner, E.; Hagens, S.; Rosenau, F.; Wilhelm, S.; Habel, A.; Jager, K.E.; Blasi, U. Reduced virulence of a Hfq mutant of Pseudomonas aeruginosa O1. Microb. Pathog. 2003, 35, 217–228. [Google Scholar] [CrossRef]
  117. Dietrich, M.; Munke, R.; Gottschald, M.; Ziska, E.; Boettcher, J.P.; Mollenkopf, H.; Friedrich, A. The effect of Hfq on global gene expression and virulence in Neisseria gonorrhoeae. FEBS J. 2009, 276, 5507–5520. [Google Scholar] [CrossRef]
  118. Meibom, K.L.; Forslund, A.L.; Kuoppa, K.; Alkhuder, K.; Dubail, I.; Dupuis, M.; Forsberg, A.; Charbit, A. Hfq, a novel pleiotropic regulator of virulence-associated genes in Francisella tularensis. Infect. Immun. 2009, 77, 1866–1880. [Google Scholar] [CrossRef]
  119. Smirnov, A.; Forstner, K.U.; Holmqvist, E.; Otto, A.; Gunster, R.; Becher, D.; Reinhardt, R.; Vogel, J. Grad-seq guides the discovery of ProQ as a major small RNA-binding protein. Proc. Natl. Acad. Sci. USA 2016, 113, 11591–11596. [Google Scholar] [CrossRef]
  120. Holmqvist, E.; Li, L.; Bischler, T.; Barquist, L.; Vogel, J. Global maps of ProQ binding in vivo reveal target recognition via RNA structure and stability control at mRNA 3′ ends. Mol. Cell 2018, 70, 971–982.e6. [Google Scholar] [CrossRef]
  121. Westermann, A.J.; Venturini, E.; Sellin, M.E.; Forstner, K.U.; Hardt, W.D.; Vogel, J. The major RNA-binding protein ProQ impacts virulence gene expression in Salmonella enterica serovar typhimurium. MBio 2019, 10, e02504-18. [Google Scholar] [CrossRef]
  122. Attaiech, L.; Boughammoura, A.; Brochier-Armanet, C.; Allatif, O.; Peillard-Fiorente, F.; Edwards, R.A.; Omar, A.R.; MacMillan, A.M.; Glover, M.; Charpentier, X. Silencing of natural transformation by an RNA chaperone and a multitarget small RNA. Proc. Natl. Acad. Sci. USA 2016, 113, 8813–8818. [Google Scholar] [CrossRef]
  123. Leonard, S.; Villard, C.; Nasser, W.; Reverchon, S.; Hommais, F. RNA chaperones Hfq and ProQ play a key role in the virulence of the plant pathogenic bacterium Dickeya dadantii. Front. Microbiol. 2021, 12, 687484. [Google Scholar] [CrossRef] [PubMed]
  124. Yuan, X.; Eldred, L.I.; Kharadi, R.R.; Slack, S.M.; Sundin, G.W. The RNA-binding protein ProQ impacts exopolysaccharide biosynthesis and second messenger cyclic di-GMP signaling in the fire blight pathogen Erwinia amylovora. Appl. Environ. Microbiol. 2022, 88, e0023922. [Google Scholar] [CrossRef] [PubMed]
  125. Kortmann, J.; Narberhaus, F. Bacterial RNA thermometers: Molecular zippers and switches. Nat Rev Microbiol 2012, 10, 255–265. [Google Scholar] [CrossRef]
  126. Waldminghaus, T.; Gaubig, L.C.; Narberhaus, F. Genome-wide bioinformatic prediction and experimental evaluation of potential RNA thermometers. Mol. Genet. Genom. 2007, 278, 555–564. [Google Scholar] [CrossRef] [PubMed]
  127. Altuvia, S.; Kornitzer, D.; Teff, D.; Oppenheim, A.B. Alternative mRNA structures of the cIII gene of bacteriophage lambda determine the rate of its translation initiation. J. Mol. Biol. 1989, 210, 265–280. [Google Scholar] [CrossRef]
  128. Waldminghaus, T.; Heidrich, N.; Brantl, S.; Narberhaus, F. Fouru: A novel type of RNA thermometer in Salmonella. Mol. Microbiol. 2007, 65, 413–424. [Google Scholar] [CrossRef] [PubMed]
  129. Johansson, J.; Mandin, P.; Renzoni, A.; Chiaruttini, C.; Springer, M.; Cossart, P. An RNA thermosensor controls expression of virulence genes in Listeria monocytogenes. Cell 2002, 110, 551–561. [Google Scholar] [CrossRef]
  130. Bohme, K.; Steinmann, R.; Kortmann, J.; Seekircher, S.; Heroven, A.K.; Berger, E.; Pisano, F.; Thiermann, T.; Wolf-Watz, H.; Narberhaus, F.; et al. Concerted actions of a thermo-labile regulator and a unique intergenic RNA thermosensor control Yersinia virulence. PLoS Pathog. 2012, 8, e1002518. [Google Scholar] [CrossRef]
  131. Kouse, A.B.; Righetti, F.; Kortmann, J.; Narberhaus, F.; Murphy, E.R. RNA-mediated thermoregulation of iron-acquisition genes in Shigella dysenteriae and pathogenic Escherichia Coli. PLoS ONE 2013, 8, e63781. [Google Scholar] [CrossRef]
  132. Murphy, E.R.; Rossmanith, J.; Sieg, J.; Fris, M.E.; Hussein, H.; Kouse, A.B.; Gross, K.; Zeng, C.; Hines, J.V.; Narberhaus, F.; et al. Regulation of OmpA translation and Shigella dysenteriae virulence by an RNA thermometer. Infect. Immun. 2020, 88, e00871-19. [Google Scholar] [CrossRef]
  133. Scheller, D.; Twittenhoff, C.; Becker, F.; Holler, M.; Narberhaus, F. OmpA, a common virulence factor, is under RNA thermometer control in Yersinia pseudotuberculosis. Front Microbiol. 2021, 12, 687260. [Google Scholar] [CrossRef] [PubMed]
  134. Loh, E.; Kugelberg, E.; Tracy, A.; Zhang, Q.; Gollan, B.; Ewles, H.; Chalmers, R.; Pelicic, V.; Tang, C.M. Temperature triggers immune evasion by Neisseria meningitidis. Nature 2013, 502, 237–240. [Google Scholar] [CrossRef] [PubMed]
  135. Weber, G.G.; Kortmann, J.; Narberhaus, F.; Klose, K.E. RNA thermometer controls temperature-dependent virulence factor expression in Vibrio cholerae. Proc. Natl. Acad. Sci. USA 2014, 111, 14241–14246. [Google Scholar] [CrossRef] [PubMed]
  136. Neupert, J.; Karcher, D.; Bock, R. Design of simple synthetic RNA thermometers for temperature-controlled gene expression in Escherichia coli. Nucleic Acids Res. 2008, 36, e124. [Google Scholar] [CrossRef]
  137. Piraner, D.I.; Abedi, M.H.; Moser, B.A.; Lee-Gosselin, A.; Shapiro, M.G. Tunable thermal bioswitches for in vivo control of microbial therapeutics. Nat. Chem. Biol. 2017, 13, 75–80. [Google Scholar] [CrossRef]
  138. Richards, J.; Belasco, J.G. Riboswitch control of bacterial RNA stability. Mol. Microbiol. 2021, 116, 361–365. [Google Scholar] [CrossRef]
  139. Mironov, A.S.; Gusarov, I.; Rafikov, R.; Lopez, L.E.; Shatalin, K.; Kreneva, R.A.; Perumov, D.A.; Nudler, E. Sensing small molecules by nascent RNA: A mechanism to control transcription in bacteria. Cell 2002, 111, 747–756. [Google Scholar] [CrossRef]
