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Biology subjects

Venturi, V.

Publications and source records attributed to Venturi, V..

3 recordsLinked to original sources

Molecularly barcoded Zika virus libraries to probe in vivo evolutionary dynamics

Defining the complex dynamics of Zika virus (ZIKV) infection in pregnancy and during transmission between vertebrate hosts and mosquito vectors is critical for a thorough understanding of viral transmission, pathogenesis, immune evasion, and potential reservoir establishment. Within-host viral diversity in ZIKV infection is low, which makes it difficult to evaluate infection dynamics. To overcome this biological hurdle, we constructed a molecularly barcoded ZIKV. This virus stock consists of a \"synthetic swarm\" whose members are genetically identical except for a run of eight consecutive degenerate codons, which creates approximately 64,000 theoretical nucleotide combinations that all encode the same amino acids. Deep sequencing this region of the ZIKV genome enables counting of individual barcode clonotypes to quantify the number and relative proportions of viral lineages present within a host. Here we used these molecularly barcoded ZIKV variants to study the dynamics of ZIKV infection in pregnant and non-pregnant macaques as well as during mosquito infection/transmission. The barcoded virus had no discernible fitness defects in vivo, and the proportions of individual barcoded virus templates remained stable throughout the duration of acute plasma viremia. ZIKV RNA also was detected in maternal plasma from a pregnant animal infected with barcoded virus for 64 days. The complexity of the virus population declined precipitously 8 days following infection of the dam, consistent with the timing of typical resolution of ZIKV in non-pregnant macaques, and remained low for the subsequent duration of viremia. Our approach showed that synthetic swarm viruses can be used to probe the composition of ZIKV populations over time in vivo to understand vertical transmission, persistent reservoirs, bottlenecks, and evolutionary dynamics.\n\nAuthor summaryUnderstanding the complex dynamics of Zika virus (ZIKV) infection during pregnancy and during transmission to and from vertebrate host and mosquito vector is critical for a thorough understanding of viral transmission, pathogenesis, immune evasion, and reservoir establishment. We sought to develop a virus model system for use in nonhuman primates and mosquitoes that allows for the genetic discrimination of molecularly cloned viruses. This \"synthetic swarm\" of viruses incorporates a molecular barcode that allows for tracking and monitoring individual viral lineages during infection. Here we infected rhesus macaques with this virus to study the dynamics of ZIKV infection in nonhuman primates as well as during mosquito infection/transmission. We found that the proportions of individual barcoded viruses remained relatively stable during acute infection in pregnant and nonpregnant animals. However, in a pregnant animal, the complexity of the virus population declined precipitously 8 days following infection, consistent with the timing of typical resolution of ZIKV in non-pregnant macaques, and remained low for the subsequent duration of viremia.

microbiology

The spent culture supernatant of Pseudomonas syringae contains azelaic acid

Pseudomonas syringae pv. actinidiae (PSA) is an emerging kiwifruit bacterial pathogen which since 2008 has caused considerable losses. No quorum sensing (QS) signaling molecule has yet been reported from PSA and the aim of this study was to identify possible intercellular signals produced by PSA. A metabolome analysis resulted in the identification of 83 putative compounds, one of them was the nine carbon saturated dicarboxylic acid azelaic acid which for several reasons was decided to further study. Firstly azelaic acid, which is a straight chained nine-carbon (C9) saturated dicarboxylic acid, has been reported in plants as mobile signal that primes systemic defenses. Secondly its structure, which is associated with fatty acid biosynthesis, is similar to other known bacterial QS signals like the Diffusible Signal Facor (DSF). Analytical and structural studies by NMR spectroscopy confirmed that in the PSA spent supernatant azelaic acid was present. Quantification studies further revealed that 20 {micro}g/L of azelaic acid was present and was also found in spent supernatants of several other P. syringae pathovars. An RNAseq transcriptome study however did not reveal whether azelaic acid behaved as a QS molecule. This is the first report of the possible natural biosynthesis of azelaic acid by bacteria.

microbiology

Impact Of Sequencing Depth And Read Length On Single Cell RNA Sequencing Data: Lessons From T Cells

Single cell RNA sequencing (scRNA-seq) has shown great potential in measuring the gene expression profiles of heterogeneous cell populations. In immunology, scRNA-seq allowed the characterisation of transcript sequence diversity of functionally relevant sub-populations of T cells, and notably the identification of the full length T cell receptor (TCR{beta}), which defines the specificity against cognate antigens. Several factors, such as RNA library capture, cell quality, and sequencing output have been suggested to affect the quality of scRNA-seq data, but these factors have not been systematically examined.\n\nWe studied the effect of read length and sequencing depth on the quality of gene expression profiles, cell type identification, and TCR{beta} reconstruction, utilising 1,305 publically available scRNA-seq datasets, and simulation-based analyses. Gene expression was characterised by an increased number of unique genes identified with short read lengths (<50 bp), but these featured higher technical variability compared to profiles from longer reads. TCR{beta} were detected in 1,027 cells (79%), with a success rate between 81% and 100% for datasets with at least 250,000 (PE) reads of length >50 bp.\n\nSufficient read length and sequencing depth can control technical noise to enable accurate identification of TCR{beta} and gene expression profiles from scRNA-seq data of T cells.

bioinformatics