Imaging and quantification of human and viral circular RNAs.

We present a robust approach for cellular detection, imaging, localization, and quantification of human and viral encoded circular RNAs (circRNA) using amplified fluorescence in situ hybridization (ampFISH). In this procedure, a pair of hairpin probes bind next to each other at contiguous stretches of sequence and then undergo a conformational reorganization which initiates a target-dependent hybridization chain reaction (HCR) resulting in deposition of an amplified fluorescent signal at the site. By harnessing the capabilities of both ampFISH and single-molecule FISH (smFISH), we selectively identified and imaged circular RNAs and their linear counterparts derived from the human genome, SARS-CoV-2 (an RNA virus), and human cytomegalovirus (HCMV, a DNA virus). Computational image processing facilitated accurate quantification of circular RNA molecules in individual cells. The specificity of ampFISH for circular RNA detection was confirmed through an in situ RNase R treatment that selectively degrades linear RNAs without impacting circular RNAs. The effectiveness of circular RNA detection was further validated by using ampFISH probes with mismatches and probe pairs that do not bind to the continuous sequence in their target RNAs but instead bind at segregated sites. An additional specificity test involved probes against the negative strands of the circular RNA sequence, absent in the cell. Importantly, our technique allows simultaneous detection of circular RNAs and their linear counterparts within the same cell with single molecule sensitivity, enabling explorations of circular RNA biogenesis, subcellular localization, and functions.

A fourfold-objective-based cloud privacy preservation model with proposed association rule hiding and deep learning assisted optimal key generation.

Numerous studies have been conducted in an attempt to preserve cloud privacy, yet the majority of cutting-edge solutions fall short when it comes to handling sensitive data. This research proposes a "privacy preservation model in the cloud environment". The four stages of recommended security preservation methodology are "identification of sensitive data, generation of an optimal tuned key, suggested data sanitization, and data restoration". Initially, owner's data enters the Sensitive data identification process. The sensitive information in the input (owner's data) is identified via Augmented Dynamic Itemset Counting (ADIC) based Associative Rule Mining Model. Subsequently, the identified sensitive data are sanitized via the newly created tuned key. The generated tuned key is formulated with new fourfold objective-hybrid optimization approach-based deep learning approach. The optimally tuned key is generated with LSTM on the basis of fourfold objectives and the new hybrid MUAOA. The created keys, as well as generated sensitive rules, are fed into the deep learning model. The MUAOA technique is a conceptual blend of standard AOA and CMBO, respectively. As a result, unauthorized people will be unable to access information. Finally, comparative evaluation is undergone and proposed LSTM+MUAOA has achieved higher values on privacy about 5.21 compared to other existing models.

Imaging the Architecture of Granulomas Induced by Mycobacterium tuberculosis Infection with Single-molecule Fluorescence In Situ Hybridization.

Granulomas are an important hallmark of Mycobacterium tuberculosis infection. They are organized and dynamic structures created when immune cells assemble around the sites of infection in the lungs that locally restrict M. tuberculosis growth and the host's inflammatory responses. The cellular architecture of granulomas is traditionally studied by immunofluorescence labeling of surface markers on the host cells. However, very few Abs are available for model animals used in tuberculosis research, such as nonhuman primates and rabbits, and secreted immunological markers such as cytokines cannot be imaged in situ using Abs. Furthermore, traditional phenotypic surface markers do not provide sufficient resolution for the detection of the many subtypes and differentiation states of immune cells. Using single-molecule fluorescence in situ hybridization (smFISH) and its derivatives, amplified smFISH and iterative smFISH, we developed a platform for imaging mRNAs encoding immune markers in rabbit and macaque tuberculosis granulomas. Multiplexed imaging for several mRNA and protein markers was followed by quantitative measurement of the expression of these markers in single cells. An analysis of the combinatorial expressions of these markers allowed us to classify the cells into several subtypes, and to chart their densities within granulomas. For one mRNA target, hypoxia-inducible factor-1α, we imaged its mRNA and protein in the same cells, demonstrating the specificity of the probes. This method paves the way for defining granular differentiation states and cell subtypes from transcriptomic data, identifying key mRNA markers for these cell subtypes, and then locating the cells in the spatial context of granulomas.

S309-CAR-NK cells bind the Omicron variants in vitro and reduce SARS-CoV-2 viral loads in humanized ACE2-NSG mice.

