Our results show that PPR tracts bind RNA via a modular recognition mechanism that differs from previously described RNA–protein recognition modes and that underpins a natural library of specific protein/RNA partners of unprecedented size and diversity. These findings provide a significant step toward the prediction of native binding sites of the enormous number of PPR proteins found in nature. Furthermore, the extraordinary evolutionary plasticity of the PPR family suggests that the PPR scaffold will be particularly amenable to redesign for new sequence specificities and functions.The pentatricopeptide repeat (PPR) is a helical repeat motif found in an exceptionally large family of RNA–binding proteins that functions in mitochondrial and chloroplast gene expression. PPR proteins harbor between 2 and 30 repeats and typically bind single-stranded RNA in a sequence-specific fashion. However, the basis for sequence-specific RNA recognition by PPR tracts has been unknown. We used computational methods to infer a code for nucleotide recognition involving two amino acids in each repeat, and we validated this model by recoding a PPR protein to bind novel RNA sequences  RNA binding proteins dictate RNA fate and function by modulating RNA processing, localization, translation, and stability. The consequences of RNA/protein interactions are determined, in part, by the position at which the protein binds the RNA. However, it is impossible to predict the target sites of most RNA binding proteins or to design them to bind chosen RNA sequences. In contrast, we show that the pentatricopeptide repeat (PPR) protein family holds exceptional promise for the rational design of specified RNA–binding properties. PPR proteins harbor tandem arrays of a repeating structural unit that form a surface for binding single-stranded RNA. We show that PPR tracts bind specific RNA nucleotides via the combinatorial action of two amino acids in each repeat. This mechanism mimics the simplicity and predictability of the Watson-Crick pairing between nucleic acid strands, but at a protein/RNA interface. Our findings will facilitate the prediction of binding sites for the large number of PPR proteins found in nature. Additionally, our demonstration that a PPR tract can be engineered to bind specified RNA sequences implies that PPR proteins can be designed to bind desired RNA targets for applications in biotechnology, medicine, and basic research. Much of modern biology deals with understanding and predicting macromolecular interactions. The biotechnological possibilities inherent in being able to predict, design and manipulate macromolecular interactions are immense. The well-understood Watson-Crick pairing between nucleic acid strands facilitates the design of nucleic acids that can interact with specific DNA or RNA sequences, and this ability underlies a huge swathe of modern research and biotechnology. Given the greater functional potentialities of proteins compared to nucleic acids and the ability to target proteins to different intracellular compartments, new opportunities would emerge from the ability to design proteins to bind specific RNA or DNA sequences. Unfortunately, most protein-nucleic acid interactions are idiosyncratic, and lack the predictability necessary to engineer specific interactions. Recently, a great deal of excitement has accompanied the characterization of Transcription-Activator-Like Effectors (TALEs), a set of modular repeat proteins that bind via a predictable code to specific double-stranded DNA sequences This study focuses on a second class of helical repeat motif that binds RNA, the pentatricopeptide repeat (PPR). PPR proteins harbor degenerate ∼35 amino acid repeats that are related to tetratricopeptide (TPR) motifs cis-elements with considerable sequence similarity. PPR10 serves to position processed mRNA termini and stabilize adjacent RNA segments in vivo by blocking exoribonucleases intruding from either direction.To develop models for sequence-specific RNA recognition by PPR tracts, we began with a focus on the maize protein PPR10, whose binding sites and mechanisms are particularly well understood Recombinant PPR10 (rPPR10) elutes from a gel filtration column at a position corresponding to a globular homodimer versus 84 kDa) and does not contribute significant signal with the interference optical system used for these experiments. With rPPR10 at 3 µM and RNA at half that concentration, PPR10 monomers partitioned into two species of similar abundance with an S value near 5 S (d for the PPR10-RNA interaction (<1 nM) To determine which form of PPR10 binds RNA, rPPR10 was analyzed by SV-AUC in the presence of its 17-nt minimal RNA ligand. This RNA is small in comparison with rPPR10  in a pair of adjacent repeats (motifs six and seven) were modified to either Tor N6S1′ . Our modor N6S1′ . A PPR10ds of ∼3 nM and 17 nM, respectively, indicating a clear preference for U over C . The  variant is less discriminating, binding the U and C substituted RNAs with similar affinities , , and  combinations at  correlate with recognition of pyrimidines . As predU over C . Conversfinities .Our results define a combinatorial two-amino acid code that can specify binding of a PPR motif to either A, G, U>C, C>U, or U = C. With this knowledge, the engineering of PPR tracts to bind a wide variety of RNA sequences is within reach. However, prediction of the natural binding sites of PPR proteins, and prediction of off-target binding by engineered PPR proteins remains challenging for two reasons. First, the natural diversity of amino acid identities at positions 6 and 1′ implies a degenerate code, and less than two-thirds of naturally occurring combinations can currently be interpreted. Second, an understanding of the energetic parameters required to establish a physiologically meaningful PPR/RNA interaction and the energetic costs of mismatches at various positions along a PPR/RNA duplex will be required to accurately predict potential binding sites. The prediction of microRNA targets is similar in concept and provides a glimpse into the challenge to come: despite the simplicity of RNA base pairing rules, the parameters that dictate microRNA targets are still being worked out Prediction of binding sites is further complicated by the fact that gaps in a PPR/RNA duplex can be tolerated in some contexts, as exemplified by PPR10's natural targets . Indeed,c. 9.5 Å versus L-type PPR motifs. Thus, we suspect that L motifs do not bind nucleotide bases, allowing a ‘mini-gap’ every third nucleotide that may relax the structural constraints.Our alignments of P-class PPR proteins to their cognate RNAs include contiguous duplexes consisting of no more than nine motifs and eight nucleotides. This is reminiscent of the binding of 8–9 nucleotides by the eight repeats in Puf proteins : TD Variant: SV-AUC was performed in a Beckman Optima XL-I ultracentrifuge with a Beckman An60Ti rotor. 400 µl of sample and 410 µl of reference buffer were analyzed in a 1.2 cm double-sector standard AUC cell. Experiments were run at 20°C at 50,000 rpm and monitored with an interference optical system. Data were collected at 3 min intervals for 8 hrs, and analyzed with SedFit atpH binding site was generated de novo as follows. Thirty-five 17-mers were constructed, each corresponding to the amino acids at a specific position within the 17 sequential PPR motifs in PPR10's interior. Terminal PPR motifs were excluded, as they have distinct properties that may adapt them to their terminal position. These 17 motifs can be arranged in 420 different ways on the 24-nucleotides that are protected by PPR10, assuming that all the motifs contact the RNA sequentially but not necessarily contiguously, and permitting gaps of any length at any position. The number of arrangements is doubled if both polarities of the protein on the RNA are considered. For each of the 840 arrangements, contingency tables were constructed for each of the 35 17-mers, scoring the number of co-occurrences of each possible amino acid/nucleotide pair . Fisher's Exact Test was used to test for independence of amino acid and nucleotides classes, as implemented in R version 2.14.2 by fisher.test. The tables were ranked by p-value. The top ranked alignment (1/29400) was for position 1. The best alignment for position 6 was also retained (ranked 71/29400). No other highly ranked alignments were physically compatible with the motif arrangement required for the alignment shown in atpH sites with various insertions and point mutations The alignment of PPR10 to its d calculations were performed as described Gel mobility shift assays and KFigure S1Alignments of PPR editing factors to their target sites. For each factor, the name of the protein and its editing site are listed, then successively the types of PPR motif, the amino acids at position 6, the amino acids at position 1′, an indication of the degree to which these amino acids ‘match’ the RNA using the code developed in this work, and lastly the RNA sequence (in lower case). ‘:’ and ‘.’ indicate experimentally validated see  and comp(PDF)Click here for additional data file.Figure S2Frequency of 6,1′ combinations in Arabidopsis PPR proteins. The most frequent combinations are shown . Only tandem pairs of motifs  were considered in this analysis, where the first motif was either a P or S motif. Combinations observed in P motifs are shown in blue, those in S motifs in green.(PDF)Click here for additional data file.Table S1Alignments of PPR10 to the PPR10 RNA footprint ranked by p-value. The table shows the top 100 alignments out of the 29400 possible. The two alignments shaded in yellow correspond to the alignments depicted in (PDF)Click here for additional data file.Table S2versus nucleotides) were constructed from the alignments in Correlations between amino acids at specific positions within PPR motifs and aligned nucleotides. Contingency tables (amino acids (PDF)Click here for additional data file.Table S3Correlations between amino acids at positions 6, 1′ and aligned nucleotides. The tables show frequencies of co-occurrence of amino acids and nucleotides from the alignments in (PDF)Click here for additional data file.