  140. Nahvi, A.; Sudarsan, N.; Ebert, M.S.; Zou, X.; Brown, K.L.; Breaker, R.R. Genetic control by a metabolite binding mRNA. Chem. Biol. 2002, 9, 1043. [Google Scholar] [CrossRef]
  141. Winkler, W.; Nahvi, A.; Breaker, R.R. Thiamine derivatives bind messenger RNAs directly to regulate bacterial gene expression. Nature 2002, 419, 952–956. [Google Scholar] [CrossRef]
  142. Serganov, A.; Nudler, E. A decade of riboswitches. Cell 2013, 152, 17–24. [Google Scholar] [CrossRef]
  143. Smith-Peter, E.; Seguin, D.L.; St-Pierre, E.; Sekulovic, O.; Jeanneau, S.; Tremblay-Tetreault, C.; Lamontagne, A.M.; Jacques, P.E.; Lafontaine, D.A.; Fortier, L.C. Inactivation of the riboswitch-controlled GMP synthase GuaA in Clostridioides difficile is associated with severe growth defects and poor infectivity in a mouse model of infection. RNA Biol. 2021, 18, 699–710. [Google Scholar] [CrossRef] [PubMed]
  144. Dixon, N.; Duncan, J.N.; Geerlings, T.; Dunstan, M.S.; McCarthy, J.E.; Leys, D.; Micklefield, J. Reengineering orthogonally selective riboswitches. Proc. Natl. Acad. Sci. USA 2010, 107, 2830–2835. [Google Scholar] [CrossRef] [PubMed]
  145. Mulhbacher, J.; Brouillette, E.; Allard, M.; Fortier, L.C.; Malouin, F.; Lafontaine, D.A. Novel riboswitch ligand analogs as selective inhibitors of guanine-related metabolic pathways. PLoS Pathog. 2010, 6, e1000865. [Google Scholar] [CrossRef] [PubMed]
  146. Dixon, N.; Robinson, C.J.; Geerlings, T.; Duncan, J.N.; Drummond, S.P.; Micklefield, J. Orthogonal riboswitches for tuneable coexpression in bacteria. Angew. Chem. Int. Ed. Engl. 2012, 51, 3620–3624. [Google Scholar] [CrossRef]
  147. Sudarsan, N.; Cohen-Chalamish, S.; Nakamura, S.; Emilsson, G.M.; Breaker, R.R. Thiamine pyrophosphate riboswitches are targets for the antimicrobial compound pyrithiamine. Chem. Biol. 2005, 12, 1325–1335. [Google Scholar] [CrossRef]
  148. Thore, S.; Frick, C.; Ban, N. Structural basis of thiamine pyrophosphate analogues binding to the eukaryotic riboswitch. J. Am. Chem. Soc. 2008, 130, 8116–8117. [Google Scholar] [CrossRef]
  149. Lee, E.R.; Blount, K.F.; Breaker, R.R. Roseoflavin is a natural antibacterial compound that binds to FMN riboswitches and regulates gene expression. RNA Biol. 2009, 6, 187–194. [Google Scholar] [CrossRef]
  150. Serganov, A.; Huang, L.; Patel, D.J. Coenzyme recognition and gene regulation by a flavin mononucleotide riboswitch. Nature 2009, 458, 233–237. [Google Scholar] [CrossRef]
  151. Warner, K.D.; Homan, P.; Weeks, K.M.; Smith, A.G.; Abell, C.; Ferre-D’Amare, A.R. Validating fragment-based drug discovery for biological RNAs: Lead fragments bind and remodel the TPP riboswitch specifically. Chem. Biol. 2014, 21, 591–595. [Google Scholar] [CrossRef]
  152. Blount, K.F.; Wang, J.X.; Lim, J.; Sudarsan, N.; Breaker, R.R. Antibacterial lysine analogs that target lysine riboswitches. Nat. Chem Biol. 2007, 3, 44–49. [Google Scholar] [CrossRef]
  153. Ster, C.; Allard, M.; Boulanger, S.; Lamontagne Boulet, M.; Mulhbacher, J.; Lafontaine, D.A.; Marsault, E.; Lacasse, P.; Malouin, F. Experimental treatment of Staphylococcus aureus bovine intramammary infection using a guanine riboswitch ligand analog. J. Dairy Sci. 2013, 96, 1000–1008. [Google Scholar] [CrossRef] [PubMed]
  154. Rizvi, N.F.; Howe, J.A.; Nahvi, A.; Klein, D.J.; Fischmann, T.O.; Kim, H.Y.; McCoy, M.A.; Walker, S.S.; Hruza, A.; Richards, M.P.; et al. Discovery of selective RNA-binding small molecules by affinity-selection mass spectrometry. ACS Chem Biol. 2018, 13, 820–831. [Google Scholar] [CrossRef] [PubMed]
  155. Howe, J.A.; Wang, H.; Fischmann, T.O.; Balibar, C.J.; Xiao, L.; Galgoci, A.M.; Malinverni, J.C.; Mayhood, T.; Villafania, A.; Nahvi, A.; et al. Selective small-molecule inhibition of an RNA structural element. Nature 2015, 526, 672–677. [Google Scholar] [CrossRef] [PubMed]
  156. Ellington, A.D.; Szostak, J.W. In vitro selection of RNA molecules that bind specific ligands. Nature 1990, 346, 818–822. [Google Scholar] [CrossRef] [PubMed]
  157. Tuerk, C.; Gold, L. Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science 1990, 249, 505–510. [Google Scholar] [CrossRef]
  158. Weigand, J.E.; Suess, B. Aptamers and riboswitches: Perspectives in biotechnology. Appl. Microbiol. Biotechnol. 2009, 85, 229–236. [Google Scholar] [CrossRef]
  159. Afrasiabi, S.; Pourhajibagher, M.; Raoofian, R.; Tabarzad, M.; Bahador, A. Therapeutic applications of nucleic acid aptamers in microbial infections. J. Biomed. Sci. 2020, 27, 6. [Google Scholar] [CrossRef]
  160. Davydova, A.; Vorobjeva, M.; Pyshnyi, D.; Altman, S.; Vlassov, V.; Venyaminova, A. Aptamers against pathogenic microorganisms. Crit. Rev. Microbiol. 2016, 42, 847–865. [Google Scholar] [CrossRef]
  161. Wan, Q.; Liu, X.; Zu, Y. Oligonucleotide aptamers for pathogen detection and infectious disease control. Theranostics 2021, 11, 9133–9161. [Google Scholar] [CrossRef]
  162. Barrangou, R.; Fremaux, C.; Deveau, H.; Richards, M.; Boyaval, P.; Moineau, S.; Romero, D.A.; Horvath, P. CRISPR provides acquired resistance against viruses in prokaryotes. Science 2007, 315, 1709–1712. [Google Scholar] [CrossRef]
  163. Brouns, S.J.; Jore, M.M.; Lundgren, M.; Westra, E.R.; Slijkhuis, R.J.; Snijders, A.P.; Dickman, M.J.; Makarova, K.S.; Koonin, E.V.; van der Oost, J. Small CRISPR RNAs guide antiviral defense in prokaryotes. Science 2008, 321, 960–964. [Google Scholar] [CrossRef] [PubMed]
  164. Makarova, K.S.; Koonin, E.V. Annotation and classification of CRISPR-Cas systems. Methods Mol. Biol. 2015, 1311, 47–75. [Google Scholar] [PubMed]
  165. Makarova, K.S.; Wolf, Y.I.; Iranzo, J.; Shmakov, S.A.; Alkhnbashi, O.S.; Brouns, S.J.J.; Charpentier, E.; Cheng, D.; Haft, D.H.; Horvath, P.; et al. Evolutionary classification of CRISPR-Cas systems: A burst of class 2 and derived variants. Nat. Rev. Microbiol. 2020, 18, 67–83. [Google Scholar] [CrossRef] [PubMed]
