The aim of this systematic review and meta‐analysis was to critically assess the published literature related to community‐acquired viral co‐infections and COVID‐19 and to evaluate the prevalence, most identified co‐pathogens, and relevant risk factors. Furthermore, we aimed to examine the clinical features and outcomes of co‐infected compared to mono‐infected COVID‐19 patients. We systematically searched PubMed, Web of Science, Embase, Scopus, and The Cochrane Library for studies published from 1 November 2019 to 13 August 2021. We included patients of all ages and any COVID‐19 severity who were screened for respiratory viral co‐infection within 48 h of COVID‐19 diagnosis. The main outcome was the proportion of patients with a respiratory viral co‐infection. The systematic review was registered to PROSPERO (CRD42021272235). Out of 6053 initially retrieved studies, 59 studies with a total of 16,643 SARS‐CoV‐2 positive patients were included. The global pooled prevalence was 5.01% (95% CI 3.34%–7.27%; I2 = 95%) based on a random‐effects model, with Influenza Viruses (1.54%) and Enteroviruses (1.32%) being the most prevalent pathogens. Subgroup analyses showed that co‐infection was significantly higher in paediatric (9.39%) than adult (3.51%) patients (p‐value = 0.02). Furthermore, co‐infected patients were more likely to be dyspnoeic and the odds of fatality (OR = 1.66) were increased. Although a relatively low proportion of COVID‐19 patients have a respiratory viral co‐infection, our findings show that multiplex viral panel testing may be advisable in patients with compatible symptoms. Indeed, respiratory virus co‐infections may be associated with adverse clinical outcomes and therefore have therapeutic and prognostic implications.
The honeybee (Apis mellifera) represents a model organism for social insects displaying behavioral plasticity. This is reflected by an age-dependent task allocation. The most protruding tasks are performed by young nurse bees and older forager bees that take care of the brood inside the hive and collect food from outside the hive, respectively. The molecular mechanism leading to the transition from nurse bees to foragers is currently under intense research. Circular RNAs, however, were not considered in this context so far. As of today, this group of non-coding RNAs was only known to exist in two other insects, Drosophila melanogaster and Bombyx mori. Here we complement the state of circular RNA research with the first characterization in a social insect. We identified numerous circular RNAs in the brain of A. mellifera nurse bees and forager bees using RNA-Seq with exonuclease enrichment. Presence and circularity were verified for the most abundant representatives. Back-splicing in honeybee occurs further towards the end of transcripts and in transcripts with a high number of exons. The occurrence of circularized exons is correlated with length and CpG-content of their flanking introns. The latter coincides with increased DNA-methylation in the respective loci. For two prominent circular RNAs the abundance in worker bee brains was quantified in TaqMan assays. In line with previous findings of circular RNAs in Drosophila, circAmrsmep2 accumulates with increasing age of the insect. In contrast, the levels of circAmrad appear age-independent and correlate with the bee’s task. Its parental gene is related to amnesia-resistant memory. We provide the first characterization of circRNAs in a social insect. Many of the RNAs identified here show homologies to circular RNAs found in Drosophila and Bombyx, indicating that circular RNAs are a common feature among insects. We find that exon circularization is correlated to DNA-methylation at the flanking introns. The levels of circAmrad suggest a task-dependent abundance that is decoupled from age. Moreover, a GO term analysis shows an enrichment of task-related functions. We conclude that circular RNAs could be relevant for task allocation in honeybee and should be investigated further in this context.
Extracellular vesicles (EVs) are released by virtually all cells and may serve as intercellular communication structures by transmitting molecules such as proteins, lipids, and nucleic acids between cells. MicroRNAs (miRNAs) are an abundant class of vesicular RNA playing a pivotal role in regulating intracellular processes. In this work, we aimed to characterize vesicular miRNA profiles released in a side-directed manner by bronchial epithelial cells from healthy and asthmatic subjects using an air−liquid interface cell culture model. EVs were isolated from a culture medium collected from either the basolateral or apical cell side of the epithelial cell cultures and characterized by nano-flow cytometry (NanoFCM) and bead-based flow cytometry. EV-associated RNA profiles were assessed by small RNA sequencing and subsequent bioinformatic analyses. Furthermore, miRNA-associated functions and targets were predicted and miRNA network analyses were performed. EVs were released at higher numbers to the apical cell side of the epithelial cells and were considerably smaller in the apical compared to the basolateral compartment. EVs from both compartments showed a differential tetraspanins surface marker expression. Furthermore, 236 miRNAs were differentially expressed depending on the EV secretion side, regardless of the disease phenotype. On the apical cell side, 32 miRNAs were significantly altered in asthmatic versus healthy conditions, while on the basolateral cell side, 23 differentially expressed miRNAs could be detected. Downstream KEGG pathway analysis predicted mTOR and MAPK signaling pathways as potential downstream targets of apically secreted miRNAs. In contrast, miRNAs specifically detected at the basolateral side were associated with processes of T and B cell receptor signaling. The study proves a compartmentalized packaging of EVs by bronchial epithelial cells supposedly associated with site-specific functions of cargo miRNAs, which are considerably affected by disease conditions such as asthma.