Coronaviruses are positive-strand RNA viruses that are important infectious agents of both animals and humans. A common feature among positive-strand RNA viruses is their assembly of replication-transcription complexes in association with cytoplasmic membranes. Upon infection, coronaviruses extensively rearrange cellular membranes into organelle-like replicative structures that consist of double-membrane vesicles and convoluted membranes to which the nonstructural proteins involved in RNA synthesis localize. Double-stranded RNA, presumably functioning as replicative intermediate during viral RNA synthesis, has been detected at the double-membrane vesicle interior. Recent studies have provided new insights into the assembly and functioning of the coronavirus replicative structures. This review will summarize the current knowledge on the biogenesis of the replicative structures, the membrane anchoring of the replication-transcription complexes, and the location of viral RNA synthesis, with particular focus on the dynamics of the coronavirus replicative structures and individual replication-associated proteins. Positive-strand RNA (+RNA) viruses are the most abundant viruses in nature. Many important pathogens belong to this category, including poliovirus (PV), hepatitis C virus (HCV) and the severe acute respiratory syndrome (SARS)-coronavirus (CoV). A distinctive common feature of +RNA viruses is the replication of their genomes in the cytoplasm of the host cell in association with rearranged cellular membranes that are remodeled into organelle-like membranous structures to which the viral replication-transcription complexes (RTCs) localize. Picorna- and Togaviridae, spherule-like invaginations for the Bromoviridae and Nodaviridae, and vesicle packets and membranous webs for the Flaviviridae . ThCoronaviridae, extensively rearrange cellular membranes into organelle-like replicative structures during infection. These replicative structures consist of double membrane vesicles (DMVs) and convoluted membranes (CMs). The viral replicase proteins involved in RNA synthesis localize to both these structures, while double-stranded RNA (dsRNA), presumably functioning as replicative intermediate during viral RNA synthesis, has been detected at the DMV interior [Also coronaviruses (CoVs), enveloped +RNA viruses that belong to the family interior ,5. RecenCoronaviridae are a family of evolutionary related, enveloped +RNA viruses that together with the Arteriviridae and the Roniviridae, belong to the order of the Nidovirales. Historically, CoVs have been recognized as important infectious agents for domestic livestock, poultry and companion animals. In contrast to the animal viruses, human CoVs (HCoVs) have been associated with relatively mild upper and lower respiratory tract infections, including ordinary common colds. However, in 2002–2003 the outbreak of a novel HCoV in China, causing severe fatal atypical pneumonia in infected individuals, demonstrated that HCoVs are also able to induce severe life-threatening disease in humans. This virus was called the SARS-CoV [The SARS-CoV ,7 and emSARS-CoV ,9. cis-acting elements that are important for replication and transcription. Two-thirds of the genome consists of two large open reading frames (ORFs), ORF1a and ORF1b. The remaining 3' one-third part encodes the structural proteins interspersed with sequences encoding some accessory proteins. A schematic picture of the prototype mouse hepatitis virus (MHV) genome is shown in Among the +RNA viruses, CoVs clearly distinguish themselves by carrying the most complex and largest genomes, which range in size from ~26 to 32 kb . DespiteThe structural and the accessory proteins are expressed from a nested set of 3' coterminal subgenomic (sg) mRNAs that are generated via discontinuous transcription during subgenome-length minus-strand RNA synthesis ,13. The The viral replicase is encoded by the two most 5' ORFs of the genomic RNA, ORF1a and ORF1b. Translation of ORF1a and ORF1b of the genomic RNA generates two very large replicase polyproteins (pp), pp1a and pp1ab. The latter is synthesized via a −1 ribosomal frameshift mechanism mediated by a pseudoknot structural element at the end of ORF1a ,17. ThesThe CoV nsps form together with the nucleocapsid (N) protein, and presumably several host proteins, the membrane-associated RTCs. To generate the functional CoV replication complexes, the replicase polyproteins pp1a and pp1ab have to be proteolytically processed to liberate the sixteen individual protein products. Cleavage of pp1a and pp1ab is performed by two viral proteinases that reside in nsp3 and nsp5: the papain-like proteases (PLpro1 and PLpro2) located in nsp3 and the chymotrypsin-like cysteine proteinase (3CLpro), or main protease (Mpro), present in nsp5 (reviewed in ). BesideThe key enzyme involved in genome replication is the RNA-dependent RNA polymerase (RdRp), which is present in nsp12 . The nspThe CoV nsp13 protein contains a superfamily 1 helicase domain with an amino-terminal zinc-binding domain that is important for the unwinding activity of duplex RNA (and DNA) in a 5'-to-3' direction ,27,28. TCoVs possess the largest genomes among the +RNA viruses . They enN-glycosylated upon insertion into the membranes of the endoplasmic reticulum (ER) [CoVs encode three nsps that contain hydrophobic stretches that are predicted to function as transmembrane domains: nsp3, nsp4 and nsp6. Consistently, membrane association has been demonstrated for the nsp3, nsp4 and nsp6 proteins of SARS-CoV ,42,43 anlum (ER) . Intereslum (ER) . This exlum (ER) ,46,47. Tlum (ER) ). The adIn addition to the nsps mentioned above, other CoV nsps are involved in RNA binding  or iUpon infection of host cells, CoVs induce a variety of membranous structures of which some have been associated with viral RNA synthesis. The first detectable membrane rearrangements in CoV-infected cells are 200 to 350 nm organelle-like structures that have been described for both MHV ,62 and tElectron tomography studies demonstrated that in SARS-CoV infected cells the DMVs and CMs form an interconnected membranous network that is also continuous with the ER . This lai.e., DMVs and CMs  with the replicative structures ; moreoveC) resulted in the relocalization of these proteins from the ER into discrete foci mostly localizing to the perinuclear region of the cell [C revealed that the membranes of the ER exhibited more curvature, although these membranes did not resemble the DMVs observed in CoV-infected cells [The CoV nonstructural membrane proteins, nsp3, 4 and 6 probably play an essential role in the membrane rearrangements required for the induction of the replicative structures and in the anchoring of the RTCs to these structures. These proteins were shown to be engaged in homo- and heterotypic interactions . Interesthe cell . Althougthe cell , in agrethe cell . Ultrasted cells , which med cells . While ced cells . We hypoN-glycosylation site in this loop also affected their morphology to some extent [Several other studies also suggest an important role for nsp4 in the generation of the replicative structures. Disruption of the nsp4 glycosylation sites present in the loop between the first and second hydrophobic region, leads to the formation of aberrant DMVs in which the inner and outer membranes are detached, while the number of CMs is increased . In agree extent .Like CoVs, other +RNA viruses also somehow induce membrane rearrangements that are required for their replication and transcription. For several of these viruses similar membrane rearrangements can be induced by the (co-)expression of nsps . ThHow are the nsps of CoVs able to induce the observed membrane rearrangements? We speculate that the similarities between the membrane-associated nsps of different +RNA viruses relate to their common ability to remodel membranes. The induction of membrane curvature in lipid bilayers is critical when remodeling host cellular membranes. The membrane-associated viral proteins may act as multimeric scaffolds able to impose such curvature, for instance by acting as wedges by inserting their amphipatic helices partially into one side of the bilayer The last few decades have provided virologists with exciting new information regarding the functions and structures of individual nsps and the characterization and formation of the membranous structures induced by +RNA viruses. These insights were obtained by classical biochemical, immunofluorescent and ultrastructural approaches. Unfortunately, little information regarding the dynamics of the  proteins present at the membranous replicative structures in living cells is known. Such studies are important as classical approaches only provide static views of cellular processes and do not necessarily reflect the dynamics underlying virus