A fluorescence-activatable reporter of flavivirus NS2B-NS3 protease activity enables live imaging of infection in single cells and viral plaques.

The genus Flavivirus in the family Flaviviridae comprises many medically important viruses, such as dengue virus (DENV), Zika virus (ZIKV), and yellow fever virus. The quest for therapeutic targets to combat flavivirus infections requires a better understanding of the kinetics of virus-host interactions during infections with native viral strains. However, this is precluded by limitations of current cell-based systems for monitoring flavivirus infection in living cells. In the present study, we report the construction of fluorescence-activatable sensors to detect the activities of flavivirus NS2B-NS3 serine proteases in living cells. The system consists of GFP-based reporters that become fluorescent upon cleavage by recombinant DENV-2/ZIKV proteases in vitro A version of this sensor containing the flavivirus internal NS3 cleavage site linker reported the highest fluorescence activation in stably transduced mammalian cells upon DENV-2/ZIKV infection. Moreover, the onset of fluorescence correlated with viral protease activity. A far-red version of this flavivirus sensor had the best signal-to-noise ratio in a fluorescent Dulbecco's plaque assay, leading to the construction of a multireporter platform combining the flavivirus sensor with reporter dyes for detection of chromatin condensation and cell death, enabling studies of viral plaque formation with single-cell resolution. Finally, the application of this platform enabled the study of cell-population kinetics of infection and cell death by DENV-2, ZIKV, and yellow fever virus. We anticipate that future studies of viral infection kinetics with this reporter system will enable basic investigations of virus-host interactions and facilitate future applications in antiviral drug research to manage flavivirus infections.

Dengue Virus Inhibition of Autophagic Flux and Dependency of Viral Replication on Proteasomal Degradation of the Autophagy Receptor p62.

UNLABELLED: Autophagic flux involves formation of autophagosomes and their degradation by lysosomes. Autophagy can either promote or restrict viral replication. In the case of Dengue virus (DENV), several studies report that autophagy supports the viral replication cycle, and describe an increase of autophagic vesicles (AVs) following infection. However, it is unknown how autophagic flux is altered to result in increased AVs. To address this question and gain insight into the role of autophagy during DENV infection, we established an unbiased, image-based flow cytometry approach to quantify autophagic flux under normal growth conditions and in response to activation by nutrient deprivation or them TOR inhibitor Torin1.We found that DENV induced an initial activation of autophagic flux, followed by inhibition of general and specific autophagy. Early after infection, basal and activated autophagic flux was enhanced. However, during established replication, basal and Torin1-activated autophagic flux was blocked, while autophagic flux activated by nutrient deprivation was reduced, indicating a block to AV formation and reduced AV degradation capacity. During late infection AV levels increased as a result of inefficient fusion of autophagosomes with lysosomes. In addition, endolysosomal trafficking was suppressed, while lysosomal activities were increased.We further determined that DENV infection progressively reduced levels of the autophagy receptor SQSTM1/p62 via proteasomal degradation. Importantly, stable overexpression of p62 significantly suppressed DENV replication, suggesting a novel role for p62 as a viral restriction factor. Overall, our findings indicate that in the course of DENV infection, autophagy shifts from a supporting to an antiviral role, which is countered by DENV. IMPORTANCE: Autophagic flux is a dynamic process starting with the formation of autophagosomes and ending with their degradation after fusion with lysosomes. Autophagy impacts the replication cycle of many viruses. However, thus far the dynamics of autophagy in case of Dengue virus (DENV) infections has not been systematically quantified. Therefore, we used high-content, imaging-based flow cytometry to quantify autophagic flux and endolysosomal trafficking in response to DENV infection. We report that DENV induced an initial activation of autophagic flux, followed by inhibition of general and specific autophagy. Further, lysosomal activity was increased, but endolysosomal trafficking was suppressed confirming the block of autophagic flux. Importantly, we provide evidence that p62, an autophagy receptor, restrict DENV replication and was specifically depleted in DENV-infected cells via increased proteasomal degradation. These results suggest that during DENV infection autophagy shifts from a proviral to an antiviral cellular process, which is counteracted by the virus.