In the era of personalized medicine, insights into the molecular mechanisms that differentially contribute to disease phenotypes, such as asthma phenotypes including obesity-associated asthma, are urgently needed. Peripheral blood was drawn from 10 obese, non-atopic asthmatic adults with a high body mass index (BMI; 36.67 ± 6.90); 10 non-obese, non-atopic asthmatic adults with normal BMI (23.88 ± 2.73); and 10 healthy controls with normal BMI (23.62 ± 3.74). All asthmatic patients were considered to represent a low type-2 asthma phenotype according to selective clinical parameters. RNA sequencing (RNA-Seq) was conducted on peripheral blood CD4+ T cells. Thousands of differentially expressed genes were identified in both asthma groups compared with heathy controls. The expression of interferon (IFN)-stimulated genes associated with IFN-related signaling pathways was specifically affected in obese asthmatics, while the gap junction and G protein-coupled receptor (GPCR) ligand binding pathways were enriched in both asthma groups. Furthermore, obesity gene markers were also upregulated in CD4+ T cells from obese asthmatics compared with the two other groups. Additionally, the enriched genes of the three abovementioned pathways showed a unique correlation pattern with various laboratory and clinical parameters. The specific activation of IFN-related signaling and viral infection pathways might provide a novel view of the molecular mechanisms associated with the development of the low type-2 obesity-associated asthma phenotype, which is a step ahead in the development of new stratified therapeutic approaches.
Background: Increasing knowledge of cancer biology and an expanding spectrum of molecularly targeted therapies provide the basis for precision oncology. Despite extensive gene diagnostics, previous reports indicate that less than 10% of patients benefit from this concept. Methods: We retrospectively analyzed all patients referred to our center’s Molecular Tumor Board (MTB) from 2018 to 2021. Molecular testing by next-generation sequencing (NGS) included a 67-gene panel for the detection of short-sequence variants and copy-number alterations, a 53- or 137-gene fusion panel and an ultra-low-coverage whole-genome sequencing for the detection of additional copy-number alterations outside the panel’s target regions. Immunohistochemistry for microsatellite instability and PD-L1 expression complemented NGS. Results: A total of 109 patients were referred to the MTB. In all, 78 patients received therapeutic proposals (70 based on NGS) and 33 were treated accordingly. Evaluable patients treated with MTB-recommended therapy (n = 30) had significantly longer progression-free survival than patients treated with other therapies (n = 17) (4.3 vs. 1.9 months, p = 0.0094). Seven patients treated with off-label regimens experienced major clinical benefits. Conclusion: The combined focused sequencing assays detected targetable alterations in the majority of patients. Patient benefits appeared to lie in the same range as with large-scale sequencing approaches.
Bacteria acquire new traits through the uptake of genetic material from the environment, a process requiring DNA processing. However, the molecular inventory mediating this process is far from being completely understood. Here, we identify YhaM in Bacillus subtilis as a conserved 3′-deoxyribonuclease essential for the uptake and processing of genetic information in the form of single-stranded DNA. Our results show that YhaM assembles into hexamers in the presence of divalent cations, enhancing substrate binding, which is achieved through its conserved oligonucleotide-binding domain. Cells lacking YhaM show a severe defect in the uptake of plasmids and genomic DNA, but the transduction of double-stranded DNA by the phage SPP1 remains unaffected. These findings highlight a critical role of YhaM in single-stranded DNA maturation during natural transformation. Importantly, this function is conserved in various Gram-positive human pathogens such as Staphylococcus aureus, suggesting that it could contribute to the spread of antibiotic resistance.
About Me
Bioinformatician and Medical Biostatistician working with sequencing and clinical data
Bioinformatician and Medical Biostatistician working with sequencing and clinical data