replication in living cells. To date, only few studies on the dynamics of the replicative structures of plus-strand RNA viruses and their associated proteins have been published ,108,109.By using a GFP-tagged version of nsp2, shown by immuno-electron microscopy (IEM) to be recruited to the DMVs and CMs, as a marker the dynamics of the CoV replicative structures were studied using live cell imaging . These sLive cell imaging studies of HCV- and Semliki Forest virus (SFV)-infected cells also reveal the presence of replicative structures that could be discriminated on the basis of their size and mobility. HCV induces the formation of a so-called membranous web, in which DMVs can be observed . Large Hper se. Additional studies are required to clarify the role of the perinuclear targeting of the CoV replicative structures during infection.The calculated velocities of the saltatory movements of the smaller nsp2-positive structures in CoV-infected cells  correspoi.e., the soluble nsp2 and N proteins and the integral membrane protein nsp4, and demonstrated that these proteins display different diffusional mobilities when present at the replicative structures.Up till now, only few studies have addressed the dynamics of individual viral proteins when present at the replicative structures. Recently, we analyzed the dynamic properties of three replication-associated proteins, in trans is recruited to the replicative structures [in vitro [in vivo as its coding sequence is maintained during evolution. Nsp2, when expressed ructures . After rructures . When exructures , similarructures ,115,116.in vitro . Yet, nsi.e., in packaging of the genomic RNA into the RNP complex, the structural N protein is also important in coronavirus replication and has been detected in the perinuclear region of infected cells colocalizing with markers for the replicative structures [In addition to its structural role in the coronavirion, ructures ,117,118.ructures , while Nructures . In contructures . This maructures ,122,123 ructures . As the in trans in infected cells, the nsp4-GFP fusion protein was detected at the ER and at the replicative structures [When expressed ructures ,81. By pructures . FRAP anructures .per se does not imply  these structures to be actively involved in RNA synthesis. Likewise, the location of viral enzymes that are required for RNA synthesis does not need to correlate with active RTCs. Moreover, newly synthesized RNAs are not necessarily located at their site of synthesis as they may diffuse or be transported away to other subcellular locations. In view of these considerations, sites active in RNA synthesis are expected to contain at least three components: the RdRp, dsRNA intermediates active in replication/transcription and nascent viral RNA.Currently, one of the most enigmatic issues regarding CoV replication is the precise localization of the sites of active viral RNA synthesis. Although CoV RNA synthesis appears to be protected by membranes  it is stNewly synthesized viral RNAs, visualized by 5-bromouridine 5’-triphosphate (BrUTP) labeling, were shown to colocalize with antibodies recognizing either nsp5 or the C-terminal part of pp1a , and werDifferent models can be put forward to explain these observations. In one model, DMVs function as the sites of active RNA synthesis. At the later times in infection, many DMVs are no longer active, while the ones that are active may contain only little dsRNA, resulting in less apparent colocalization of dsRNA and EU labeling. In another model, DMVs are non-functional end-stage products. They are not actively involved in RNA synthesis, but rather harbor dsRNAs that are not (longer) functioning as intermediates in RNA synthesis. In this model, which is in agreement with the presumed absence of pores in these structures , the CMsFor most other +RNA viruses the identification of the sites of active RNA synthesis appears less complicated. Nascent RNAs, as well as nsps, have been shown to label the spherules that are observed in BMV- , SFV- 1 or flockCoV replicative structures/RTCs are macromolecular assemblies, the components of which are engaged in a plethora of protein-protein, protein-RNA, and protein-lipid interactions ,116,131.per se, as inhibition of either process will result in reduced RNA synthesis, protein expression and DMV formation. Therefore, assays are needed in which the formation of replicative structures can be studied independent of viral replication. Such assays may be provided by co-expression of viral proteins [One of the difficulties associated with these studies is the complexity of discriminating whether host proteins are directly involved in the formation of the replicative structures themselves or in RNA synthesis proteins ,85 that proteins . Reticulproteins ,134,135 proteins . It willproteins ,136. AlsIn addition to the role of virus and host proteins in formation of the replicative structures, lipids may also be important in this process. Dynamic alteration of the lipid composition can induce curvature of membranes to some extent ,137,138,Finally, as all processes occurring in living cells are inherently dynamic in nature, it is also desirable to get more insight into the biogenesis and functioning of the replicative structures using various live cell imaging approaches. For example, photoactivatable fluorescent proteins can be used to investigate the formation of the replicative structures in real-time by ‘optical pulse-labeling’ in living cells, while the behavior of individual nsps associated with the RTCs can be studied by selectively ‘switching-on’ (sub)populations of proteins ,146. Fur


E. coli DNA polymerase III as a conceptual framework; and 3) the promise of genetic and therapeutic interference with fidelity regulation as an approach for attenuation and treatment of CoVs.Coronaviruses (CoVs) are positive-sense single-stranded RNA viruses and contain the largest known RNA genomes, ranging from 27 to 32 kilobases in length. CoVs are capable of trans-species movement as evidenced by the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) epidemic in 2002–2003 RNA viruses rely primarily on low-fidelity replication by RNA-dependent RNA polymerases (RdRps) to facilitate viral adaptation to complex host environments in vitroin vitroin vivoIn addition to these mechanisms, CoVs encode several additional RNA-processing functions within their 16 nonstructural proteins (nsp1–16), including a 3′-to-5′ exoribonuclease  core (αεθ), which contains a polymerase (α subunit), a DEDDh exonuclease (ε subunit), and an exonuclease stimulatory protein (θ subunit) The identification of a proofreading exoribonuclease distinct from the CoV RNA-dependent RNA polymerase (nsp12-RdRp) suggests that CoVs might use a multi-protein complex for RNA synthesis and regulation of fidelity. A possible analogy would be the in vitro by up to 35-fold E. coli pol III core, theta is a ∼76 amino acid protein with no known enzymatic function that has been shown to both bind and stabilize the pol III ε subunit and stimulate ε-mediated removal of terminal mismatches The CoV nsp10 is a ∼130 amino acid protein with no identified enzymatic function that has been demonstrated to bind and enhance nsp14-ExoN activity E. coli pol III as a model, in addition to the αεθ core, the pol III holoenzyme requires additional subunits including a processivity factor (β sliding clamp), single-strand DNA-binding proteins (SSB), and a helicase  functions have been identified within the CoV replicase. SARS-CoV nsp9 dimerizes and binds both ssDNA and ssRNA in a sequence-independent manner Might other CoV nonstructural proteins be associated with this putative multi-subunit polymerase? And how would such a complex be assembled? Again using in vitro and in vivo studies demonstrate the limited antiviral activity and variable effectiveness of RBV against SARS-CoV infection in vivo, suggesting that small-molecule inhibition of ExoN activity would also significantly impact virus infection and virulence Ribavirin (RBV) and 5-fluorouracil (5-FU) have been shown to be mutagenic for many RNA viruses (reviewed in Coronaviruses encode a proofreading exoribonuclease that is responsible for genome expansion, increased robustness to mutations, and resistance to mis-incorporations during RNA synthesis, as well as being required for virulence. The stability of the ExoN− genotype and phenotype provides a powerful model for the study of additional CoV fidelity determinants and of the effects of altered fidelity on virus replication, fitness, host-species range, and response to environmental changes. Experiments testing the proposed multi-subunit fidelity complex will yield exciting new insights into how CoVs ignore the RNA virus playbook and instead seem to play by their own rules while dancing on the edge of genetic disaster.


