Identification of dihydromyricetin as a natural DNA methylation inhibitor with rejuvenating activity in human skin

Changes in DNA methylation patterning have been reported to be a key hallmark of aged human skin. The altered DNA methylation patterns are correlated with deregulated gene expression and impaired tissue functionality, leading to the well-known skin aging phenotype. Searching for small molecules, which correct the aged methylation pattern therefore represents a novel and attractive strategy for the identification of anti-aging compounds. DNMT1 maintains epigenetic information by copying methylation patterns from the parental (methylated) strand to the newly synthesized strand after DNA replication. We hypothesized that a modest inhibition of this process promotes the restoration of the ground-state epigenetic pattern, thereby inducing rejuvenating effects. In this study, we screened a library of 1800 natural substances and 640 FDA-approved drugs and identified the well-known antioxidant and anti-inflammatory molecule dihydromyricetin (DHM) as an inhibitor of the DNA methyltransferase DNMT1. DHM is the active ingredient of several plants with medicinal use and showed robust inhibition of DNMT1 in biochemical assays. We also analyzed the effect of DHM in cultivated keratinocytes by array-based methylation profiling and observed a moderate, but significant global hypomethylation effect upon treatment. To further characterize DHM-induced methylation changes, we used published DNA methylation clocks and newly established age predictors to demonstrate that the DHM-induced methylation change is associated with a reduction in the biological age of the cells. Further studies also revealed re-activation of age-dependently hypermethylated and silenced genes in vivo and a reduction in age-dependent epidermal thinning in a 3-dimensional skin model. Our findings thus establish DHM as an epigenetic inhibitor with rejuvenating effects for aged human skin.

Landscape of protein-protein interactions during hepatitis C virus assembly and release

Assembly of infectious hepatitis C virus (HCV) particles requires multiple cellular proteins including for instance apolipoprotein E (ApoE). To describe these protein-protein interactions, we performed an affinity purification mass spectrometry screen of HCV-infected cells. We used functional viral constructs with epitope-tagged envelope protein 2 (E2), protein (p) 7, or nonstructural protein 4B (NS4B) as well as cells expressing a tagged variant of ApoE. We also evaluated assembly stage-dependent remodeling of protein complexes by using viral mutants carrying point mutations abrogating particle production at distinct steps of the HCV particle production cascade. Five ApoE binding proteins, 12 p7 binders, 7 primary E2 interactors, and 24 proteins interacting with NS4B were detected. Cell-derived PREB, STT3B, and SPCS2 as well as viral NS2 interacted with both p7 and E2. Only GTF3C3 interacted with E2 and NS4B, highlighting that HCV assembly and replication complexes exhibit largely distinct interactomes. An HCV core protein mutation, preventing core protein decoration of lipid droplets, profoundly altered the E2 interactome. In cells replicating this mutant, E2 interactions with HSPA5, STT3A/B, RAD23A/B, and ZNF860 were significantly enhanced, suggesting that E2 protein interactions partly depend on core protein functions. Bioinformatic and functional studies including STRING network analyses, RNA interference, and ectopic expression support a role of Rad23A and Rad23B in facilitating HCV infectious virus production. Both Rad23A and Rad23B are involved in the endoplasmic reticulum (ER)-associated protein degradation (ERAD). Collectively, our results provide a map of host proteins interacting with HCV assembly proteins, and they give evidence for the involvement of ER protein folding machineries and the ERAD pathway in the late stages of the HCV replication cycle.IMPORTANCEHepatitis C virus (HCV) establishes chronic infections in the majority of exposed individuals. This capacity likely depends on viral immune evasion strategies. One feature likely contributing to persistence is the formation of so-called lipo-viro particles. These peculiar virions consist of viral structural proteins and cellular lipids and lipoproteins, the latter of which aid in viral attachment and cell entry and likely antibody escape. To learn about how lipo-viro particles are coined, here, we provide a comprehensive overview of protein-protein interactions in virus-producing cells. We identify numerous novel and specific HCV E2, p7, and cellular apolipoprotein E-interacting proteins. Pathway analyses of these interactors show that proteins participating in processes such as endoplasmic reticulum (ER) protein folding, ER-associated protein degradation, and glycosylation are heavily engaged in virus production. Moreover, we find that the proteome of HCV replication sites is distinct from the assembly proteome, suggesting that transport process likely shuttles viral RNA to assembly sites.

Development of an epigenetic clock to predict visual age progression of human skin

Aging is a complex process characterized by the gradual decline of physiological functions, leading to increased vulnerability to age-related diseases and reduced quality of life. Alterations in DNA methylation (DNAm) patterns have emerged as a fundamental characteristic of aged human skin, closely linked to the development of the well-known skin aging phenotype. These changes have been correlated with dysregulated gene expression and impaired tissue functionality. In particular, the skin, with its visible manifestations of aging, provides a unique model to study the aging process. Despite the importance of epigenetic age clocks in estimating biological age based on the correlation between methylation patterns and chronological age, a second-generation epigenetic age clock, which correlates DNAm patterns with a particular phenotype, specifically tailored to skin tissue is still lacking. In light of this gap, we aimed to develop a novel second-generation epigenetic age clock explicitly designed for skin tissue to facilitate a deeper understanding of the factors contributing to individual variations in age progression. To achieve this, we used methylation patterns from more than 370 female volunteers and developed the first skin-specific second-generation epigenetic age clock that accurately predicts the skin aging phenotype represented by wrinkle grade, visual facial age, and visual age progression, respectively. We then validated the performance of our clocks on independent datasets and demonstrated their broad applicability. In addition, we integrated gene expression and methylation data from independent studies to identify potential pathways contributing to skin age progression. Our results demonstrate that our epigenetic age clock, VisAgeX, specifically predicting visual age progression, not only captures known biological pathways associated with skin aging, but also adds novel pathways associated with skin aging.

Neighbourhood watch: genomic epidemiology of SARS-CoV-2 variants circulating in a German federal state, Mecklenburg-Western Pomerania, in 2020-2022

ABSTRACTGlobal and even national genome surveillance approaches do not provide the resolution necessary for rapid and accurate direct response by local public health authorities. Hence, a regional network of microbiological laboratories in collaboration with the health departments of all districts of the German federal state of Mecklenburg-Western Pomerania (M-V) was formed to investigate the regional molecular epidemiology of circulating SARS-CoV-2 lineages between 11/2020 and 03/2022. More than 4750 samples from all M-V counties were sequenced using Illumina and Nanopore technologies. Overall, 3493 (73.5%) sequences fulfilled quality criteria for time-resolved and/or spatially-resolved maximum likelihood phylogenic analyses and k-mean/ median clustering (KMC). We identified 116 different Pangolin virus lineages that can be assigned to 16 Nextstrain clades. The ten most frequently detected virus lineages belonged to B.1.1.7, AY.122, AY.43, BA.1, B.1.617.2, BA.1.1, AY.9.2, AY.4, P.1 and AY.126. Time-resolved phylogenetic analyses showed the occurrence of virus clades as determined worldwide, but with a substantial delay of one to two months. Further spatio-temporal phylogenetic analyses revealed a regional outbreak of a Gamma variant limited to western M-V counties. Finally, KMC elucidated a successive introduction of the various virus lineages into M-V, possibly triggered by vacation periods with increased (inter-) national travel activities. The COVID-19 pandemic in M-V was shaped by a combination of several SARS-CoV-2 introductions, lockdown measures, restrictive quarantine of patients and the lineage specific replication rate. Complementing global and national surveillance, regional surveillance adds value by providing a higher level of surveillance resolution tailored to local health authorities.

Correction: Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks

[This corrects the article DOI: 10.1371/journal.pone.0271610.].

High-resolution kinetic characterization of the RIG-I-signaling pathway and the antiviral response

RIG-I recognizes viral dsRNA and activates a cell-autonomous antiviral response. Upon stimulation, it triggers a signaling cascade leading to the production of type I and III IFNs. IFNs are secreted and signal to elicit the expression of IFN-stimulated genes, establishing an antiviral state of the cell. The topology of this pathway has been studied intensively, however, its exact dynamics are less understood. Here, we employed electroporation to synchronously activate RIG-I, enabling us to characterize cell-intrinsic innate immune signaling at a high temporal resolution. Employing IFNAR1/IFNLR-deficient cells, we could differentiate primary RIG-I signaling from secondary signaling downstream of the IFN receptors. Based on these data, we developed a comprehensive mathematical model capable of simulating signaling downstream of dsRNA recognition by RIG-I and the feedback and signal amplification by IFN. We further investigated the impact of viral antagonists on signaling dynamics. Our work provides a comprehensive insight into the signaling events that occur early upon virus infection and opens new avenues to study and disentangle the complexity of the host-virus interface.

