From the simplest organism to the most complex, RNA contributes to the intricate regulatory processes that are mounted in response to stress, environmental changes or as part of intricate programs of development. Throughout all domains of life, regulatory RNA can affect the expression of genetic information by modulating the rates of messen- ger RNA translation and decay (1,2). In the model bacte- ria Escherichia coli and Bacillus subtilis, RNA-based reg- ulation (riboregulation) is mediated by ribonucleases that function also in general RNA turnover and processing of precursors into mature forms (3,4). For E. coli, the key en- zyme of RNA metabolism and riboregulation is RNase E, a conserved endoribonuclease which forms a large multi- enzyme complex, known as the degradosome, that incorpo- rates the DEAD-box helicase RhlB, the phosphorylytic ex- oribonuclease polynucleotide phosphorylase (PNPase) and the glycolytic enzyme enolase (5) (Figure 1). Auxiliary pro- teins, such as poly-A polymerase, are also recruited in sub- stoichiometric amounts depending on growth conditions (6) and may tailor and direct the activity of the degrado- some. In situ cross-linking followed by RNA deep sequenc- ing have cataloged hundreds of small regulatory RNAs (sR- NAs) and mRNAs that are associated with RNase E (7). The action of sRNAs in E. coli and numerous bacterial species is facilitated by RNA chaperones such as Hfq, which is a member of the widely occurring Sm / Lsm protein family (8,9). Hfq cooperates with RNase E to activate the cleavage of target RNAs that are tagged by cognate sRNAs (10,11).
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ABSTRACT Small regulatory RNAs play an important role in the adaptation to changing conditions. Here, we describe a differentially expressed small regulatory RNA (sRNA) that affects various cellular processes in the plant pathogen Agrobacte- rium tumefaciens. Using a combination of bioinformatic predictions and comparative proteomics, we identiﬁed nine targets, most of which are positively regulated by the sRNA. According to these targets, we named the sRNA PmaR for peptidoglycan bio- synthesis, motility, and ampicillin resistance regulator. Agrobacterium spp. are long known to be naturally resistant to high ampicillin concentrations, and we can now explain this phenotype by the positive PmaR-mediated regulation of the beta- lactamase gene ampC. Structure probing revealed a spoon-like structure of the sRNA, with a single-stranded loop that is engaged in target interaction in vivo and in vitro. Several riboregulators have been implicated in antibiotic resistance mecha- nisms, such as uptake and efﬂux transporters, but PmaR represents the ﬁrst example of an sRNA that directly controls the expression of an antibiotic resistance gene.
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In their natural habitats, bacteria constantly adapt to changing environmental conditions while simultaneously anticipating further disturbances. To efficiently cope with these changes, intri- cate interlinked metabolic and genetic regulation has evolved . This complex regulatory net- work includes the action of small regulatory RNAs (sRNAs) . sRNAs are a widespread means for bacterial cells to coordinate (stress) responses by fine-tuning levels of mRNAs or proteins, and they have been studied in great detail in Gram-negative bacteria . Regulation by some sRNAs takes place by short complementary base pairing to their target mRNA mole- cules, for instance in the region of the ribosome-binding site (RBS) to inhibit translation or trigger mRNA degradation. In Gram-negative bacteria many of these sRNA-mRNA interac- tions are mediated by the RNA chaperone Hfq . However, the Hfq homologue in the Gram- positive model bacterium Bacillus subtilis has no effect on the regulation of the eight sRNA tar- gets reported in this species so far [5–7]. Owing to the complexity of sRNA regulation, only a relatively small number of studies have focused specifically on the physiological necessity of sRNA-target interactions. This is again particularly true for Gram-positive bacteria, such as B. subtilis, despite the fact that many potential sRNAs have been identified [8, 9].