Reoviridae family are non-enveloped multi-layered viruses with a double stranded RNA genome consisting of 9 to 12 genome segments. Bluetongue virus is the prototype orbivirus , causing disease in ruminants, and is spread by Culicoides biting midges. Obviously, several steps in the Reoviridae family replication cycle require virus specific as well as segment specific recognition by viral proteins, but detailed processes in these interactions are still barely understood. Recently, we have shown that expression of NS3 and NS3a proteins encoded by genome segment 10 of bluetongue virus is not essential for virus replication. This gave us the unique opportunity to investigate the role of RNA sequences in the segment 10 open reading frame in virus replication, independent of its protein products. Reverse genetics was used to generate virus mutants with deletions in the open reading frame of segment 10. Although virus with a deletion between both start codons was not viable, deletions throughout the rest of the open reading frame led to the rescue of replicating virus. However, all bluetongue virus deletion mutants without functional protein expression of segment 10 contained inserts of RNA sequences originating from several viral genome segments. Subsequent studies showed that these RNA inserts act as RNA elements, needed for rescue and replication of virus. Functionality of the inserts is orientation-dependent but is independent from the position in segment 10. This study clearly shows that RNA in the open reading frame of Reoviridae members does not only encode proteins, but is also essential for virus replication.Members of the  Reoviridae consists of non-enveloped viruses with a multi-layered capsid. They have a double stranded RNA (dsRNA) genome, consisting of 9 to 12 genome segments, and one copy of each segment is efficiently recruited and incorporated into each virus particle The family of Orbivirus) is one of the most extensively studied Reoviridae members, and is transmitted to ruminants by Culicoides biting midges. Clinical manifestations associated with BTV infections can course from subclinical to severe haemorrhagic disease, characterized by fever, lameness, coronitis and swelling of the head, particularly the lips and tongue Bluetongue virus  consist of seven structural proteins (VP1 - VP7) forming an architecturally complex structure of an inner (VP3), middle (VP7) and outer (VP2 and VP5) capsid layer. These layers encapsidate the viral polymerase (VP1) For successful virus replication, RNA segments are specifically recognized by viral proteins at different stages in the replication cycle, such as transcription, extrusion from core particles, translation, recruitment into viral inclusion bodies (VIBs), replication and assembly of new virus particles. The mechanism for selective packaging of the genome segments is still one of the most prominent and intriguing questions in this research field.In orbivirus replication, after cell entry and removal of the outer shell, core particles transcribe capped mRNAs originating from all viral segments, which are extruded into the cytoplasm. These mRNAs are recruited from the cytoplasm into VIBs formed by NS2. NS2 may has a role in the recruitment of RNA from the cytoplasm by binding to the 5′- and 3′-untranslated regions (UTRs). However, undefined RNA sequences in the open reading frame (ORF) are also recognized by NS2 Reoviridae RNA important for virus replication was hampered by the dual function of this RNA in both translation and replication. Reverse genetics has been developed for several BTV strains in vitro propagation of BTV in cis by RNA inserts from several other genome segments. These findings are a first step to define RNA sequences involved in replication of Reoviridae members.Until recently, research on sequences in coding BSR cells (a clone of baby hamster kidney (BHK) cells E.coli competent cells (Invitrogen) and were isolated using the High Pure Plasmid Isolation Kit (Roche) or the QIAfilter Plasmid Midi Kit (Qiagen).Plasmids containing cDNA of Seg-1 to Seg-10 of BTV1 (Genbank accession numbers FJ969719-FJ969728) and Seg-10 of BTV8 (AM498060) have been described in vitro RNA transcription using the MESSAGE mMACHINE T7 Ultra Kit (Ambion) as described previously Plasmid DNA was linearized by restriction enzymes as described earlier 5 BSR cells were transfected in a 24-wells plate using 1.5 μl lipofectamin 2000 (Invitrogen) and 600 ng RNA in total, containing Seg-1, 3, 4, 5, 8, and 9 in equimolar amounts, encoding VP1, VP3, VP4, NS1, NS2 and VP6 respectively. Eighteen hours post transfection, BSR monolayers were transfected again with in total 600 ng of all 10 RNA segments in equimolar amounts. All transfections were performed in duplicate. Wells were screened for cytopathogenic effect (CPE) at 48 h post transfection and one well was fixed with methanol:aceton and immunostained with α-VP7 monoclonal antibody (MAb) (American Type Culture Collection (ATCC)-CRL-1875) according to standard procedures BTV mutants were generated using reverse genetics as previously described 5′-GTTAAAAAGTGTCGCTGCC-3′) and R-full-S10 (5′-GTAAGTGTGTAGTGTCGCGCAC-3′) and the one-step RT-PCR kit (Qiagen). Briefly, 5 μl isolated RNA was added to 10 μl 5x Qiagen one-step PCR buffer, 2 μl dNTP mix, 0.6 mM of each primer and 2 μl enzyme mix in a total volume of 50 μl. Reverse transcription was performed for 30 min at 45°C. After an activation step of 15 min at 94°C, cDNA was amplified in 40 cycles of 1 min at 94°C, 1 min at 45°C and 2 min at 72°C, followed by a terminal extension step at 72°C for 10 min.Viral RNA was isolated from 200 μl of infected cell culture medium using the High Pure Viral RNA kit (Roche) according to manufacturer’s protocol and eluted in 50 μl RNase-free water. Entire BTV Seg-10 was reverse transcribed and amplified using primers F-full-S10* (The amplicon was separated on a 1% agarose gel by electrophoresis and isolated using the Zymoclean gel DNA recovery kit (Zymo Research) according to the manufacturer′s protocol. The sequence of amplicons was determined using appropriate primers and the BigDye Terminator v1.1 Cycle Sequencing Kit (Applied Biosystems) in an ABI PRISMH 3130 Genetic Analyzer (Applied Biosystems). The complete consensus sequence was assembled and determined using Lasergene SeqMan Pro Software .50/ml). Experiments were independently repeated four times and significant differences in virus titers were determined using a paired Student’s T-test, with p<0.05.BSR cells in wells of a 24-wells plate were infected with a multiplicity of infection (MOI) of 0.1. Virus was attached to the cells for 1.5 h at 37°C. By washing with medium, free circulating virus was removed and fresh medium was added. This time point was set as time point 0 . Incubation at 37°C was continued and supernatant from one of the wells was each time harvested at indicated time points between 0–54 hpi. An equal volume of fresh medium was added to the attached cells in the well of which the supernatant was harvested and virus in the cell fraction was harvested at the same time points after freeze thawing that well at –80°C. Virus titers of cell fractions and supernatants were determined by end point dilution on BSR cells and expressed as tissue culture infectious dose per ml  according to manufacturer’s protocol. Approximately 200 ng dsRNA was separated by 4–12% polyacrylamide gel electrophoresis (PAGE) and visualized by silver staining using the SilverXpress kit (Invitrogen).BSR monolayers were infected with mutant BTV. Medium was discarded at 24 hpi and 0.1 ml/cmin vitro synthesized RNAs using reverse genetics , RNASAlign (http://www.bio8.cs.hku.hk/RNASAlign/) and Alifold  software. No obvious similarities in RNA structures were found, although many RNA structures could be predicted in all RNA inserts, and even the RNA insert of 67 base pairs originating from Seg-2 in ΔD contained a predicted RNA (pseudoknot) structure (not shown). We suggest that these inserts complement in cis for the deleted RNA sequence in Seg-10 by a yet unknown mechanism.Larger than expected Seg-10 amplicons indicated an insertion or duplication of RNA sequences. All designed deletions in Seg-10 were confirmed, but for each deletion mutant the sequence of at least one subpopulation with an insertion was also confirmed. All RNA inserts were from viral origin and were inserted in the positive orientation. However, inserts varied in length and originated from several genome segments. We found RNA inserts from genome segments 1, 2, 6, 8, 9 and a partial duplication of remaining sequences in deletion Seg-10. Further, these viral RNA sequences seemed to be randomly inserted, since inserts were found at different positions in deletion Seg-10 . Insertein vitro RNA synthesis and subsequently used for virus rescue. Two days post second transfection (dpt), plaques were already clearly visible by immunostaining (not shown). Since ΔD mutant production was less efficient, this demonstrates that inserts of viral sequences in deletion Seg-10 increase the efficiency of virus rescue. Furthermore, except for ΔH (see discussion), deletion BTV mutants without quickly arising subpopulations containing inserts in Seg-10 could not be propagated, indicating that inserting these RNA inserts is essential for virus rescue. Genetic stability of newly rescued ΔD(S2) was confirmed for at least three virus passages by dsRNA analysis (not shown), and RT-PCR amplification of Seg-10  with an insertion from Seg-2 770–836, , and ΔD Figure , were dif Seg-10 .in cis by the Seg-2 sequence of only 67 base pairs in length.Seg-10 of deletion BTV mutant ΔD(S2) was further shortened resulting in a Seg-10 of 320 base pairs in length, named ΔD(S2del) . BTV mutin cis complementation and advantageous sequences were quickly inserted similar to virus rescue for other deletions in Seg-10. These results show that the position of the viral insert is not important, whereas the orientation of the insert is crucial for its function in virus replication. We conclude that inserted RNA sequences are in cis RNA elements needed for virus replication and that these elements can originate from several genome segments.The same Seg-2 insert was further analysed. First, the Seg-2 insert was repositioned further downstream in