Automated antigen assays display a high heterogeneity for the detection of SARS-CoV-2 variants of concern, including several Omicron sublineages

Diagnostic tests for direct pathogen detection have been instrumental to contain the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Automated, quantitative, laboratory-based nucleocapsid antigen (Ag) tests for SARS-CoV-2 have been launched alongside nucleic acid-based test systems and point-of-care (POC) lateral-flow Ag tests. Here, we evaluated four commercial Ag tests on automated platforms for the detection of different sublineages of the SARS-CoV-2 Omicron variant of concern (VoC) (B.1.1.529) in comparison with "non-Omicron" VoCs. A total of 203 Omicron PCR-positive respiratory swabs (53 BA.1, 48 BA.2, 23 BQ.1, 39 XBB.1.5 and 40 other subvariants) from the period February to March 2022 and from March 2023 were examined. In addition, tissue culture-expanded clinical isolates of Delta (B.1.617.2), Omicron-BA.1, -BF.7, -BN.1 and -BQ.1 were studied. These results were compared to previously reported data from 107 clinical "non-Omicron" samples from the end of the second pandemic wave (February to March 2021) as well as cell culture-derived samples of wildtype (wt) EU-1 (B.1.177), Alpha VoC (B.1.1.7) and Beta VoC (B.1.351)). All four commercial Ag tests were able to detect at least 90.9% of Omicron-containing samples with high viral loads (Ct < 25). The rates of true-positive test results for BA.1/BA.2-positive samples with intermediate viral loads (Ct 25-30) ranged between 6.7% and 100.0%, while they dropped to 0 to 15.4% for samples with low Ct values (> 30). This heterogeneity was reflected also by the tests' 50%-limit of detection (LoD50) values ranging from 44,444 to 1,866,900 Geq/ml. Respiratory samples containing Omicron-BQ.1/XBB.1.5 or other Omicron subvariants that emerged in 2023 were detected with enormous heterogeneity (0 to 100%) for the intermediate and low viral load ranges with LoD50 values between 23,019 and 1,152,048 Geq/ml. In contrast, detection of "non-Omicron" samples was more sensitive, scoring positive in 35 to 100% for the intermediate and 1.3 to 32.9% of cases for the low viral loads, respectively, corresponding to LoD50 values ranging from 6181 to 749,792 Geq/ml. All four assays detected cell culture-expanded VoCs Alpha, Beta, Delta and Omicron subvariants carrying up to six amino acid mutations in the nucleocapsid protein with sensitivities comparable to the non-VoC EU-1. Overall, automated quantitative SARS-CoV-2 Ag assays are not more sensitive than standard rapid antigen tests used in POC settings and show a high heterogeneity in performance for VoC recognition. The best of these automated Ag tests may have the potential to complement nucleic acid-based assays for SARS-CoV-2 diagnostics in settings not primarily focused on the protection of vulnerable groups. In light of the constant emergence of new Omicron subvariants and recombinants, most recently the XBB lineage, these tests' performance must be regularly re-evaluated, especially when new VoCs carry mutations in the nucleocapsid protein or immunological and clinical parameters change.

Ten rapid antigen tests for SARS-CoV-2 widely differ in their ability to detect Omicron-BA.4 and -BA.5

Since late 2021, the variant landscape of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been dominated by the variant of concern (VoC) Omicron and its sublineages. We and others have shown that the detection of Omicron-BA.1 and -BA.2-positive respiratory specimens by rapid antigen tests (RATs) is impaired compared to Delta VoC-containing samples. Here, in a single-center retrospective laboratory study, we evaluated the performance of ten most commonly used RATs for the detection of Omicron-BA.4 and -BA.5 infections. We used 171 respiratory swab specimens from SARS-CoV-2 RNA-positive patients, of which 71 were classified as BA.4 and 100 as BA.5. All swabs were collected between July and September 2022. 50 SARS-CoV-2 PCR-negative samples from healthy individuals, collected in October 2022, showed high specificity in 9 out of 10 RATs. When assessing analytical sensitivity using clinical specimens, the 50% limit of detection (LoD50) ranged from 7.6 × 104 to 3.3 × 106 RNA copies subjected to the RATs for BA.4 compared to 6.8 × 104 to 3.0 × 106 for BA.5. Overall, intra-assay differences for the detection of these two Omicron subvariants were not significant for both respiratory swabs and tissue culture-expanded virus isolates. In contrast, marked heterogeneity was observed among the ten RATs: to be positive in these point-of-care tests, up to 443-fold (BA.4) and up to 56-fold (BA.5) higher viral loads were required for the worst performing RAT compared to the best performing RAT. True-positive rates for Omicron-BA.4- or -BA.5-containing specimens in the highest viral load category (Ct values < 25) ranged from 94.3 to 34.3%, dropping to 25.6 to 0% for samples with intermediate Ct values (25-30). We conclude that the high heterogeneity in the performance of commonly used RATs remains a challenge for the general public to obtain reliable results in the evolving Omicron subvariant-driven pandemic.

Long-term outcome in vaccine-induced immune thrombocytopenia and thrombosis

BACKGROUND

Rapid diagnosis and treatment has improved outcome of patients with vaccine-induced immune thrombocytopenia and thrombosis (VITT). However, after the acute episode, many questions on long-term management of VITT remained unanswered.

OBJECTIVES

To analyze, in patients with VITT, the long-term course of anti-platelet factor 4 (PF4) antibodies; clinical outcomes, including risk of recurrent thrombosis and/or thrombocytopenia; and the effects of new vaccinations.

METHODS

71 patients with serologically confirmed VITT in Germany were enrolled into a prospective longitudinal study and followed for a mean of 79 weeks from March 2021 to January 2023. The course of anti-PF4 antibodies was analyzed by consecutive anti-PF4/heparin immunoglobulin G enzyme-linked immunosorbent assay and PF4-enhanced platelet activation assay.

RESULTS

Platelet-activating anti-PF4 antibodies became undetectable in 62 of 71 patients (87.3%; 95% CI, 77.6%-93.2%). In 6 patients (8.5%), platelet-activating anti-PF4 antibodies persisted for >18 months. Five of 71 patients (7.0%) showed recurrent episodes of thrombocytopenia and/or thrombosis; in 4 of them (80.0%), alternative explanations beside VITT were present. After further COVID-19 vaccination with a messenger RNA vaccine, no reactivation of platelet-activating anti-PF4 antibodies or new thrombosis was observed. No adverse events occurred in our patients subsequently vaccinated against influenza, tick-borne encephalitis, varicella, tetanus, diphtheria, pertussis, and polio. No new thrombosis occurred in the 24 patients (33.8%) who developed symptomatic SARS-CoV-2 infection following recovery from acute VITT.

CONCLUSION

Once the acute episode of VITT has passed, patients appear to be at low risk for recurrent thrombosis and/or thrombocytopenia.

Evaluating heart rate variability with 10 second multichannel electrocardiograms in a large population-based sample

Introduction

Heart rate variability (HRV), defined as the variability of consecutive heart beats, is an important biomarker for dysregulations of the autonomic nervous system (ANS) and is associated with the development, course, and outcome of a variety of mental and physical health problems. While guidelines recommend using 5 min electrocardiograms (ECG), recent studies showed that 10 s might be sufficient for deriving vagal-mediated HRV. However, the validity and applicability of this approach for risk prediction in epidemiological studies is currently unclear to be used.

Methods

This study evaluates vagal-mediated HRV with ultra-short HRV (usHRV) based on 10 s multichannel ECG recordings of N = 4,245 and N = 2,392 participants of the Study of Health in Pomerania (SHIP) from two waves of the SHIP-TREND cohort, additionally divided into a healthy and health-impaired subgroup. Association of usHRV with HRV derived from long-term ECG recordings (polysomnography: 5 min before falling asleep [N = 1,041]; orthostatic testing: 5 min of rest before probing an orthostatic reaction [N = 1,676]) and their validity with respect to demographic variables and depressive symptoms were investigated.

Results

High correlations (r = .52-.75) were revealed between usHRV and HRV. While controlling for covariates, usHRV was the strongest predictor for HRV. Furthermore, the associations of usHRV and HRV with age, sex, obesity, and depressive symptoms were similar.

Conclusion

This study provides evidence that usHRV derived from 10 s ECG might function as a proxy of vagal-mediated HRV with similar characteristics. This allows the investigation of ANS dysregulation with ECGs that are routinely performed in epidemiological studies to identify protective and risk factors for various mental and physical health problems.

A Mixture Method for Robust Detection HCV Early Diagnosis Biomarker with ML Approach and Molecular Docking

Given the substantial correlation between early diagnosis and prolonged patient survival in HCV patients, it is vital to identify a reliable and accessible biomarker. The purpose of this research was to identify accurate miRNA biomarkers to aid in the early diagnosis of HCV and to identify key target genes for anti-hepatic fibrosis therapeutics. The expression of 188 miRNAs in 42 HCV liver patients with different functional states and 23 normal livers were determined using RT-qPCR. After screening out differentially expressed miRNA (DEmiRNAs), the target genes were predicted. To validate target genes, an HCV microarray dataset was subjected to five machine learning algorithms (Random Forest, Adaboost, Bagging, Boosting, XGBoost) and then, based on the best model, importance features were selected. After identification of hub target genes, to evaluate the potency of compounds that might hit key hub target genes, molecular docking was performed. According to our data, eight DEmiRNAs are associated with early stage and eight DEmiRNAs are linked to a deterioration in liver function and an increase in HCV severity. In the validation phase of target genes, model evaluation revealed that XGBoost (AUC = 0.978) outperformed the other machine learning algorithms. The results of the maximal clique centrality algorithm determined that CDK1 is a hub target gene, which can be hinted at by hsa-miR-335, hsa-miR-140, hsa-miR-152, and hsa-miR-195. Because viral proteins boost CDK1 activation for cell mitosis, pharmacological inhibition may have anti-HCV therapeutic promise. The strong affinity binding of paeoniflorin (-6.32 kcal/mol) and diosmin (-6.01 kcal/mol) with CDK1 was demonstrated by molecular docking, which may result in attractive anti-HCV compounds. The findings of this study may provide significant evidence, in the context of the miRNA biomarkers, for early-stage HCV diagnosis. In addition, recognized hub target genes and small molecules with high binding affinity may constitute a novel set of therapeutic targets for HCV.

Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies

Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called "replication factories"), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and showed that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency, which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, such as polyprotein cleavage and viral RNA synthesis, may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the in vitro viral replication early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth.