Corrigendum: Case Series: Maraviroc and pravastatin as a therapeutic option to treat long COVID/Post-acute sequalae of COVID (PASC).

[This corrects the article DOI: 10.3389/fmed.2023.1122529.].

Long COVID diagnostic with differentiation from chronic lyme disease using machine learning and cytokine hubs.

The absence of a long COVID (LC) or post-acute sequelae of COVID-19 (PASC) diagnostic has profound implications for research and potential therapeutics given the lack of specificity with symptom-based identification of LC and the overlap of symptoms with other chronic inflammatory conditions. Here, we report a machine-learning approach to LC/PASC diagnosis on 347 individuals using cytokine hubs that are also capable of differentiating LC from chronic lyme disease (CLD). We derived decision tree, random forest, and gradient-boosting machine (GBM) classifiers and compared their diagnostic capabilities on a dataset partitioned into training (178 individuals) and evaluation (45 individuals) sets. The GBM model generated 89% sensitivity and 96% specificity for LC with no evidence of overfitting. We tested the GBM on an additional random dataset (106 LC/PASC and 18 Lyme), resulting in high sensitivity (97%) and specificity (90%) for LC. We constructed a Lyme Index confirmatory algorithm to discriminate LC and CLD.

Sphingolipid-Based Synergistic Interactions to Enhance Chemosensitivity in Lung Cancer Cells.

Tumor heterogeneity leads to drug resistance in cancer treatment with the crucial role of sphingolipids in cell fate and stress signaling. We analyzed sphingolipid metabolism and autophagic flux to study chemotherapeutic interactions on the A549 lung cancer model. Loaded cells with fluorescent sphingomyelin analog (BODIPY) and mCherry-EGFP-LC3B were used to track autophagic flux and assess cytotoxicity when cells are exposed to chemotherapy (epirubicin, cisplatin, and paclitaxel) together with sphingolipid pathway inhibitors and autophagy modulators. Our cell model approach employed fluorescent sphingolipid biosensors and a Gaussian Mixture Model of cell heterogeneity profiles to map the influence of chemotherapy on the sphingolipid pathway and infer potential synergistic interactions. Results showed significant synergy, especially when combining epirubicin with autophagy inducers (rapamycin and Torin), reducing cell viability. Cisplatin also synergized with a ceramidase inhibitor. However, paclitaxel often led to antagonistic effects. Our mapping model suggests that combining chemotherapies with autophagy inducers increases vesicle formation, possibly linked to ceramide accumulation, triggering cell death. However, the in silico model proposed ceramide accumulation in autophagosomes, and kinetic analysis provided evidence of sphingolipid colocalization in autophagosomes. Further research is needed to identify specific sphingolipids accumulating in autophagosomes. These findings offer insights into potential strategies for overcoming chemotherapy resistance by targeting the sphingolipid pathway.

Gene dosage compensation: Origins, criteria to identify compensated genes, and mechanisms including sensor loops as an emerging systems-level property in cancer.

The gene dosage compensation hypothesis presents a mechanism through which the expression of certain genes is modulated to compensate for differences in the dose of genes when additional chromosomes are present. It is one of the means through which cancer cells actively cope with the potential damaging effects of aneuploidy, a hallmark of most cancers. Dosage compensation arises through several processes, including downregulation or overexpression of specific genes and the relocation of dosage-sensitive genes. In cancer, a majority of compensated genes are generally thought to be regulated at the translational or post-translational level, and include the basic components of a compensation loop, including sensors of gene dosage and modulators of gene expression. Post-translational regulation is mostly undertaken by a general degradation or aggregation of remaining protein subunits of macromolecular complexes. An increasingly important role has also been observed for transcriptional level regulation. This article reviews the process of targeted gene dosage compensation in cancer and other biological conditions, along with the mechanisms by which cells regulate specific genes to restore cellular homeostasis. These mechanisms represent potential targets for the inhibition of dosage compensation of specific genes in aneuploid cancers. This article critically examines the process of targeted gene dosage compensation in cancer and other biological contexts, alongside the criteria for identifying genes subject to dosage compensation and the intricate mechanisms by which cells orchestrate the regulation of specific genes to reinstate cellular homeostasis. Ultimately, our aim is to gain a comprehensive understanding of the intricate nature of a systems-level property. This property hinges upon the kinetic parameters of regulatory motifs, which we have termed "gene dosage sensor loops." These loops have the potential to operate at both the transcriptional and translational levels, thus emerging as promising candidates for the inhibition of dosage compensation in specific genes. Additionally, they represent novel and highly specific therapeutic targets in the context of aneuploid cancer.

