A Competitive Endogenous RNA Network Based on Differentially Expressed lncRNA in Lipopolysaccharide‐Induced Acute Lung Injury in Mice

Non-coding RNAs have remarkable roles in acute lung injury (ALI) initiation. Nevertheless, the significance of long non-coding RNAs (lncRNAs) in ALI is still unknown. Herein, we purposed to identify potential key genes in ALI and create a competitive endogenous RNA (ceRNA) modulatory network to uncover possible molecular mechanisms that affect lung injury. We generated a lipopolysaccharide-triggered ALI mouse model, whose lung tissue was subjected to RNA sequencing, and then we conducted bioinformatics analysis to select genes showing differential expression (DE) and to build a lncRNA-miRNA (microRNA)- mRNA (messenger RNA) modulatory network. Besides, GO along with KEGG assessments were conducted to identify major biological processes and pathways, respectively, involved in ALI. Then, RT-qPCR assay was employed to verify levels of major RNAs. A protein-protein interaction (PPI) network was created using the Search Tool for the Retrieval of Interacting Genes (STRING) database, and the hub genes were obtained with the Molecular Complex Detection plugin. Finally, a key ceRNA subnetwork was built from major genes and their docking sites. Overall, a total of 8,610 lncRNAs were identified in the normal and LPS groups. Based on the 308 DE lncRNAs [p-value < 0.05, |log2 (fold change) | > 1] and 3,357 DE mRNAs [p-value < 0.05, |log2 (fold change) | > 1], lncRNA-miRNA and miRNA-mRNA pairs were predicted using miRanda. The lncRNA-miRNA-mRNA network was created from 175 lncRNAs, 22 miRNAs, and 209 mRNAs in ALI. The RT-qPCR data keep in step with the RNA sequencing data. GO along with KEGG analyses illustrated that DE mRNAs in this network were mainly bound up with the inflammatory response, developmental process, cell differentiation, cell proliferation, apoptosis, and the NF-kappa B, PI3K-Akt, HIF-1, MAPK, Jak-STAT, and Notch signaling pathways. A PPI network on the basis of the 209 genes was established, and three hub genes (Nkx2-1, Tbx2, and Atf5) were obtained from the network. Additionally, a lncRNA-miRNA-hub gene subnetwork was built from 15 lncRNAs, 3 miRNAs, and 3 mRNAs. Herein, novel ideas are presented to expand our knowledge on the regulation mechanisms of lncRNA-related ceRNAs in the pathogenesis of ALI.

Random clonal expansion as a limiting factor in transplantable in vivo CRISPR/Cas9 screens

Transplantable in vivo CRISPR/Cas9 knockout screens, in which cells are transduced in vitro and inoculated into mice to form tumours in vivo, offer the opportunity to evaluate gene function in a cancer model that incorporates the multicellular interactions of the tumour microenvironment. In this study, we sought to develop a head and neck squamous cell carcinoma (HNSCC) tumour xenograft model for whole-genome screens that could maintain high gRNA representation during tumour initiation and progression. To achieve this, we sought early-passage HNSCC cell lines with a high frequency of tumour initiation-cells, and identified the pseudodiploid UT-SCC-54C line as a suitable model from 23 HNSCC lines tested based on a low tumourigenic dose for 50% takes (TD50) of 1100 cells in NSG mice. On transduction with the GeCKOv2 whole-genome gRNA library (119,461 unique gRNAs), high (80-95%) gRNA representation was maintained in early (up to 14 d) UT-SCC-54C tumours in NSG mice, but not in UT-SCC-74B tumours (TD50=9200). However, loss of gRNA representation was observed in UT-SCC-54C tumours following growth for 38-43 days, which correlated with a large increase in bias among gRNA read counts due to stochastic expansion of clones in the tumours. Applying binomial thinning simulations revealed that the UT-SCC-54C model would have 40-90% statistical power to detect drug sensitivity genes with log2 fold change effect sizes of 1-2 in early tumours with gRNA libraries of up to 10,000 gRNAs and modest group sizes of 5 tumours. In large tumours, this model would have had 45% power to detect log2 fold change effect sizes of 2-3 with libraries of 2,000 gRNAs and 14 tumours per group. Based on our findings, we conclude that gRNA library size, sample size and tumour size are all parameters that can be individually optimised to ensure transplantable in vivo CRISPR screens can successfully evaluate gene function.

