Identification of Novel Therapeutic Candidates Against SARS-CoV-2 Infections: An Application of RNA Sequencing Toward mRNA Based Nanotherapeutics

Utilizing Nanopore direct RNA sequencing of blood from patients with sepsis for discovery of co- and post-transcriptional disease biomarkers

BACKGROUND

RNA sequencing of whole blood has been increasingly employed to find transcriptomic signatures of disease states. These studies traditionally utilize short-read sequencing of cDNA, missing important aspects of RNA expression such as differential isoform abundance and poly(A) tail length variation.

METHODS

We used Oxford Nanopore Technologies sequencing to sequence native mRNA extracted from whole blood from 12 patients with definite bacterial and viral sepsis and compared with results from matching Illumina short-read cDNA sequencing data. Additionally, we explored poly(A) tail length variation, novel transcript identification, and differential transcript usage.

RESULTS

The correlation of gene count data between Illumina cDNA- and Nanopore RNA-sequencing strongly depended on the choice of analysis pipeline; NanoCount for Nanopore and Kallisto for Illumina data yielded the highest mean Pearson's correlation of 0.927 at the gene level and 0.736 at the transcript isoform level. We identified 2 genes with differential polyadenylation, 9 genes with differential expression and 4 genes with differential transcript usage between bacterial and viral infection. Gene ontology gene set enrichment analysis of poly(A) tail length revealed enrichment of long tails in mRNA of genes involved in signaling and short tails in oxidoreductase molecular functions. Additionally, we detected 240 non-artifactual novel transcript isoforms.

CONCLUSIONS

Nanopore RNA- and Illumina cDNA-gene counts are strongly correlated, indicating that both platforms are suitable for discovery and validation of gene count biomarkers. Nanopore direct RNA-seq provides additional advantages by uncovering additional post- and co-transcriptional biomarkers, such as poly(A) tail length variation and transcript isoform usage.

Transcriptomic profiling of severe and critical COVID-19 patients reveals alterations in expression, splicing and polyadenylation

Coronavirus disease 2019 (COVID-19) is a multi-systemic illness that became a pandemic in March 2020. Although environmental factors and comorbidities can influence disease progression, there is a lack of prognostic markers to predict the severity of COVID-19 illness. Identifying these markers is crucial for improving patient outcomes and appropriately allocating scarce resources. Here, an RNA-sequencing study was conducted on blood samples from unvaccinated, hospitalized patients divided by disease severity; 367 moderate, 173 severe, and 199 critical. Using a bioinformatics approach, we identified differentially expressed genes (DEGs), alternative splicing (AS) and alternative polyadenylation (APA) events that were severity-dependent. In the severe group, we observed a higher expression of kappa immunoglobulins compared to the moderate group. In the critical cohort, a majority of AS events were mutually exclusive exons and APA genes mostly had longer 3'UTRs. Interestingly, multiple genes associated with cytoskeleton, TUBA4A, NRGN, BSG, and CD300A, were differentially expressed, alternatively spliced and polyadenylated in the critical group. Furthermore, several inflammation-related pathways were observed predominantly in critical vs. moderate. We demonstrate that integrating multiple downstream analyses of transcriptomics, from moderate, severe, and critical patients confers a significant advantage in identifying relevant dysregulated genes and pathways.

CD177, MYBL2, and RRM2 Are Potential Biomarkers for Musculoskeletal Infections

BACKGROUND

Biomarkers of infection are measurable indicators that reflect the presence of an infection in the body. They are particularly valuable for detecting infections and tracking treatment responses. Previous transcriptome analysis of peripheral blood mononuclear cells (PBMCs) collected from patients during the active phase of diabetic foot infection identified the upregulation of several genes, including a neutrophil-specific cell surface glycoprotein, CD177, an Myb-related transcription factor 2 (MYBL2), and ribonucleotide reductase regulatory subunit M2 (RRM2). We aimed to investigate whether these observations in diabetic foot infections could be extrapolated to other musculoskeletal infections.

QUESTIONS/PURPOSES

(1) Are the protein concentrations of CD177, MYBL2, and RRM2 elevated in serum or PBMCs of patients with musculoskeletal infections? (2) Do serum and PBMC concentrations of CD177, MYBL2, and RRM2 decrease in response to antibiotic therapy? (3) Can these biomarkers give diagnostic accuracy and differentiate patients with musculoskeletal infections from controls?