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The discovery of small non-coding RNAs, such as miRNA and piRNA, has dramatically changed our understanding of the role RNA plays in organisms. Recent studies show that a novel small non-coding RNA generated from cleavage of tRNA or pre-tRNA, called tRNA-derived small RNA (tsRNA), serves as a new regulator of gene expression. tsRNA has been determined participate in regulating some specific physiological and pathological processes. Although knowledge regarding the biological roles of miRNA and piRNA is expanding, whether tsRNAs play similar roles remains poorly understood. Here, we review the current knowledge regarding the mechanisms of action and biological functions of tsRNAs in intracellular, extracellular and intergenerational inheritance, and highlight the potential application of tsRNAs in human diseases, and present the current problems and future research directions.
oxidative stress, [1, 8, 12, 35, 36]. While phenotypic characterization of sRNA deletion mutants, including 10 gain-of-function phenotypes out of 27 mutants tested, confirmed their roles in metabolic regulation, stress adaptation and complex behavior [12, 36], their targets are still unknown with a few exceptions. Some of these exceptions comes from the study of M. mazei cultures grown under nitrogen starvation conditions where RNA-seq experiments revealed the differential expression of a number of sRNAs in response to nitrogen availability [23, 37]. This then resulted in the identification of the first in vivo targets for archaeal intergenic sRNAs [23, 37]. A potential target for one of these sRNAs, sRNA 162 , was a bicistronic mRNA encoding for a
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The regulators Fur and RyhB also play an important role in controlling Fe-S biogenesis (17). Fur, the iron sensor regulator, represses transcription of several genes involved in iron import and metabolism when it is bound to Fe (18). Fur also represses expression of the noncoding RNA (small RNA [sRNA]) RyhB. Under iron limitation, Fur repression is alleviated, and RyhB is synthesized and regulates, mostly negatively, the expression of more than 50 genes, the majority of which encode iron-containing proteins (19). Thus, RyhB is thought to reallocate bioavailable iron to essential targets, helping the cell to cope with iron scarcity (20). RyhB base pairs to the iscRSUA mRNA upstream of the iscS gene, inducing the degradation of the 3= part of the mRNA, while the 5= part containing iscR remains stable (17). In this way, RyhB favors the use of the Suf system during iron starvation. Notably, Fur also represses the suf operon, encoding the Suf system, thus contributing to switching from ISC to SUF under those conditions (21).
onstrated that 83 sRNAs are differentially expressed in TSB versus human serum (Tables 2 and 3). This represents 27% of the known sRNAs in strain USA300. It is not easy to interpret how their differential regulation affects the bacterial cell (because the bio- logical functions of most of them are unknown); however, certain inferences can be made. The newly identified tsr25 sRNA demon- strated a 582-fold increase in expression in human serum. It is tempting to speculate that increased expression of tsr25 in serum suggests that it plays an important role during S. aureus blood- stream infections. A small number of conserved, well-studied sRNAs were also among the differentially regulated sRNAs in se- rum. 4.5S RNA, a component of the signal recognition particle, was upregulated 12-fold in human serum, perhaps reflecting al- tered protein secretion and/or protein composition in the cell membrane in this environment. Another important cellular RNA that has been well explored is 6S RNA (ssrS), which we demon- strate also has a 12-fold increase in expression during growth in serum. In Escherichia coli, 6S RNA binds to the housekeeping sigma factor 70 and inhibits transcription from 70 -dependent