Transcriptomics Analysis of Lens from Patients with Posterior Subcapsular Congenital Cataract

To gain insight into the aetiology of posterior subcapsular congenital cataract from the perspective of transcriptional changes, we conducted an mRNA sequencing analysis of the lenses in posterior subcapsular congenital cataract patients and in normal children. There were 1,533 differentially expressed genes from 19,072 genes in the lens epithelial cells of the posterior subcapsular congenital cataract patients compared to in the normal controls at a cut-off criteria of |log2 fold change| of >1 and a p-value of <0.05, including 847 downregulated genes and 686 upregulated genes. To further narrow down the DEGs, we utilised the stricter criteria of |log2 fold change| of >1 and an FDR value of <0.05, and we identified 551 DEGs, including 97 upregulated genes and 454 downregulated genes. This study also identified 1,263 differentially expressed genes of the 18,755 genes in lens cortex and nuclear fibres, including 646 downregulated genes and 617 upregulated genes. The downregulated genes in epithelial cells were significantly enriched in the structural constituent of lenses, lens development and lens fibre cell differentiation. After filtering the DEGs using the databases iSyTE and Cat-Map, several high-priority candidate genes related to posterior subcapsular congenital cataract such as GRIFIN, HTRA1 and DAPL1 were identified. The findings of our study may provide a deeper understanding of the mechanisms of posterior subcapsular congenital cataract and help in the prevention and treatment of this disease.

579. Design and Immunogenicity of a Pan-SARS-CoV-2 Synthetic DNA Vaccine

Background First-generation COVID-19 vaccines are matched to spike protein of the Wuhan-H1 (WT) strain. Convalescent and vaccinee samples show reduced neutralization of SARS-CoV-2 variants of concern (VOC). Next generation DNA vaccines could be matched to single variants or synthetically designed for broader coverage of multiple VOCs. Methods The synthetic consensus (SynCon®) sequence for INO-4802 SARS-CoV-2 spike with focused RBD changes and dual proline mutations was codon-optimized (Figure 1). Sequences for wild-type (pWT) and B.1.351 (pB.1.351) were similarly optimized. Immunogenicity was evaluated in BALB/c mice. Pre-clinical efficacy was assessed in the Syrian Hamster model. Figure 1. Design Strategy for INO-4802 Results INO-4802 induced potent neutralizing antibody responses against WT, B.1.1.7, P.1, and B.1.351 VOC in a murine model. pWT vaccinated animals showed a 3-fold reduction in mean neutralizing ID50 for the B.1.351 pseudotyped virus. INO-4802 immunized animals had significantly higher (p = 0.0408) neutralizing capacity (mean ID50 816.16). ID50 of pB.1.351 serum was reduced 7-fold for B.1.1.7 and significantly lower (p = 0.0068) than INO-4802 (317.44). INO-4802 neutralized WT (548.28) comparable to pWT. INO-4802 also neutralized P.1 (1026.6) (Figure 2). pWT, pB.1.351 or INO-4802 induced similar T-cell responses against all variants. INO-4802 skewed towards a TH1-response. All hamsters vaccinated with INO-4802 or pB.1.351 were protected from weight loss after B.1.351 live virus challenge. 4/6 pWT immunized hamsters were completely protected. pWT immunized hamsters neutralized WT (1090) but not B.1.351 (39.16). INO-4802 neutralized both WT (672.2) and B.1.351 (1121) (Figure 3). We observed higher increase of binding titers following heterologous boost with INO-4802 (3.6 – 4.4 log2-fold change) than homologous boost with pWT (2.0 – 2.4 log2 fold change) (Figure 4). Figure 2. INO-4802 Induces Functional Humoral Immune Response Against SARS-CoV-2 Variants of Concern Figure 3. INO-4802 Protects Hamsters Against Challenge With B.1.351 Live Virus Figure 4. Heterologous Boost with INO-4802 Induces Humoral Immune Response Against SARS-CoV-2 Variants Conclusion Vaccines matching single VOCs, like pB.1.351 and pWT, elicit responses against the matched antigen but have reduced cross-reactivity. Presenting a pan-SARS-CoV-2 approach, INO-4802 may offer substantial advantages in terms of cross-strain protection, reduced susceptibility to escape mutants and non-restricted geographical use. Disclosures Katherine Schultheis, MSc, Inovio Pharmaceuticals (Employee) Charles C. Reed, PhD, Inovio Pharmaceuticals (Employee, Shareholder) Viviane M. Andrade, PhD, Inovio Pharmaceuticals Inc. (Employee) Richa Kalia, MS, Inovio Pharmaceuticals (Employee, Other Financial or Material Support, I have stock options with Inovio Pharmaceuticals as an employee.) Jared Tur, PhD, Inovio (Employee) Blake Schouest, PhD, Inovio Pharmaceuticals (Employee) Dustin Elwood, PhD, Inovio Pharmaceuticals (Employee) Arthur Doan, n/a, Inovio (Employee) Patrick Pezzoli, BS, Inovio (Employee) Dinah Amante, BS, Inovio (Employee) David Weiner, PhD, Inovio (Board Member, Grant/Research Support, Shareholder, I serve on the SAB in addition to the above activities) J Joseph Kim, PhD, Inovio (Employee) Laurent Humeau, PhD, Inovio Pharmaceuticals (Employee) Stephanie Ramos, PhD, Inovio Pharmaceuticals (Employee) Trevor R. F. Smith, PhD, Inovio (Employee, Shareholder) Kate Broderick, PhD, Inovio (Employee).