  166. Chylinski, K.; Le Rhun, A.; Charpentier, E. The tracrRNA and Cas9 families of type II CRISPR-Cas immunity systems. RNA Biol. 2013, 10, 726–737. [Google Scholar] [CrossRef]
  167. Makarova, K.S.; Haft, D.H.; Barrangou, R.; Brouns, S.J.; Charpentier, E.; Horvath, P.; Moineau, S.; Mojica, F.J.; Wolf, Y.I.; Yakunin, A.F.; et al. Evolution and classification of the CRISPR-Cas systems. Nat. Rev. Microbiol. 2011, 9, 467–477. [Google Scholar] [CrossRef]
  168. Sampson, T.R.; Saroj, S.D.; Llewellyn, A.C.; Tzeng, Y.L.; Weiss, D.S. A CRISPR/Cas system mediates bacterial innate immune evasion and virulence. Nature 2013, 497, 254–257. [Google Scholar] [CrossRef]
  169. Ma, K.; Cao, Q.; Luo, S.; Wang, Z.; Liu, G.; Lu, C.; Liu, Y. Cas9 enhances bacterial virulence by repressing the RegR transcriptional regulator in Streptococcus agalactiae. Infect. Immun. 2018, 86, e00552-17. [Google Scholar] [CrossRef]
  170. Gao, N.J.; Al-Bassam, M.M.; Poudel, S.; Wozniak, J.M.; Gonzalez, D.J.; Olson, J.; Zengler, K.; Nizet, V.; Valderrama, J.A. Functional and proteomic analysis of Streptococcus pyogenes virulence upon loss of its native Cas9 nuclease. Front Microbiol. 2019, 10, 1967. [Google Scholar] [CrossRef]
  171. Heidrich, N.; Hagmann, A.; Bauriedl, S.; Vogel, J.; Schoen, C. The CRISPR/Cas system in Neisseria meningitidis affects bacterial adhesion to human nasopharyngeal epithelial cells. RNA Biol. 2019, 16, 390–396. [Google Scholar] [CrossRef]
  172. Shabbir, M.A.; Wu, Q.; Shabbir, M.Z.; Sajid, A.; Ahmed, S.; Sattar, A.; Tang, Y.; Li, J.; Maan, M.K.; Hao, H.; et al. The CRISPR-Cas system promotes antimicrobial resistance in Campylobacter jejuni. Future Microbiol. 2018, 13, 1757–1774. [Google Scholar] [CrossRef]
  173. Gunderson, F.F.; Cianciotto, N.P. The CRISPR-associated gene Cas2 of Legionella pneumophila is required for intracellular infection of amoebae. mBio 2013, 4, e00074-00013. [Google Scholar] [CrossRef] [PubMed]
  174. Tang, B.; Gong, T.; Zhou, X.; Lu, M.; Zeng, J.; Peng, X.; Wang, S.; Li, Y. Deletion of cas3 gene in Streptococcus mutans affects biofilm formation and increases fluoride sensitivity. Arch. Oral. Biol. 2019, 99, 190–197. [Google Scholar] [CrossRef] [PubMed]
  175. Cui, L.; Wang, X.; Huang, D.; Zhao, Y.; Feng, J.; Lu, Q.; Pu, Q.; Wang, Y.; Cheng, G.; Wu, M.; et al. CRISPR-Cas3 of Salmonella upregulates bacterial biofilm formation and virulence to host cells by targeting quorum-sensing systems. Pathogens 2020, 9, 53. [Google Scholar] [CrossRef] [PubMed]
  176. Li, R.; Fang, L.; Tan, S.; Yu, M.; Li, X.; He, S.; Wei, Y.; Li, G.; Jiang, J.; Wu, M. Type I CRISPR-Cas targets endogenous genes and regulates virulence to evade mammalian host immunity. Cell Res. 2016, 26, 1273–1287. [Google Scholar] [CrossRef] [PubMed]
  177. Bourgogne, A.; Garsin, D.A.; Qin, X.; Singh, K.V.; Sillanpaa, J.; Yerrapragada, S.; Ding, Y.; Dugan-Rocha, S.; Buhay, C.; Shen, H.; et al. Large scale variation in Enterococcus faecalis illustrated by the genome analysis of strain OG1RF. Genome Biol. 2008, 9, R110. [Google Scholar] [CrossRef] [PubMed]
  178. Mangas, E.L.; Rubio, A.; Alvarez-Marin, R.; Labrador-Herrera, G.; Pachon, J.; Pachon-Ibanez, M.E.; Divina, F.; Perez-Pulido, A.J. Pangenome of Acinetobacter baumannii uncovers two groups of genomes, one of them with genes involved in CRISPR/Cas defence systems associated with the absence of plasmids and exclusive genes for biofilm formation. Microb. Genom. 2019, 5. [Google Scholar] [CrossRef]
  179. Zegans, M.E.; Wagner, J.C.; Cady, K.C.; Murphy, D.M.; Hammond, J.H.; O’Toole, G.A. Interaction between bacteriophage Dms3 and host CRISPR region inhibits group behaviors of Pseudomonas aeruginosa. J. Bacteriol. 2009, 191, 210–219. [Google Scholar] [CrossRef]
  180. Patterson, A.G.; Jackson, S.A.; Taylor, C.; Evans, G.B.; Salmond, G.P.C.; Przybilski, R.; Staals, R.H.J.; Fineran, P.C. Quorum sensing controls adaptive immunity through the regulation of multiple CRISPR-Cas systems. Mol. Cell 2016, 64, 1102–1108. [Google Scholar] [CrossRef]
  181. Hoyland-Kroghsbo, N.M.; Paczkowski, J.; Mukherjee, S.; Broniewski, J.; Westra, E.; Bondy-Denomy, J.; Bassler, B.L. Quorum sensing controls the Pseudomonas aeruginosa CRISPR-Cas adaptive immune system. Proc. Natl. Acad. Sci. USA 2017, 114, 131–135. [Google Scholar] [CrossRef]
  182. Deltcheva, E.; Chylinski, K.; Sharma, C.M.; Gonzales, K.; Chao, Y.; Pirzada, Z.A.; Eckert, M.R.; Vogel, J.; Charpentier, E. CRISPR RNA maturation by trans-encoded small RNA and host factor RNase III. Nature 2011, 471, 602–607. [Google Scholar] [CrossRef]
  183. Gomaa, A.A.; Klumpe, H.E.; Luo, M.L.; Selle, K.; Barrangou, R.; Beisel, C.L. Programmable removal of bacterial strains by use of genome-targeting CRISPR-Cas systems. mBio 2014, 5, e00928-13. [Google Scholar] [CrossRef] [PubMed]
  184. Abudayyeh, O.O.; Gootenberg, J.S.; Konermann, S.; Joung, J.; Slaymaker, I.M.; Cox, D.B.; Shmakov, S.; Makarova, K.S.; Semenova, E.; Minakhin, L.; et al. C2c2 is a single-component programmable RNA-guided RNA-targeting CRISPR effector. Science 2016, 353, aaf5573. [Google Scholar] [CrossRef] [PubMed]
  185. East-Seletsky, A.; O’Connell, M.R.; Knight, S.C.; Burstein, D.; Cate, J.H.; Tjian, R.; Doudna, J.A. Two distinct RNase activities of CRISPR-c2c2 enable guide-RNA processing and RNA detection. Nature 2016, 538, 270–273. [Google Scholar] [CrossRef] [PubMed]
  186. Kiga, K.; Tan, X.E.; Ibarra-Chavez, R.; Watanabe, S.; Aiba, Y.; Sato’o, Y.; Li, F.Y.; Sasahara, T.; Cui, B.; Kawauchi, M.; et al. Development of CRISPR-Cas13a-based antimicrobials capable of sequence-specific killing of target bacteria. Nat. Commun. 2020, 11, 2934. [Google Scholar] [CrossRef] [PubMed]
  187. Gootenberg, J.S.; Abudayyeh, O.O.; Lee, J.W.; Essletzbichler, P.; Dy, A.J.; Joung, J.; Verdine, V.; Donghia, N.; Daringer, N.M.; Freije, C.A.; et al. Nucleic acid detection with CRISPR-Cas13a/c2c2. Science 2017, 356, 438–442. [Google Scholar] [CrossRef] [PubMed]
