Identification of serum MicroRNAs as diagnostic biomarkers for influenza H7N9 infection

Nanomaterial-based biosensors for avian influenza virus: A new way forward

Avian influenza virus (AIV) is a zoonotic virus that can be transmitted from animals to humans. Although human infections are rare, the virus has a high mortality rate when contracted. Appropriate detection methods are thus crucial for combatting this pathogen. There is a growing demand for rapid, selective, and accurate methods of identifying the virus. Numerous biosensors have been designed and commercialized to detect AIV. However, they all have considerable shortcomings. Nanotechnology offers a new way forward. Nanomaterials produce more eco-friendly, rapid, and portable diagnostic systems. They also exhibit high sensitivity and selectivity while achieving a low detection limit (LOD). This paper reviews state-of-the-art nanomaterial-based biosensors for AIV detection, such as those composed of quantum dots, gold, silver, carbon, silica, nanodiamond, and other nanoparticles. It also offers insight into potential trial protocols for creating more effective methods of identifying AIV and discusses key issues associated with developing nanomaterial-based biosensors.

Circulating Plasma miRNA Homologs in Mice and Humans Reflect Familial Cerebral Cavernous Malformation Disease

Patients with familial cerebral cavernous malformation (CCM) inherit germline loss of function mutations and are susceptible to progressive development of brain lesions and neurological sequelae during their lifetime. To date, no homologous circulating molecules have been identified that can reflect the presence of germ line pathogenetic CCM mutations, either in animal models or patients. We hypothesize that homologous differentially expressed (DE) plasma miRNAs can reflect the CCM germline mutation in preclinical murine models and patients. Herein, homologous DE plasma miRNAs with mechanistic putative gene targets within the transcriptome of preclinical and human CCM lesions were identified. Several of these gene targets were additionally found to be associated with CCM-enriched pathways identified using the Kyoto Encyclopedia of Genes and Genomes. DE miRNAs were also identified in familial-CCM patients who developed new brain lesions within the year following blood sample collection. The miRNome results were then validated in an independent cohort of human subjects with real-time-qPCR quantification, a technique facilitating plasma assays. Finally, a Bayesian-informed machine learning approach showed that a combination of plasma levels of miRNAs and circulating proteins improves the association with familial-CCM disease in human subjects to 95% accuracy. These findings act as an important proof of concept for the future development of translatable circulating biomarkers to be tested in preclinical studies and human trials aimed at monitoring and restoring gene function in CCM and other diseases.

miRNAs: The Key Regulator of COVID-19 Disease

As many parts of the world continue to fight the innumerable waves of COVID-19 infection, SARS-CoV-2 continues to sculpt its antigenic determinants to enhance its virulence and evolvability. Several vaccines were developed and used around the world, and oral antiviral medications are being developed against SARS-CoV-2. However, studies showed that the virus is mutating in line with the antibody's neutralization escape; thus, new therapeutic alternatives are solicited. We hereby review the key role that miRNAs can play as epigenetic mediators of the cross-talk between SARS-CoV-2 and the host cells. The limitations resulting from the "virus intelligence" to escape and antagonize the host miRNAs as well as the possible mechanisms that could be used in the viral evasion strategies are discussed. Lastly, we suggest new therapeutic approaches based on viral miRNAs.

Enhancing the yield of seasonal influenza viruses through manipulation of microRNAs in Madin-Darby canine kidney cells

Annual influenza vaccine is recommended to reduce the occurrence of seasonal influenza and its complications. Thus far, Madin-Darby canine kidney (MDCK) cell line has been used to manufacture cell-based influenza vaccines. Even though host microRNAs may facilitate viral replication, the interaction between MDCK cells-derived microRNAs and seasonal influenza viruses has been less frequently investigated. Therefore, this study highlighted microRNA profiles of MDCK cells to increase the yield of seasonal influenza virus production by manipulating cellular microRNAs. MDCK cells were infected with influenza A or B virus at a multiplicity of infection (MOI) of 0.01, and microRNA collections were then subjected to MiSeq (Illumina) Sequencing. The validated profiles revealed that cfa-miR-340, cfa-miR-146b, cfa-miR-197, and cfa-miR-215 were the most frequently upregulated microRNAs. The effect of candidate microRNA inhibition and overexpression on viral replication was determined using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and enzyme-linked immunosorbent assay (ELISA). The hybridization pattern between candidate miRNAs and viral genes was performed using miRBase and RNAhybrid web-based programs. Moreover, the predicted microRNA-binding sites were validated by a 3'-UTR reporter assay. The results indicated that cfa-miR-146b could directly target the PB1 gene of A/pH1N1 and the PA gene of B/Yamagata. Furthermore, cfa-miR-215 could silence the PB1 gene of A/pH1N1 and the PB1 gene of B/Victoria. However, the PB2 gene of the A/H3N2 virus was silenced by cfa-miR-197. In addition, the HA and NA sequences of influenza viruses harvested from the cell cultures treated with microRNA inhibitors were analyzed. The sequencing results revealed no difference in the antigenic HA and NA sequences between viruses isolated from the cells treated with microRNA inhibitors and the parental viruses. In conclusion, these findings suggested that MDCK cell-derived microRNAs target viral genes in a strain-specific manner for suppressing viral replication. Conversely, the use of such microRNA inhibitors may facilitate the production of influenza viruses.