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Viral constructs. The molecular biology protocols used here followed those described by Sambrook et al. (37). Throughout this report, plasmids will be designated with a p subnotation, which will be omitted when discussing the corresponding transcripts or viral RNA. Plasmid pTBSV-100, a full-length in- fectious cDNA clone of a TBSV cherry isolate (19), was used to generate the mutants described in this report. For the construction of pTHB19, a reverse primer (5⬘-GGCTTCGAATTAGTGATGGTGATGGTGATGCTCGAAGGT TTGAGTACC-3⬘) was designed to add 18 nt at the BstBI site (underlined) located at nt 4385, followed by a PCR in combination with the forward primer (seq22A; 5⬘-GTGTCCTGCGAGGGGCC-3⬘) to amplify a TBSV fragment be- tween nt 3819 and 4385. For cloning of the PCR product, pKAN157⌬EcoRV (6) was used, which contains the BamHI (nt 2439)-to-SphI (nt 4801) fragment of pTBSV-100 but in which an internal EcoRV fragment (nt 3410 to nt 4101) was deleted to remove a BstBI site at nt 4036. This plasmid and the PCR product were both digested with HpaI and BstBI and then ligated to generate an inter- mediate construct, pKAN157⌬EcoRV-HB19. Subsequently, the HpaI-to-SalI fragment of pKAN157⌬EcoRV-HB19 was used to replace the same restriction fragment of pTBSV-100 to generate pTHB19. To construct pTHS19, a SacI site (underlined in the sequences below) was generated at the 3⬘ end of the p19 ORF of pHS49 (39) by oligonucleotide-directed mutagenesis with a primer (5⬘-GA AGGCGAGCTCGACAGACTC-3⬘) to produce pHS49/19S. The NcoI-to-SalI fragment of pTBSV-100 was replaced with the same fragment of pHS49/19S to generate an intermediate construct, pTS19, that contains the SacI site at the 3⬘ end of p19. To add 18 nt at the SacI site, a reverse primer (5⬘-GGCGAGCTCT TAGTGATGGTGATGGTGATGCTCGCCTTCTTTTTCG-3⬘) was used for a PCR with forward primer seq22A (positioned 20 nt upstream of the 5⬘ end of p22) to amplify the fragment between nt 3819 and 4403. This PCR product was
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have identiﬁed all functional regulatory variants in advance, investigators will be faced with the challenge of interpreting some of the strongest association signals. Many of the associ- ation studies have a multi-phase design, wherein a fraction of the SNPs with the top statistical signiﬁcance in the ﬁrst phase are genotyped in a subsequent phase in a new set of individ- uals. The statistical exercise must eventually give way to biological interpretation, however, and the identiﬁcation of the causal variant will be necessary. Although most of the conﬁrmed disease-causing variants are located in coding regions, this observation is due to an ascertainment bias in the ability to predict the potential functional consequences of nucleotide variation. As the human genome is composed of only , 3–5 per cent coding DNA, and studies increasingly attribute function to non-coding DNA, it might be expected that much of the disease-causing variation will be non-coding
In addition, we observed a very interesting enrichment distribution of the br isoforms. The Z1 isoform showed high enrichment in all four DHS dynamics, but predominantly in Tn-D. The Z2 and Z3 isoforms, instead, displayed Tn-D specificity. This finding is intriguing: it is known that the relative ratio of br isoforms accumulation is necessary for a context-dependent response to ecdysone (Emery et al., 1994), however our data suggest that they may also have distinct roles at the regulatory level. Z1 isoform could function more broadly, whereas Z2 and Z3 isoforms seem to specifically target closing DHSs. With regard to the latter, it is difficult to distinguish whether Z2 and Z3 isoforms directly act as repressors, or if their TFBSs simply need to be masked to avoid binding events. Br-Z2 was reported to have a repressive function in the fat body through biochemical experiments (Mugat et al., 2000), however in the same study br-Z3 was claimed to activate gene expression. In our knockdown experiment (Paragraph 4.2.3, also discussed in this chapter in paragraph 5.5) we show that the absence of all br isoforms indeed leads to lack of chromatin closing, pointing to the repressive action of br. Nevertheless, isoform-specific knockdowns of br would further elucidate its different roles in closing chromatin.
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CRISPR, a DNA segment with 20-50bp short repetitive sequences, was first discovered in 1987 , being found to be associated with a set of genes named CRISPR-associated genes-cas genes . There are three types (I-III) of CRISPR-Cas systems . Among them, the Type II CRISPR-Cas9 system is the first genome editing application in eukaryotic cells [34, 35] and the most widely used for genome editing. It consists of three components: the RNA-guided endonuclease Cas9 , the crRNA and the trans-activating crRNA (tracrRNA) . Therefore, it could recognize and cut the target double-stranded DNA using the Cas9 HNH and RuvC-like nuclease domains [38, 39]. For gene targeting applications, either dual-RNA guides or chimeric single-molecule guide RNAs (sgRNAs) [34, 35], [40-46] is indispensable. Several guide RNAs (gRNAs) ,- to target HBV of genotype A, B, C or D in vitro and in vivo have been designed (table 1).
