High-Throughput Sequencing of Small RNAs for Diagnostics of Grapevine Viruses and Viroids in Russia

The use of high-throughput sequencing (HTS) technology has led to significant progress in the identification of many viruses and their genetic variants. In this study, we used the HTS platform to sequence small RNAs (sRNAs) of grapevine to study the virome. Isolation of RNA was performed using symptomatic grapevines collected from commercial vineyards in Krasnodar Krai in 2017–2018. To determine the viromes of vineyards, we used an integrated approach that included a bioinformatic analysis of the results of sRNA HTS and the molecular method RT-PCR, which made it possible to identify 13 viruses and 4 viroids. Grapevine leafroll-associated virus 4 (GLRaV-4), Grapevine Syrah Virus-1 (GSyV-1), Raspberry bushy dwarf virus (RBDV), Australian grapevine viroid (AGVd), and Grapevine yellow speckle viroid 2 (GYSVd-2) were identified for the first time in Russia. Out of 38 samples analyzed, 37 had mixed infections with 4–11 viruses, indicating a high viral load. Analysis of the obtained sequences of fragments of virus genomes made it possible to identify recombination events in GLRaV-1, GLRaV-2, GLRaV-3, GLRaV-4, GVT, GPGV, GRSPaV, GVA, and GFLV. The obtained results indicate a wide spread of the viruses and a high genetic diversity in the vineyards of Krasnodar Krai and emphasize the urgent need to develop and implement long-term strategies for the control of viral grapevine diseases.

Agent-based simulations for protecting nursing homes with prevention and vaccination strategies

Due to its high lethality among older people, the safety of nursing homes has been of central importance during the COVID-19 pandemic. With test procedures and vaccines becoming available at scale, nursing homes might relax prohibitory measures while controlling the spread of infections. By control we mean that each index case infects less than one other person on average. Here, we develop an agent-based epidemiological model for the spread of SARS-CoV-2 calibrated to Austrian nursing homes to identify optimal prevention strategies. We find that the effectiveness of mitigation testing depends critically on test turnover time (time until test result), the detection threshold of tests and mitigation testing frequencies. Under realistic conditions and in absence of vaccinations, we find that mitigation testing of employees only might be sufficient to control outbreaks if tests have low turnover times and detection thresholds. If vaccines that are 60% effective against high viral load and transmission are available, control is achieved if 80% or more of the residents are vaccinated, even without mitigation testing and if residents are allowed to have visitors. Since these results strongly depend on vaccine efficacy against infection, retention of testing infrastructures, regular testing and sequencing of virus genomes is advised to enable early identification of new variants of concern.

Simplified, Shear Induced Generation of Double Emulsions for Robust Compartmentalization during Single Genome Analysis

Drop microfluidics has driven innovations for high throughput, low input analysis techniques such as single-cell RNA-seq. However, the instability of single emulsion (SE) drops occasionally causes significant merging during drop processing, limiting most applications to single-step reactions in drops. Here, we show that double emulsion (DE) drops address this critical limitation and completely prevent content mixing, which is essential for single entity analysis. DEs show excellent stability during thermal cycling. More importantly, DEs undergo rupture into the continuous phase instead of merging, preventing content mixing and eliminating unstable drops from the downstream analysis. Due to the lack of drop merging, the monodispersity of drops is maintained throughout a workflow, enabling the deterministic manipulation of drops downstream. We also developed a simple, one-layer fabrication method for DE drop makers. This design is powerful as it allows robust production of single-core DEs at a wide range of flow rates and better control over the shell thickness, both of which have been significant limitations of conventional two-layer devices. This approach makes the fabrication of DE devices much more accessible, facilitating its broader adoption. Finally, we show that DE droplets effectively maintain the compartmentalization of single virus genomes during PCR-based amplification and barcoding, while SEs mixed contents due to merging. With their resistance to content mixing, DE drops have key advantages for multistep reactions in drops, which is limited in SEs due to merging and content mixing.

Estimated quantity of swine virus genomes based on quantitative PCR analysis in spray-dried porcine plasma samples collected from multiple manufacturing plants.

This survey was conducted to estimate the incidence and level of potential viral contamination in commercially collected porcine plasma. Samples of spray dried porcine plasma (SDPP) were collected over a 12- month period from eight spray drying facilities in Spain, England, Northern Ireland, Brazil, Canada, and the United States. In this survey, viral load for several porcine pathogens including SVA, TGEV, PRRSV (EU and US strains), PEDV, PCV2, SIV, SDCoV and PPV were determined by qPCR. Regression of Ct on TCID50 of serial diluted stock solution of each virus allowed the estimate of potential viral level in SDPP and unprocessed liquid plasma (using typical solids content of commercially collected porcine plasma). In this survey SVA, TGEV or SDCoV were not detected in any of the SDPP samples. Brazil SDPP samples were free of PRRSV and PEDV. Samples of SDPP from North America primarily contained the PRRSV-US strain while the European samples contained the PRRSV-EU strain (except for one sample from each region containing a low estimated level of the alternative PRRSV strain). Estimated viral level tended to be low ranging from <1.0 log 10 TCID 50 to <2.5 log 10 TCID 50 . Estimated level of SIV was the exception with a very low incidence rate but higher estimated viral load <3.9 log 10 TCID 50 . In summary, the incidence of potential viral contamination in commercially collected porcine plasma was variable and estimated virus level in samples containing viral DNA/RNA was low.

Taxonomy-aware, sequence similarity ranking reliably predicts phage–host relationships

Background Characterizing phage–host interactions is critical to understanding the ecological role of both partners and effective isolation of phage therapeuticals. Unfortunately, experimental methods for studying these interactions are markedly slow, low-throughput, and unsuitable for phages or hosts difficult to maintain in laboratory conditions. Therefore, a number of in silico methods emerged to predict prokaryotic hosts based on viral sequences. One of the leading approaches is the application of the BLAST tool that searches for local similarities between viral and microbial genomes. However, this prediction method has three major limitations: (i) top-scoring sequences do not always point to the actual host; (ii) mosaic virus genomes may match to many, typically related, bacteria; and (iii) viral and host sequences may diverge beyond the point where their relationship can be detected by a BLAST alignment. Results We created an extension to BLAST, named Phirbo, that improves host prediction quality beyond what is obtainable from standard BLAST searches. The tool harnesses information concerning sequence similarity and bacteria relatedness to predict phage–host interactions. Phirbo was evaluated on three benchmark sets of known virus–host pairs, and it improved precision and recall by 11–40 percentage points over currently available, state-of-the-art, alignment-based, alignment-free, and machine-learning host prediction tools. Moreover, the discriminatory power of Phirbo for the recognition of virus–host relationships surpassed the results of other tools by at least 10 percentage points (area under the curve = 0.95), yielding a mean host prediction accuracy of 57% and 68% at the genus and family levels, respectively, and drops by 12 percentage points when using only a fraction of viral genome sequences (3 kb). Finally, we provide insights into a repertoire of protein and ncRNA genes that are shared between phages and hosts and may be prone to horizontal transfer during infection. Conclusions Our results suggest that Phirbo is a simple and effective tool for predicting phage–host relationships.