Recent Advances in Plasma-Engineered Polymers for Biomarker-Based Viral Detection and Highly Multiplexed Analysis

Infectious diseases remain a pervasive threat to global and public health, especially in many countries and rural urban areas. The main causes of such severe diseases are the lack of appropriate analytical methods and subsequent treatment strategies due to limited access to centralized and equipped medical centers for detection. Rapid and accurate diagnosis in biomedicine and healthcare is essential for the effective treatment of pathogenic viruses as well as early detection. Plasma-engineered polymers are used worldwide for viral infections in conjunction with molecular detection of biomarkers. Plasma-engineered polymers for biomarker-based viral detection are generally inexpensive and offer great potential. For biomarker-based virus detection, plasma-based polymers appear to be potential biological probes and have been used directly with physiological components to perform highly multiplexed analyses simultaneously. The simultaneous measurement of multiple clinical parameters from the same sample volume is possible using highly multiplexed analysis to detect human viral infections, thereby reducing the time and cost required to collect each data point. This article reviews recent studies on the efficacy of plasma-engineered polymers as a detection method against human pandemic viruses. In this review study, we examine polymer biomarkers, plasma-engineered polymers, highly multiplexed analyses for viral infections, and recent applications of polymer-based biomarkers for virus detection. Finally, we provide an outlook on recent advances in the field of plasma-engineered polymers for biomarker-based virus detection and highly multiplexed analysis.

Interplay between host non-coding RNAs and influenza viruses

Influenza virus infection through seasonal epidemics and occasional pandemics has been a major public health concern for decades. Incomplete protection from vaccination and increased antiviral resistance due to frequent mutations of influenza viruses have led to a continuous need for new therapeutic options. The functional significance of host protein and influenza virus interactions has been established, but relatively less is known about the interaction of host noncoding RNAs, including microRNAs and long noncoding RNAs, with influenza viruses. In this review, we summarize host noncoding RNA profiles during influenza virus infection and the regulation of influenza virus infection by host noncoding RNAs. Influenza viral non-coding RNAs are briefly discussed. Increased understanding of the molecular regulation of influenza viral replication will be beneficial in identifying potential therapeutic targets against the influenza virus.

Machine Learning-Assisted Array-Based Detection of Proteins in Serum Using Functionalized MoS2 Nanosheets and Green Fluorescent Protein Conjugates

Abnormal concentrations of a specific protein or the presence of some biomarker proteins may indicate life-threatening diseases. Pattern-based detection of specific analytes using affinity-regulated receptors is one of the potential alternatives to specific antigen-antibody-based detection. In this report, we have schemed a sensor array by using various functionalized two-dimensional (2D)-MoS2 nanosheets and green fluorescent protein (GFP) as the receptor and the signal transducer, respectively. Two-dimensional MoS2 has been used as a promising candidate for recognition of the bioanalytes because of its high surface-to-volume ratio compared to those of other nanomaterials. Easy surface tunability of this material provides additional advantages to analyze the target of interest. The optimized 2D-MoS2-GFP conjugates are able to discriminate 15 different proteins at 50 nM concentration with a detection limit of 1 nM. Moreover, proteins in the binary mixture and in the presence of serum were discriminated successfully. Ten different proteins in serum media at relevant concentrations were classified successfully with 100% jackknifed classification accuracy, which proves the potentiality of the above system. We have also implemented and discussed the implication of using different machine learning models on the pattern recognition problem associated with array-based sensing.

Profile of circulating microRNAs in myalgic encephalomyelitis and their relation to symptom severity, and disease pathophysiology

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a complex chronic disease, rooted in multi-system dysfunctions characterized by unexplained debilitating fatigue. Post-exertional malaise (PEM), defined as the exacerbation of the patient's symptoms following minimal physical or mental stress, is a hallmark of ME/CFS. While multiple case definitions exist, there is currently no well-established biomarkers or laboratory tests to diagnose ME/CFS. Our study aimed to investigate circulating microRNA expression in severely ill ME/CFS patients before and after an innovative stress challenge that stimulates PEM. Our findings highlight the differential expression of eleven microRNAs associated with a physiological response to PEM. The present study uncovers specific microRNA expression signatures associated with ME/CFS in response to PEM induction and reports microRNA expression patterns associated to specific symptom severities. The identification of distinctive microRNA expression signatures for ME/CFS through a provocation challenge is essential for the elucidation of the ME/CFS pathophysiology, and lead to accurate diagnoses, prevention measures, and effective treatment options.