Proteomic analysis of genetically stratified low-grade meningioma

Aims Meningioma is the most common primary intracranial tumour. Although ~80% are benign WHO grade I and show high rates of recurrence. Surgery is the main therapeutic approach, yet location can hamper complete resection and chemotherapies are ineffective. Moreover, accurate biomarkers for clinical management are lacking. Approximately 60% sporadic meningiomas harbour mutations in the NF2gene, while mutations in genes including TRAF7, KLF4, AKT1, SMO and PIK3CAhave been identified majority in the NF2-positive low grade-tumours. Moreover, mutations in TRAF7 mostly co-occur with a KLF4K409Q or with AKT1E17K mutation. The mutations and their molecular manifestations consequently affect the signalling pathways at the protein level. The molecular mechanisms behind meningioma tumourigenesis are still obscure and the identification of specific biomarker is necessary to enable their implementation in routine diagnostics and therapeutics. Therefore, we aim to identify novel biomarkers and therapeutic targets of genetically stratified low-grade meningioma by characterising the proteomic landscape. Method Frozen tumour samples have already been analysed for NF2-/- by next generation sequencing and genotyped for common mutational hotspots in non-NF2 meningioma such as TRAF7, KLF4 and AKT1 and grouped in to three different mutational groups: AKT1E17K/TRAF7, KLF4K409Q/TRAF7and NF2-/- and all these mutations will be compared to normal healthy meninges. For global proteomics, proteins were separated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LC-MS/MS analysis. Raw mass spectrometry data files were processed by MaxQuant (1.6.2.10) and Perseus software (1.6.1.3). Quantitative phospho-proteomics was performed using TMT 10plex labelling approach followed by motif analysis using motif-X algorithm. GO enrichment analyses were performed using (DAVID) v6.8 against all human proteins. Potential candidates from expression data analysis will be validated via Western Blot and immunohistochemistry. Results We have quantified 4162 proteins across all mutational meningioma subgroups and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of mutational subgroups revealing clusters of differentially expressed proteins. Comparative analysis showed 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p&lt;0.05) among all mutational subtypes vs. normal meninges, indicating proteomic landscapes of mutational subtypes to be highly variable. In contrast, 257 proteins were commonly significantly downregulated (log2 fold-change≤-1; p&lt;0.05) and enriched with molecular functions including aldehyde dehydrogenase and oxido-reductase. Mutational subtype-specific analysis identified 162 proteins significantly upregulated in AKT1E17K/TRAF7 vs. remaining sample groups to be enriched in the oxidative phosphorylation pathway. However, only 14 and 7 proteins were commonly significantly upregulated in KLF4K409Q/TRAF7 and NF2-/- mutant meningioma subtypes respectively. Several of these up-regulated proteins including ANNEXIN-3, CRABP2, CLIC3 and Endoglin were already verified via WB. Lastly, analyses of 6600 phospho-sites (n=8) predicted regulatory kinases including CHEK1, CHEK2 and LCK. Conclusion Global proteomic and phos-phoproteomics analysis has led to the identification of proteins differentially expressed in mutant subtypes. Results of this study to date suggest that a proteomic approach is an effective tool to identify distinct patterns in genetically distinct meningioma subgroups. Further validation and functional verification (with inhibitory or knockdown approaches) of potential candidates will allow us to identify potential drug targets/biomarkers for meningiomas.