the cDNA of ΔD, named ΔD(S2reposition) . Second,th passage. A subpopulation missing both a large part of GFP and the Seg-2 element was also identified. However, here the Seg-2 element was replaced by insertion of a Seg-6 RNA element. Again, Seg-10 subpopulations without additional viral sequence were not found, which strongly indicates that RNA elements from viral origin are essential for BTV replication. Further, foreign RNA sequences, such as the ORF of GFP, cannot compensate for deletions in Seg-10. We conclude that several RNA regions in the ORF encoding NS3a are needed for virus replication. Although the mechanism of this is unknown yet, we further conclude that the function of these RNA sequences can be complemented in cis by inserting RNA sequences of other genome segments in the sense orientation.The large deletion in ΔD(S2del) might enable insertion of non-viral sequences. The ORF of green fluorescent protein (GFP) was therefore inserted (in frame) downstream of the Seg-2 element in the cDNA of ΔD(S2del) . Mutant Our group showed that BTV mutants without NS3/NS3a expression (AUG1+2 mut) show reduced CPE and reduced release of virus in culture medium Reoviridae genome is composed of 9-12 linear dsRNA genome segments. Single copies of each genome segment need to be incorporated in the virus particle to form infectious virus. The exact mechanism by which this is orchestrated is unknown. Protein-RNA interactions specific for the virus segments in general and specific for each individual segment play an important role to direct this process in an efficient way. For BTV as representative of the orbivirus genus, proteins VP1, VP3, VP4, VP6, NS1, and NS2 have RNA binding capacity, but the exact RNA sequences involved in binding and segment recognition have not been elucidated The Studies on RNA binding in coding regions have been limited to cell-free systems, due to interference of introduced mutations with translation of supposed essential viral proteins. We have recently found that translation of NS3/NS3a from BTV Seg-10 is not essential for BTV replication BunyaviridaeReoviridae. BTV mutants with deletions in Seg-10 were generated, but deletion of RNA sequences between both start codons, in fact the 5′-UTR of NS3a (mutant ΔA), appeared detrimental for virus rescue, showing its importance. This sequence is highly conserved as is shown by its use in molecular diagnostics Virus rescue without adding RNA of Seg-10 using reverse genetics has failed, indicating that sequences in Seg-10 are truly essential for virus rescue, as has been shown for Seg-9 Rescue of all other deletion mutants in the Seg-10 ORF was possible, but RNA inserts from several genome segments were found in deletion Seg-10, very quickly after virus rescue. The original deletion Seg-10 was still detectable, but detection was rapidly declining, whereas detection of Seg-10 with an insertion was rising. Although there is apparently still a small subpopulation in the virus pool present that does not contain the insertion, the original deletion mutant can never form a virus pool not containing subpopulations with insertions. This shows that the RNA inserts are essential for virus replication, since no virus pools without insertions can be generated.in cis complementation. Again, like for ΔH, this confirms that non-essential NS3 is highly beneficial for BTV replication.The only mutant without additional insert was ΔH. BTV ΔH still expresses C-terminal truncated NS3/NS3a, as was confirmed by IPMA (not shown). C-terminal truncated NS3/NS3a is still functional The RNA sequences were probably inserted by replicative recombination events. Such events are common in viral evolution Reoviridae members is compartmentalized and synchronized. Plus strand RNA synthesis to generate mRNA occurs only in core particles, synthesis of minus strand RNA to form dsRNA occurs only after assembly in newly formed virus particles. Therefore, template switch for replicative recombination will occur between strands of viral origin and of the same polarity. On the other hand, the rescue of mutant ΔD(S2inverted) showed that inserts in the inverted orientation are not functional and nonviral RNA inserts are not beneficial for virus replication as was shown by rescue of mutant ΔD(S2delGFP).BTV deletion mutants have inserted RNA sequences exclusively from viral origin and exclusively in the positive orientation. Generally, viral RNA synthesis of in cis RNA elements.The RNA sequences seem to be inserted at random positions in Seg-10. Also, the rescue of mutant ΔD(S2reposition) showed that the inserts are still functional at another location in Seg-10. This indicates that the inserts are independent of adjacent sequences and function as distinct Sequences of all found inserts were compared but no sequence or structure homologies were found. In a few occasions overlapping sequences or very similar inserts were independently found suggesting a preference of inserting these sequences.Additional to encoding proteins, viral RNAs contain functions important for a variety of processes, such as transcription, replication and recruitment for packaging in the virus particle. RNA secondary structures and in particular pseudoknots are associated with a remarkable range of functions often involved in initiation of translation and ribosomal frame shifting, but could also be binding sites for proteins or single-stranded loops of RNA Obviously, RNA inserts considerably enhance the efficiency of virus rescue using reverse genetics and are always found in deletion Seg-10 without expression of functional NS3. However, the mechanism in which these RNA sequences are involved is yet unknown.One possibility is the recognition by NS2. NS2 is involved in the formation of VIBs The inserts can also be bound by VP6. It is suggested that VP6 binds to RNA for its helicase activity, but also plays a role in RNA packaging by a still unknown mechanism Another possibility for insert necessity, is that the optimal length of Seg-10 might be advantageous for the stability of a virus particle, since it is known that RNA can direct the assembly of the capsid and sometimes enhances capsid stability , the original Seg-2 insert eventually changed into an insertion of Seg-6. It will be interesting to continue passaging of virus mutants in order to find the most optimal RNA sequence of deletion Seg-10 without expression of NS3/NS3a proteins. With the same aim, growth competition experiments between independently generated BTV mutants only differing in Seg-10 sequences could be performed.Taken together, in addition to encoding proteins, RNA in BTV ORFs is also essential for virus replication itself. This system, in which RNA elements can be studied in virus replication without interference of translation, is a first step to elucidate the exact role and function of these RNA elements. The developed system with the protein-lacking genome segment 10 enables research on the role of RNA sequences in RNA replication, virus assembly, segment recognition and other processes in which RNA-RNA or protein-RNA interactions in the replication of dsRNA viruses are involved. Processes such as viral evolution and inter- and intragenic recombination can also be studied now.


Technical advances in the collection of clinical material, such as laser capture microdissection and cell sorting, provide the advantage of yielding more refined and homogenous populations of cells. However, these attractive advantages are counter balanced by the significant difficultly in obtaining adequate nucleic acid yields to allow transcriptomic analyses. Established technologies are available to carry out global transcriptomics using nanograms of input RNA, however, many clinical samples of low cell content would be expected to yield RNA within the picogram range. To fully exploit these clinical samples the challenge of isolating adequate RNA yield directly and generating sufficient microarray probes for global transcriptional profiling from this low level RNA input has been addressed in the current report. We have established an optimised RNA isolation workflow specifically designed to yield maximal RNA from minimal cell numbers. This procedure obtained RNA yield sufficient for carrying out global transcriptional profiling from vascular endothelial cell biopsies, clinical material not previously amenable to global transcriptomic approaches. In addition, by assessing the performance of two linear isothermal probe generation methods at decreasing input levels of good quality RNA we demonstrated robust detection of a class of low abundance transcripts (GPCRs) at input levels within the picogram range, a lower level of RNA input (50 pg) than previously reported for global transcriptional profiling and report the ability to interrogate the transcriptome from only 10 pg of input RNA. By exploiting an optimal RNA isolation workflow specifically for samples of low cell content, and linear isothermal RNA amplification methods for low level RNA input we were able to perform global transcriptomics on valuable and potentially informative clinically derived vascular endothelial biopsies here for the first time. These workflows provide the ability to robustly exploit ever more common clinical samples yielding extremely low cell numbers and RNA yields for global transcriptomics. Microarray technologies permitting global gene expression profiling have represented a major advance in genomic science. Gene expression profiles can generate parallel quantitative and repeated measurements of tens of thousands of transcripts simultaneously in one sample, allowing rational comparison of the transcriptome across a vast array of experimental conditions. Several advances in RNA amplification techniques and microarray technologies have led to the wide use of global gene expression profiling in biomedical research, adopted as standard in both academia and industry in vitro transcription (IVT) with T7 RNA polymerase of double-stranded cDNA, firstly generated by reverse-transcription of mRNA utilising a poly(T) oligonucleotide complementary to the 3′ poly(A) tail of mRNA  tracts) Historically, microarray probe generation has been achieved by More targeted approaches to gene expression profiling, such as real-time quantitative PCR (qPCR), have the advantage