Automated multiplex nucleic acid tests for rapid detection of SARS-CoV-2, influenza A and B infection with direct reverse-transcription quantitative PCR (dirRT-qPCR) assay in a centrifugal microfluidic platform

The coronavirus disease 2019 (COVID-19) pandemic, caused by the new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, has posed a threat to public health worldwide. Also, influenza virus has caused a large number of deaths annually. Since co-infection of SARS-CoV-2 and influenza virus, which share similar symptoms, hampers current treatment efficiency, multiple simultaneous detection of these viruses is needed to provide the right treatment for patients. We developed a microfluidic disc-direct RT-qPCR (dirRT-qPCR) assay for rapid multiplex detection of SARS-CoV-2, influenza A and B viral infection in pharyngeal swab samples in an automated manner. Choices of the DNA polymerase, concentrations of dTPs and MgCl2 were characterized to optimize the assay. A detection limit of 2 × 101 copies per reaction was found in all three viral RNAs with as little as 2 μL of swab samples. The accuracy of our assay was evaluated with 2127 clinical swab samples of infection with these three viruses and healthy controls, and it possessed a consistency rate of 100, 99.54 and 99.25% in SARS-CoV-2, influenza A and B detection in comparison to standard RT-qPCR. The reported scheme of our assay is capable of screening other viral infections for up to 16 targets simultaneously. The whole diagnosis could be completed in 1.5 hours after simple sample loading by a non-technical expert. This constitutes an enabling strategy for large-scale point-of-care screening of multiple viral infections, which ultimately lead to a pathway for resolving the critical issue of early diagnosis for the prevention and control of viral outbreaks.

Implications of SARS-CoV-2 Mutations for Genomic RNA Structure and Host microRNA Targeting

The SARS-CoV-2 virus is a recently-emerged zoonotic pathogen already well adapted to transmission and replication in humans. Although the mutation rate is limited, recently introduced mutations in SARS-CoV-2 have the potential to alter viral fitness. In addition to amino acid changes, mutations could affect RNA secondary structure critical to viral life cycle, or interfere with sequences targeted by host miRNAs. We have analysed subsets of genomes from SARS-CoV-2 isolates from around the globe and show that several mutations introduce changes in Watson-Crick pairing, with resultant changes in predicted secondary structure. Filtering to targets matching miRNAs expressed in SARS-CoV-2-permissive host cells, we identified ten separate target sequences in the SARS-CoV-2 genome; three of these targets have been lost through conserved mutations. A genomic site targeted by the highly abundant miR-197-5p, overexpressed in patients with cardiovascular disease, is lost by a conserved mutation. Our results are compatible with a model that SARS-CoV-2 replication within the human host is constrained by host miRNA defences. The impact of these and further mutations on secondary structures, miRNA targets or potential splice sites offers a new context in which to view future SARS-CoV-2 evolution, and a potential platform for engineering conditional attenuation to vaccine development, as well as providing a better understanding of viral tropism and pathogenesis.

miR-6086 inhibits ovarian cancer angiogenesis by downregulating the OC2/VEGFA/EGFL6 axis

miRNAs have emerged as a pivotal component of gene regulatory networks, mediating cytokines secretion, cell cycle, and differentiation regulation. However, how miRNAs collaborate with transcription factors and downstream effector proteins that determine the fate of ovarian cancer cells remains to be understood, especially regarding to mechanism of tumor angiogenesis regulation. Based on the qRT-PCR and IHC analysis, we found that miR-6086 was maintained a very low level both in ovarian cancer cell lines and tissues. Further, we identified OC2 and EGFL6 as the direct targets of miR-6086 by luciferase assay and we observed an inverse relationship between the expression of miR-6086 and the OC2/VEGFA/EGFL6 axis. The Western blotting analysis suggested that OC2 could directly upregulate VEGFA and indirectly up-regulate EGFL6 through VEGFA. Moreover, miR-6086 could indirectly downregulate VEGFA through OC2. In addition, miR-6086, siOC2 and siEGFL6 could negatively regulate the tumor growth and angiogenesis of ovarian cancer (Skov3) in the animal studies, with the inhibition rates of 77.07%, 69.89%, and 73.62%, respectively (**p < 0.01). Moreover, the tumor cell proliferation, migration, and invasion of ovarian cancer cell lines (Caov3 and Skov3) and vascular formation (HUVECs) were significantly suppressed in vitro, by decreasing the AKT/MAPK pathways (*p < 0.05). Taken together, our results reveal that miR-6086 can suppress the angiogenesis networks in ovarian cancer by down-regulating the OC2/VEGFA/EGFL6 axis, directly or indirectly, which may provide potential targets for tumor therapeutics.

