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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.
Bioinformatics Algorithms and Predictive Models: The Grand Challenge in Computational Virology
(2021)
Never in the past has the relevance of bioinformatic and predictive tools been more central
in the field of virology as today. SARS-CoV-2 has brought along a huge health burden, but also
a deeper awareness that scientific progress can no longer be effective without extensive systems
for data storage, sharing and analysis, as well as computational tools dedicated to molecular
epidemiology, NGS data analysis, prediction of drug targets, multi-OMIC data integration, and
many other applications.
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.
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.
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 ofIR to the human genome have long been the subject of research, yet still comparatively little isknown 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 alterationsin human gingiva fibroblasts (HGF) that were acutely exposed to 0.5, 2, and 10 Gy of 240 kVX-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 topologicallyassociating domains (TADs). Chromosome 19 consistently accumulated the highest SNVs andInDels events. Translocations showed variable patterns but with recurrent chromosomes of origin(e.g., Chr7 andChr16). IR-induced InDels showed a relative increase in number relative to SNVs anda characteristic signature with respect to the frequency of triplet deletions in areas without repetitiveor microhomology features. Overall experimental conditions and datasets the majority of SNVs pergenome had no or little predicted functional impact with a maximum of 62, showing damagingpotential. A dose-dependent effect of IR was surprisingly not apparent. We also observed a significantreduction in transition/transversion (Ti/Tv) ratios for IR-dependent SNVs, which could point to acontribution of the mismatch repair (MMR) system that strongly favors the repair of transitions overtransversions, to the IR-induced DNA-damage response in human cells. Taken together, our resultsshow the presence of distinguishable characteristic patterns of IR-induced DNA-alterations on agenome-wide level and implicate DNA-repair mechanisms in the formation of these signatures
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.
Global 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.
ITN—VIROINF: Understanding (Harmful) Virus-Host Interactions by Linking Virology and Bioinformatics
(2021)
Liver diseases are important causes of morbidity and mortality worldwide. The aim of
this study was to identify differentially expressed microRNAs (miRNAs), target genes, and key
pathways as innovative diagnostic biomarkers in liver patients with different pathology and functional
state. We determined, using RT-qPCR, the expression of 472 miRNAs in 125 explanted livers from
subjects with six different liver pathologies and from control livers. ANOVA was employed to
obtain differentially expressed miRNAs (DEMs), and miRDB (MicroRNA target prediction database)
was used to predict target genes. A miRNA–gene differential regulatory (MGDR) network was
constructed for each condition. Key miRNAs were detected using topological analysis. Enrichment
analysis for DEMs was performed using the Database for Annotation, Visualization, and Integrated
Discovery (DAVID). We identified important DEMs common and specific to the different patient
groups and disease progression stages. hsa-miR-1275 was universally downregulated regardless
the disease etiology and stage, while hsa-let-7a*, hsa-miR-195, hsa-miR-374, and hsa-miR-378 were
deregulated. The most significantly enriched pathways of target genes controlled by these miRNAs
comprise p53 tumor suppressor protein (TP53)-regulated metabolic genes, and those involved in
regulation of methyl-CpG-binding protein 2 (MECP2) expression, phosphatase and tensin homolog
(PTEN) messenger RNA (mRNA) translation and copper homeostasis. Our findings show a novel
panel of deregulated miRNAs in the liver tissue from patients with different liver pathologies. These
miRNAs hold potential as biomarkers for diagnosis and staging of liver diseases.