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Library preparation and sequencing. Library preparation and sequencing were performed by the Wellcome Trust Centre for Human Genetics, Oxford. The rRNA-depleted fraction was selected from the total RNA provided before conversion to cDNA. Second-strand cDNA synthesis incorporated dUTP. The cDNA was then end repaired, A tailed, and adapter ligated. Prior to ampliﬁcation, samples underwent uridine digestion. The prepared libraries were size selected and multiplexed and subjected to quality control (QC) before 75-bp paired-end sequencing was performed over one lane of a ﬂow cell. Data were aligned to the reference genome and subjected to quality checks. Standard data ﬁles were provided as fastq and bam ﬁles. Quality control and adapter trimming were applied to the 368 million raw 75-bp paired-end Illumina reads using TrimGalore v0.4.2 with the parameters – q 20, –length 30, and –strin- gency 5 (https://www.bioinformatics.babraham.ac.uk/projects/trim_galore/). On average, ⬃ 0.01% of reads were removed per sample. Alignment-free mapping and quantiﬁcation of the reads with respect to the reference transcriptome for Paracoccus denitriﬁcans PD1222 were carried out using Kallisto v0.43.0; a k-mer size of 31 was used to build the transcriptome index, and the quantiﬁcation procedure used 100 bootstraps per sample ((27)). The reference transcriptome was obtained from Ensembl Bacteria as cDNA sequences in FASTA format. The R (v3.4.0) statistical software environment was used for the RNA-seq analyses. The bioconductor packages used were tximport v1.4.0 (28) (to summarize Kallisto’s transcript- level quantiﬁcation as matrices of counts) and DESeq2 v1.16.0 (29) (to analyze the differential expression levels of transcripts between conditions). The R packages ggplot2, ggrepel (https://CRAN.R-project.org/ package ⫽ ggrepel), and dplyr (https://CRAN.R-project.org/package ⫽ dplyr) were used for generating plots.
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C ancer is the leading cause of death worldwide. It is well known that genetic factors play a major role in the cancer pathogenesis, which is a complex, multifactorial disease. Researchers use quantitative methods for the analysis of nucleotide and protein sequence alterations in cancer and for the construction of mathematical models for oncogenes regulation. The patterns of the cell protein synthesis apparatus, many molecular, subcellular and cellular processes were revealed. A large number of mathematical attempts have appeared to describe the work of genes, genetic ensembles, and biosynthetic cell activity from various points of view. These attempts have been made to formalize the concept of oncogene, functional sections of the genome and genetic ensembles. However, already there are many years after the start of these studies, it can be stated that the development of generally acceptable formalizations and the identification of regulatory mechanisms of gene activity in cancer are still actual. The situation was especially aggravated after the discovery of the phenomena of overlapping codes, gene
We found many pathways associated with differentially expressed miRNA in ASD temporal cortex were similarly associated with nervous system and immune function, as well as basic cellular processes previously reported to be dysregulated in ASD. Of the 34 predicted pathways and processes that were represented in the target genes of miRNA in STS and PAC (Fig. 4), a number have been im- plicated in previous ASD studies including glutamatergic, dopaminergic, and cholinergic synapse pathways, axon guidance, synaptic vesicle cycling, neurotrophins, immune pathways, hedgehog and Wnt signaling, spliceosome, and RNA degradation [2–4, 27, 60]. Comparing our broader temporal cortex findings with previous analyses, it is not- able that 44 of the 75 pathways regulated by differentially expressed miRNA in our study are shared with the 57 path- ways reported to be affected by copy number variants in ASD  (Fig. 5, Additional file 1: Table S4). Moreover, we found 7 and 15 pathways, respectively, are shared with the 16 and 24 pathways reported to demonstrate alterations in the two prior analyses of mRNA expression ASD temporal cortex [4, 33] (Fig. 5). Common functions associated with pathways across all studies of ASD temporal cortex include cell cycle, metabolic, and neuron-related pathways and processes. Given the substantial number of convergent pathways between studies of temporal cortex mRNA and miRNA expression, it is highly plausible that miRNA are exerting a regulatory influence over mRNA associated with atypical cortical function in ASD.