Technological Advances in Multiscale Analysis of Single Cells in Biomedicine

Single-cell analysis has recently received significant attention in biomedicine. With the advances in super-resolution microscopy, fluorescence labeling, and nanoscale biosensing, new information may be obtained for the design of cancer diagnosis and therapeutic interventions. The discovery of cellular heterogeneity further stresses the importance of single-cell analysis to improve our understanding of disease mechanism and to develop new strategies for disease treatment. To this end, many studies are exploited at the single-cell level for high throughput, highly parallel, and quantitative analysis. Technically, microfluidics are also designed to facilitate single-cell isolation and enrichment for downstream detection and manipulation in a robust, sensitive, and automated manner. Further achievements are made possible by consolidating optically label-free, electrical, and molecular sensing techniques. Moreover, these technologies are coupled with computing algorithms for high throughput and automated quantitative analysis with a short turnaround time. To reflect on how the technological developments have advanced single-cell analysis, this mini-review is aimed to offer readers an introduction to single-cell analysis with a brief historical development and the recent progresses that have enabled multiscale analysis of single-cells in the last decade. The challenges and future trends are also discussed with the view to inspire forthcoming technical developments.

Highly Sensitive in Vitro Diagnostic System of Pandemic Influenza A (H1N1) Virus Infection with Specific MicroRNA as a Biomarker

Several microRNAs (miRNAs) have been reported to be closely related to influenza A virus infection, replication, and immune response. Therefore, the development of the infectious-disease detection system using miRNAs as biomarkers is actively underway. Herein, we identified two miRNAs (miR-181c-5p and miR-1254) as biomarkers for detection of pandemic influenza A H1N1 virus infection and proposed the catalytic hairpin assembly-based in vitro diagnostic (CIVD) system for a highly sensitive diagnosis; this system is composed of two sets of cascade hairpin probes enabling to detect miR-181c-5p and miR-1254. We demonstrated that CIVD kits could not only detect subnanomolar levels of target miRNAs but also distinguish even single-base mismatches. Moreover, this CIVD kit has shown excellent detection performance in real intracellular RNA samples and confirmed results similar to those of conventional methods (microarray and quantitative real-time polymerase chain reaction).

Integrated analysis of microRNA-mRNA expression in A549 cells infected with influenza A viruses (IAVs) from different host species

Although several miRNAs have been demonstrated to be involved in the influenza virus replication cycle, the identification of miRNAs and mRNAs that are expressed in A549 cells infected with influenza A viruses (IAVs) from different host species has remained poorly studied. To investigate the molecular mechanisms associated with the differential expression of miRNAs during influenza A virus infection, we performed global miRNA and mRNA expression profiling in A549 cells infected with human-origin seasonal influenza A virus H3N2 (Human_Br07), swine-origin influenza A virus H1N1 (SW_3861) or avian-origin influenza A virus H3N2 (AVI_9990). The miRNA and mRNA expression profiles were obtained by microarray and high-throughput sequencing analyses, respectively. The integrated analysis of differentially expressed miRNAs (DEMs) and differentially expressed genes (DEGs) was performed using bioinformatics tools, and the expression of miRNAs and mRNAs was validated by real-time quantitative polymerase chain reaction (RT-qPCR). We identified 20 miRNAs (6 upregulated and 14 downregulated) and 1286 mRNAs (935 upregulated and 351 downregulated) exhibiting the same differential expression trends in three infected groups of cells compared with an uninfected control. An integrated analysis of these expression profiles identified 79 miRNA-mRNA pairs associated with the influenza A reference pathway, and 107 miRNA-mRNA interactions were correlated with the defense of the virus. Additionally, the obtained results were supported by an RT-qPCR analysis of 8 differentially expressed miRNAs (hsa-miR-210-3p, hsa-miR-296-5p, hsa-miR-371a-5p, hsa-miR-762, hsa-miR-937-5p, hsa-miR-1915-3p, hsa-miR-3665, and hsa-miR-1290) and 13 differentially expressed mRNAs (IFNL1, CXCL10, RSAD2, MX1, OAS2, IFIT2, IFI44 L, MX2, XAF1, NDRG1, FGA, EGLN3, and TFRC). Our findings indicate that dysregulated miRNA expression plays a crucial role in infection caused by IAVs originating from different species and provide a foundation for further investigations of the molecular regulatory mechanisms of miRNAs involved in influenza A virus infection.