Recent progress on chimeric antigen receptor (CAR)-NK cells has shown promising results in treating CD19-positive lymphoid tumors with minimal toxicities [including graft versus host disease (GvHD) and cytokine release syndrome (CRS) in clinical trials. Nevertheless, the use of CAR-NK cells in combating viral infections has not yet been fully explored. Previous studies have shown that CAR-NK cells expressing S309 single-chain fragment variable (scFv), hereinafter S309-CAR-NK cells, can bind to SARS-CoV-2 wildtype pseudotyped virus (PV) and effectively kill cells expressing wild-type spike protein in vitro. In this study, we further demonstrate that the S309-CAR-NK cells can bind to different SARS-CoV-2 variants, including the B.1.617.2 (Delta), B.1.621 (Mu), and B.1.1.529 (Omicron) variants in vitro. We also show that S309-CAR-NK cells reduce virus loads in the NOD/SCID gamma (NSG) mice expressing the human angiotensin-converting enzyme 2 (hACE2) receptor challenged with SARS-CoV-2 wild-type (strain USA/WA1/2020). Our study demonstrates the potential use of S309-CAR-NK cells for inhibiting infection by SARS-CoV-2 and for the potential treatment of COVID-19 patients unresponsive to otherwise currently available therapeutics. IMPORTANCE: Chimeric antigen receptor (CAR)-NK cells can be "off-the-shelf" products that treat various diseases, including cancer, infections, and autoimmune diseases. In this study, we engineered natural killer (NK) cells to express S309 single-chain fragment variable (scFv), to target the Spike protein of SARS-CoV-2, hereinafter S309-CAR-NK cells. Our study shows that S309-CAR-NK cells are effective against different SARS-CoV-2 variants, including the B.1.617.2 (Delta), B.1.621 (Mu), and B.1.1.529 (Omicron) variants. The S309-CAR-NK cells can (i) directly bind to SARS-CoV-2 pseudotyped virus (PV), (ii) competitively bind to SARS-CoV-2 PV with 293T cells expressing the human angiotensin-converting enzyme 2 (hACE2) receptor (293T-hACE2 cells), (iii) specifically target and lyse A549 cells expressing the spike protein, and (iv) significantly reduce the viral loads of SARS-CoV-2 wild-type (strain USA/WA1/2020) in the lungs of NOD/SCID gamma (NSG) mice expressing hACE2 (hACE2-NSG mice). Altogether, the current study demonstrates the potential use of S309-CAR-NK immunotherapy as an alternative treatment for COVID-19 patients.

Endothelial nitric oxide synthase (eNOS) gene polymorphism (Glu298asp) and nitric oxide (NO) levels in patients with ST-segment elevation myocardial infarction (STEMI).

BACKGROUND: Genetic polymorphism in endothelial Nitric Oxide Synthase (eNOS) are associated with occurrence of multiple cardiovascular diseases (CVDs). METHODS: This study included 300 young ST-segment elevation myocardial infarction (STEMI) patients and 300 healthy controls. STEMI patients were divided into two groups: premature coronary artery disease [CAD] (STEMI<40 years of age) and older STEMI (>40 years of age). Genetic polymorphisms in the eNOS gene (894G/T) was evaluated in both subjects and controls. Plasma levels of nitric oxide (NO) were estimated for both patients as well as controls. RESULTS: Mean age of the study population was 49.7 ± 9.2 years with premature CAD being present in 58 (19.3 %) patients. No significant difference at genotypic (P = 0.589, odds ratio (OR) = 0.9, 95 % CI = 0.6-1.6) and allelic level (P = 0.173, OR = 1.2, 95 % CI = 0.9-1.4) was observed between STEMI patients and healthy controls. Genotype 894 TT had significantly higher frequency in STEMI patients >40 years (P = 0.047, OR: 2.5; 95 % CI = 1.0-6.0). No significant difference at genotypic (P = 0.279) and allelic level (P = 0.493) was observed between premature CAD (STEMI age <40 years) and healthy controls. NO levels (131 ± 59.6 µM vs 118.11 ± 49.96 µM; P = 0.001) was significantly higher in healthy controls as compared to STEMI patients >40 years of age (P= 0.001). CONCLUSION: There was significant association of eNOS gene polymorphism Glu298Asp with STEMI patients > 40 years. However, this association was not observed in premature CAD patients. Lower levels of NO in STEMI patients >40 years suggests its potential role as a marker of CVD.

Brain tropism acquisition: The spatial dynamics and evolution of a measles virus collective infectious unit that drove lethal subacute sclerosing panencephalitis.

It is increasingly appreciated that pathogens can spread as infectious units constituted by multiple, genetically diverse genomes, also called collective infectious units or genome collectives. However, genetic characterization of the spatial dynamics of collective infectious units in animal hosts is demanding, and it is rarely feasible in humans. Measles virus (MeV), whose spread in lymphatic tissues and airway epithelia relies on collective infectious units, can, in rare cases, cause subacute sclerosing panencephalitis (SSPE), a lethal human brain disease. In different SSPE cases, MeV acquisition of brain tropism has been attributed to mutations affecting either the fusion or the matrix protein, or both, but the overarching mechanism driving brain adaptation is not understood. Here we analyzed MeV RNA from several spatially distinct brain regions of an individual who succumbed to SSPE. Surprisingly, we identified two major MeV genome subpopulations present at variable frequencies in all 15 brain specimens examined. Both genome types accumulated mutations like those shown to favor receptor-independent cell-cell spread in other SSPE cases. Most infected cells carried both genome types, suggesting the possibility of genetic complementation. We cannot definitively chart the history of the spread of this virus in the brain, but several observations suggest that mutant genomes generated in the frontal cortex moved outwards as a collective and diversified. During diversification, mutations affecting the cytoplasmic tails of both viral envelope proteins emerged and fluctuated in frequency across genetic backgrounds, suggesting convergent and potentially frequency-dependent evolution for modulation of fusogenicity. We propose that a collective infectious unit drove MeV pathogenesis in this brain. Re-examination of published data suggests that similar processes may have occurred in other SSPE cases. Our studies provide a primer for analyses of the evolution of collective infectious units of other pathogens that cause lethal disease in humans.