METHODS

From April 2023 to June 2024, we treated 26 patients presenting with clinical symptoms and signs of acute musculoskeletal infections, including elevated inflammatory markers (white blood cell [WBC] and C-reactive protein [CRP]) and local changes such as swelling, erythema, tenderness or pain, warmth, purulent drainage, sinus tract, or wound leading to bone or hardware. Diagnosis included periprosthetic joint infection (PJI), foot and ankle infection (FAI), fracture-related infection (FRI), and septic arthritis of the native joints. Patients with chronic recurrent osteomyelitis, PJI, or FRI were excluded from the study. Among the 26 patients deemed potentially eligible, 19% (5) were excluded for the following reasons: prison inmate (1), unable to provide consent because of severe sepsis (1), mental illness (1), and declined to participate (2). Of the 81% (21) of patients who provided consent, cultures from 9.5% (2) were negative. These two patients were ultimately diagnosed with inflammatory arthritis: gout (1) and rheumatoid arthritis (1); thus, the musculoskeletal infection group for analysis consisted of 73.1% (19 of 26) of patients. A control group of 21 patients undergoing elective foot or ankle deformity correction surgery without infections or systemic inflammation was included. Because foot or ankle deformity is highly unlikely to influence the immunologic profile of the subjects, we believed that these patients would serve as an appropriate control group. Other than the absence of infection and the lower prevalence of diabetes mellitus, the control group was comparable to the study group in terms of demographics and clinical factors, including age and sex distribution. We collected blood samples from both patients and controls and quantified CD177, MYBL2, and RRM2 RNA transcription levels in the PBMC using qRT-PCR. We also assessed protein concentrations in the serum and PBMC using an enzyme-linked immunosorbent assay. A comparative analysis of the three biomarkers was performed on 19 patients with musculoskeletal infections with positive cultures and 21 controls to assess their diagnostic potential using the unpaired nonparametric t-test with the Mann-Whitney test. We obtained 8-week follow-up blood samples from seven patients with musculoskeletal infections who clinically healed. Healing was defined by normalization of inflammatory markers (WBC and CRP) and absence of swelling, erythema, local tenderness or pain, warmth, purulent drainage, sinus tract, or open wound. We performed a comparative analysis of the seven patients during active infection and after treatment to determine a change in the level of CD177, MYBL2, and RRM2 in their serum and PBMCs. These findings were also compared with those of the control group. We evaluated the diagnostic accuracy of CD177, MYBL2, and RRM2 for musculoskeletal infections using receiver operating characteristic (ROC) curve analysis.

RESULTS

The musculoskeletal infections group showed a larger increased serum and PBMC concentrations of CD177, MYBL2, and RRM2 proteins compared with the control group. The mean protein concentrations of CD177, MYBL2, and RRM2 were increased in the serum and PBMC of the musculoskeletal infections group compared with the controls. Serum levels of all biomarkers investigated were higher in musculoskeletal infections group compared with the control group (CD177 227 [155 to 432] versus 54 [10 to 100], difference of medians 173, p < 0.01; MYBL2 255 [231 to 314] versus 180 [148 to 214], difference of medians 75, p < 0.01; RRM2 250 [216 to 305] versus 190 [148 to 255], difference of medians 60, p < 0.01). Similarly, PBMC levels of all biomarkers were higher in the musculoskeletal infections group (CD177 55.3 [39.1 to 80.5] versus 17.5 [10.5 to 27.5], difference of medians 37.8, p < 0.01; MYBL2 144 [114 to 190] versus 91 [70 to 105], difference of medians 53, p < 0.01; RRM2 168 [143 to 202] versus 100 [77.5 to 133], difference of medians 68, p < 0.01). Additionally, serum levels of all biomarkers decreased in seven patients with musculoskeletal infections after infection treatment (CD177 3080 [2690 to 3320] versus 4250 [3100 to 8640], difference of medians 1170, p < 0.01; MYBL2 4340 [4120 to 4750] versus 5010 [4460 to 5880], difference of medians 670, p < 0.01; RRM2 4350 [3980 to 5000] versus 5025 [4430 to 6280], difference of medians 675, p = 0.01). Similarly, PBMC levels of all biomarkers were lower after infection treatment (CD177 805 [680 to 980] versus 1025 [750 to 1610], difference of medians 220, p < 0.01; MYBL2 2300 [2100 to 2550] versus 2680 [2220 to 3400], difference of medians 380, p = 0.02; RRM2 2720 [2500 to 3200] versus 3350 [2825 to 4030], difference of medians 630, p < 0.01). The area under the ROC curve for diagnosing musculoskeletal infections in the serum and PBMC was as follows: CD177 95% confidence interval [CI] > 0.99 and > 0.99, MYBL2 95% CI > 0.99 and > 0.99, and RRM2 95% CI = 0.96 and > 0.99, respectively.