  188. Rodrigues, M.; McBride, S.W.; Hullahalli, K.; Palmer, K.L.; Duerkop, B.A. Conjugative delivery of CRISPR-Cas9 for the selective depletion of antibiotic-resistant enterococci. Antimicrob. Agents Chemother. 2019, 63, e01454-19. [Google Scholar] [CrossRef] [PubMed]
  189. Palacios Araya, D.; Palmer, K.L.; Duerkop, B.A. CRISPR-based antimicrobials to obstruct antibiotic-resistant and pathogenic bacteria. PLoS Pathog. 2021, 17, e1009672. [Google Scholar] [CrossRef] [PubMed]
  190. Bikard, D.; Euler, C.W.; Jiang, W.; Nussenzweig, P.M.; Goldberg, G.W.; Duportet, X.; Fischetti, V.A.; Marraffini, L.A. Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials. Nat. Biotechnol. 2014, 32, 1146–1150. [Google Scholar] [CrossRef]
  191. Yao, X.; Lyu, P.; Yoo, K.; Yadav, M.K.; Singh, R.; Atala, A.; Lu, B. Engineered extracellular vesicles as versatile ribonucleoprotein delivery vehicles for efficient and safe CRISPR genome editing. J. Extracell. Vesicles 2021, 10, e12076. [Google Scholar] [CrossRef]
  192. Wan, F.; Draz, M.S.; Gu, M.; Yu, W.; Ruan, Z.; Luo, Q. Novel strategy to combat antibiotic resistance: A sight into the combination of CRISPR/Cas9 and nanoparticles. Pharmaceutics 2021, 13, 352. [Google Scholar] [CrossRef]
  193. Ganbaatar, U.; Liu, C. CRISPR-based COVID-19 testing: Toward next-generation point-of-care diagnostics. Front Cell Infect. Microbiol. 2021, 11, 663949. [Google Scholar] [CrossRef] [PubMed]
  194. Casati, B.; Verdi, J.P.; Hempelmann, A.; Kittel, M.; Klaebisch, A.G.; Meister, B.; Welker, S.; Asthana, S.; Di Giorgio, S.; Boskovic, P.; et al. Rapid, adaptable and sensitive Cas13-based COVID-19 diagnostics using ADESSO. Nat. Commun. 2022, 13, 3308. [Google Scholar] [CrossRef] [PubMed]
  195. Fozouni, P.; Son, S.; Diaz de Leon Derby, M.; Knott, G.J.; Gray, C.N.; D’Ambrosio, M.V.; Zhao, C.; Switz, N.A.; Kumar, G.R.; Stephens, S.I.; et al. Amplification-free detection of SARS-CoV-2 with CRISPR-Cas13a and mobile phone microscopy. Cell 2021, 184, 323–333. [Google Scholar] [CrossRef] [PubMed]
  196. Eisenstein, M. Seven technologies to watch in 2022. Nature 2022, 601, 658–661. [Google Scholar] [CrossRef] [PubMed]
  197. Frese, K.S.; Katus, H.A.; Meder, B. Next-generation sequencing: From understanding biology to personalized medicine. Biology 2013, 2, 378–398. [Google Scholar] [CrossRef]
  198. Wang, Z.; Gerstein, M.; Snyder, M. Rna-seq: A revolutionary tool for transcriptomics. Nat. Rev. Genet. 2009, 10, 57–63. [Google Scholar] [CrossRef]
  199. Wang, Y.; Mashock, M.; Tong, Z.; Mu, X.; Chen, H.; Zhou, X.; Zhang, H.; Zhao, G.; Liu, B.; Li, X. Changing technologies of RNA sequencing and their applications in clinical oncology. Front Oncol. 2020, 10, 447. [Google Scholar] [CrossRef]
  200. Hong, M.; Tao, S.; Zhang, L.; Diao, L.T.; Huang, X.; Huang, S.; Xie, S.J.; Xiao, Z.D.; Zhang, H. RNA sequencing: New technologies and applications in cancer research. J. Hematol. Oncol. 2020, 13, 166. [Google Scholar] [CrossRef]
  201. Colgan, A.M.; Cameron, A.D.; Kroger, C. If it transcribes, we can sequence it: Mining the complexities of host-pathogen-environment interactions using RNA-seq. Curr. Opin. Microbiol. 2017, 36, 37–46. [Google Scholar] [CrossRef]
  202. Saliba, A.E.; Santos, C.S.; Vogel, J. New RNA-seq approaches for the study of bacterial pathogens. Curr. Opin. Microbiol. 2017, 35, 78–87. [Google Scholar] [CrossRef]
  203. Pobre, V.; Graca-Lopes, G.; Saramago, M.; Ankenbauer, A.; Takors, R.; Arraiano, C.M.; Viegas, S.C. Prediction of novel non-coding RNAs relevant for the growth of Pseudomonas putida in a bioreactor. Microbiology 2020, 166, 149–156. [Google Scholar] [CrossRef] [PubMed]
  204. Viegas, S.C.; Apura, P.; Martinez-Garcia, E.; de Lorenzo, V.; Arraiano, C.M. Modulating heterologous gene expression with portable mRNA-stabilizing 5′-UTR sequences. ACS Synth. Biol. 2018, 7, 2177–2188. [Google Scholar] [CrossRef] [PubMed]
  205. Salihoglu, R.; Onal-Suzek, T. Tissue microbiome associated with human diseases by whole transcriptome sequencing and 16S metagenomics. Front Genet. 2021, 12, 585556. [Google Scholar] [CrossRef] [PubMed]
  206. Smith, S.E.; Huang, W.; Tiamani, K.; Unterer, M.; Khan Mirzaei, M.; Deng, L. Emerging technologies in the study of the virome. Curr. Opin. Virol. 2022, 54, 101231. [Google Scholar] [CrossRef] [PubMed]
  207. Li, J.; Wang, Y.; Du, Y.; Zhang, H.; Fan, Q.; Sun, L.; Yi, L.; Wang, S. mRNA-seq reveals the quorum sensing system LuxS gene contributes to the environmental fitness of Streptococcus suis type 2. BMC Microbiol. 2021, 21, 111. [Google Scholar] [CrossRef]
  208. Moll, P.; Ante, M.; Seitz, A.; Reda, T. Quantseq 3′ mRNA sequencing for RNA quantification. Nat. Methods 2014, 11, i–iii. [Google Scholar] [CrossRef]
  209. Oh, S.J.; Gim, J.A.; Lee, J.K.; Park, H.; Shin, O.S. Coxsackievirus B3 infection of human neural progenitor cells results in distinct expression patterns of innate immune genes. Viruses 2020, 12, 325. [Google Scholar] [CrossRef]
  210. Bermudez-Barrientos, J.R.; Ramirez-Sanchez, O.; Chow, F.W.; Buck, A.H.; Abreu-Goodger, C. Disentangling sRNA-seq data to study RNA communication between species. Nucleic Acids Res. 2020, 48, e21. [Google Scholar] [CrossRef]
  211. Antoine, L.; Bahena-Ceron, R.; Devi Bunwaree, H.; Gobry, M.; Loegler, V.; Romby, P.; Marzi, S. RNA modifications in pathogenic bacteria: Impact on host adaptation and virulence. Genes 2021, 12, 1125. [Google Scholar] [CrossRef]
  212. Motorin, Y.; Marchand, V. Analysis of RNA modifications by second- and third-generation deep sequencing: 2020 update. Genes 2021, 12, 278. [Google Scholar] [CrossRef]
  213. Kimura, S.; Dedon, P.C.; Waldor, M.K. Comparative tRNA sequencing and RNA mass spectrometry for surveying tRNA modifications. Nat. Chem. Biol. 2020, 16, 964–972. [Google Scholar] [CrossRef] [PubMed]