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The PRE is important for high-level HBV gene expression by acting at the posttranscriptional level to increase the amount of cytoplasmic mRNA (16, 19, 39). It can also increase the amount of unspliced HIV-derived mRNA in the cytoplasm (19), similar to the RRE in the presence of Rev, which are known cis- and trans-acting effectors of RNA export, respec- tively. Therefore, the PRE has the attributes of an RNA export element. To begin to understand the molecular mechanism of PRE function, we have looked for cellular proteins that bind to PRE. Two cellular proteins, approximately 35 and 55 kDa in mass, were previously shown to bind to the PRE (21). The smaller protein was identified as GAPDH (40), whose role in PRE function is as yet undefined. The data presented here show that the other PRE binding protein is PTB, a well-known RNA binding nuclear protein. PTB binds to two pyrimidine- rich regions of the critical central region of PRE. These two sites are entirely conserved among 12 HBV isolates of all six
Next, we determined the RNA binding specificity of ELAV family members in vitro using the well-characterized ELAV binding sequence in the ewg gene (pA-I), which comprises 135 bp (17, 60, 61). For these binding experiments, we generated recombinant proteins in E. coli for ELAV, FNE and RBP9, but also for human HuR, because it is functionally closest to ELAV family proteins in Drosophila (Fig 3A, Supplemental Fig S4 and Supplemental Table 1). Surprisingly, all proteins bound ewg pA-I RNA in a narrow affinity range and also co- operatively formed multimeric complexes similar to ELAV in electrophoretic mobility shift assays (EMSA, Figs 3B and C). Multimeric complexes of rFNE and rHuR assembled on pA-I RNA run faster in accordance with their size (Figs 3A and B), which has previously been observed with the N-terminally truncated form of ELAV, RBD60 (73). Binding constants for rELAV, rFNE, rRBP9 and rHuR were 22 nM, 47 nM, 23 nM and 49 nM, respectively (Fig 3C).
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A full analysis of the apoptosis-associated alterations that were observed in the Drosophila S2 and human Jurkat cell proteomes will be described elsewhere. However, of the !2,000 most abundant Drosophila proteins examined using this ap- proach, we identified 44 protein spots that either disappeared from apoptotic cells or that appeared as cleavage products in these cells (Fig. 1A). Similarly, !160 protein spots were ob- served to undergo caspase-dependent modification in Jurkat cell-free extracts (Fig. 1B). Of the !44 potential caspase sub- strates identified from Drosophila S2 cells, four of these were components of the proteasome complex and were identified as ! type 2, ! type 4, and " type 4 subunits of the core 20 S proteasome and subunit Rpt1 of the 19 S regulatory complex (Fig. 2A). In addition, we also identified the $ subunit of the 11 S proteasome activator complex (PA28$) and the ubiquitin- specific protease IsoT as caspase substrates in Jurkat cell-free extracts (Fig. 2B). Collectively, these data suggested that pro- teasomes and ubiquitin-proteasome pathway enzymes are tar- geted by caspases during apoptosis of fly and mammalian cells. Caspase-dependent Cleavage of Human Proteasome Sub- units—To explore in more detail the possibility that the pro- teasome is subjected to extensive caspase-dependent proteoly- sis during apoptosis, we concentrated on the Jurkat system because antibodies are readily available against most of the human proteasome constituents, whereas few are available for their fly counterparts. It has been established previously that addition of Cyt c and dATP to Jurkat cell-free extracts triggers a cascade of caspase activation events involving all of the cell death-associated caspases (16). Using this system, we observed that several of the 19 S proteasome regulatory subunits (Rpt5/ S6a, Rpn2/S1, and Rpn10/S5a) underwent cleavage upon trig- gering of caspase activation within Jurkat extracts (Fig. 3, D and E). Moreover, in agreement with our proteomic analysis of the same cells, the proteasomal activator PA28$ was also found to be cleaved in Jurkat extracts after Cyt c/dATP treatment (Fig. 3F). To confirm that apoptosis-associated proteolysis of the proteasome subunits was the result of direct caspase cleav- age, Cyt c/dATP-treated extracts were incubated in the pres- ence or absence of the broad specificity caspase inhibitor, Z- VAD-fmk. As shown in Fig. 4A, under conditions where caspase activation was blocked by Z-VAD-fmk, cleavage of all of the proteasome-associated subunits was completely abrogated.