Transcriptomic Response of L. monocytogenes to Co-Culture with S. cerevisiae

The aim of the present study was to assess the transcriptomic response of L. monocytogenes during co-culture with three S. cerevisiae strains. For this purpose, BHI broth was inoculated with 7 log CFU·mL−1 L. monocytogenes serotype 4b strain LQC 15257, isolated from a strawberry sample and 4 log CFU·mL−1 S. cerevisiae strains Y32, Y34 and Y37, isolated from spontaneous olive fermentation. Sampling took place after 24 and 48 h incubation at 5 and 20 °C. RNA was extracted, stabilized and the transcription of virulence associated genes prfA, sigB, hly, plcA, plcB, inlA, inlB, inlC and inlJ, was assessed by RT-qPCR. Co-culture with the yeast strains mostly affected the transcription of sigB and inlJ, the upregulation of which during growth at 5 °C for 24 h, reached 10.13 and 9.76 log2(fold change), respectively. Similarly, the effect that incubation time had on the relative transcription of the genes under study was dependent on the co-cultivating yeast strain. On the other hand, the effect of the yeast strain was less pronounced when the relative transcription of the genes under study was assessed between 20 °C and 5 °C. In that case, incubation temperature seemed to have an important effect since, in the 79.2% of the samples analyzed, upregulation was evident, irrespective of yeast strain presence. These results highlight the complex trophic relationships that take place during co-existence between L. monocytogenes and S. cerevisiae.

OPTC-1. Proteomic analysis of genetically stratified low-grade meningioma

Introduction Meningioma are the most common primary intracranial tumour. According to WHO, ~80% tumours are benign grade I. Although, some grade I tumour clinically show aggressive behaviour. Radio-surgery are the main therapeutic approaches, chemotherapies are ineffective. Accurate biomarkers for clinical management are lacking. The mutational profile of low-grade meningioma is well-defined, with non-NF2 mutated tumours harbouring recurrent mutations in genes including TRAF7, KLF4, AKT1 and SMO. Here, we aim to identify novel biomarkers and therapeutic targets of genetically stratified low-grade meningioma by characterising the proteomic landscape. Materials and methods Meningioma specimens were stratified according to mutational background: AKT1E17K/TRAF7, KLF4K409Q/TRAF7 and NF2-/-. Proteins were separated by SDS-PAGE followed by in-gel tryptic digestion and sample preparation for LC-MS/MS analysis. Raw mass spectrometry data files were processed by MaxQuant and Perseus software. Quantitative phospho-proteomics was performed using TMT-10plex labelling approach followed by motif analysis using motif-X algorithm. GO enrichment analyses were performed using DAVID against all human proteins. Results and Conclusions We have quantified 4162 proteins across all mutational meningioma subgroups and normal meninges (n=31). Hierarchical clustering analysis showed distinct proteomic profiles of mutational subgroups revealing clusters of differentially expressed proteins (DEPs). Comparative analysis showed 10 proteins were commonly significantly upregulated (log2 fold-change≥1; p&lt;0.05) among all mutational subtypes vs. normal meninges, indicating proteomic landscapes of mutational subtypes to be highly variable. In contrast, 257 proteins were commonly significantly downregulated (log2 fold-change≤-1; p&lt;0.05) and enriched with molecular functions including aldehyde dehydrogenase and oxido-reductase. Mutational subtype-specific analysis identified 162 proteins significantly upregulated in AKT1E17K/TRAF7 vs. remaining sample groups to be enriched in the oxidative phosphorylation pathway. Lastly, analyses of 6600 phospho-sites (n=8) predicted regulatory kinases including EGFR and PKCα. Several of these up-regulated proteins and kinases already verified via WB. Further validation and functional verification will allow us to identify potential drug targets/biomarkers for meningioma.

DNA Methylation Profiling for the Diagnosis and Prognosis of Patients with Nontuberculous Mycobacterium Lung Disease

The incidence of nontuberculous Mycobacterium (NTM) lung disease is rapidly increasing; however, its diagnosis and prognosis remain unclear while selecting patients who will respond to appropriate treatment. Differences in DNA methylation patterns between NTM patients with good or poor prognosis could provide important therapeutic targets. We used the Illumina MethylationEPIC (850k) DNA methylation microarray to determine the pattern between differentially methylated regions (DMRs) in NTM patients with good or poor prognosis (n = 4/group). Moreover, we merged and compared 20 healthy controls from previous Illumina Methylation450k DNA methylation microarray data. We selected and visualized the DMRs in the form of heatmaps, and enriched terms associated with these DMRs were identified by functional annotation with the “pathfinder” package. In total, 461 and 293 DMRs (|Log2 fold change| > 0.1 and p < 0.03) were more methylated in patients with four poor and four good prognoses, respectively. Furthermore, 337 and 771 DMRs (|Log2 fold change| > 0.08 and p < 0.001) were more methylated in eight NTM patients and 20 healthy controls, respectively. TGFBr1 was significantly less methylated, whereas HLA-DR1 and HLA-DR5 were more methylated in patients with poor prognosis (compared to those with good prognosis). LRP5, E2F1, and ADCY3 were the top three less-methylated genes in NTM patients (compared with the controls). The mTOR and Wnt signaling pathway-related genes were less methylated in patients with NTM. Collectively, genes related to Th1-cell differentiation, such as TGFBr1 and HLA-DR, may be used as biomarkers for predicting the treatment response in patients with NTM lung disease.