  214. Cahova, H.; Winz, M.L.; Hofer, K.; Nubel, G.; Jaschke, A. NAD captureseq indicates NAD as a bacterial cap for a subset of regulatory RNAs. Nature 2015, 519, 374–377. [Google Scholar] [CrossRef] [PubMed]
  215. Morales-Filloy, H.G.; Zhang, Y.; Nubel, G.; George, S.E.; Korn, N.; Wolz, C.; Jaschke, A. The 5′ NAD cap of RNAIII modulates toxin production in Staphylococcus aureus isolates. J. Bacteriol. 2020, 202, e00591-19. [Google Scholar] [CrossRef]
  216. Deng, X.; Chen, K.; Luo, G.Z.; Weng, X.; Ji, Q.; Zhou, T.; He, C. Widespread occurrence of N6-methyladenosine in bacterial mRNA. Nucleic Acids Res. 2015, 43, 6557–6567. [Google Scholar] [CrossRef] [PubMed]
  217. Melamed, S.; Peer, A.; Faigenbaum-Romm, R.; Gatt, Y.E.; Reiss, N.; Bar, A.; Altuvia, Y.; Argaman, L.; Margalit, H. Global mapping of small RNA-target interactions in bacteria. Mol. Cell 2016, 63, 884–897. [Google Scholar] [CrossRef]
  218. Hor, J.; Garriss, G.; Di Giorgio, S.; Hack, L.M.; Vanselow, J.T.; Forstner, K.U.; Schlosser, A.; Henriques-Normark, B.; Vogel, J. Grad-seq in a gram-positive bacterium reveals exonucleolytic sRNA activation in competence control. EMBO J. 2020, 39, e103852. [Google Scholar] [CrossRef] [PubMed]
  219. Jovic, D.; Liang, X.; Zeng, H.; Lin, L.; Xu, F.; Luo, Y. Single-cell RNA sequencing technologies and applications: A brief overview. Clin. Transl. Med. 2022, 12, e694. [Google Scholar] [CrossRef]
  220. Hoffman, D.; Tevet, Y.; Trzebanski, S.; Rosenberg, G.; Vainman, L.; Solomon, A.; Hen-Avivi, S.; Ben-Moshe, N.B.; Avraham, R. A non-classical monocyte-derived macrophage subset provides a splenic replication niche for intracellular Salmonella. Immunity 2021, 54, 2712–2723e2716. [Google Scholar] [CrossRef]
  221. SoRelle, E.D.; Dai, J.; Reinoso-Vizcaino, N.M.; Barry, A.P.; Chan, C.; Luftig, M.A. Time-resolved transcriptomes reveal diverse B cell fate trajectories in the early response to Epstein-Barr virus infection. Cell Rep. 2022, 40, 111286. [Google Scholar] [CrossRef]
  222. Imdahl, F.; Vafadarnejad, E.; Homberger, C.; Saliba, A.E.; Vogel, J. Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria. Nat. Microbiol. 2020, 5, 1202–1206. [Google Scholar] [CrossRef]
  223. Pan, Y.; Cao, W.; Mu, Y.; Zhu, Q. Microfluidics facilitates the development of single-cell RNA sequencing. Biosensors 2022, 12, 450. [Google Scholar] [CrossRef] [PubMed]
  224. Sharma, C.M.; Hoffmann, S.; Darfeuille, F.; Reignier, J.; Findeiss, S.; Sittka, A.; Chabas, S.; Reiche, K.; Hackermuller, J.; Reinhardt, R.; et al. The primary transcriptome of the major human pathogen Helicobacter pylori. Nature 2010, 464, 250–255. [Google Scholar] [CrossRef] [PubMed]
  225. Papenfort, K.; Forstner, K.U.; Cong, J.P.; Sharma, C.M.; Bassler, B.L. Differential RNA-seq of Vibrio cholerae identifies the VqmR small RNA as a regulator of biofilm formation. Proc. Natl. Acad. Sci. USA 2015, 112, E766–E775. [Google Scholar] [CrossRef] [PubMed]
  226. Cervantes-Rivera, R.; Puhar, A. Whole-genome identification of transcriptional start sites by differential RNA-seq in bacteria. Bio. Protoc. 2020, 10, e3757. [Google Scholar] [CrossRef] [PubMed]
  227. Fuchs, M.; Lamm-Schmidt, V.; Sulzer, J.; Ponath, F.; Jenniches, L.; Kirk, J.A.; Fagan, R.P.; Barquist, L.; Vogel, J.; Faber, F. An RNA-centric global view of Clostridioides difficile reveals broad activity ofHfq in a clinically important gram-positive bacterium. Proc. Natl. Acad. Sci. USA 2021, 118, e2103579118. [Google Scholar] [CrossRef] [PubMed]
  228. Wolf, T.; Kammer, P.; Brunke, S.; Linde, J. Two’s company: Studying interspecies relationships with dual RNA-seq. Curr. Opin. Microbiol 2018, 42, 7–12. [Google Scholar] [CrossRef] [PubMed]
  229. Thanert, R.; Goldmann, O.; Beineke, A.; Medina, E. Host-inherent variability influences the transcriptional response of Staphylococcus aureus during in vivo infection. Nat. Commun. 2017, 8, 14268. [Google Scholar] [CrossRef]
  230. Westermann, A.J.; Forstner, K.U.; Amman, F.; Barquist, L.; Chao, Y.; Schulte, L.N.; Muller, L.; Reinhardt, R.; Stadler, P.F.; Vogel, J. Dual RNA-seq unveils noncoding RNA functions in host-pathogen interactions. Nature 2016, 529, 496–501. [Google Scholar] [CrossRef]
  231. Lopez-Agudelo, V.A.; Baena, A.; Barrera, V.; Cabarcas, F.; Alzate, J.F.; Beste, D.J.V.; Rios-Estepa, R.; Barrera, L.F. Dual RNA sequencing of Mycobacterium tuberculosis-infected human splenic macrophages reveals a strain-dependent host-pathogen response to infection. Int. J. Mol. Sci. 2022, 23, 1803. [Google Scholar] [CrossRef]
  232. Maulding, N.D.; Seiler, S.; Pearson, A.; Kreusser, N.; Stuart, J.M. Dual RNA-seq analysis of SARS-CoV-2 correlates specific human transcriptional response pathways directly to viral expression. Sci. Rep. 2022, 12, 1329. [Google Scholar] [CrossRef]
  233. Avital, G.; Avraham, R.; Fan, A.; Hashimshony, T.; Hung, D.T.; Yanai, I. Scdual-seq: Mapping the gene regulatory program of Salmonella infection by host and pathogen single-cell RNA-sequencing. Genome Biol. 2017, 18, 200. [Google Scholar] [CrossRef] [PubMed]
  234. Seelbinder, B.; Wallstabe, J.; Marischen, L.; Weiss, E.; Wurster, S.; Page, L.; Loffler, C.; Bussemer, L.; Schmitt, A.L.; Wolf, T.; et al. Triple RNA-seq reveals synergy in a human virus-fungus co-infection model. Cell Rep. 2020, 33, 108389. [Google Scholar] [CrossRef] [PubMed]
  235. Schadt, E.E.; Turner, S.; Kasarskis, A. A window into third-generation sequencing. Hum. Mol. Genet. 2010, 19, R227–R240. [Google Scholar] [CrossRef] [PubMed]
  236. Goodwin, S.; McPherson, J.D.; McCombie, W.R. Coming of age: Ten years of next-generation sequencing technologies. Nat. Rev. Genet. 2016, 17, 333–351. [Google Scholar] [CrossRef] [PubMed]
  237. Sater, M.R.; Lamelas, A.; Wang, G.; Clark, T.A.; Roltgen, K.; Mane, S.; Korlach, J.; Pluschke, G.; Schmid, C.D. DNA methylation assessed by SMRT sequencing is linked to mutations in Neisseria meningitidis isolates. PLoS ONE 2015, 10, e0144612. [Google Scholar] [CrossRef] [PubMed]