Variable detection of Omicron-BA.1 and -BA.2 by SARS-CoV-2 rapid antigen tests

During 2022, the COVID-19 pandemic has been dominated by the variant of concern (VoC) Omicron (B.1.1.529) and its rapidly emerging subvariants, including Omicron-BA.1 and -BA.2. Rapid antigen tests (RATs) are part of national testing strategies to identify SARS-CoV-2 infections on site in a community setting or to support layman's diagnostics at home. We and others have recently demonstrated an impaired RAT detection of infections caused by Omicron-BA.1 compared to Delta. Here, we evaluated the performance of five SARS-CoV-2 RATs in a single-centre laboratory study examining a total of 140 SARS-CoV-2 PCR-positive respiratory swab samples, 70 Omicron-BA.1 and 70 Omicron-BA.2, as well as 52 SARS-CoV-2 PCR-negative swabs collected from March 8th until April 10th, 2022. One test did not meet minimal criteria for specificity. In an assessment of the analytical sensitivity in clinical specimen, the 50% limit of detection (LoD50) ranged from 4.2 × 104 to 9.2 × 105 RNA copies subjected to the RAT for Omicron-BA.1 compared to 1.3 × 105 to 1.5 × 106 for Omicron-BA.2. Overall, intra-assay differences for the detection of Omicron-BA.1-containing and Omicron-BA.2-containing samples were non-significant, while a marked overall heterogeneity among the five RATs was observed. To score positive in these point-of-care tests, up to 22-fold (LoD50) or 68-fold (LoD95) higher viral loads were required for the worst performing compared to the best performing RAT. The rates of true-positive test results for these Omicron subvariant-containing samples in the highest viral load category (Ct values < 25) ranged between 44.7 and 91.1%, while they dropped to 8.7 to 22.7% for samples with intermediate Ct values (25-30). In light of recent reports on the emergence of two novel Omicron-BA.2 subvariants, Omicron-BA.2.75 and BJ.1, awareness must be increased for the overall reduced detection rate and marked differences in RAT performance for these Omicron subvariants.

Virus variant-specific clinical performance of SARS coronavirus two rapid antigen tests in point-of-care use, from November 2020 to January 2022

OBJECTIVES

Antigen rapid diagnostic tests (RDTs) for SARS coronavirus 2 (SARS-CoV-2) are quick, widely available, and inexpensive. Consequently, RDTs have been established as an alternative and additional diagnostic strategy to quantitative reverse transcription polymerase chain reaction (RT-qPCR). However, reliable clinical and large-scale performance data specific to a SARS-CoV-2 virus variant of concern (VOC) are limited, especially for the Omicron VOC. The aim of this study was to compare RDT performance among different VOCs.

METHODS

This single-centre prospective performance assessment compared RDTs from three manufacturers (NADAL, Panbio, MEDsan) with RT-qPCR including deduced standardized viral load from oropharyngeal swabs for detection of SARS-CoV-2 in a clinical point-of-care setting from November 2020 to January 2022.

RESULTS

Among 35 479 RDT/RT-qPCR tandems taken from 26 940 individuals, 164 of the 426 SARS-CoV-2 positive samples tested true positive with an RDT corresponding to an RDT sensitivity of 38.50% (95% CI, 34.00-43.20%), with an overall specificity of 99.67% (95% CI, 99.60-99.72%). RDT sensitivity depended on viral load, with decreasing sensitivity accompanied by descending viral load. VOC-dependent sensitivity assessment showed a sensitivity of 42.86% (95% CI, 32.82-53.52%) for the wild-type SARS-CoV-2, 43.42% (95% CI, 32.86-54.61%) for the Alpha VOC, 37.67% (95% CI, 30.22-45.75%) for the Delta VOC, and 33.67% (95% CI, 25.09-43.49%) for the Omicron VOC. Sensitivity in samples with high viral loads of ≥10⁶ SARS-CoV-2 RNA copies per mL was significantly lower in the Omicron VOC (50.00%; 95% CI, 36.12-63.88%) than in the wild-type SARS-CoV-2 (79.31%; 95% CI, 61.61-90.15%; p 0.015).

DISCUSSION

RDT sensitivity for detection of the Omicron VOC is reduced in individuals infected with a high viral load, which curtails the effectiveness of RDTs. This aspect furthert: limits the use of RDTs, although RDTs are still an irreplaceable diagnostic tool for rapid, economic point-of-care and extensive SARS-CoV-2 screening.

Virotherapy combined with anti-PD-1 transiently reshapes the tumor immune environment and induces anti-tumor immunity in a preclinical PDAC model

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is largely refractory to cancer immunotherapy with PD-1 immune checkpoint blockade (ICB). Oncolytic virotherapy has been shown to synergize with ICB. In this work, we investigated the combination of anti-PD-1 and oncolytic measles vaccine in an immunocompetent transplantable PDAC mouse model.

Methods

We characterized tumor-infiltrating T cells by immunohistochemistry, flow cytometry and T cell receptor sequencing. Further, we performed gene expression profiling of tumor samples at baseline, after treatment, and when tumors progressed. Moreover, we analyzed systemic anti-tumor and anti-viral immunity.

Results

Combination treatment significantly prolonged survival compared to monotherapies. Tumor-infiltrating immune cells were increased after virotherapy. Gene expression profiling revealed a unique, but transient signature of immune activation after combination treatment. However, systemic anti-tumor immunity was induced by virotherapy and remained detectable even when tumors progressed. Anti-PD-1 treatment did not impact anti-viral immunity.

Discussion

Our results indicate that combined virotherapy and ICB induces anti-tumor immunity and reshapes the tumor immune environment. However, further refinement of this approach may be required to develop its full potential and achieve durable efficacy.

Vaccine-hesitant individuals accumulate additional COVID-19 risk due to divergent perception and behaviors related to SARS-CoV-2 testing: a population-based, cross-sectional study

Purpose

To investigate the perception of SARS-CoV-2 detection methods, information sources, and opinions on appropriate behavior after receiving negative or positive test results.

Methods

In a questionnaire-based, cross-sectional study conducted between September 1 and November 17, 2021, epidemiological, behavioral, and COVID-19-related data were acquired from the public in Munich, Germany.

Results

Most of the 1388 participants obtained information from online media (82.8%) as well as state and federal authorities (80.3%). 93.4% believed in the accuracy of SARS-CoV-2 PCR testing and 41.2% in the accuracy of rapid antigen tests (RATs). However, RATs were preferred for testing (59.1%) over PCR (51.1%). 24.0% of all individuals were willing to ignore hygiene measures and 76.9% were less afraid of SARS-CoV-2 transmission after receiving a negative PCR test (5.9% and 48.8% in case of a negative RAT). 28.8% reported not to self-isolate after receiving a positive RAT. Multivariate analyses revealed that non-vaccinated individuals relied less on information from governmental authorities (p = 0.0004) and more on social media (p = 0.0216), disbelieved in the accuracy of the PCR test (p ≤ 0.0001) while displaying strong preference towards using RATs (p ≤ 0.0001), were more willing to abandon pandemic-related hygiene measures (p ≤ 0.0001), less afraid of transmitting SARS-CoV-2 after a negative RAT (p ≤ 0.0001), and less likely to isolate after a positive RAT (p ≤ 0.0001).

Conclusion

Insights into preferred information sources as well as perception, preferences, and behavior related to SARS-CoV-2 testing and hygiene measures are key to refining public health information and surveillance campaigns. Non-vaccinated individuals’ divergent believes and behaviors possibly increase their COVID-19 risk.

Supplementary Information

The online version contains supplementary material available at 10.1007/s15010-022-01947-z .

Quantitative interpretation of PF4/heparin-EIA optical densities in predicting platelet-activating VITT antibodies

BACKGROUND

Vaccine-induced immune thrombotic thrombocytopenia (VITT) is a prothrombotic, heparin-induced thrombocytopenia (HIT)-mimicking, adverse reaction caused by platelet-activating anti-platelet factor 4 (PF4) antibodies that occurs rarely after adenovirus vector-based COVID-19 vaccination. Strength of PF4-dependent enzyme immunoassay (EIA) reactivity-judged by optical density (OD) measurements-strongly predicts platelet-activating properties of HIT antibodies in a functional test. Whether a similar relationship holds for VITT antibodies is unknown.

OBJECTIVES

To evaluate probability for positive platelet activation testing for VITT antibodies based upon EIA OD reactivity; and to investigate simple approaches to minimize false-negative platelet activation testing for VITT.

METHODS

All samples referred for VITT testing were systematically evaluated by semiquantitative in-house PF4/heparin-EIA (OD readings) and PF4-induced platelet activation (PIPA) testing within a cohort study. EIA-positive sera testing PIPA-negative were retested following 1/4 to 1/10 dilution. Logistic regression was performed to predict the probability of a positive PIPA per magnitude of EIA reactivity.

RESULTS

Greater EIA ODs in sera from patients with suspected VITT correlated strongly with greater likelihood of PIPA reactivity. Of 61 sera (with OD values >1.0) testing negative in the PIPA, a high proportion (27/61, 44.3%) became PIPA positive when tested at 1/4 to 1/10 dilution.

CONCLUSIONS

VITT serology resembles HIT in that greater EIA OD reactivity predicts higher probability of positive testing for platelet-activating antibodies. Unlike the situation with HIT antibodies, however, diluting putative VITT serum increases probability of a positive platelet activation assay, suggesting that optimal complex formation depends on the stoichiometric ratio of PF4 and anti-PF4 VITT antibodies.

Application of a maximal-clique based community detection algorithm to gut microbiome data reveals driver microbes during influenza A virus infection

Influenza A Virus (IAV) infection followed by bacterial pneumonia often leads to hospitalization and death in individuals from high risk groups. Following infection, IAV triggers the process of viral RNA replication which in turn disrupts healthy gut microbial community, while the gut microbiota plays an instrumental role in protecting the host by evolving colonization resistance. Although the underlying mechanisms of IAV infection have been unraveled, the underlying complex mechanisms evolved by gut microbiota in order to induce host immune response following IAV infection remain evasive. In this work, we developed a novel Maximal-Clique based Community Detection algorithm for Weighted undirected Networks (MCCD-WN) and compared its performance with other existing algorithms using three sets of benchmark networks. Moreover, we applied our algorithm to gut microbiome data derived from fecal samples of both healthy and IAV-infected pigs over a sequence of time-points. The results we obtained from the real-life IAV dataset unveil the role of the microbial families Ruminococcaceae, Lachnospiraceae, Spirochaetaceae and Prevotellaceae in the gut microbiome of the IAV-infected cohort. Furthermore, the additional integration of metaproteomic data enabled not only the identification of microbial biomarkers, but also the elucidation of their functional roles in protecting the host following IAV infection. Our network analysis reveals a fast recovery of the infected cohort after the second IAV infection and provides insights into crucial roles of Desulfovibrionaceae and Lactobacillaceae families in combating Influenza A Virus infection. Source code of the community detection algorithm can be downloaded from https://github.com/AniBhar84/MCCD-WN.