Bovine Intelectin 2 Expression as a Biomarker of Paratuberculosis Disease Progression

Paratuberculosis (PTB), a chronic granulomatous enteritis caused by Mycobacterium avium subsp. paratuberculosis (MAP), is responsible for important economic losses in the dairy industry. Our previous RNA-sequencing (RNA-Seq) analysis showed that bovine intelectin 2 (ITLN2) precursor gene was overexpressed in ileocecal valve (ICV) samples of animals with focal (log2 fold-change = 10.6) and diffuse (log2 fold-change = 6.8) PTB-associated lesions compared to animals without lesions. This study analyzes the potential use of ITLN2, a protein that has been described as fundamental in the innate immune response to infections, as a biomarker of MAP infection. The presence of ITLN2 was investigated by quantitative immunohistochemical analysis of ICV samples of 20 Holstein Friesian cows showing focal (n = 5), multifocal (n = 5), diffuse (n = 5) and no histological lesions (n = 5). Significant differences were observed in the mean number of ITLN2 immunostained goblet and Paneth cells between the three histopathological types and the control. The number of immunolabelled cells was higher in the focal histopathological type (116.9 ± 113.9) followed by the multifocal (108.7 ± 140.5), diffuse (76.5 ± 97.8) and control types (41.0 ± 81.3). These results validate ITLN2 as a post-mortem biomarker of disease progression.

Growth Hormone Releasing Hormone Reduces Plasma Markers of Immune Activation and Hepatic Immune Pathways in Nonalcoholic Fatty Liver Disease

Introduction: The GH/IGF-1 axis affects multiple metabolic pathways, and animal models demonstrate that it also modulates immune function. Little is known, however, regarding effects of augmenting GH secretion on immune function in humans. This study used proteomics and gene set enrichment analysis to assess effects of a GH releasing hormone (GHRH) analog, tesamorelin, on circulating immune markers and immune-related gene pathways in the liver in people with HIV (PWH) and NAFLD. We hypothesized that tesamorelin would decrease circulating markers of immune activation in conjunction with previously reported reductions in visceral fat and hepatic triglyceride. Methods: 92 biomarkers associated with immune function (Olink Immuno-Oncology panel) were measured in plasma samples from 61 PWH with NAFLD who participated in a double-blind, randomized, 12-month trial of tesamorelin versus identical placebo. Proteins differentially altered by tesamorelin at a false discovery rate &lt; 0.1 were considered significantly changed. Gene set enrichment analysis targeted to immune pathways was subsequently performed on liver tissue from serial biopsies. Results: Compared to placebo, tesamorelin decreased circulating concentrations of 13 proteins, including four chemokines (C-C Motif Chemokine Ligands 3 [CCL3, effect size -0.38 Log2 fold change], 4 [CCL4, -0.36 Log2 fold change], and 13 [CCL13 or MCP4, -0.42 Log2 fold change] and interleukin-8 [-0.50 Log2 fold change]), two cytokines (interleukin-10 [-0.32 Log2 fold change] and cytokine stimulating factor 1 [-0.22 Log2 fold change]), and four T-cell associated molecules (CD8A [-0.37 Log2 fold change], Cytotoxic And Regulatory T Cell Molecule [CRTAM, -0.47 Log2 fold change], granzyme A [-0.53 Log2 fold change], and adhesion G protein-coupled receptor G1 [ADGRG1, -0.54 Log2 fold change]), as well as arginase-1 [-0.95 Log2 fold change], galectin-9 [-0.26 Log2 fold change], and hepatocyte growth factor [-0.30 Log2 fold change]. No proteins in the panel were significantly increased by tesamorelin. Network analysis indicated close interaction among the gene pathways responsible for the reduced proteins, with imputational analyses suggesting down regulation of a closely related cluster of immune pathways. Targeted transcriptomics using tissue from liver biopsy confirmed an end-organ signal of down-regulated immune pathways, including pathways involved in antigen presentation, complement activation, toll like receptor and inflammatory signaling, and T-cell activation. Conclusions: Long-term treatment with tesamorelin decreased circulating markers of T-cell and monocyte/macrophage activity, with corresponding downregulation of immune pathways in the liver. These findings suggest that augmenting pulsatile GH may ameliorate immune activation in a population with metabolic dysregulation and systemic inflammation.