Case series: Maraviroc and pravastatin as a therapeutic option to treat long COVID/Post-acute sequelae of COVID (PASC).

Post-acute sequelae of COVID (PASC), or long COVID, is a multisystem complication of SARS-CoV-2 infection that continues to debilitate millions worldwide thus highlighting the public health importance of identifying effective therapeutics to alleviate this illness. One explanation behind PASC may be attributed to the recent discovery of persistent S1 protein subunit of SARS-CoV-2 in CD16+ monocytes up to 15 months after infection. CD16+ monocytes, which express both CCR5 and fractalkine receptors (CX3CR1), play a role in vascular homeostasis and endothelial immune surveillance. We propose targeting these receptors using the CCR5 antagonist, maraviroc, along with pravastatin, a fractalkine inhibitor, could disrupt the monocytic-endothelial-platelet axis that may be central to the etiology of PASC. Using five validated clinical scales (NYHA, MRC Dyspnea, COMPASS-31, modified Rankin, and Fatigue Severity Score) to measure 18 participants' response to treatment, we observed significant clinical improvement in 6 to 12 weeks on a combination of maraviroc 300 mg per oral twice a day and pravastatin 10 mg per oral daily. Subjective neurological, autonomic, respiratory, cardiac and fatigue symptoms scores all decreased which correlated with statistically significant decreases in vascular markers sCD40L and VEGF. These findings suggest that by interrupting the monocytic-endothelial-platelet axis, maraviroc and pravastatin may restore the immune dysregulation observed in PASC and could be potential therapeutic options. This sets the framework for a future double-blinded, placebo-controlled randomized trial to further investigate the drug efficacy of maraviroc and pravastatin in treating PASC.

Multistability in Macrophage Activation Pathways and Metabolic Implications.

Macrophages are innate immune cells with a dynamic range of reversible activation states including the classical pro-inflammatory (M1) and alternative anti-inflammatory (M2) states. Deciphering how macrophages regulate their transition from one state to the other is key for a deeper understanding of inflammatory diseases and relevant therapies. Common regulatory motifs reported for macrophage transitions, such as positive or double-negative feedback loops, exhibit a switchlike behavior, suggesting the bistability of the system. In this review, we explore the evidence for multistability (including bistability) in macrophage activation pathways at four molecular levels. First, a decision-making module in signal transduction includes mutual inhibitory interactions between M1 (STAT1, NF-KB/p50-p65) and M2 (STAT3, NF-KB/p50-p50) signaling pathways. Second, a switchlike behavior at the gene expression level includes complex network motifs of transcription factors and miRNAs. Third, these changes impact metabolic gene expression, leading to switches in energy production, NADPH and ROS production, TCA cycle functionality, biosynthesis, and nitrogen metabolism. Fourth, metabolic changes are monitored by metabolic sensors coupled to AMPK and mTOR activity to provide stability by maintaining signals promoting M1 or M2 activation. In conclusion, we identify bistability hubs as promising therapeutic targets for reverting or blocking macrophage transitions through modulation of the metabolic environment.

Generation and Implementation of Reporter BHK-21 Cells for Live Imaging of Flavivirus Infection.

The genus Flavivirus within the family Flaviviridae includes many viral species of medical importance, such as yellow fever virus (YFV), Zika virus (ZIKV), and dengue virus (DENV), among others. Presently, the identification of flavivirus-infected cells is based on either the immunolabeling of viral proteins, the application of recombinant reporter replicons and viral genomes, or the use of cell-based molecular reporters of the flaviviral protease NS2B-NS3 activity. Among the latter, our flavivirus-activatable GFP and mNeptune reporters contain a quenching peptide (QP) joined to the fluorescent protein by a linker consisting of a cleavage site for the flavivirus NS2B-NS3 proteases (AAQRRGRIG). When the viral protease cleaves the linker, the quenching peptide is removed, and the fluorescent protein adopts a conformation promoting fluorescence. Here we provide a detailed protocol for the generation, selection and implementation of stable BHK-21 cells expressing our flavivirus genetically-encoded molecular reporters, suitable to monitor the viral infection by live-cell imaging. We also describe the image analysis procedures and provide the required software pipelines. Our reporter cells allow the implementation of single-cell infection kinetics as well as plaque assays for both reference and native strains of flaviviruses by live-cell imaging. Graphic abstract: Workflow for the generation and implementation of reporter BHK-21 cells for live imaging of flavivirus infection.

A Fluorescent Real-Time Plaque Assay Enables Single-Cell Analysis of Virus-Induced Cytopathic Effect by Live-Cell Imaging.

Conventional plaque assays rely on the use of overlays to restrict viral infection allowing the formation of distinct foci that grow in time as the replication cycle continues leading to countable plaques that are visualized with standard techniques such as crystal violet, neutral red, or immunolabeling. This classical approach takes several days until large enough plaques can be visualized and counted with some variation due to subjectivity in plaque recognition. Since plaques are clonal lesions produced by virus-induced cytopathic effect, we applied DNA fluorescent dyes with differential cell permeability to visualize them by live-cell imaging. We could observe different stages of that cytopathic effect corresponding to an early wave of cells with chromatin-condensation followed by a wave of dead cells with membrane permeabilization within plaques generated by different animal viruses. This approach enables an automated plaque identification using image analysis to increase single plaque resolution compared to crystal violet counterstaining and allows its application to plaque tracking and plaque reduction assays to test compounds for both antiviral and cytotoxic activities. This fluorescent real-time plaque assay sums to those next-generation technologies by combining this robust classical method with modern fluorescence microscopy and image analysis approaches for future applications in virology.

Perturbation-Based Modeling Unveils the Autophagic Modulation of Chemosensitivity and Immunogenicity in Breast Cancer Cells.

In the absence of new therapeutic strategies, chemotherapeutic drugs are the most widely used strategy against metastatic breast cancer, in spite of eliciting multiple adverse effects and having low responses with an average 5-year patient survival rate. Among the new therapeutic targets that are currently in clinical trials, here, we addressed the association between the regulation of the metabolic process of autophagy and the exposure of damage-associated molecular patterns associated (DAMPs) to immunogenic cell death (ICD), which has not been previously studied. After validating an mCHR-GFP tandem LC3 sensor capacity to report dynamic changes of the autophagic metabolic flux in response to external stimuli and demonstrating that both basal autophagy levels and response to diverse autophagy regulators fluctuate among different cell lines, we explored the interaction between autophagy modulators and chemotherapeutic agents in regards of cytotoxicity and ICD using three different breast cancer cell lines. Since these interactions are very complex and variable throughout different cell lines, we designed a perturbation-based model in which we propose specific modes of action of chemotherapeutic agents on the autophagic flux and the corresponding strategies of modulation to enhance the response to chemotherapy. Our results point towards a promising therapeutic potential of the metabolic regulation of autophagy to overcome chemotherapy resistance by eliciting ICD.

Immune-Based Prediction of COVID-19 Severity and Chronicity Decoded Using Machine Learning.

Expression of CCR5 and its cognate ligands have been implicated in COVID-19 pathogenesis, consequently therapeutics directed against CCR5 are being investigated. Here, we explored the role of CCR5 and its ligands across the immunologic spectrum of COVID-19. We used a bioinformatics approach to predict and model the immunologic phases of COVID so that effective treatment strategies can be devised and monitored. We investigated 224 individuals including healthy controls and patients spanning the COVID-19 disease continuum. We assessed the plasma and isolated peripheral blood mononuclear cells (PBMCs) from 29 healthy controls, 26 Mild-Moderate COVID-19 individuals, 48 Severe COVID-19 individuals, and 121 individuals with post-acute sequelae of COVID-19 (PASC) symptoms. Immune subset profiling and a 14-plex cytokine panel were run on all patients from each group. B-cells were significantly elevated compared to healthy control individuals (P<0.001) as was the CD14+, CD16+, CCR5+ monocytic subset (P<0.001). CD4 and CD8 positive T-cells expressing PD-1 as well as T-regulatory cells were significantly lower than healthy controls (P<0.001 and P=0.01 respectively). CCL5/RANTES, IL-2, IL-4, CCL3, IL-6, IL-10, IFN-γ, and VEGF were all significantly elevated compared to healthy controls (all P<0.001). Conversely GM-CSF and CCL4 were in significantly lower levels than healthy controls (P=0.01). Data were further analyzed and the classes were balanced using SMOTE. With a balanced working dataset, we constructed 3 random forest classifiers: a multi-class predictor, a Severe disease group binary classifier and a PASC binary classifier. Models were also analyzed for feature importance to identify relevant cytokines to generate a disease score. Multi-class models generated a score specific for the PASC patients and defined as S1 = (IFN-γ + IL-2)/CCL4-MIP-1ß. Second, a score for the Severe COVID-19 patients was defined as S2 = (IL-6+sCD40L/1000 + VEGF/10 + 10*IL-10)/(IL-2 + IL-8). Severe COVID-19 patients are characterized by excessive inflammation and dysregulated T cell activation, recruitment, and counteracting activities. While PASC patients are characterized by a profile able to induce the activation of effector T cells with pro-inflammatory properties and the capacity of generating an effective immune response to eliminate the virus but without the proper recruitment signals to attract activated T cells.

Persistence of SARS CoV-2 S1 Protein in CD16+ Monocytes in Post-Acute Sequelae of COVID-19 (PASC) up to 15 Months Post-Infection.

The recent COVID-19 pandemic is a treatment challenge in the acute infection stage but the recognition of chronic COVID-19 symptoms termed post-acute sequelae SARS-CoV-2 infection (PASC) may affect up to 30% of all infected individuals. The underlying mechanism and source of this distinct immunologic condition three months or more after initial infection remains elusive. Here, we investigated the presence of SARS-CoV-2 S1 protein in 46 individuals. We analyzed T-cell, B-cell, and monocytic subsets in both severe COVID-19 patients and in patients with post-acute sequelae of COVID-19 (PASC). The levels of both intermediate (CD14+, CD16+) and non-classical monocyte (CD14Lo, CD16+) were significantly elevated in PASC patients up to 15 months post-acute infection compared to healthy controls (P=0.002 and P=0.01, respectively). A statistically significant number of non-classical monocytes contained SARS-CoV-2 S1 protein in both severe (P=0.004) and PASC patients (P=0.02) out to 15 months post-infection. Non-classical monocytes were sorted from PASC patients using flow cytometric sorting and the SARS-CoV-2 S1 protein was confirmed by mass spectrometry. Cells from 4 out of 11 severe COVID-19 patients and 1 out of 26 PASC patients contained ddPCR+ peripheral blood mononuclear cells, however, only fragmented SARS-CoV-2 RNA was found in PASC patients. No full length sequences were identified, and no sequences that could account for the observed S1 protein were identified in any patient. That non-classical monocytes may be a source of inflammation in PASC warrants further study.

MYC dosage compensation is mediated by miRNA-transcription factor interactions in aneuploid cancer.

We hypothesize that dosage compensation of critical genes arises from systems-level properties for cancer cells to withstand the negative effects of aneuploidy. We identified several candidate genes in cancer multiomics data and developed a biocomputational platform to construct a mathematical model of their interaction network with micro-RNAs and transcription factors, where the property of dosage compensation emerged for MYC and was dependent on the kinetic parameters of its feedback interactions with three micro-RNAs. These circuits were experimentally validated using a genetic tug-of-war technique to overexpress an exogenous MYC, leading to overexpression of the three microRNAs involved and downregulation of endogenous MYC. In addition, MYC overexpression or inhibition of its compensating miRNAs led to dosage-dependent cytotoxicity in MYC-amplified colon cancer cells. Finally, we identified negative correlation of MYC dosage compensation with patient survival in TCGA breast cancer patients, highlighting the potential of this mechanism to prevent aneuploid cancer progression.

Transcriptomic determinants of the response of ST-111 Pseudomonas aeruginosa AG1 to ciprofloxacin identified by a top-down systems biology approach.

Pseudomonas aeruginosa is an opportunistic pathogen that thrives in diverse environments and causes a variety of human infections. Pseudomonas aeruginosa AG1 (PaeAG1) is a high-risk sequence type 111 (ST-111) strain isolated from a Costa Rican hospital in 2010. PaeAG1 has both blaVIM-2 and blaIMP-18 genes encoding for metallo-ß-lactamases, and it is resistant to ß-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. Ciprofloxacin (CIP) is an antibiotic commonly used to treat P. aeruginosa infections, and it is known to produce DNA damage, triggering a complex molecular response. In order to evaluate the effects of a sub-inhibitory CIP concentration on PaeAG1, growth curves using increasing CIP concentrations were compared. We then measured gene expression using RNA-Seq at three time points (0, 2.5 and 5 h) after CIP exposure to identify the transcriptomic determinants of the response (i.e. hub genes, gene clusters and enriched pathways). Changes in expression were determined using differential expression analysis and network analysis using a top-down systems biology approach. A hybrid model using database-based and co-expression analysis approaches was implemented to predict gene-gene interactions. We observed a reduction of the growth curve rate as the sub-inhibitory CIP concentrations were increased. In the transcriptomic analysis, we detected that over time CIP treatment resulted in the differential expression of 518 genes, showing a complex impact at the molecular level. The transcriptomic determinants were 14 hub genes, multiple gene clusters at different levels (associated to hub genes or as co-expression modules) and 15 enriched pathways. Down-regulation of genes implicated in several metabolism pathways, virulence elements and ribosomal activity was observed. In contrast, amino acid catabolism, RpoS factor, proteases, and phenazines genes were up-regulated. Remarkably, > 80 resident-phage genes were up-regulated after CIP treatment, which was validated at phenomic level using a phage plaque assay. Thus, reduction of the growth curve rate and increasing phage induction was evidenced as the CIP concentrations were increased. In summary, transcriptomic and network analyses, as well as the growth curves and phage plaque assays provide evidence that PaeAG1 presents a complex, concentration-dependent response to sub-inhibitory CIP exposure, showing pleiotropic effects at the systems level. Manipulation of these determinants, such as phage genes, could be used to gain more insights about the regulation of responses in PaeAG1 as well as the identification of possible therapeutic targets. To our knowledge, this is the first report of the transcriptomic analysis of CIP response in a ST-111 high-risk P. aeruginosa strain, in particular using a top-down systems biology approach.

Dengue Virus Infection of Primary Human Smooth Muscle Cells.

Dengue virus (DENV) infection of humans is presently the most important arthropod-borne viral global threat, for which no suitable or reliable animal model exists. Reports addressing the effect of DENV on vascular components other than endothelial cells are lacking. Dengue virus infection of vascular smooth muscle cells, which play a physiological compensatory response to hypotension in arteries and arterioles, has not been characterized, thus precluding our understanding of the role of these vascular components in dengue pathogenesis. Therefore, we studied the permissiveness of primary human umbilical artery smooth muscle cells (HUASMC) to DENV 1-4 infection and compared with the infection in the previously reported primary human umbilical vein endothelial cells (HUVEC) and the classically used, non-transformed, and highly permissive Lilly Laboratories Cell-Monkey Kidney 2 cells. Our results show that HUASMC are susceptible and productive to infection with the four DENV serotypes, although to a lesser extent when compared with the other cell lines. This is the first report of DENV permissiveness in human smooth muscle cells, which might represent an unexplored pathophysiological contributor to the vascular collapse observed in severe human dengue infection.