Mathematical modeling of plus-strand RNA virus replication to identify broad-spectrum antiviral treatment strategies

Plus-strand RNA viruses are the largest group of viruses. Many are human pathogens that inflict a socio-economic burden. Interestingly, plus-strand RNA viruses share remarkable similarities in their replication. A hallmark of plus-strand RNA viruses is the remodeling of intracellular membranes to establish replication organelles (so-called "replication factories"), which provide a protected environment for the replicase complex, consisting of the viral genome and proteins necessary for viral RNA synthesis. In the current study, we investigate pan-viral similarities and virus-specific differences in the life cycle of this highly relevant group of viruses. We first measured the kinetics of viral RNA, viral protein, and infectious virus particle production of hepatitis C virus (HCV), dengue virus (DENV), and coxsackievirus B3 (CVB3) in the immuno-compromised Huh7 cell line and thus without perturbations by an intrinsic immune response. Based on these measurements, we developed a detailed mathematical model of the replication of HCV, DENV, and CVB3 and show that only small virus-specific changes in the model were necessary to describe the in vitro dynamics of the different viruses. Our model correctly predicted virus-specific mechanisms such as host cell translation shut off and different kinetics of replication organelles. Further, our model suggests that the ability to suppress or shut down host cell mRNA translation may be a key factor for in vitro replication efficiency which may determine acute self-limited or chronic infection. We further analyzed potential broad-spectrum antiviral treatment options in silico and found that targeting viral RNA translation, especially polyprotein cleavage, and viral RNA synthesis may be the most promising drug targets for all plus-strand RNA viruses. Moreover, we found that targeting only the formation of replicase complexes did not stop the viral replication in vitro early in infection, while inhibiting intracellular trafficking processes may even lead to amplified viral growth.

Author summary

Plus-strand RNA viruses comprise a large group of related and medically relevant viruses. The current global pandemic of COVID-19 caused by the SARS-coronavirus-2 as well as the constant spread of diseases such as dengue and chikungunya fever show the necessity of a comprehensive and precise analysis of plus-strand RNA virus infections. Plus-strand RNA viruses share similarities in their life cycle. To understand their within-host replication strategies, we developed a mathematical model that studies pan-viral similarities and virus-specific differences of three plus-strand RNA viruses, namely hepatitis C, dengue, and coxsackievirus. By fitting our model to in vitro data, we found that only small virus-specific variations in the model were required to describe the dynamics of all three viruses. Furthermore, our model predicted that ribosomes involved in viral RNA translation seem to be a key player in plus-strand RNA replication efficiency, which may determine acute or chronic infection outcome. Furthermore, our in-silico drug treatment analysis suggests that targeting viral proteases involved in polyprotein cleavage, in combination with viral RNA replication, may represent promising drug targets with broad-spectrum antiviral activity.

Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks

BACKGROUND

Approaching epidemiological data with flexible machine learning algorithms is of great value for understanding disease-specific association patterns. However, it can be difficult to correctly extract and understand those patterns due to the lack of model interpretability.

METHOD

We here propose a machine learning workflow that combines random forests with Bayesian network surrogate models to allow for a deeper level of interpretation of complex association patterns. We first evaluate the proposed workflow on synthetic data. We then apply it to data from the large population-based Study of Health in Pomerania (SHIP). Based on this combination, we discover and interpret broad patterns of individual serum TSH concentrations, an important marker of thyroid functionality.

RESULTS

Evaluations using simulated data show that feature associations can be correctly recovered by combining random forests and Bayesian networks. The presented model achieves predictive accuracy that is similar to state-of-the-art models (root mean square error of 0.66, mean absolute error of 0.55, coefficient of determination of R2 = 0.15). We identify 62 relevant features from the final random forest model, ranging from general health variables over dietary and genetic factors to physiological, hematological and hemostasis parameters. The Bayesian network model is used to put these features into context and make the black-box random forest model more understandable.

CONCLUSION

We demonstrate that the combination of random forest and Bayesian network analysis is helpful to reveal and interpret broad association patterns of individual TSH concentrations. The discovered patterns are in line with state-of-the-art literature. They may be useful for future thyroid research and improved dosing of therapeutics.

Riociguat attenuates left ventricular proteome and microRNA profile changes after experimental aortic stenosis in mice

BACKGROUND AND PURPOSE

Development and progression of heart failure (HF) involve endothelial and myocardial dysfunction as well as a dysregulation of the nitric oxide - soluble guanylyl cyclase - cyclic guanosine monophosphate (NO-sGC-cGMP) signalling pathway. Recently, we reported that the sGC stimulator riociguat (RIO) has beneficial effects on cardiac remodelling and progression of HF in response to chronic pressure overload. Here, we examined if these favourable RIO effects are also reflected in alterations of the myocardial proteome and microRNA profiles.

EXPERIMENTAL APPROACH

Male C57BL/6N mice underwent transverse aortic constriction (TAC) and sham operated mice served as controls. TAC and sham animals were randomised and treated with either RIO or vehicle for five weeks, starting three weeks post-surgery when cardiac hypertrophy was established. Afterwards we performed mass spectrometric proteome analyses and microRNA sequencing of proteins and RNAs, respectively, isolated from left ventricles (LV).

KEY RESULTS

TAC-induced changes of the LV proteome were significantly reduced by RIO treatment. Bioinformatics analyses revealed that RIO improved TAC-induced cardiovascular disease related pathways, metabolism and energy production, e.g. reversed alterations in the levels of myosin heavy chain 7 (MYH7), cardiac phospholamban (PLN), and ankyrin repeat domain-containing protein 1 (ANKRD1). RIO also attenuated TAC-induced changes of microRNA levels in the LV.

CONCLUSION AND IMPLICATIONS

The sGC stimulator RIO has beneficial effects on cardiac structure and function during pressure overload, which is accompanied by a reversal of TAC-induced changes of the cardiac proteome and microRNA profile. Our data support the potential of RIO as a novel HF therapeutic.

Impaired detection of omicron by SARS-CoV-2 rapid antigen tests

Since autumn 2020, rapid antigen tests (RATs) have been implemented in several countries as an important pillar of the national testing strategy to rapidly screen for infections on site during the SARS-CoV-2 pandemic. The current surge in infection rates around the globe is driven by the variant of concern (VoC) omicron (B.1.1.529). Here, we evaluated the performance of nine SARS-CoV-2 RATs in a single-centre laboratory study. We examined a total of 115 SARS-CoV-2 PCR-negative and 166 SARS-CoV-2 PCR-positive respiratory swab samples (101 omicron, 65 delta (B.1.617.2)) collected from October 2021 until January 2022 as well as cell culture-expanded clinical isolates of both VoCs. In an assessment of the analytical sensitivity in clinical specimen, the 50% limit of detection (LoD50) ranged from 1.77 × 106 to 7.03 × 107 RNA copies subjected to the RAT for omicron compared to 1.32 × 105 to 2.05 × 106 for delta. To score positive in these point-of-care tests, up to 10-fold (LoD50) or 101-fold (LoD95) higher virus loads were required for omicron- compared to delta-containing samples. The rates of true positive test results for omicron samples in the highest virus load category (Ct values < 25) ranged between 31.4 and 77.8%, while they dropped to 0-8.3% for samples with intermediate Ct values (25-30). Of note, testing of expanded virus stocks suggested a comparable RAT sensitivity of both VoCs, questioning the predictive value of this type of in vitro-studies for clinical performance. Given their importance for national test strategies in the current omicron wave, awareness must be increased for the reduced detection rate of omicron infections by RATs and a short list of suitable RATs that fulfill the minimal requirements of performance should be rapidly disclosed.

Most anti-PF4 antibodies in vaccine-induced immune thrombotic thrombocytopenia are transient

Vaccine-induced thrombotic thrombocytopenia (VITT) is triggered by vaccination against COVID-19 with adenovirus vector vaccines (ChAdOx1 nCoV-19; Ad26.COV2-S). In this observational study, we followed VITT patients for changes in their reactivity of platelet-activating antiplatelet factor 4 (PF4) immunoglobulin G (IgG) antibodies by an anti-PF4/heparin IgG enzyme immunoassay (EIA) and a functional test for PF4-dependent, platelet-activating antibodies, and new thrombotic complications. Sixty-five VITT patients (41 females; median, 51 years; range, 18-80 years) were followed for a median of 25 weeks (range, 3-36 weeks). In 48/65 patients (73.8%; CI, 62.0% to 83.0%) the functional assay became negative. The median time to negative functional test result was 15.5 weeks (range, 5-28 weeks). In parallel, EIA optical density (OD) values decreased from median 3.12 to 1.52 (P < .0001), but seroreversion to a negative result was seen in only 14 (21.5%) patients. Five (7.5%) patients showed persistent platelet-activating antibodies and high EIA ODs for >11 weeks. None of the 29 VITT patients who received a second vaccination dose with an mRNA COVID-19 vaccine developed new thromboses or relevant increase in anti-PF4/heparin IgG EIA OD, regardless of whether PF4-dependent platelet-activating antibodies were still present. PF4-dependent platelet-activating antibodies are transient in most patients with VITT. VITT patients can safely receive a second COVID-19 mRNA-vaccine shot.