  238. Han, S.; Liu, J.; Li, M.; Zhang, Y.; Duan, X.; Chen, H.; Cai, Z.; Yang, L.; Liu, Y. DNA methyltransferase regulates nitric oxide homeostasis and virulence in a chronically adapted Pseudomonas aeruginosa strain. mSystems 2022, 7, e0043422. [Google Scholar] [CrossRef]
  239. Depledge, D.P.; Srinivas, K.P.; Sadaoka, T.; Bready, D.; Mori, Y.; Placantonakis, D.G.; Mohr, I.; Wilson, A.C. Direct RNA sequencing on nanopore arrays redefines the transcriptional complexity of a viral pathogen. Nat. Commun. 2019, 10, 754. [Google Scholar] [CrossRef]
  240. Tan, S.; Dvorak, C.M.T.; Murtaugh, M.P. Characterization of emerging swine viral diseases through oxford nanopore sequencing using senecavirus a as a model. Viruses 2020, 12, 1136. [Google Scholar] [CrossRef]
  241. Tombacz, D.; Prazsak, I.; Csabai, Z.; Moldovan, N.; Denes, B.; Snyder, M.; Boldogkoi, Z. Long-read assays shed new light on the transcriptome complexity of a viral pathogen. Sci. Rep. 2020, 10, 13822. [Google Scholar] [CrossRef]
  242. Zhao, N.; Cao, J.; Xu, J.; Liu, B.; Chen, D.; Xia, B.; Chen, L.; Zhang, W.; Zhang, Y.; Zhang, X.; et al. Targeting RNA with next- and third-generation sequencing improves pathogen identification in clinical samples. Adv. Sci. 2021, 8, e2102593. [Google Scholar] [CrossRef]
  243. Avershina, E.; Frye, S.A.; Ali, J.; Taxt, A.M.; Ahmad, R. Ultrafast and cost-effective pathogen identification and resistance gene detection in a clinical setting using nanopore flongle sequencing. Front Microbiol. 2022, 13, 822402. [Google Scholar] [CrossRef] [PubMed]
  244. Natesan Pushparaj, P.; Damiati, L.A.; Denetiu, I.; Bakhashab, S.; Asif, M.; Hussain, A.; Ahmed, S.; Hamdard, M.H.; Rasool, M. Deciphering SARS-CoV-2-associated pathways from RNA sequencing data of COVID-19-infected A549 cells and potential therapeutics using in silico methods. Medicine 2022, 101, e29554. [Google Scholar] [CrossRef] [PubMed]
  245. Andersson, J.A.; Peniche, A.G.; Galindo, C.L.; Boonma, P.; Sha, J.; Luna, R.A.; Savidge, T.C.; Chopra, A.K.; Dann, S.M. New host-directed therapeutics for the treatment of Clostridioides difficile infection. MBio 2020, 11, e00053-20. [Google Scholar] [CrossRef] [PubMed]
  246. Afgan, E.; Baker, D.; van den Beek, M.; Blankenberg, D.; Bouvier, D.; Cech, M.; Chilton, J.; Clements, D.; Coraor, N.; Eberhard, C.; et al. The galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update. Nucleic Acids Res. 2016, 44, W3–W10. [Google Scholar] [CrossRef] [PubMed]
  247. Henderson, C.A.; Vincent, H.A.; Callaghan, A.J. Reprogramming gene expression by targeting RNA-based interactions: A novel pipeline utilizing RNA array technology. ACS Synth. Biol. 2021, 10, 1847–1858. [Google Scholar] [CrossRef]
  248. Walsh, E.E.; Frenck, R.W., Jr.; Falsey, A.R.; Kitchin, N.; Absalon, J.; Gurtman, A.; Lockhart, S.; Neuzil, K.; Mulligan, M.J.; Bailey, R.; et al. Safety and immunogenicity of two RNA-based COVID-19 vaccine candidates. N. Engl. J. Med. 2020, 383, 2439–2450. [Google Scholar] [CrossRef]
  249. Hegarty, J.P.; Stewart, D.B. Advances in therapeutic bacterial antisense biotechnology. Appl. Microbiol. Biotechnol. 2018, 102, 1055–1065. [Google Scholar] [CrossRef]
  250. Sully, E.K.; Geller, B.L. Antisense antimicrobial therapeutics. Curr. Opin Microbiol. 2016, 33, 47–55. [Google Scholar] [CrossRef]
  251. Hammond, S.M.; Aartsma-Rus, A.; Alves, S.; Borgos, S.E.; Buijsen, R.A.M.; Collin, R.W.J.; Covello, G.; Denti, M.A.; Desviat, L.R.; Echevarría, L.; et al. Delivery of oligonucleotide-based therapeutics: Challenges and opportunities. EMBO Mol. Med. 2021, 13, e13243. [Google Scholar] [CrossRef]
  252. Schafer, M.E.; Browne, H.; Goldberg, J.B.; Greenberg, D.E. Peptides and Antibiotic Therapy: Advances in Design and Delivery. Accounts of Chemical Research. 2021, 54, 2377–2385. [Google Scholar] [CrossRef]
  253. Geller, B.L.; Li, L.; Martinez, F.; Sully, E.; Sturge, C.R.; Daly, S.M.; Pybus, C.; Greenberg, D.E. Morpholino oligomers tested in vitro, in biofilm and in vivo against multidrug-resistant Klebsiella pneumoniae. J. Antimicrob. Chemother. 2018, 73, 1611–1619. [Google Scholar] [CrossRef] [PubMed]
  254. Wesolowski, D.; Alonso, D.; Altman, S. Combined effect of a peptide-morpholino oligonucleotide conjugate and a cell-penetrating peptide as an antibiotic. Proc. Natl. Acad. Sci. USA 2013, 110, 8686–8689. [Google Scholar] [CrossRef] [PubMed]
  255. Nielsen, P.E.; Egholm, M. An introduction to peptide nucleic acid. Curr. Issues Mol. Biol. 1999, 1, 89–104. [Google Scholar] [PubMed]
  256. Good, L.; Awasthi, S.K.; Dryselius, R.; Larsson, O.; Nielsen, P.E. Bactericidal antisense effects of peptide–PNA conjugates. Nat. Biotechnol. 2001, 19, 360–364. [Google Scholar] [CrossRef]
  257. Nekhotiaeva, N.; Awasthi, S.K.; Nielsen, P.E.; Good, L. Inhibition of Staphylococcus aureus gene expression and growth using antisense peptide nucleic acids. Mol. Ther. 2004, 10, 652–659. [Google Scholar] [CrossRef]
  258. Yan, M.; Sahin, O.; Lin, J.; Zhang, Q. Role of the CmeABC efflux pump in the emergence of fluoroquinolone-resistant Campylobacter under selection pressure. J. Antimicrob. Chemother. 2006, 58, 1154–1159. [Google Scholar] [CrossRef]
  259. Oh, E.; Zhang, Q.; Jeon, B. Target optimization for peptide nucleic acid (PNA)-mediated antisense inhibition of the CmeABC multidrug efflux pump in Campylobacter jejuni. J. Antimicrob. Chemother. 2013, 69, 375–380. [Google Scholar] [CrossRef]
  260. Doessing, H.; Vester, B. Locked and unlocked nucleosides in functional nucleic acids. Molecules 2011, 16, 4511–4526. [Google Scholar] [CrossRef]
  261. Liang, S.; He, Y.; Xia, Y.; Wang, H.; Wang, L.; Gao, R.; Zhang, M. Inhibiting the growth of methicillin-resistant Staphylococcus aureus in vitro with antisense peptide nucleic acid conjugates targeting the ftsZ gene. Int. J. Infect. Dis. 2015, 30, 1–6. [Google Scholar] [CrossRef]