ered to be one of the most important virulence factors of this bacteria. Many studies have investigated the mechanisms of H. pylori and CagA. Via the type IV secretion system (TFSS), CagA can translocate into host gastric cells and regulate downstream molecular signaling path- ways, affecting cell apoptosis and activate host cell survival. Kinds of molecular and axis have been reported in H. pylori infections or H. pylori CagA. It is necessary to give a whole profile of genes involved in the infection. The current study used comparative transcriptome analysis via RNA-seq screening, aiming to identify differ- entially-expressed genes regulated by H. pylori infections or H. pylori CagA.
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As described in Chapter 1, numerous synthetic RNA-based regulatory systems have been developed. However, despite recent advances in the design of RNA devices that process and transmit specified molecular inputs to regulated gene expression events 15, 16 , the absence of successful adaptations of these earlier genetic devices to the regulation of functional responses in mammalian cells highlights remaining difficulties in translating designs that regulate reporter gene expression to functional control. Here, we report a synthetic, small-molecule-responsive RNA-based gene regulatory system in mammalian cells and demonstrate its application in advancing cell-based therapies through the control of cell-fate decisions. We develop a genetic strategy for effectively controlling T-cell expansion based on drug-responsive RNA regulators that exert tight control over key upstream signaling molecules in the proliferation pathway. Our work demonstrates an RNA-based regulatory system that exhibits unique properties critical for translation to therapeutic applications, including adaptability to diverse input molecules and genetic targets, tunable regulatory stringency, and rapid input response.
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The secondary and tertiary orders of RNA structure are crucial for a suite of RNA-related functions, including regulation of translation, gene expression and RNA turnover. The temperature sensitivity of RNA secondary and tertiary structures is exploited by bacteria to fabricate RNA thermosensing systems that allow a rapid adaptive response to temperature change. RNA thermometers (RNATs) present in non-coding regions of certain mRNAs of pathogenic bacteria enable rapid upregulation of translation of virulence proteins when the temperature of the bacterium rises after entering a mammalian host. Rapid upregulation of translation of bacterial heat- shock proteins likewise is governed in part by RNATs. Turnover of mRNA may be regulated by temperature-sensitive RNA structures. Whereas the roles of temperature-sensitive RNA structures similar to RNATs in Eukarya and Archaea are largely unknown, there would appear to be a potential for all taxa to adaptively regulate their thermal physiology through exploitation of RNA-based thermosensory responses akin to those of bacteria. In animals, these responses might include regulation of translation of stress-induced proteins, alternative splicing of messenger RNA precursors, differential expression of allelic proteins, modulation of activities of small non- coding RNAs, regulation of mRNA turnover and control of RNA editing. New methods for predicting, detecting and experimentally modifying RNA secondary structure offer promising windows into these fascinating aspects of RNA biochemistry. Elucidating whether animals too have exploited the types of RNA thermosensing tools that are used so effectively by bacteria seems likely to provide exciting new insights into the mechanisms of evolutionary adaptation and acclimatization to temperature.