The proteogenomic subtypes of acute myeloid leukemia

Acute myeloid leukemia (AML) is an aggressive blood cancer with a poor prognosis. We report a comprehensive proteogenomic analysis of bone marrow biopsies from 252 uniformly treated AML patients to elucidate the molecular pathophysiology of AML in order to inform future diagnostic and therapeutic approaches. In addition to in-depth quantitative proteomics, our analysis includes cytogenetic profiling and DNA/RNA sequencing. We identify five proteomic AML subtypes, each reflecting specific biological features spanning genomic boundaries. Two of these proteomic subtypes correlate with patient outcome, but none is exclusively associated with specific genomic aberrations. Remarkably, one subtype (Mito-AML), which is captured only in the proteome, is characterized by high expression of mitochondrial proteins and confers poor outcome, with reduced remission rate and shorter overall survival on treatment with intensive induction chemotherapy. Functional analyses reveal that Mito-AML is metabolically wired toward stronger complex I-dependent respiration and is more responsive to treatment with the BCL2 inhibitor venetoclax.

Inflammatory fibroblasts mediate resistance to neoadjuvant therapy in rectal cancer

Standard cancer therapy targets tumor cells without considering possible damage on the tumor microenvironment that could impair therapy response. In rectal cancer patients we find that inflammatory cancer-associated fibroblasts (iCAFs) are associated with poor chemoradiotherapy response. Employing a murine rectal cancer model or patient-derived tumor organoids and primary stroma cells, we show that, upon irradiation, interleukin-1α (IL-1α) not only polarizes cancer-associated fibroblasts toward the inflammatory phenotype but also triggers oxidative DNA damage, thereby predisposing iCAFs to p53-mediated therapy-induced senescence, which in turn results in chemoradiotherapy resistance and disease progression. Consistently, IL-1 inhibition, prevention of iCAFs senescence, or senolytic therapy sensitizes mice to irradiation, while lower IL-1 receptor antagonist serum levels in rectal patients correlate with poor prognosis. Collectively, we unravel a critical role for iCAFs in rectal cancer therapy resistance and identify IL-1 signaling as an attractive target for stroma-repolarization and prevention of cancer-associated fibroblasts senescence.

Sepsis induces interleukin 6, gp130/JAK2/STAT3, and muscle wasting

BACKGROUND

Sepsis and inflammation can cause intensive care unit-acquired weakness (ICUAW). Increased interleukin-6 (IL-6) plasma levels are a risk factor for ICUAW. IL-6 signalling involves the glycoprotein 130 (gp130) receptor and the JAK/STAT-pathway, but its role in sepsis-induced muscle wasting is uncertain. In a clinical observational study, we found that the IL-6 target gene, SOCS3, was increased in skeletal muscle of ICUAW patients indicative for JAK/STAT-pathway activation. We tested the hypothesis that the IL-6/gp130-pathway mediates ICUAW muscle atrophy.

METHODS

We sequenced RNA (RNAseq) from tibialis anterior (TA) muscle of cecal ligation and puncture-operated (CLP) and sham-operated wildtype (WT) mice. The effects of the IL-6/gp130/JAK2/STAT3-pathway were investigated by analysing the atrophy phenotype, gene expression, and protein contents of C2C12 myotubes. Mice lacking Il6st, encoding gp130, in myocytes (cKO) and WT controls, as well as mice treated with the JAK2 inhibitor AG490 or vehicle were exposed to CLP or sham surgery for 24 or 96 h.

RESULTS

Analyses of differentially expressed genes in RNAseq (≥2-log2-fold change, P < 0.01) revealed an activation of IL-6-signalling and JAK/STAT-signalling pathways in muscle of septic mice, which occurred after 24 h and lasted at least for 96 h during sepsis. IL-6 treatment of C2C12 myotubes induced STAT3 phosphorylation (three-fold, P < 0.01) and Socs3 mRNA expression (3.1-fold, P < 0.01) and caused myotube atrophy. Knockdown of Il6st diminished IL-6-induced STAT3 phosphorylation (-30.0%; P < 0.01), Socs3 mRNA expression, and myotube atrophy. JAK2 (- 29.0%; P < 0.01) or STAT3 inhibition (-38.7%; P < 0.05) decreased IL-6-induced Socs3 mRNA expression. Treatment with either inhibitor attenuated myotube atrophy in response to IL-6. CLP-operated septic mice showed an increased STAT3 phosphorylation and Socs3 mRNA expression in TA muscle, which was reduced in septic Il6st-cKO mice by 67.8% (P < 0.05) and 85.6% (P < 0.001), respectively. CLP caused a loss of TA muscle weight, which was attenuated in Il6st-cKO mice (WT: -22.3%, P < 0.001, cKO: -13.5%, P < 0.001; WT vs. cKO P < 0.001). While loss of Il6st resulted in a reduction of MuRF1 protein contents, Atrogin-1 remained unchanged between septic WT and cKO mice. mRNA expression of Trim63/MuRF1 and Fbxo32/Atrogin-1 were unaltered between CLP-treated WT and cKO mice. AG490 treatment reduced STAT3 phosphorylation (-22.2%, P < 0.05) and attenuated TA muscle atrophy in septic mice (29.6% relative reduction of muscle weight loss, P < 0.05). The reduction in muscle atrophy was accompanied by a reduction in Fbxo32/Atrogin-1-mRNA (-81.3%, P < 0.05) and Trim63/MuRF1-mRNA expression (-77.6%, P < 0.05) and protein content.

CONCLUSIONS

IL-6 via the gp130/JAK2/STAT3-pathway mediates sepsis-induced muscle atrophy possibly contributing to ICUAW.

Evidence for increased SARS-CoV-2 susceptibility and COVID-19 severity related to pre-existing immunity to seasonal coronaviruses

The importance of pre-existing immune responses to seasonal endemic coronaviruses (HCoVs) for the susceptibility to SARS-CoV-2 infection and the course of COVID-19 is the subject of an ongoing scientific debate. Recent studies postulate that immune responses to previous HCoV infections can either have a slightly protective or no effect on SARS-CoV-2 pathogenesis and, consequently, be neglected for COVID-19 risk stratification. Challenging this notion, we provide evidence that pre-existing, anti-nucleocapsid antibodies against endemic α-coronaviruses and S2 domain-specific anti-spike antibodies against β-coronavirus HCoV-OC43 are elevated in patients with COVID-19 compared to pre-pandemic donors. This finding is particularly pronounced in males and in critically ill patients. Longitudinal evaluation reveals that antibody cross-reactivity or polyclonal stimulation by SARS-CoV-2 infection are unlikely to be confounders. Thus, specific pre-existing immunity to seasonal coronaviruses may increase susceptibility to SARS-CoV-2 and predispose individuals to an adverse COVID-19 outcome, guiding risk management and supporting the development of universal coronavirus vaccines.

Proteomic mapping of atrial and ventricular heart tissue in patients with aortic valve stenosis

Aortic valve stenosis (AVS) is one of the most common valve diseases in the world. However, detailed biological understanding of the myocardial changes in AVS hearts on the proteome level is still lacking. Proteomic studies using high-resolution mass spectrometry of formalin-fixed and paraffin-embedded (FFPE) human myocardial tissue of AVS-patients are very rare due to methodical issues. To overcome these issues this study used high resolution mass spectrometry in combination with a stem cell-derived cardiac specific protein quantification-standard to profile the proteomes of 17 atrial and 29 left ventricular myocardial FFPE human myocardial tissue samples from AVS-patients. In our proteomic analysis we quantified a median of 1980 (range 1495–2281) proteins in every single sample and identified significant upregulation of 239 proteins in atrial and 54 proteins in ventricular myocardium. We compared the proteins with published data. Well studied proteins reflect disease-related changes in AVS, such as cardiac hypertrophy, development of fibrosis, impairment of mitochondria and downregulated blood supply. In summary, we provide both a workflow for quantitative proteomics of human FFPE heart tissue and a comprehensive proteomic resource for AVS induced changes in the human myocardium.

Convergent use of phosphatidic acid for hepatitis C virus and SARS-CoV-2 replication organelle formation

Double membrane vesicles (DMVs) serve as replication organelles of plus-strand RNA viruses such as hepatitis C virus (HCV) and SARS-CoV-2. Viral DMVs are morphologically analogous to DMVs formed during autophagy, but lipids driving their biogenesis are largely unknown. Here we show that production of the lipid phosphatidic acid (PA) by acylglycerolphosphate acyltransferase (AGPAT) 1 and 2 in the ER is important for DMV biogenesis in viral replication and autophagy. Using DMVs in HCV-replicating cells as model, we found that AGPATs are recruited to and critically contribute to HCV and SARS-CoV-2 replication and proper DMV formation. An intracellular PA sensor accumulated at viral DMV formation sites, consistent with elevated levels of PA in fractions of purified DMVs analyzed by lipidomics. Apart from AGPATs, PA is generated by alternative pathways and their pharmacological inhibition also impaired HCV and SARS-CoV-2 replication as well as formation of autophagosome-like DMVs. These data identify PA as host cell lipid involved in proper replication organelle formation by HCV and SARS-CoV-2, two phylogenetically disparate viruses causing very different diseases, i.e. chronic liver disease and COVID-19, respectively. Host-targeting therapy aiming at PA synthesis pathways might be suitable to attenuate replication of these viruses.