of conceptually requiring less input material and indeed are vital in validating gene expression profiles identified and inferred from array-based global transcriptome datasets and as the molecular platform in standard nucleic acid molecular diagnostics. qPCR used along side advances in microfluidics technology has demonstrated the possibility of gene expression analysis at the single cell level in vitro transcription-based methods using 100 and 200 ng of input RNA, respectively, followed by hybridisation to Affymetrix GeneChips In response to growing requirements to carry out global gene expression profiling on limited sample material further advances in RNA amplification have arisen, providing numerous technologies claiming the ability to process RNA amounts within the nanogram range Continuing technical advances in sample collection or dissection have consequently resulted in informative interrogation of important clinical material comprised of hundreds or thousands of cells rather than from millions as was previously possible Whilst there are reports comparing RNA amplification methods which have successfully carried out microarray gene expression profiling from picograms of RNA Successful microarray analysis on RNA isolated from minimal cell samples has been previously reported. ESC colonies The ability to extract adequate material for global molecular analyses from smaller clinical samples paves the way for less invasive sample collection techniques within the clinic, for example a ‘finger pick’ for blood versus a full phlebotomy procedure. Small clinical specimens also have specific value in translational medicine where collection is more permissive to repeated sampling, facilitating longitudinal biomarker discovery and validation assessments.One clinical sample type for which the ability to carry out transcriptional profiling  has previously been significantly hampered due to lack of cell numbers and RNA yield but could lead to significant advancements in understanding disease mechanisms, patient stratification and disease progression are vascular endothelial cell scraping biopsies In order to guarantee maximum RNA yield from these minimal cell samples, an optimised RNA isolation workflow was established specifically designed to minimise RNA loss throughout the procedure, whilst still being amenable to downstream array probe generation. For successful microarray analysis unbiased and efficient amplification of this RNA is also required. The WT-Ovation RNA amplification systems  used for cDNA probe generation are commonly mentioned in reports of microarray gene expression profiling using picograms of RNA In the present study we identify the optimal workflow which allows (a) efficient RNA isolation from minimal cell numbers, (b) efficient microarray probe generation from picograms of input RNA which allows the continued detection of a rare class of transcripts  over a range of abundances and (c) the generation of global gene expression profiles from clinically relevant vascular endothelial biopsies previously restricted to focussed interrogation.in vitro “analogue” of the human vascular endothelial cell biopsies utilised in this study Human umbilical venous endothelial cells represent an Optimisation of the RNA isolation workflow included the assessment of several carrier molecules (C), linear acrylamide) with combinations of Isopropanol/Ethanol precipitation with ammonium acetate to aid in RNA yield retention compared to commercial column-based isolation techniques (Qiagen RNeasy Micro). Only one carrier (poly(A) RNA) was shown to be advantageous in final yields of RNA under the conditions assessed, but is unfortunately incompatible with downstream array probe synthesis techniques (data not shown). The RNeasy column-based technologies can incorporate optional QIAshredder™ homogenisation of the cell lysate and an on-column DNase I treatment to eliminate genomic DNA from subsequent RNA samples. In a series of preliminary investigations, QIAshredder cell lysate homogenisation at low levels of input cells, <3000 cells was shown to be detrimental to the resultant RNA yield compared to vigorous vortexing (data not shown). On-column DNase I treatment also resulted in an overall 20% loss in RNA yield (data not shown). As an alternative to enzymatic elimination of genomic DNA, gDNA Wipeout reagent (Qiagen) has been demonstrated to result in genomic DNA free-RNA, even from input template amounts of 1 µg RNA with moderate gDNA contamination. Whilst we were able to verify no negative effect on RNA yield of introduction of this step using this proprietary reagent, it was also apparent that the resultant RNA samples containing gDNA Wipeout reagent were incompatible with downstream probe synthesis technologies, thus necessitating removal by further purification schema.Analysis of the resultant cDNA from both process A and following optimisation, process B by comparison to a reference HUVEC RNA calibration set clearly demonstrated that optimisation of the RNA isolation workflow resulted in significantly increased yields of isolated RNA (approximately 2–3 fold higher), particularly important at the 200 cell range , Table 1Vascular endothelial cell biopsy clinical samples were collected following written informed consent from 114 patients  in a study that had been approved by the local ethics committee. Biological interpretation of these data and accompanying clinical observations will be reported elsewhere. All samples were processed through the optimal RNA isolation workflow outlined here (process B). Assessment of yielded RNA was performed by converting 10% of the yielded RNA to cDNA in parallel with a HUVEK cell RNA standard curve for comparative assessment using β-Actin qCPR. The average yield across all 114 samples was 1032.6±848.6 pg (mean ± standard deviation), with a median of 778 pg and an absolute range of 73 pg to 5027 pg of total RNA. Of the 114 clinical biopsies, 36.8% yielded over 1 ng and 28.1% of samples yielded less than 500 pg of RNA. With the assumption that RNA content per cell is similar in purified endothelial cells as in HUVEK cells, our approximations of numbers of cells yielded in the collection procedure equates to a range of 9 to 638 cells, with a median of 97 cells. These data illustrate the requirement for a microarray workflow capable of operation at below 500 pg to maximise cohort utility and successfully interrogate vascular endothelial biopsies by microarray technology.The efficacies of WT-Ovation FFPE RNA amplification system V2 and WT-Ovation One-Direct RNA amplification system were assessed using RNA template input within the picogram range.Both kits were assessed over a range of input levels within their own working ranges. Previously, studies using HUVEC RNA titrations had suggested that sscDNA probe yield and quality would be compromised below 200 pg in the WT-Ovation FFPE RNA amplification system (data not shown). HUVEC RNA dilutions were split (when input overlapping across systems), used as input template for both systems and processed in parallel .The WT-Ovation FFPE RNA amplification system V2 is marketed for use with RNA derived from FFPE material, within a working range of 50 ng–100 ng input. For this reason 50 ng of high quality HUVEC RNA was used as a positive control for the performance of the system. Quality assessment shows that the sscDNA molecules generated from 50 ng of HUVEC RNA are of broad distribution in length, averaging approximately 500–1000 nucleotides, suggesting efficient sscDNA synthesis . It can The WT-Ovation One-Direct kit is specifically intended for amplification of RNA within the 500–10 pg range for hybridisation to microarrays. Technical duplicates of HUVEC total RNA were processed, reproducibly yielding dscDNA probe quantities in excess of the 5 µg required for array hybridisation . CompareUsing the WT-Ovation FFPE system, the sscDNA probes generated from 50 ng of input RNA result in GeneChip metrics with 61% present calls . Whilst The WT-Ovation One-Direct dscDNA probes from 500 pg and 250 pg of RNA input result in present calls similar to that achieved with the WT-Ovation FFPE system at the same overlapping input amount  500 pg,. β-actin2≥6) and 42 (log2≥7) GPCR transcripts when using 50 ng and 52 (log2≥6) and 35 (log2≥7) transcripts from 250 pg input (2≥6) and 83% (log2≥7) of transcripts detected at 50 ng of RNA still present when using 200 times less input of 250 pg RNA (2≥6) and 26 (log2≥7) GPCR transcripts are robustly detected at 50 pg of input RNA, representing 74% (log2≥6) and 66% (log2≥7) overlap with those detected when using 500 pg (2≥7), with a 34% overlap with those detected at 500 pg input using the WT-Ovation One-Direct system  results in greater accessibility of the mRNA molecule for the subsequent enzymatic steps in the sscDNA generation procedure, at least for this class of transcripts.To assess the retention of low abundant transcripts with decreasing RNA input levels and reduced probe set detection, microarray data was filtered for those probe sets representing a family of proteins, G protein-coupled receptors (GPCR), which are highly important for cellular signalling, however, known to be generally of low abundance and notoriously difficult to detect using microarray technology pg input . Signifi0 pg RNA . When utg 500 pg . Expresst system . HoweverIn order to determine the preferred approach for microarray analysis using vascular endothelial biopsies, RNA derived from a representative test sample was equally split and processed through both the WT-Ovation FFPE RNA amplification system V2 and the WT-Ovation One-Direct RNA amplification system. An input level of 300 pg of total RNA was chosen to allow comparison of both systems. Resultant yields of cDNA probe obtained from 300 pg of input RNA were 4.3 µg and 11.9 µg in the WT-Ovation FFPE and WT-Ovation One-Direct systems, respectively . The sscsscDNA probe generation using the WT-Ovation FFPE RNA amplification system V2 was carried out using RNA from vascular endothelial cell biopsy samples, with all inputs normalised to 300 pg RNA. With the assumption of an RNA content of 8 pg/cell, this equates to our global profiling being performed on the RNA equivalent of 37 purified endothelial cells. Whilst it is possible to generate