  262. Meng, J.; Da, F.; Ma, X.; Wang, N.; Wang, Y.; Zhang, H.; Li, M.; Zhou, Y.; Xue, X.; Hou, Z.; et al. Antisense growth inhibition of methicillin-resistant Staphylococcus aureus by locked nucleic acid conjugated with cell-penetrating peptide as a novel FtsZ inhibitor. Antimicrob. Agents Chemother. 2015, 59, 914–922. [Google Scholar] [CrossRef]
  263. Khvorova, A.; Watts, J.K. The chemical evolution of oligonucleotide therapies of clinical utility. Nat. Biotechnol. 2017, 35, 238–248. [Google Scholar] [CrossRef] [PubMed]
  264. Moustafa, D.A.; Wu, A.W.; Zamora, D.; Daly, S.M.; Sturge, C.R.; Pybus, C.; Geller, B.L.; Goldberg, J.B.; Greenberg, D.E. Peptide-conjugated phosphorodiamidate morpholino oligomers retain activity against multidrug-resistant Pseudomonas aeruginosa in vitro and in vivo. mBio 2021, 12, e02411-20. [Google Scholar] [CrossRef] [PubMed]
  265. Traykovska, M.; Penchovsky, R. Engineering antisense oligonucleotides as antibacterial agents that target FMN riboswitches and inhibit the growth of Staphylococcus aureus, Listeria monocytogenes, and Escherichia coli. ACS Synth. Biol. 2022, 11, 1845–1855. [Google Scholar] [CrossRef] [PubMed]
  266. Cullen, B.R. Viruses and RNA interference: Issues and controversies. J. Virol. 2014, 88, 12934–12936. [Google Scholar] [CrossRef]
  267. Bitko, V.; Barik, S. Phenotypic silencing of cytoplasmic genes using sequence-specific double-stranded short interfering RNA and its application in the reverse genetics of wild type negative-strand RNA viruses. BMC Microbiol. 2001, 1, 34. [Google Scholar] [CrossRef]
  268. Levanova, A.; Poranen, M.M. RNA interference as a prospective tool for the control of human viral infections. Front. Microbiol. 2018, 9, 2151. [Google Scholar] [CrossRef]
  269. Wu, C.J.; Huang, H.W.; Liu, C.Y.; Hong, C.F.; Chan, Y.L. Inhibition of SARS-CoV replication by siRNA. Antivir. Res 2005, 65, 45–48. [Google Scholar] [CrossRef]
  270. Baldassi, D.; Ambike, S.; Feuerherd, M.; Cheng, C.C.; Peeler, D.J.; Feldmann, D.P.; Porras-Gonzalez, D.L.; Wei, X.; Keller, L.A.; Kneidinger, N.; et al. Inhibition of SARS-CoV-2 replication in the lung with siRNA/VIPER polyplexes. J. Control. Release 2022, 345, 661–674. [Google Scholar] [CrossRef]
  271. DeVincenzo, J.; Lambkin-Williams, R.; Wilkinson, T.; Cehelsky, J.; Nochur, S.; Walsh, E.; Meyers, R.; Gollob, J.; Vaishnaw, A. A randomized, double-blind, placebo-controlled study of an RNAi-based therapy directed against respiratory syncytial virus. Proc. Natl. Acad. Sci. USA 2010, 107, 8800–8805. [Google Scholar] [CrossRef]
  272. Chandra, P.K.; Kundu, A.K.; Hazari, S.; Chandra, S.; Bao, L.L.; Ooms, T.; Morris, G.F.; Wu, T.; Mandel, T.K.; Dash, S. Inhibition of hepatitis Cvirus replication by intracellular delivery of multiple siRNAs by nanosomes. Mol. Ther. 2012, 20, 1724–1736. [Google Scholar] [CrossRef]
  273. Gottlieb, J.; Zamora, M.R.; Hodges, T.; Musk, A.W.; Sommerwerk, U.; Dilling, D.; Arcasoy, S.; DeVincenzo, J.; Karsten, V.; Shah, S.; et al. ALN-RSV01 for prevention of bronchiolitis obliterans syndrome after respiratory syncytial virus infection in lung transplant recipients. J. Heart Lung Transpl. 2016, 35, 213–221. [Google Scholar] [CrossRef] [PubMed]
  274. Kubowicz, P.; Zelaszczyk, D.; Pekala, E. RNAi in clinical studies. Curr. Med. Chem 2013, 20, 1801–1816. [Google Scholar] [CrossRef] [PubMed]
  275. Yang, L.; Tang, L.; Zhang, M.; Liu, C. Recent advances in the molecular design and delivery technology of mRNA for vaccination against infectious diseases. Front Immunol. 2022, 13, 896958. [Google Scholar] [CrossRef] [PubMed]
  276. Zhang, C.; Maruggi, G.; Shan, H.; Li, J. Advances in mRNA vaccines for infectious diseases. Front Immunol. 2019, 10, 594. [Google Scholar] [CrossRef] [PubMed]
  277. Jirikowski, G.F.; Sanna, P.P.; Maciejewski-Lenoir, D.; Bloom, F.E. Reversal of diabetes insipidus in Brattleboro rats: Intrahypothalamic injection of vasopressin mRNA. Science 1992, 255, 996–998. [Google Scholar] [CrossRef] [PubMed]
  278. Dolgin, E. The tangled history of mRNA vaccines. Nature 2021, 597, 318–324. [Google Scholar] [CrossRef] [PubMed]
  279. Malone, R.W.; Felgner, P.L.; Verma, I.M. Cationic liposome-mediated RNA transfection. Proc. Natl. Acad. Sci. USA 1989, 86, 6077–6081. [Google Scholar] [CrossRef]
  280. Conry, R.M.; LoBuglio, A.F.; Wright, M.; Sumerel, L.; Pike, M.J.; Johanning, F.; Benjamin, R.; Lu, D.; Curiel, D.T. Characterization of a messenger RNA polynucleotide vaccine vector. Cancer Res. 1995, 55, 1397–1400. [Google Scholar]
  281. Bailey, A.L.; Cullis, P.R. Membrane fusion with cationic liposomes: Effects of target membrane lipid composition. Biochemistry 1997, 36, 1628–1634. [Google Scholar] [CrossRef]
  282. Kariko, K.; Muramatsu, H.; Ludwig, J.; Weissman, D. Generating the optimal mRNA for therapy: HPLC purification eliminates immune activation and improves translation of nucleoside-modified, protein-encoding mRNA. Nucleic Acids Res. 2011, 39, e142. [Google Scholar] [CrossRef]
  283. Kariko, K.; Muramatsu, H.; Welsh, F.A.; Ludwig, J.; Kato, H.; Akira, S.; Weissman, D. Incorporation of pseudouridine into mRNA yields superior nonimmunogenic vector with increased translational capacity and biological stability. Mol. Ther. 2008, 16, 1833–1840. [Google Scholar] [CrossRef] [PubMed]
  284. Andries, O.; Mc Cafferty, S.; De Smedt, S.C.; Weiss, R.; Sanders, N.N.; Kitada, T. N-1-methylpseudouridine-incorporated mRNA outperforms pseudouridine-incorporated mRNA by providing enhanced protein expression and reduced immunogenicity in mammalian cell lines and mice. J. Control. Release 2015, 217, 337–344. [Google Scholar] [CrossRef] [PubMed]
  285. Geall, A.J.; Verma, A.; Otten, G.R.; Shaw, C.A.; Hekele, A.; Banerjee, K.; Cu, Y.; Beard, C.W.; Brito, L.A.; Krucker, T.; et al. Nonviral delivery of self-amplifying RNA vaccines. Proc. Natl. Acad. Sci. USA 2012, 109, 14604–14609. [Google Scholar] [CrossRef] [PubMed]