Comparison of four commercial, automated antigen tests to detect SARS-CoV-2 variants of concern

A versatile portfolio of diagnostic tests is essential for the containment of the severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) pandemic. Besides nucleic acid-based test systems and point-of-care (POCT) antigen (Ag) tests, quantitative, laboratory-based nucleocapsid Ag tests for SARS-CoV-2 have recently been launched. Here, we evaluated four commercial Ag tests on automated platforms and one POCT to detect SARS-CoV-2. We evaluated PCR-positive (n = 107) and PCR-negative (n = 303) respiratory swabs from asymptomatic and symptomatic patients at the end of the second pandemic wave in Germany (February–March 2021) as well as clinical isolates EU1 (B.1.117), variant of concern (VOC) Alpha (B.1.1.7) or Beta (B.1.351), which had been expanded in a biosafety level 3 laboratory. The specificities of automated SARS-CoV-2 Ag tests ranged between 97.0 and 99.7% (Lumipulse G SARS-CoV-2 Ag (Fujirebio): 97.03%, Elecsys SARS-CoV-2 Ag (Roche Diagnostics): 97.69%; LIAISON^® SARS-CoV-2 Ag (Diasorin) and SARS-CoV-2 Ag ELISA (Euroimmun): 99.67%). In this study cohort of hospitalized patients, the clinical sensitivities of tests were low, ranging from 17.76 to 52.34%, and analytical sensitivities ranged from 420,000 to 25,000,000 Geq/ml. In comparison, the detection limit of the Roche Rapid Ag Test (RAT) was 9,300,000 Geq/ml, detecting 23.58% of respiratory samples. Receiver-operating-characteristics (ROCs) and Youden’s index analyses were performed to further characterize the assays’ overall performance and determine optimal assay cutoffs for sensitivity and specificity. VOCs carrying up to four amino acid mutations in nucleocapsid were detected by all five assays with characteristics comparable to non-VOCs. In summary, automated, quantitative SARS-CoV-2 Ag tests show variable performance and are not necessarily superior to a standard POCT. The efficacy of any alternative testing strategies to complement nucleic acid-based assays must be carefully evaluated by independent laboratories prior to widespread implementation.

In-depth profiling of COVID-19 risk factors and preventive measures in healthcare workers

Purpose

To determine risk factors for coronavirus disease 2019 (COVID-19) in healthcare workers (HCWs), characterize symptoms, and evaluate preventive measures against SARS-CoV-2 spread in hospitals.

Methods

In a cross-sectional study conducted between May 27 and August 12, 2020, after the first wave of the COVID-19 pandemic, we obtained serological, epidemiological, occupational as well as COVID-19-related data at a quaternary care, multicenter hospital in Munich, Germany.

Results

7554 HCWs participated, 2.2% of whom tested positive for anti-SARS-CoV-2 antibodies. Multivariate analysis revealed increased COVID-19 risk for nurses (3.1% seropositivity, 95% CI 2.5–3.9%, p = 0.012), staff working on COVID-19 units (4.6% seropositivity, 95% CI 3.2–6.5%, p = 0.032), males (2.4% seropositivity, 95% CI 1.8–3.2%, p = 0.019), and HCWs reporting high-risk exposures to infected patients (5.5% seropositivity, 95% CI 4.0–7.5%, p = 0.0022) or outside of work (12.0% seropositivity, 95% CI 8.0–17.4%, p < 0.0001). Smoking was a protective factor (1.1% seropositivity, 95% CI 0.7–1.8% p = 0.00018) and the symptom taste disorder was strongly associated with COVID-19 (29.8% seropositivity, 95% CI 24.3–35.8%, p < 0.0001). An unbiased decision tree identified subgroups with different risk profiles. Working from home as a preventive measure did not protect against SARS-CoV-2 infection. A PCR-testing strategy focused on symptoms and high-risk exposures detected all larger COVID-19 outbreaks.

Conclusion

Awareness of the identified COVID-19 risk factors and successful surveillance strategies are key to protecting HCWs against SARS-CoV-2, especially in settings with limited vaccination capacities or reduced vaccine efficacy.

Supplementary Information

The online version contains supplementary material available at 10.1007/s15010-021-01672-z.

Applications of artificial intelligence/machine learning approaches in cardiovascular medicine: a systematic review with recommendations

Aims

Artificial intelligence (AI) and machine learning (ML) promise vast advances in medicine. The current state of AI/ML applications in cardiovascular medicine is largely unknown. This systematic review aims to close this gap and provides recommendations for future applications.

Methods and results

Pubmed and EMBASE were searched for applied publications using AI/ML approaches in cardiovascular medicine without limitations regarding study design or study population. The PRISMA statement was followed in this review. A total of 215 studies were identified and included in the final analysis. The majority (87%) of methods applied belong to the context of supervised learning. Within this group, tree-based methods were most commonly used, followed by network and regression analyses as well as boosting approaches. Concerning the areas of application, the most common disease context was coronary artery disease followed by heart failure and heart rhythm disorders. Often, different input types such as electronic health records and images were combined in one AI/ML application. Only a minority of publications investigated reproducibility and generalizability or provided a clinical trial registration.

Conclusions

A major finding is that methodology may overlap even with similar data. Since we observed marked variation in quality, reporting of the evaluation and transparency of data and methods urgently need to be improved.

Hypertension delays viral clearance and exacerbates airway hyperinflammation in patients with COVID-19

In coronavirus disease 2019 (COVID-19), hypertension and cardiovascular diseases are major risk factors for critical disease progression. However, the underlying causes and the effects of the main anti-hypertensive therapies-angiotensin-converting enzyme inhibitors (ACEIs) and angiotensin receptor blockers (ARBs)-remain unclear. Combining clinical data (n = 144) and single-cell sequencing data of airway samples (n = 48) with in vitro experiments, we observed a distinct inflammatory predisposition of immune cells in patients with hypertension that correlated with critical COVID-19 progression. ACEI treatment was associated with dampened COVID-19-related hyperinflammation and with increased cell intrinsic antiviral responses, whereas ARB treatment related to enhanced epithelial-immune cell interactions. Macrophages and neutrophils of patients with hypertension, in particular under ARB treatment, exhibited higher expression of the pro-inflammatory cytokines CCL3 and CCL4 and the chemokine receptor CCR1. Although the limited size of our cohort does not allow us to establish clinical efficacy, our data suggest that the clinical benefits of ACEI treatment in patients with COVID-19 who have hypertension warrant further investigation.

Modeling transcriptomic age using knowledge-primed artificial neural networks

The development of 'age clocks', machine learning models predicting age from biological data, has been a major milestone in the search for reliable markers of biological age and has since become an invaluable tool in aging research. However, beyond their unquestionable utility, current clocks offer little insight into the molecular biological processes driving aging, and their inner workings often remain non-transparent. Here we propose a new type of age clock, one that couples predictivity with interpretability of the underlying biology, achieved through the incorporation of prior knowledge into the model design. The clock, an artificial neural network constructed according to well-described biological pathways, allows the prediction of age from gene expression data of skin tissue with high accuracy, while at the same time capturing and revealing aging states of the pathways driving the prediction. The model recapitulates known associations of aging gene knockdowns in simulation experiments and demonstrates its utility in deciphering the main pathways by which accelerated aging conditions such as Hutchinson-Gilford progeria syndrome, as well as pro-longevity interventions like caloric restriction, exert their effects.

MO081THE INFLUENCE OF VITAMIN D3 ON PODOCYTE DIFFERENTIATION IN SITU AND IN VITRO

Background and Aims

Dedifferentiation of podocytes affects their complex 3 D morphology and is the main initiator for the development of chronic kidney disease (CKD). Unfortunately, there is no causal therapy for CKD until today. Thus, inadequate and late treatment lead to end-stage renal disease which subsequently makes renal replacement therapy inevitable. To address this, new treatment options are of high significance for CKD patients. Recently, vitamin D3 (VitD) became a promising candidate, but it is controversially discussed. In the present study, we investigated the influence of VitD on podocyte differentiation and the related pathways in situ and in vitro.

Method

We combined a podocyte dedifferentiation model (GlomAssay) with an automated imaging procedure (Aquifer Imaging Machine). We analyzed cultured glomeruli from transgenic mice expressing cyan-fluorescent protein (CFP) under the control of the nephrin promoter which were treated with VitD and its` analogue (calcipotriol). In this model, the decreasing CFP fluorescence is as a read out for podocyte (de)differentiation. Additionally, VitD-, calcipotriol- and VitD receptor (VDR) inhibitor (PS121912)-treated glomeruli were investigated by RNA-Seq and LC-MS/MS to reveal the molecular effects of VitD on podocyte differentiation. Furthermore, we treated cultured murine podocytes with VitD, calcipotriol and PS121912 to elucidate the morphological and molecular changes by immunofluorescence staining, RT-qPCR and Western blot.

Results

VitD- and calcipotriol-treated glomeruli showed a significantly higher intensity of CFP fluorescence after 9 days, indicating higher level of nephrin compared to the control. This was verified by RT-qPCR and Western blot for nephrin and CFP. Additionally, we found an upregulation of VDR in VitD- and calcipotriol-treated glomeruli compared to controls. By transcriptomic and proteomic analysis, we identified molecular patterns that are specific for the different treated groups. Thus, we observed differential gene expression in VitD- and Wnt-signaling pathway as well as regulated genes that are essential for the actin cytoskeleton, focal adhesion formation and the slit membrane. Beside this, cultured podocytes showed a significant upregulation of the slit membrane protein nephrin, VDR and CYP24A1 by VitD. This is accompanied by an altered morphology of the podocytes due to a reorganization of the actin cytoskeleton.

Conclusion

Our results show that VitD influences podocyte differentiation in situ and in vitro by the regulation of specific signaling pathways.

ITN-VIROINF: Understanding (Harmful) Virus-Host Interactions by Linking Virology and Bioinformatics

Many recent studies highlight the fundamental importance of viruses. Besides their important role as human and animal pathogens, their beneficial, commensal or harmful functions are poorly understood. By developing and applying tailored bioinformatical tools in important virological models, the Marie Skłodowska-Curie Initiative International Training Network VIROINF will provide a better understanding of viruses and the interaction with their hosts. This will open the door to validate methods of improving viral growth, morphogenesis and development, as well as to control strategies against unwanted microorganisms. The key feature of VIROINF is its interdisciplinary nature, which brings together virologists and bioinformaticians to achieve common goals.

Computational strategies to combat COVID-19: useful tools to accelerate SARS-CoV-2 and coronavirus research

SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is a novel virus of the family Coronaviridae. The virus causes the infectious disease COVID-19. The biology of coronaviruses has been studied for many years. However, bioinformatics tools designed explicitly for SARS-CoV-2 have only recently been developed as a rapid reaction to the need for fast detection, understanding and treatment of COVID-19. To control the ongoing COVID-19 pandemic, it is of utmost importance to get insight into the evolution and pathogenesis of the virus. In this review, we cover bioinformatics workflows and tools for the routine detection of SARS-CoV-2 infection, the reliable analysis of sequencing data, the tracking of the COVID-19 pandemic and evaluation of containment measures, the study of coronavirus evolution, the discovery of potential drug targets and development of therapeutic strategies. For each tool, we briefly describe its use case and how it advances research specifically for SARS-CoV-2. All tools are free to use and available online, either through web applications or public code repositories. Contact:evbc@unj-jena.de.

From heterogeneous healthcare data to disease-specific biomarker networks: A hierarchical Bayesian network approach

In this work, we introduce an entirely data-driven and automated approach to reveal disease-associated biomarker and risk factor networks from heterogeneous and high-dimensional healthcare data. Our workflow is based on Bayesian networks, which are a popular tool for analyzing the interplay of biomarkers. Usually, data require extensive manual preprocessing and dimension reduction to allow for effective learning of Bayesian networks. For heterogeneous data, this preprocessing is hard to automatize and typically requires domain-specific prior knowledge. We here combine Bayesian network learning with hierarchical variable clustering in order to detect groups of similar features and learn interactions between them entirely automated. We present an optimization algorithm for the adaptive refinement of such group Bayesian networks to account for a specific target variable, like a disease. The combination of Bayesian networks, clustering, and refinement yields low-dimensional but disease-specific interaction networks. These networks provide easily interpretable, yet accurate models of biomarker interdependencies. We test our method extensively on simulated data, as well as on data from the Study of Health in Pomerania (SHIP-TREND), and demonstrate its effectiveness using non-alcoholic fatty liver disease and hypertension as examples. We show that the group network models outperform available biomarker scores, while at the same time, they provide an easily interpretable interaction network.

High-dimensional and heterogeneous healthcare data, such as electronic health records or epidemiological study data, contain much information on yet unknown risk factors that are associated with disease development. The identification of these risk factors may help to improve prevention, diagnosis, and therapy. Bayesian networks are powerful statistical models that can decipher these complex relationships. However, high dimensionality and heterogeneity of data, together with missing values and high feature correlation, make it difficult to automatically learn a good model from data. To facilitate the use of network models, we present a novel, fully automated workflow that combines network learning with hierarchical clustering. The algorithm reveals groups of strongly related features and models the interactions among those groups. It results in simpler network models that are easier to analyze. We introduce a method of adaptive refinement of such models to ensure that disease-relevant parts of the network are modeled in great detail. Our approach makes it easy to learn compact, accurate, and easily interpretable biomarker interaction networks. We test our method extensively on simulated data as well as data from the Study of Health in Pomerania (SHIP-Trend) by learning models of hypertension and non-alcoholic fatty liver disease.

Stimulation of soluble guanylyl cyclase (sGC) by riociguat attenuates heart failure and pathological cardiac remodelling

BACKGROUND AND PURPOSE

Heart failure is associated with an impaired NO-soluble guanylyl cyclase (sGC)-cGMP pathway and its augmentation is thought to be beneficial for its therapy. We hypothesized that stimulation of sGC by the sGC stimulator riociguat prevents pathological cardiac remodelling and heart failure in response to chronic pressure overload.

EXPERIMENTAL APPROACH

Transverse aortic constriction or sham surgery was performed in C57BL/6N mice. After 3 weeks of transverse aortic constriction when heart failure was established, animals receive either riociguat or its vehicle for 5 additional weeks. Cardiac function was evaluated weekly by echocardiography. Eight weeks after surgery, histological analyses were performed to evaluate remodelling and the transcriptome of the left ventricles (LVs) was analysed by RNA sequencing. Cell culture experiments were used for mechanistically studies.

KEY RESULTS

Transverse aortic constriction resulted in a continuous decrease of LV ejection fraction and an increase in LV mass until week 3. Five weeks of riociguat treatment resulted in an improved LV ejection fraction and a decrease in the ratio of left ventricular mass to total body weight (LVM/BW), myocardial fibrosis and myocyte cross-sectional area. RNA sequencing revealed that riociguat reduced the expression of myocardial stress and remodelling genes (e.g. Nppa, Nppb, Myh7 and collagen) and attenuated the activation of biological pathways associated with cardiac hypertrophy and heart failure. Riociguat reversed pathological stress response in cultivated myocytes and fibroblasts.

CONCLUSION AND IMPLICATIONS

Stimulation of the sGC reverses transverse aortic constriction-induced heart failure and remodelling, which is associated with improved myocardial gene expression.

Mathematical modeling of hepatitis C RNA replication, exosome secretion and virus release

Hepatitis C virus (HCV) causes acute hepatitis C and can lead to life-threatening complications if it becomes chronic. The HCV genome is a single plus strand of RNA. Its intracellular replication is a spatiotemporally coordinated process of RNA translation upon cell infection, RNA synthesis within a replication compartment, and virus particle production. While HCV is mainly transmitted via mature infectious virus particles, it has also been suggested that HCV-infected cells can secrete HCV RNA carrying exosomes that can infect cells in a receptor independent manner. In order to gain insight into these two routes of transmission, we developed a series of intracellular HCV replication models that include HCV RNA secretion and/or virus assembly and release. Fitting our models to in vitro data, in which cells were infected with HCV, suggests that initially most secreted HCV RNA derives from intracellular cytosolic plus-strand RNA, but subsequently secreted HCV RNA derives equally from the cytoplasm and the replication compartments. Furthermore, our model fits to the data suggest that the rate of virus assembly and release is limited by host cell resources. Including the effects of direct acting antivirals in our models, we found that in spite of decreasing intracellular HCV RNA and extracellular virus concentration, low level HCV RNA secretion may continue as long as intracellular RNA is available. This may possibly explain the presence of detectable levels of plasma HCV RNA at the end of treatment even in patients that ultimately attain a sustained virologic response.

Approximately 70 million people are chronically infected with hepatitis C virus (HCV), which if left untreated may lead to cirrhosis and liver cancer. However, modern drug therapy is highly effective and hepatitis C is the first chronic virus infection that can be cured with short-term therapy in almost all infected individuals. The within-host transmission of HCV occurs mainly via infectious virus particles, but experimental studies suggest that there may be additional receptor-independent cell-to-cell transmission by exosomes that carry the HCV genome. In order to understand the intracellular HCV lifecycle and HCV RNA spread, we developed a series of mathematical models that take both exosomal secretion and viral secretion into account. By fitting these models to in vitro data, we found that secretion of both HCV RNA as well as virus probably occurs and that the rate of virus assembly is likely limited by cellular co-factors on which the virus strongly depends for its own replication. Furthermore, our modeling predicted that the parameters governing the processes in the viral lifecycle that are targeted by direct acting antivirals are the most sensitive to perturbations, which may help explain their ability to cure this infection.

Interaction of Staphylococcus aureus and Host Cells upon Infection of Bronchial Epithelium during Different Stages of Regeneration

The primary barrier that protects our lungs against infection by pathogens is a tightly sealed layer of epithelial cells. When the integrity of this barrier is disrupted as a consequence of chronic pulmonary diseases or viral insults, bacterial pathogens will gain access to underlying tissues. A major pathogen that can take advantage of such conditions is Staphylococcus aureus, thereby causing severe pneumonia. In this study, we investigated how S. aureus responds to different conditions of the human epithelium, especially nonpolarization and fibrogenesis during regeneration using an in vitro infection model. The infective process was monitored by quantification of the epithelial cell and bacterial populations, fluorescence microscopy, and mass spectrometry. The results uncover differences in bacterial internalization and population dynamics that correlate with the outcome of infection. Protein profiling reveals that, irrespective of the polarization state of the epithelial cells, the invading bacteria mount similar responses to adapt to the intracellular milieu. Remarkably, a bacterial adaptation that was associated with the regeneration state of the epithelial cells concerned the early upregulation of proteins controlled by the redox-responsive regulator Rex when bacteria were confronted with a polarized cell layer. This is indicative of the modulation of the bacterial cytoplasmic redox state to maintain homeostasis early during infection even before internalization. Our present observations provide a deeper insight into how S. aureus can take advantage of a breached epithelial barrier and show that infected epithelial cells have limited ability to respond adequately to staphylococcal insults.

Genome-Wide DNA Alterations in X-Irradiated Human Gingiva Fibroblasts

While ionizing radiation (IR) is a powerful tool in medical diagnostics, nuclear medicine, and radiology, it also is a serious threat to the integrity of genetic material. Mutagenic effects of IR to the human genome have long been the subject of research, yet still comparatively little is known about the genome-wide effects of IR exposure on the DNA-sequence level. In this study, we employed high throughput sequencing technologies to investigate IR-induced DNA alterations in human gingiva fibroblasts (HGF) that were acutely exposed to 0.5, 2, and 10 Gy of 240 kV X-radiation followed by repair times of 16 h or 7 days before whole-genome sequencing (WGS). Our analysis of the obtained WGS datasets revealed patterns of IR-induced variant (SNV and InDel) accumulation across the genome, within chromosomes as well as around the borders of topologically associating domains (TADs). Chromosome 19 consistently accumulated the highest SNVs and InDels events. Translocations showed variable patterns but with recurrent chromosomes of origin (e.g., Chr7 and Chr16). IR-induced InDels showed a relative increase in number relative to SNVs and a characteristic signature with respect to the frequency of triplet deletions in areas without repetitive or microhomology features. Overall experimental conditions and datasets the majority of SNVs per genome had no or little predicted functional impact with a maximum of 62, showing damaging potential. A dose-dependent effect of IR was surprisingly not apparent. We also observed a significant reduction in transition/transversion (Ti/Tv) ratios for IR-dependent SNVs, which could point to a contribution of the mismatch repair (MMR) system that strongly favors the repair of transitions over transversions, to the IR-induced DNA-damage response in human cells. Taken together, our results show the presence of distinguishable characteristic patterns of IR-induced DNA-alterations on a genome-wide level and implicate DNA-repair mechanisms in the formation of these signatures.