array datasets from this range of input RNA material without the requirement to normalise RNA input for all samples, data outlined here clearly demonstrate that omission of normalisation of input quantities would likely introduce further magnitudes of variability . To maxiA broad spectrum of sscDNA quality derived from vascular endothelial RNA was observed, with the size distribution of some cDNAs peaking at 500–1000 nucleotides as would be expected for highest quality probes, but others generated sscDNA peaking at less than 500 nts, representing less efficient synthesis. Twenty-one of the sscDNAs displayed a high level of short fragments (<200 nucleotides) deemed as non-specific amplification and failed to display a significant amount of efficient and template specific amplification so were not hybridised to GeneChips . By visuMean array quality control metrics were assessed for all 64 vascular endothelial biopsy samples hybridised to GeneChips. Mean % present calls of 32.0%±7.21% (mean ± SD)  were achA great deal of progress has been made over the past few years in reducing the amount of input material required to carry out global transcriptional profiling using microarray technology. There are several reports of microarray datasets produced using laser capture micro-dissected material and from clinical biopsies which have yielded only nanograms of RNA material RNA extraction methods shown to successfully yield good quality RNA of sufficient amounts from thousands or millions of cells are of course not necessarily optimised for use when using samples containing hundreds of cells. We observed several steps in traditional RNA extraction workflows to have a detrimental effect on RNA yield from minimal cell numbers, for example passing cell lysates through homogenisation matrices or carrying out on-column DNAse I treatments. The negative impact of these workflow components on RNA yield becomes evident only when using lower amounts of starting material. However, by altering these workflows and using titrated cell numbers we have succeeded in establishing an optimal RNA extraction process which yields approximately 2.5 times higher RNA yields when utilising below 3000 cells. Isolating RNA from cell populations such as these is challenging and whilst an average estimate of RNA content per cell may be in the range of 10 pg, depending on the cell type, is still not guaranteed to yield amounts of RNA within the nanogram range. To ensure maximum exploitation of the minimal cell samples available to us, we also sought to establish an RNA amplification method capable of producing robust array hybridisation probes, resulting in data capable of capturing biological information of interest, from RNA within the picogram range.2>0.95) to those obtained using 50 ng of input RNA. This translated to retention of 84% of the genes detected at 50 ng input remaining as a robust signal at 250 pg input when studying a family of genes (GPCRs) known to be of low abundance and difficult to detect by conventional microarray analysis. When processing clinical biopsies containing minimal cell numbers good quality cDNA and array metrics were obtained, although a reduction in sscDNA yield was observed. However, this reflected loss of synthesised material rather than poor overall synthesis, resulting from sscDNA purification schema employed at that time and which has since been changed to an alternative.The WT-Ovation FFPE RNA amplification system is specifically designed for use with RNA of reduced integrity from FFPE material. This system employs random priming in addition to PolyA priming and incorporates a secondary SPIA linear amplification step. In this study we proposed to exploit this increased amplification power for use with minimal input RNA amounts extracted from any tissue matrix. The FFPE system demonstrated that 250 pg of input RNA yields the same high quality cDNA probes and GeneChips with high correlation (R2>0.92). Unfortunately, as might be expected we did not observe this high level of performance when using 10 pg of input RNA as these samples generate R2 values of 0.77–0.86 when compared to higher input levels, with apparent loss of detection of higher abundance transcripts. We conclude therefore that the One-Direct system can further push the lower limits of material required for probe synthesis for microarray experiments to 50 pg of input when using high quality RNA, without significant impact on resulting information generated. Nonetheless, 10 pg of input RNA still results in generation of arrays from which a large amount of transcriptional information can be derived . However, it should be noted that variation in input RNA results in differences in the transcriptional information captured by array, and which is particularly evident at low input levels. Therefore, whilst quantification of such low levels following primary RNA isolation is challenging, we recommend that this is performed to allow subsequent input normalisation (as outlined in the current study) and eventual maximisation of ability to interrogate variability due to biology rather than technical parameters.Further opportunity for increased amplification power when using RNA input within the picogram range is offered by the One-Direct RNA amplification system, designed for use with high quality RNA ranging from 500 pg down to 10 pg of input. We assessed this using titrated high quality RNA within the kits working range and found that reducing RNA input in this kit does not influence the quality of cDNA probe generated, with all samples from 500 pg to 10 pg producing similar populations of cDNA probe size distribution. The cDNA probes generated at all input levels using the One-Direct system did consist of shorter probe fragments than those generated from at little as 250 pg using the FFPE system. However, this does not appear to significantly affect the performance of the subsequent microarrays as illustrated by the similarities in the microarray metrics from the FFPE and One-Direct system at the same levels of input RNA. Within the One-Direct system high correlation between GeneChips from decreasing input material can been seen from 500 pg down to 50 pg of input  over the cells. Following removal of the 1 x HEPES Buffered Saline Solution, 1 ml of 1×0.05% Trysin/EDTA solution (Sigma-Aldrich) was added to the flask. Cells were loosened by placement in the incubator for 1 minute followed by the addition of 1 x Trypsin Neutralizing Solution and then suspension in 1 x HEPES Buffered Saline Solution. The cell suspension was centrifuged for 5 minutes at 220 x g and the cell pellet resuspended in 1 x HEPES Buffered Saline Solution. Following a second centrifugation the cell pellet was resuspended in fresh 1 x HEPES Buffered Saline Solution.Low passage Human umbilical venous endothelial cell line (HUVEC) was obtained from Millipore and were maintained in EGM-2 BulletKit medium  according to the manufacturers recommendations at 37°C in 5% COFour 200 µl aliquots of the cell suspension were removed to 1.5 ml tubes. To each aliquot 200 µl of Solution A-100  was added and each tube vortexed for 30 seconds. 200 µl of Solution B-100 was then added to each tube followed by vortexing for 30 seconds. The cell solution was analysed by a NucleoCounter (ChemoMetec A/S) following loading of each sample in to a Cell Counting Cartridge. All samples were counted for cell number in quadruplicate and diluted in 1 x HEPES buffer to the desired cell number (ranging from 3000 to 200 cells) in a final volume of 50 µl. To each 50 µl sample of known cell number, 300 µl of buffer RLT/2-mercaptoethanol (Qiagen) was added and all samples stored at −80°C prior to processing.Venous endothelial cells were collected from healthy controls, patients with insulin resistance and coronary artery disease. The study was approved by the Tayside committee on Medical Ethics. All patients gave written informed consent and all experiments were carried out in accordance to the Helsinki Declaration.Endothelial cells were collected after the volunteer had been laid supine for 30 minutes using a modified technique of venous endothelial biopsy as described by Each sample was split between 4 eppendorf tubes (approx 500 µl/tube) and 5 µl of dynabeads , pre-coated with mouse anti-human CD146 monoclonal antibody , was added to each tube. The tubes were incubated at 4°C for 25 mins with rotation before being placed in a magnetic rack. A magnet was used to collect the beads and the supernatant removed and discarded. The remaining beads were then washed twice with sterile ECDS (500 µl per wash), once with 500 µl sterile Hanks Balanced Salt Solution (HBSS) and twice with sterile Phosphate Buffered Saline (PBS) (500 µl per wash). After the first PBS wash the supernatant was discarded but after the second, approximately 50 µl of liquid was retained to resuspend the beads. Buffer RLT/2-mercaptoethanol  was added to the bead suspension. Brief vortexing to disrupt the cells from the beads and then separation by 2 minutes on the magnet was carried out. Finally, the resultant lysate was transferred to a fresh, sterile eppendorf tube and stored at −80°C. The entire cell separation procedure was completed within 1 hour of venous cell biopsy.6 HUVEC using the RNeasy Mini RNA isolation kit (Qiagen) according to manufacturer's instructions. Briefly, 350 µl HUVEC lysate samples were thawed following storage at −80°C. To ensure complete cell lysis the samples were vortexed vigorously for 10 seconds and pulse spun. An equal volume (350 µl) of 70% ethanol was added to the cell lysate and mixed by pipetting. The entire sample was applied to an RNeasy Mini Spin Column in a 2 ml collection tube. The RNeasy Mini Spin Columns were centrifuged for 15 seconds at 16,300 x g. The flow-through was re-applied to the same RNeasy Mini Spin Column and the centrifugation repeated. 