CONCLUSION

We may utilize blood-based tests for CD177, MYBL2, and RRM2 to aid in the diagnosis of musculoskeletal infections, particularly when arthrocentesis or obtaining tissue culture is challenging. They may also assist in monitoring treatment response. As some of these biomarkers may also be elevated in other inflammatory conditions, a large-scale clinical study is needed to confirm their reliability in differentiating musculoskeletal infections from other inflammatory conditions.

CLINICAL RELEVANCE

CD177, MYBL2, and RRM2 proteins in blood samples may serve as novel biomarkers for diagnosing and monitoring treatment response in musculoskeletal infections.

Proteomic biomarkers of long-term lung function decline in textile workers: a 35-year longitudinal study

BACKGROUND

Occupational exposures contribute significantly to obstructive lung disease among textile workers. However, biomarkers associated with such declines are not available.

OBJECTIVES

We conducted a large-scale proteomic study to explore protein biomarkers potentially associated with long-term lung function decline.

METHODS

Shanghai Textile Workers Cohort was established in 1981 with 35 years of follow-up, assessing textile workers' lung functions every five years. Quantitative serum proteomics was performed on all 453 workers at 2016 survey. We employed four distinct models to examine the association between forced expiratory volume in one second (FEV1) and proteins, and consolidated the findings using an aggregated Cauchy association test. Furthermore, proteomic data of UK Biobank (UKB) was used to explore the associations of potential protein markers and decline of FEV1, and the interactions of these proteins were examined through STRING database. Associations were also externally validated using two-sample Mendelian randomizations (MR).

RESULTS

15 of 907 analyzed proteins displayed potential associations with long-term FEV1 decline, including two hemoglobin subunits: hemoglobin subunit beta (HBB, FDR-qACAT = 0.040), alpha globin chain (HBA2, FDR-qACAT = 0.045), and four immunoglobulin subunits: immunoglobulin kappa variable 3-7 (IGKV3-7, FDR-qACAT = 0.003), immunoglobulin heavy chain variable region (IgH, FDR-qACAT = 0.011). Five proteins were significantly associated with the rate of decline of FEV1 in UKB, in which RAB6A, LRRN1, and BSG were also found to be associated with proteins identified in Shanghai Textile Workers Cohort using STRING database. MR indicated bidirectional associations between HBB and FEV1 (P < 0.05), while different immunoglobulin subunits exhibited varying associations with FEV1.

IMPACT STATEMENT

We performed a large-scale proteomic study of the longest-follow-up pulmonary function cohort of textile workers to date. We discovered multiple novel proteins associated with long-term decline of FEV1 that have potential for identifying new biomarkers associated with long-term lung function decline among occupational populations, and may identify individuals at risk, as well as potential pharmaceutical targets for early intervention.

Bioinformatics and system biology approach to identify potential common pathogenesis for COVID-19 infection and sarcopenia

Sarcopenia is a condition characterized by age-related loss of muscle mass and strength. Increasing evidence suggests that patients with sarcopenia have higher rates of coronavirus 2019 (COVID-19) infection and poorer post-infection outcomes. However, the exact mechanism and connections between the two is unknown. In this study, we used high-throughput data from the GEO database for sarcopenia (GSE111016) and COVID-19 (GSE171110) to identify common differentially expressed genes (DEGs). We conducted GO and KEGG pathway analyses, as well as PPI network analysis on these DEGs. Using seven algorithms from the Cytoscape plug-in cytoHubba, we identified 15 common hub genes. Further analyses included enrichment, PPI interaction, TF-gene and miRNA-gene regulatory networks, gene-disease associations, and drug prediction. Additionally, we evaluated immune cell infiltration with CIBERSORT and assessed the diagnostic accuracy of hub genes for sarcopenia and COVID-19 using ROC curves. In total, we identified 66 DEGs (34 up-regulated and 32 down-regulated) and 15 hub genes associated with sarcopenia and COVID-19. GO and KEGG analyses revealed functions and pathways between the two diseases. TF-genes and TF-miRNA regulatory network suggest that FOXOC1 and hsa-mir-155-5p may be identified as key regulators, while gene-disease analysis showed strong correlations with hub genes in schizophrenia and bipolar disorder. Immune infiltration showed a correlation between the degree of immune infiltration and the level of infiltration of different immune cell subpopulations of hub genes in different datasets. The ROC curves for ALDH1L2 and KLF5 genes demonstrated their potential as diagnostic markers for both sarcopenia and COVID-19. This study suggests that sarcopenia and COVID-19 may share pathogenic pathways, and these pathways and hub genes offer new targets and strategies for early diagnosis, effective treatment, and tailored therapies for sarcopenia patients with COVID-19.