Reciprocal Effects of Fibroblast Growth Factor Receptor Signaling on Dengue Virus Replication and Virion Production

Dengue virus (DENV) is a human arboviral pathogen accounting for 390 million infections every year. The available vaccine has limited efficacy, and DENV-specific drugs have not been generated. To better understand DENV-host cell interaction, we employed RNA interference-based screening of the human kinome and identified fibroblast growth factor receptor 4 (FGFR4) to control the DENV replication cycle. Pharmacological inhibition of FGFR exerts a reciprocal effect by reducing DENV RNA replication and promoting the production of infectious virus particles. Addressing the latter effect, we found that the FGFR signaling pathway modulates intracellular distribution of DENV particles in a PI3K-dependent manner. Upon FGFR inhibition, virions accumulate in the trans-Golgi network compartment, where they undergo enhanced maturation cleavage of the envelope protein precursor membrane (prM), rendering virus particles more infectious. This study reveals an unexpected reciprocal role of a cellular receptor tyrosine kinase regulating DENV RNA replication and the production of infectious virions.

Determination of Immediate vs. Kinetic Growth Retardation in Physically Plasma-treated Cells by Experimental and Modelling Data

BACKGROUND/AIM

The antiproliferative effects of cold atmospheric plasma (CAP) make it a promising application option in oncology. The aim of the present study was to examine whether short-term CAP treatment leads to an initial partial elimination of the treated cells or to long-term impairement and inhibition of cell growth.

MATERIALS AND METHODS

Cells were treated with CAP and biostatistical modelling was used to estimate growth rates over the incubation time. Four cell lines (U2-OS and MNNG osteosarcoma cells, 3T3 fibroblasts, HaCaT keratinocytes) and three CAP sources (MiniJet-R, kINPen MED, Maxium) were used.

RESULTS

The antiproliferative efficacy of CAP was due to a significant reduction in cell count during treatment and the long-lasting inhibition of growth rate in the remaining cells, detectable in all cell lines and after treatment using all three CAP devices.

CONCLUSION

Induction of cell death and inhibition of cell growth are part of a general mechanism of biological CAP efficacy. However, data contradict the hypothesis that cancer cells respond more sensitively to CAP treatment compared to non-malignant cells.

Ionizing Radiation Alters the Transition/Transversion Ratio in the Exome of Human Gingiva Fibroblasts

Little is known about the mutational impact of ionizing radiation (IR) exposure on a genome-wide level in mammalian tissues. Recent advancements in sequencing technology have provided powerful tools to perform exome-wide analyses of genetic variation. This also opened up new avenues for studying and characterizing global genomic IR-induced effects. However, genotypes generated by next generation sequencing (NGS) studies can contain errors, which may significantly impact the power to detect signals in common and rare variant analyses. These genotyping errors are not explicitly detected by the standard Genotype Analysis ToolKit (GATK) and Variant Quality Score Recalibration (VQSR) tool and thus remain a potential source of false-positive variants in whole exome sequencing (WES) datasets. In this context, the transition-transversion ratio (Ti/Tv) is commonly used as an additional quality check. In case of IR experiments, this is problematic when Ti/Tv itself might be influenced by IR treatment. It was the aim of this study to determine a suitable threshold for variant filters for NGS datasets from irradiated cells in order to achieve high data quality using Ti/Tv, while at the same time being able to investigate radiation-specific effects on the Ti/Tv ratio for different radiation doses. By testing a variety of filter settings and comparing the obtained results with publicly available datasets, we observe that a coverage filter setting of depth (DP) 3 and genotype quality (GQ) 20 is sufficient for high quality single nucleotide variants (SNVs) calling in an analysis combining GATK and VSQR and that Ti/Tv values are a consistent and useful indicator for data quality assessment for all tested NGS platforms. Furthermore, we report a reduction in Ti/Tv in IR-induced mutations in primary human gingiva fibroblasts (HGFs), which points to an elevated proportion of transversions among IR-induced SNVs and thus might imply that mismatch repair (MMR) plays a role in the cellular damage response to IR-induced DNA lesions.

Mechanistic modeling explains the dsRNA length-dependent activation of the RIG-I mediated immune response

In cell-intrinsic antiviral immunity, cytoplasmic receptors such as retinoic acid-inducible gene I (RIG-I) detect viral double-stranded RNA (dsRNA) and trigger a signaling cascade activating the interferon (IFN) system. This leads to the transcription of hundreds of interferon-stimulated genes (ISGs) with a wide range of antiviral effects. This recognition of dsRNA not only has to be very specific to discriminate foreign from self but also highly sensitive to detect even very low numbers of pathogenic dsRNA molecules. Previous work indicated an influence of the dsRNA length on the binding behavior of RIG-I and its potential to elicit antiviral signaling. However, the molecular mechanisms behind the binding process are still under debate. We compare two hypothesized RIG-I binding mechanisms by translating them into mathematical models and analyzing their potential to describe published experimental data. The models consider the length of the dsRNA as well as known RIG-I binding motifs and describe RIG-I pathway activation after stimulation with dsRNA. We show that internal RIG-I binding sites in addition to cooperative RIG-I oligomerization are essential to describe the experimentally observed RIG-I binding behavior and immune response activation for different dsRNA lengths and concentrations. The combination of RIG-I binding to internal sites on the dsRNA and cooperative oligomerization compensates for a lack of high-affinity binding motifs and triggers a strong antiviral response for long dsRNAs. Model analysis reveals dsRNA length-dependency as a potential mechanism to discriminate between different types of dsRNAs: It allows for sensitive detection of small numbers of long dsRNAs, a typical by-product of viral replication, while ensuring tolerance against non-harming small dsRNAs.

A Coupled Mathematical Model of the Intracellular Replication of Dengue Virus and the Host Cell Immune Response to Infection

Dengue virus (DV) is a positive-strand RNA virus of the Flavivirus genus. It is one of the most prevalent mosquito-borne viruses, infecting globally 390 million individuals per year. The clinical spectrum of DV infection ranges from an asymptomatic course to severe complications such as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS), the latter because of severe plasma leakage. Given that the outcome of infection is likely determined by the kinetics of viral replication and the antiviral host cell immune response (HIR) it is of importance to understand the interaction between these two parameters. In this study, we use mathematical modeling to characterize and understand the complex interplay between intracellular DV replication and the host cells' defense mechanisms. We first measured viral RNA, viral protein, and virus particle production in Huh7 cells, which exhibit a notoriously weak intrinsic antiviral response. Based on these measurements, we developed a detailed intracellular DV replication model. We then measured replication in IFN competent A549 cells and used this data to couple the replication model with a model describing IFN activation and production of IFN stimulated genes (ISGs), as well as their interplay with DV replication. By comparing the cell line specific DV replication, we found that host factors involved in replication complex formation and virus particle production are crucial for replication efficiency. Regarding possible modes of action of the HIR, our model fits suggest that the HIR mainly affects DV RNA translation initiation, cytosolic DV RNA degradation, and naïve cell infection. We further analyzed the potential of direct acting antiviral drugs targeting different processes of the DV lifecycle in silico and found that targeting RNA synthesis and virus assembly and release are the most promising anti-DV drug targets.

Reconstruction and Analysis of Cattle Metabolic Networks in Normal and Acidosis Rumen Tissue

Simple Summary

Economics of feedlot beef production dictate that beef cattle must gain weight at their maximum potential rate; this involves getting them quickly onto a full feed of high fermentable diet which can induce the ruminal acidosis disease. The molecular host mechanisms that occur as a response to the acidosis, are mostly unknown. For answering this question, the rumen epithelial transcriptome in acidosis and control fattening steers were obtained. By RNA sequencing we found the different expression profiles of genes in normal and acidosis induced steers. Then we constructed two metabolic networks for normal and acidosis tissue based on gene expression profile. Our results suggest that rapid shifts to diets rich in fermentable carbohydrates cause an increased concentration of ruminal volatile fatty acids (VFA) and toxins and significant changes in transcriptome profiles and metabolites of rumen epithelial tissue, with negative effects on economic consequences of poor performance and animal health.

Abstract

The objective of this study was to develop a system-level understanding of acidosis biology. Therefore, the genes expression differences between the normal and acidosis rumen epithelial tissues were first examined using the RNA-seq data in order to understand the molecular mechanisms involved in the disease and then their corresponding metabolic networks constructed. A number of 1074 genes, 978 isoforms, 1049 transcription start sites (TSS), 998 coding DNA sequence (CDS) and 2 promoters were identified being differentially expressed in the rumen tissue between the normal and acidosis samples (p < 0.05). The functional analysis of 627 up-regulated genes revealed their involvement in ion transmembrane transport, filament organization, regulation of cell adhesion, regulation of the actin cytoskeleton, ATP binding, glucose transmembrane transporter activity, carbohydrate binding, growth factor binding and cAMP metabolic process. Additionally, 111 differentially expressed enzymes were identified between the rumen epithelial tissue of the normal and acidosis steers with 46 up-regulated and 65 down-regulated ones in the acidosis group. The pathways and reactions analyses associated with the up-regulated enzymes indicate that most of these enzymes are involved in the fatty acid metabolism, biosynthesis of amino acids, pyruvate and carbon metabolism while most of the down-regulated ones are involved in purine and pyrimidine, vitamin B6 and antibiotics metabolisms. The degree distribution of both metabolic networks follows a power-law one, hence displaying a scale-free property. The top 15 hub metabolites were determined in the acidosis metabolic network with most of them involved in the fatty acid oxidation, VFA biosynthesis, amino acid biogenesis and glutathione metabolism which plays an important role in the stress condition. The limitations of this study were low number of animals and using only epithelial tissue (ventral sac) for RNA-seq.