  286. Corbett, K.S.; Edwards, D.K.; Leist, S.R.; Abiona, O.M.; Boyoglu-Barnum, S.; Gillespie, R.A.; Himansu, S.; Schafer, A.; Ziwawo, C.T.; DiPiazza, A.T.; et al. SARS-CoV-2 mRNA vaccine design enabled by prototype pathogen preparedness. Nature 2020, 586, 567–571. [Google Scholar] [CrossRef]
  287. Bogers, W.M.; Oostermeijer, H.; Mooij, P.; Koopman, G.; Verschoor, E.J.; Davis, D.; Ulmer, J.B.; Brito, L.A.; Cu, Y.; Banerjee, K.; et al. Potent immune responses in rhesus macaques induced by nonviral delivery of a self-amplifying RNA vaccine expressing HIV type 1 envelope with a cationic nanoemulsion. J. Infect. Dis. 2015, 211, 947–955. [Google Scholar] [CrossRef]
  288. Pollard, R.B.; Rockstroh, J.K.; Pantaleo, G.; Asmuth, D.M.; Peters, B.; Lazzarin, A.; Garcia, F.; Ellefsen, K.; Podzamczer, D.; van Lunzen, J.; et al. Safety and efficacy of the peptide-based therapeutic vaccine for Hiv-1, Vacc-4x: A phase 2 randomised, double-blind, placebo-controlled trial. Lancet Infect. Dis. 2014, 14, 291–300. [Google Scholar] [CrossRef]
  289. Flynn, N.M.; Forthal, D.N.; Harro, C.D.; Judson, F.N.; Mayer, K.H.; Para, M.F. Placebo-controlled phase 3 trial of a recombinant glycoprotein 120 vaccine to prevent HIV-1 infection. J. Infect. Dis. 2005, 191, 654–665. [Google Scholar]
  290. Steichen, J.M.; Kulp, D.W.; Tokatlian, T.; Escolano, A.; Dosenovic, P.; Stanfield, R.L.; McCoy, L.E.; Ozorowski, G.; Hu, X.; Kalyuzhniy, O.; et al. HIV vaccine design to target germline precursors of glycan-dependent broadly neutralizing antibodies. Immunity 2016, 45, 483–496. [Google Scholar] [CrossRef]
  291. Pardi, N.; Carreno, J.M.; O’Dell, G.; Tan, J.; Bajusz, C.; Muramatsu, H.; Rijnink, W.; Strohmeier, S.; Loganathan, M.; Bielak, D.; et al. Development of a pentavalent broadly protective nucleoside-modified mRNA vaccine against influenza B viruses. Nat Commun 2022, 13, 4677. [Google Scholar] [CrossRef]
  292. Feldman, R.A.; Fuhr, R.; Smolenov, I.; Mick Ribeiro, A.; Panther, L.; Watson, M.; Senn, J.J.; Smith, M.; Almarsson, Ö.; Pujar, H.S.; et al. mRNA vaccines against H10N8 and H7N9 influenza viruses of pandemic potential are immunogenic and well tolerated in healthy adults in phase 1 randomized clinical trials. Vaccine 2019, 37, 3326–3334. [Google Scholar] [CrossRef]
  293. Scorza, F.B.; Pardi, N. New kids on the block: RNA-based influenza virus vaccines. Vaccines 2018, 6, 20. [Google Scholar] [CrossRef] [PubMed]
  294. Maruggi, G.; Chiarot, E.; Giovani, C.; Buccato, S.; Bonacci, S.; Frigimelica, E.; Margarit, I.; Geall, A.; Bensi, G.; Maione, D. Immunogenicity and protective efficacy induced by self-amplifying mRNA vaccines encoding bacterial antigens. Vaccine 2017, 35, 361–368. [Google Scholar] [CrossRef] [PubMed]
  295. Meyer, M.; Huang, E.; Yuzhakov, O.; Ramanathan, P.; Ciaramella, G.; Bukreyev, A. Modified mRNA-based vaccines elicit robust immune responses and protect guinea pigs from ebola virus disease. J. Infect. Dis. 2018, 217, 451–455. [Google Scholar] [CrossRef] [PubMed]
  296. Kowalzik, F.; Schreiner, D.; Jensen, C.; Teschner, D.; Gehring, S.; Zepp, F. mRNA-based vaccines. Vaccines 2021, 9, 390. [Google Scholar] [CrossRef]
Figure 3. CRISPR technologies. (A) CRISPR-based antimicrobials. The system has been successfully tested through the directed degradation of the antibiotic resistance gene located in a plasmid (left side) leading to the recovery of the bacterial antibiotic sensitivity or the directed degradation of chromosomal genes, and consequently, cell death (bactericidal) [186]. (B) CRISPR-based diagnostics. When CRISPR effector proteins (Cas) recognize the specific target site, their collateral cleavage capability is triggered (this indiscriminate nucleic acid cleavage only happens when the crRNA finds its match). The addition of a reporter, that only releases the signal upon cleavage, enables the emission of a signal that can be easily detected [187]. Figure created using BioRender.com (accessed on 11 November 2022).
Figure 3. CRISPR technologies. (A) CRISPR-based antimicrobials. The system has been successfully tested through the directed degradation of the antibiotic resistance gene located in a plasmid (left side) leading to the recovery of the bacterial antibiotic sensitivity or the directed degradation of chromosomal genes, and consequently, cell death (bactericidal) [186]. (B) CRISPR-based diagnostics. When CRISPR effector proteins (Cas) recognize the specific target site, their collateral cleavage capability is triggered (this indiscriminate nucleic acid cleavage only happens when the crRNA finds its match). The addition of a reporter, that only releases the signal upon cleavage, enables the emission of a signal that can be easily detected [187]. Figure created using BioRender.com (accessed on 11 November 2022).
Microorganisms 10 02303 g003
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Costa, V.G.; Costa, S.M.; Saramago, M.; Cunha, M.V.; Arraiano, C.M.; Viegas, S.C.; Matos, R.G. Developing New Tools to Fight Human Pathogens: A Journey through the Advances in RNA Technologies. Microorganisms 2022, 10, 2303. https://doi.org/10.3390/microorganisms10112303

AMA Style

Costa VG, Costa SM, Saramago M, Cunha MV, Arraiano CM, Viegas SC, Matos RG. Developing New Tools to Fight Human Pathogens: A Journey through the Advances in RNA Technologies. Microorganisms. 2022; 10(11):2303. https://doi.org/10.3390/microorganisms10112303

Chicago/Turabian Style

Costa, Vanessa G., Susana M. Costa, Margarida Saramago, Marta V. Cunha, Cecília M. Arraiano, Sandra C. Viegas, and Rute G. Matos. 2022. "Developing New Tools to Fight Human Pathogens: A Journey through the Advances in RNA Technologies" Microorganisms 10, no. 11: 2303. https://doi.org/10.3390/microorganisms10112303

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop