Impact of non-coding RNAs in genetic disease and papillomavirus lifecycle

Non-coding RNAs are vital to several diverse biological processes. Untranslated regions of mRNAs (UTRs) and variability therein can often cause differential regulation of transcripts. This regulation is often effected by microRNAs (miRNAs), small non-coding RNAs that interacts with 3’UTRs to regulate gene expression post-transcriptionally. Here we investigate the variation in the 3’UTR of SERPINA1 gene, mutations of which cause the often life-threatening Alpha-1-antitrypsin deficiency (A1AD), and effects on miRNA. We screened 50 miRNA mimics and determined their overexpression does not affect secreted alpha-1-antitrypsin (AAT). Additionally, we showed through the use of a poxvirus protein to degrade miRNAs that underexpression of miRNAs does not affect secreted AAT. Using luciferase reporters we determine that in cultured cells, there are no liver-specific trans-factors that act on the SERPINA1 3’UTR, of any length, to regulate gene expression. We sequenced the 3’UTRs from the largest cohort of of A1AD patients to date and determined that 3’UTR variation does not contribute to disease severity in patients with one form of A1AD, and that in a cell culture context, miRNAs do not regulate secreted AAT. We conclude that neither 3’UTR variation nor miRNAs affect wild-type secreted AAT. In addition to genetic disease, miRNAs regulate multiple aspects of the host-pathogen interface. Until now no widely accepted PV-encoded miRNAs have been described. We have developed miRNA Discovery by forced Genomic Expression (miDGE), a new wet bench approach to miRNA identification that screens numerous pathogen genomes in parallel. Using miDGE, we screened over 75 different PV genomes for the ability to code for miRNAs. We conclusively demonstrate a lack of PV miRNA expression in cancers associated with infections of several high risk HPVs. However, we identified five different miRNAs encoded by four different PVs (Human PVs 17, 37, 41 and Fringilla colebs (Fc) PV). We show that miRNAs from two PVs (HPV41 & FcPV) are able to regulate transcripts corresponding to the early region of the PV genome.. Combined, these findings identify the first canonical PV miRNAs and support that miRNAs of either host or viral origin are important regulators of the PV life cycle.Microbiolog

Discovering ligands for a microRNA precursor with peptoid microarrays

We have screened peptoid microarrays to identify specific ligands for the RNA hairpin precursor of miR-21, a microRNA involved in cancer and heart disease. Microarrays were printed by spotting a library of 7680 N-substituted oligoglycines (peptoids) onto glass slides. Two compounds on the array specifically bind RNA having the sequence and predicted secondary structure of the miR-21 precursor hairpin and have specific affinity for the target in solution. Their binding induces a conformational change around the hairpin loop, and the most specific compound recognizes the loop sequence and a bulged uridine in the proximal duplex. Functional groups contributing affinity and specificity were identified, and by varying a critical methylpyridine group, a compound with a dissociation constant of 1.9 μM for the miR-21 precursor hairpin and a 20-fold discrimination against a closely-related hairpin was created. This work describes a systematic approach to discovery of ligands for specific pre-defined novel RNA structures. It demonstrates discovery of new ligands for an RNA for which no specific lead compounds were previously known by screening a microarray of small molecules

Ketohexokinase-mediated fructose metabolism is lost in hepatocellular carcinoma and can be leveraged for metabolic imaging

The ability to break down fructose is dependent on ketohexokinase (KHK) that phosphorylates fructose to fructose-1-phosphate (F1P). We show that KHK expression is tightly controlled and limited to a small number of organs and is down-regulated in liver and intestinal cancer cells. Loss of fructose metabolism is also apparent in hepatocellular adenoma and carcinoma (HCC) patient samples. KHK overexpression in liver cancer cells results in decreased fructose flux through glycolysis. We then developed a strategy to detect this metabolic switch in vivo using hyperpolarized magnetic resonance spectroscopy. Uniformly deuterating [2-13C]-fructose and dissolving in D2O increased its spin-lattice relaxation time (T1) fivefold, enabling detection of F1P and its loss in models of HCC. In summary, we posit that in the liver, fructolysis to F1P is lost in the development of cancer and can be used as a biomarker of tissue function in the clinic using metabolic imaging

Identification of virus-encoded microRNAs in divergent Papillomaviruses.

MicroRNAs (miRNAs) are small RNAs that regulate diverse biological processes including multiple aspects of the host-pathogen interface. Consequently, miRNAs are commonly encoded by viruses that undergo long-term persistent infection. Papillomaviruses (PVs) are capable of undergoing persistent infection, but as yet, no widely-accepted PV-encoded miRNAs have been described. The incomplete understanding of PV-encoded miRNAs is due in part to lack of tractable laboratory models for most PV types. To overcome this, we have developed miRNA Discovery by forced Genome Expression (miDGE), a new wet bench approach to miRNA identification that screens numerous pathogen genomes in parallel. Using miDGE, we screened over 73 different PV genomes for the ability to code for miRNAs. Our results show that most PVs are unlikely to code for miRNAs and we conclusively demonstrate a lack of PV miRNA expression in cancers associated with infections of several high risk HPVs. However, we identified five different high-confidence or highly probable miRNAs encoded by four different PVs (Human PVs 17, 37, 41 and a Fringilla coelebs PV (FcPV1)). Extensive in vitro assays confirm the validity of these miRNAs in cell culture and two FcPV1 miRNAs are further confirmed to be expressed in vivo in a natural host. We show that miRNAs from two PVs (HPV41 & FcPV1) are able to regulate viral transcripts corresponding to the early region of the PV genome. Combined, these findings identify the first canonical PV miRNAs and support that miRNAs of either host or viral origin are important regulators of the PV life cycle

High-scoring PV pre-miRNA predictions.

<p>High-scoring PV pre-miRNA predictions.</p

miDGE identifies PV-encoded miRNA candidates.

<p><b>(A)</b> Neighbor-joining tree calculated on alignment of L1 nucleotide sequences of the better-covered papillomaviruses (n = 73 with >95% DNA coverage) included in miDGE library. Color indicates genus membership, with miRNA-encoding papillomaviruses in bold and select high risk cancer-associated papillomaviruses in italics. <b>(B)</b> Small RNA coverage distribution of top-scoring miDGE miRNA candidates that were predicted by MiRDeep2. <b>(C)</b> Structures of PV pre-miRNAs were predicted by minimal free energy folding using the RNAfold algorithm. The positions of mature miRNAs observed in small RNA-seq libraries are indicated in red. <b>(D)</b> The position of identified viral pre-miRNAs is denoted by the hairpin shape. The identified seed sequence matches are noted at their respective positions with the sequences of the miRNA and potential targets.</p

PV-encoded miRNAs are active in RISC.

<p>RISC reporter assays for the PV-encoded miRNAs where HEK293 cells were co-transfected with a firefly luciferase transfection control and <i>Renilla</i> luciferase reporter with either perfectly complementary sequence matches for each indicated miRNA, or its respective negative control seed complement mutant. Either of these were co-transfected with control empty miRNA expression vector (blue), the relevant PV miRNA-expression vector (orange), or negative control irrelevant miRNA expression vector (SV40) (gray). Average <i>Renilla</i> luciferase activity relative to firefly luciferase normalized to empty miRNA expression vector control is shown for fcpv1-miR-F1 (N = 3), fcpv1-miR-F2 (N = 5), hpv41-miR-H1 (N = 5), hpv17-miR-H1 (N = 3), and hpv37-miR-H1 (N = 4). Statistical test performed was a Two-Sample t Test. The average <i>Renilla</i> luciferase activity normalized to firefly luciferase activity is shown, error bars indicate Standard Error, and asterisks indicate statistical significance, (*) p≤0.05; (**) p≤0.01.</p

PV-encoded miRNAs can regulate transcript sequences in early genes.

<p>RISC reporter assays for the PV-encoded miRNAs. In all panels, the average <i>Renilla</i> luciferase activity normalized to firefly luciferase activity is shown, error bars indicate Standard Error, and asterisks indicate statistical significance, (*) p≤0.05; (**) p≤0.01. <b>(A)</b> HEK293T cells were co-transfected with either a control empty miRNA expression vector (control) or the indicated PV miRNA expression vector along with both the normalization control firefly luciferase vector and a <i>Renilla</i> luciferase-based reporter plasmids with vector UTR (Empty 3’UTR) or FcPV1 genomic DNA containing both putative miRNA docking sites (FcPV1 Early), N = 4. Statistical test performed was a One-Sample t Test. <b>(B)</b> HEK293T cells were co-transfected with either the SV40 miRNA expression vector (Control) or the indicated PV miRNA expression vector and both the control firefly luciferase vector and the <i>Renilla</i> luciferase-based reporter plasmids with vector UTR (Empty), FcPV1 E1 genomic sequence (E1), or the seed sequence mutant (E1 mut), N = 4. Statistical test performed was a One-Sample t Test. <b>(C)</b> HEK293T cells were co-transfected with either the SV40 miRNA expression vector (Control) or the indicated PV miRNA expression vector and both the control firefly luciferase vector and the <i>Renilla</i> luciferase-based reporter plasmids with vector UTR (Empty), FcPV1 E2 genomic sequence (E2), or the seed sequence mutant (E2 mut), N = 12. Statistical test performed was a One-Sample t Test. <b>(D)</b> HEK293T cells were co-transfected with either the SV40 miRNA expression vector (Control) or the HPV41 miRNA expression vector and both the control firefly luciferase vector and the <i>Renilla</i> luciferase-based reporter plasmids with vector UTR (Empty), HPV41 genomic DNA containing both putative miRNA sites (HPV41 Early), the site in E1 (HPV41 E1), the seed sequence mutant (E1 mut) N = 7 or the site in E2 (HPV41 E2), N = 4. Statistical test performed was a One-Sample t Test.</p

Small RNA-seq read & mapping statistics.

<p>Small RNA-seq read & mapping statistics.</p