Portraying the dark side of endogenous IFN-λ for promoting cancer progression and immunoevasion in pan-cancer

BACKGROUND

IFN-λ has been shown to have a dual function in cancer, with its tumor-suppressive roles being well-established. However, the potential existence of a negative ''tumor-promoting'' effect of endogenous IFN-λ is still not fully understood.

METHODS

We conducted a comprehensive review and analysis of the perturbation of IFN-λ genes across various cancer types. Correlation coefficients were utilized to examine the relationship between endogenous IFN-λ expression and clinical factors, immune cell infiltration, tumor microenvironment, and response to immunotherapy. Genes working together with IFN-λ were obtained by constructing the correlation-based network related to IFN-λ and the gene interaction network in the KEGG pathway and IFN-λ-related genes obtained from the networks were integrated as candidate markers for the prognosis model. We then applied univariate and multivariate COX regression models to select cancer-specific independent prognostic markers associated with IFN-λ and to investigate risk factors for these genes by survival analysis. Additionally, computational methods were used to analyze the transcriptome, copy number variations, genetic mutations, and methylation of IFN-λ-related patient groups.

RESULT

Endogenous expression of IFN-λ has been linked to poor prognosis in cancer patients, with the genes IFN-λ2 and IFN-λ3 serving as independent prognostic markers. IFN-λ acts in conjunction with related genes such as STAT1, STAT2, and STAT3 to affect the JAK-STAT signaling pathway, which promotes tumor progression. Abnormalities in IFN-λ genes are associated with changes in immune checkpoints and immune cell infiltration, which in turn affects cancer- and immune-related pathways. While there is increased immune cell infiltration in patients with IFN-λ expression, this does not improve survival prognosis, as T-cell dysfunction and an inflammatory environment are also present. The amplification of IFNL2 and IFNL3 copy number variants drives specific endogenous expression of IFN-λ in patients, and those with this specific expression have been found to have more mutations in the TP53 gene and lower levels of DNA methylation.

CONCLUSION

Our study integrated multi-omics data to provide a comprehensive insight into the dark side of endogenous IFN-λ, providing a fundamental resource for further discovery and therapeutic exploration in cancer.

Adaptive best subset selection algorithm and genetic algorithm aided ensemble learning method identified a robust severity score of COVID-19 patients

We used an integrated ensemble learning method to build a stable prediction model for severity in COVID-19 patients, which was validated in multicenter cohorts.

Serum proteomics hint at an early T-cell response and modulation of SARS-CoV-2-related pathogenic pathways in COVID-19-ARDS treated with Ruxolitinib

Background

Acute respiratory distress syndrome (ARDS) in corona virus disease 19 (COVID-19) is triggered by hyperinflammation, thus providing a rationale for immunosuppressive treatments. The Janus kinase inhibitor Ruxolitinib (Ruxo) has shown efficacy in severe and critical COVID-19. In this study, we hypothesized that Ruxo's mode of action in this condition is reflected by changes in the peripheral blood proteome.

Methods

This study included 11 COVID-19 patients, who were treated at our center's Intensive Care Unit (ICU). All patients received standard-of-care treatment and n = 8 patients with ARDS received Ruxo in addition. Blood samples were collected before (day 0) and on days 1, 6, and 10 of Ruxo treatment or, respectively, ICU admission. Serum proteomes were analyzed by mass spectrometry (MS) and cytometric bead array.

Results

Linear modeling of MS data yielded 27 significantly differentially regulated proteins on day 1, 69 on day 6 and 72 on day 10. Only five factors (IGLV10-54, PSMB1, PGLYRP1, APOA5, WARS1) were regulated both concordantly and significantly over time. Overrepresentation analysis revealed biological processes involving T-cells only on day 1, while a humoral immune response and complement activation were detected at day 6 and day 10. Pathway enrichment analysis identified the NRF2-pathway early under Ruxo treatment and Network map of SARS-CoV-2 signaling and Statin inhibition of cholesterol production at later time points.

Conclusion

Our results indicate that the mechanism of action of Ruxo in COVID-19-ARDS can be related to both known effects of this drug as a modulator of T-cells and the SARS-CoV-2-infection.