350 µl of buffer RW1 was applied to each RNeasy Mini Spin Columns followed by centrifugation for 15 seconds at 16,300 x g. A DNase I incubation mix was prepared by combining 10 µl of DNase I and 70 µl of Buffer RDD per sample. DNase treatment was performed by pipetting 80 µl of DNase I incubation mix directly on to the RNeasy Mini Spin column membrane and incubating at room temperature for 15 minutes. To wash the RNeasy Mini Spin Column, 350 µl of Buffer RW1 was added and centrifuged for 15 seconds at 16,300 x g followed by 500 µl of Buffer RPE and centrifugation for 2 minute at 16,300 x g. An additional centrifugation for 1 minute at 16,300 x g was carried out to dry the column membrane. RNA was eluted into fresh 1.5 ml microcentrifuge tubes using 50 µl of RNase-free water followed by centrifugation for 1 minute at 16,300 x g.Total RNA was isolated from 1×10When isolating RNA from titrated minimal cell numbers (3000 – 200) total RNA was isolated using the RNeasy Micro RNA isolation kit (Qiagen) following the manufacturers instructions (process A) or with modifications (process B) . RNA isog. An equal volume (350 µl) of 70% ethanol was added to the cell lysate and mixed by pipetting. The entire sample was applied to an RNeasy MinElute Spin Column in a 2 ml collection tube. The RNeasy MinElute Spin Columns were centrifuged for 15 seconds at 16,300 x g. The flow-through was re-applied to the same RNeasy MinElute Spin Column and the centrifugation repeated. 350 µl of buffer RW1 was applied to each RNeasy MinElute Spin Column followed by centrifugation for 15 seconds at 16,300 x g. A DNase I incubation mix was prepared by combining 10 µl of DNase I and 70 µl of Buffer RDD per sample. DNase treatment was performed by pipetting 80 µl of DNase I incubation mix directly on to the RNeasy Mini Spin column membrane and incubating at room temperature for 15 minutes. To wash the RNeasy Mini Spin Column, 350 µl of Buffer RW1 was added and centrifuged for 15 seconds at 16,300 x g followed by 500 µl of Buffer RPE and centrifugation for 15 seconds at 16,300 x g. A further 500 µl of 80% Ethanol was added and the column centrifuged for 2 minutes at 16,300 x g. An additional centrifugation for 5 minutes at 16,300 x g was carried out to dry the column membrane. RNA was eluted into fresh 1.5 ml microcentrifuge tubes by adding 20 µl of RNase-free water on to the membrane followed by centrifugation for 1 minute at 16,300x g. The eluate was reapplied to the same RNeasy MinElute Spin Column and the centrifugation repeated. All samples were stored at −80°C prior to further processing.When following the manufacturer's instructions (process A) the cells were suspended and lysed by vortexing vigorously for 10 seconds and pulse spun. Sample were homogenised by pipetting the cell lysate directly onto a QIAshredder Spin Column (QIagen) placed in a 2 ml collection tube and centrifuged for 2 minutes at 16,300 x g. The flow-through was re-applied to the same RNeasy MinElute Spin Column and the centrifugation repeated. 700 µl of buffer RW1 was applied to each RNeasy MinElute Spin Column followed by centrifugation for 15 seconds at 16,300 x g. To wash the RNeasy MinElute Spin Column, 500 µl of Buffer RPE was added and centrifuged for 15 seconds at 16,300 x g followed by 500 µl of 80% Ethanol and centrifugation for 2 minute at 16,300 x g. An additional centrifugation for 5 minutes at 16,300 x g was carried out to dry the column membrane. RNA was eluted into fresh 1.5 ml microcentrifuge tubes by incubating 20 µl of RNase-free water on the membrane for 1 minute followed by centrifugation for 1 minute at 16,300 x g. The eluate was reapplied to the same RNeasy MinElute Spin Column and the incubation and centrifugation repeated.Total RNA from minimal cell numbers was also extracted using the RNeasy Micro RNA isolation kit with the following modifications (process B) . Cells wGenomic DNA (gDNA) elimination was carried out on the total RNA samples from minimal cell numbers by gDNA Wipeout buffer treatment . Firstly, the 20 µl RNA samples were dried down in a Concentrator 5301 (Eppendorf) without heat for 9 minutes to obtain a final volume of 12 µl. To each concentrated RNA sample 2 µl of gDNA Wipeout buffer was added and incubated at 40°C for 5 minutes.g. The flow-through was re-applied to the same RNeasy MinElute Spin Column and the centrifugation repeated. 500 µl of buffer RPE was applied to each RNeasy MinElute Spin Column followed by centrifugation for 15 seconds at 16,300 x g. To wash the RNeasy MinElute Spin Column, 500 µl of 80% Ethanol and added and the columns centrifuged for 2 minute at 16,300 x g. An additional centrifugation for 5 minutes at 16,300x g was carried out to dry the column membrane. RNA was eluted into fresh 1.5 ml microcentrifuge tubes by incubating 20 µl of RNase-free water on the membrane for 1 minute followed by centrifugation for 1 minute at 16,300 x g. The eluate was reapplied to the same RNeasy MinElute Spin Column and the incubation and centrifugation repeated. All samples were stored at −80°C prior to further processing.Total RNA was recovered from the gDNA elimination reaction using the RNeasy Micro kit (Qiagen) RNA clean up protocol. Briefly, 86 µl of RNase-free water was added to the gDNA elimination reactions. 350 µl of buffer RLT/2-mercaptoethanol was added and mixed by pipetting. 250 µl of 100% Ethanol was added and mix by pipetting. The entire sample was applied to an RNeasy MinElute Spin Column in a 2 ml collection tube. The RNeasy MinElute Spin Columns were centrifuged for 15 seconds at 16,300 x 6 HUVEC was measured using a Nanodrop ND-8000 spectrophotometer . RNA quality was assessed in part by OD260/280 ratios but primarily by use of an Agilent 2100 Bioanalyzer .The quantity of total RNA from 1×10The quantity of total RNA from titrated minimal cell numbers and vascular endothelial biopsies was measured following reverse transcription of the RNA to cDNA and subsequent real-time quantitative PCR along with a calibration curve of RNA from the same cells. RNA reverse transcription was carried out using the Quantitect Reverse Transcription Kit (Qiagen) following the manufacturers instructions. Briefly, both unknown samples and standard curve samples made from HUVEC RNA dilutions of known concentration ranging from 500 ng–1 pg RNA were made up to 12 µl volume using RNase-free water. When measuring RNA quantity from HUVEC titrated minimal cell numbers, all of the isolated RNA was used in the Quantitect Reverse Transcription Kit (Qiagen). Following RNA isolation optimisation using either HUVEC titrated minimal cell numbers or vascular endothelial biopsies, 10% of isolated RNA was used for reverse transcription. gDNA Wipeout buffer (7 x) was added to each sample and mixed by pipetting. All samples were incubated at 42°C for 5 minutes and placed immediately on ice. A reverse transcription reaction was carried out by adding 1 µl of RT enzyme, 4 µl of Quantiscript buffer (5 x) and 1 µl of RT primer mix to each sample followed by incubation at 42°C for 20 minutes. The reaction was halted by a further incubation at 95°C for 3 minutes. All reaction were stored at −20°C prior to further processing.5-GGACTTCGAGCAAGAGATGG-3 and Reverse primer: 5-AGCACTGTGTTGGCGTACAG-3. PCR master mix was loaded to each well and the plate centrifuged at 2,000 x g for 20 seconds and run on a 7900HT (ABI).Quantitect cDNA samples generated from minimal cell numbers and vascular endothelial biopsies or standard curve RNA dilutions were diluted 1∶25 or 1∶100, respectively for input in the real-time quantitative PCR. All quantification was carried out using β-actin as the target gene for amplification. SybrGreen (Bio-rad) along with β-actin primers used for quantification of HUVEC titrated minimal cells and vascular endothelial cell biopsy samples. Forward primer: Preparation of cDNA SPIA probes for microarray hybridisation, was carried out with varying amounts of total HUVEC RNA (50 ng–10 pg) or vascular endothelial cell samples using NuGEN Technologies  WT-Ovation™ FFPE RNA amplification system V2 or WT-Ovation™ One-Direct RNA amplification system according to the manufacturers' instructions. cDNA probes generated using the WT-Ovation™ FFPE RNA amplification system V2 from RNA isolated from titrated minimal cell samples were purified prior to quantification using either the DNA clean and concentrator system (Zymo) or QIAquick PCR purification kit (Qiagen). All cDNA generated using the WT-Ovation™ One-Direct RNA amplification system was purified using the MinElute system (Qiagen) as directed by Nugen Technolgies, Inc. All cDNA probes generated from vascular endothelial biopsy samples were purified using the QIAquick PCR purification kit (Qiagen). The vascular endothelial cell biopsy samples were all processed for cDNA probe generation in batches including positive controls of 50 ng and 300 pg HUVEC total RNA and a no template control reaction. Synthesised cDNA probe concentration was measured by Nanodrop ND-8000 . The NuGEN Technologies FL-Ovation™ cDNA Biotin Module V2 was used for cDNA fragmentation and biotin labelling of amplified cDNA for subsequent hybridisation to the microarrays . The quality of the cDNA probes was assessed before and after fragmentation with the Agilent 2100 Bioanalyzer using RNA Nano chips .cDNA probes generated from NuGen Technologies RNA amplification systems were hybridised to Affymetrix Human Genome U133 Plus 2.0 Arrays  as described in the Affymetrix Expression Analysis Technical Manual. Briefly, 5 µg (HUVEC) or 4.5 µg  of fragmented and labelled cDNA, together with spiked hybridisation controls (GeneChip Expression 3′ Amplification Reagents – hybridisation controls), was hybridised for 18 hrs at 45°C in a rotating oven. Following hybridisation GeneChip washing and staining was performed using the GeneChip Hybridisation Wash and Stain kit  on an Affymetrix GeneChip Fluidics Station 450 using the appropriate fluidic script for the U133 Plus 2.0 microarrays with cDNA (FS450-0004). GeneChips were scanned immediately following staining in an Affymetrix GeneChip Scanner 3000 . MIAME-compliant array data can be accessed via Gene Expression Omnibus (GEO), GSE21723.2 transformation.Report files summarising the quality of target and control detection for each microarray were generated by GeneChip Operating Software Version 1.4 (GCOS) using the MAS5.0 algorithm . Quality control analysis was performed using Expression Console (Affymetrix) and Partek Genomics Suite. Correlation between GeneChips was assessed by Pearson's Correlation on the signal from all probes following MAS5.0 data extraction. Principal component analyses (PCA) were carried out using Partek Genomics Suite on MAS5.0 normalised data followed by Log