A Genetic Barcode Approach to Elucidate the Mechanisms of Polyomavirus Persistent Infection in vivo

Human polyomaviruses are highly prevalent in the general population and establish a long-term asymptomatic infection in healthy individuals. However, a change in the immune status or hormone levels can lead to life-threatening diseases, including tumors. These diseases typically require reactivation from a persistent infection. Currently, a long-standing question in the field of virology is understanding how polyomaviruses undergo a life-long persistent infection in their natural host. Indeed, despite the high seroprevalence of polyomaviruses, little is understood about the mechanisms allowing the establishment, maintenance or reactivation from a long-term persistent infection. The objective of my PhD thesis was to demonstrate whether polyomaviruses undergo a “smoldering” infection, as commonly suggested in literature, or a cryptic true latency, akin to Herpesviruses. In order to solve this enigma, I engineered an innovative genetic barcoded murine polyomavirus to tract single genomes in vivo and to define the early and late genes expression patterns associated to each genome involved in the persistent infection. This barcoded virus approach combined with a non-invasive urine-monitoring system that allows the longitudinal study of PyV persistence, will consent to elucidate for the first time the mode of polyomavirus persistence in vivo using a limited number of mice. Deciphering the mechanisms of persistence may lead to new therapies and preventive strategies against serious Human diseases

Cross sectional evaluation of the gut-microbiome metabolome axis in an Italian cohort of IBD patients.

Inflammatory bowel disease (IBD) is a chronic inflammatory disease of the gastrointestinal tract of uncertain origin, which includes ulcerative colitis (UC) and Crohn's disease (CD). The composition of gut microbiota may change in IBD affected individuals, but whether dysbiosis is the cause or the consequence of inflammatory processes in the intestinal tissue is still unclear. Here, the composition of the microbiota and the metabolites in stool of 183 subjects (82 UC, 50 CD, and 51 healthy controls) were determined. The metabolites content and the microbiological profiles were significantly different between IBD and healthy subjects. In the IBD group, Firmicutes, Proteobacteria, Verrucomicrobia, and Fusobacteria were significantly increased, whereas Bacteroidetes and Cyanobacteria were decreased. At genus level Escherichia, Faecalibacterium, Streptococcus, Sutterella and Veillonella were increased, whereas Bacteroides, Flavobacterium, and Oscillospira decreased. Various metabolites including biogenic amines, amino acids, lipids, were significantly increased in IBD, while others, such as two B group vitamins, were decreased in IBD compared to healthy subjects. This study underlines the potential role of an inter-omics approach in understanding the metabolic pathways involved in IBD. The combined evaluation of metabolites and fecal microbiome can be useful to discriminate between healthy subjects and patients with IBD

Global impact of Torque teno virus infection in wild and domesticated animals

Infection with Torque teno viruses (TTVs) is not restricted to humans. Different domestic and wild animal species are naturally infected with species-specific TTVs worldwide. Due to the global spread of the infection, it is likely that essentially all animals are naturally infected with species-specific TTVs, and that co-evolution of TTVs with their hosts probably occurred. Although TTVs are potentially related to many diseases, the evidence of the widespread infection in healthy human and nonhuman hosts raised doubts about their pathogenic potential. Nonetheless, their role as superimposed agents of other diseases or as triggers for impairment of immune surveillance is currently under debate. The possible contribution of animal TT viruses to interspecies transmission and their role as zoonotic agents are currently topics of discussion

Interpreting and de-noising genetically engineered barcodes in a DNA virus.

The concept of a nucleic acid barcode applied to pathogen genomes is easy to grasp and the many possible uses are straightforward. But implementation may not be easy, especially when growing through multiple generations or assaying the pathogen long-term. The potential problems include: the barcode might alter fitness, the barcode may accumulate mutations, and construction of the marked pathogens may result in unintended barcodes that are not as designed. Here, we generate approximately 5,000 randomized barcodes in the genome of the prototypic small DNA virus murine polyomavirus. We describe the challenges faced with interpreting the barcode sequences obtained from the library. Our Illumina NextSeq sequencing recalled much greater variation in barcode sequencing reads than the expected 5,000 barcodes-necessarily stemming from the Illumina library processing and sequencing error. Using data from defined control virus genomes cloned into plasmid backbones we develop a vetted post-sequencing method to cluster the erroneous reads around the true virus genome barcodes. These findings may foreshadow problems with randomized barcodes in other microbial systems and provide a useful approach for future work utilizing nucleic acid barcoded pathogens

Percent of erroneous barcodes in Illumina sequencing reads of single-plasmid controls: original (raw), quality thresholds for any base with two thresholds, and clustering with different Levenshtein distances applied.

Percent of erroneous barcodes in Illumina sequencing reads of single-plasmid controls: original (raw), quality thresholds for any base with two thresholds, and clustering with different Levenshtein distances applied.</p

Linearity plots of 10-plasmid controls with L3 clustering parameter.

The log10 transformed x-axis shows the copy number of plasmid inputs, the log10 transformed y-axis represents L3 clustered read counts. Linear regression trendlines are plotted in gray, with corresponding R2 values. Linearity of the 10-plasmid control series 10P-A and 10P-G is shown (the linearity of additional 10-plasmid controls is shown in S6 Fig).</p

Illumina sequencing reads from 10-plasmid controls using different clustering distances.

The y-axis depicts the barcode sequence; the x-axis shows the square root-transformed percentage of total read counts. The colored bars represent the control barcodes. Gray bars represent the most common erroneous barcodes within a library. The plots compare the raw percentages (no clustering) with clustering using Starcode’s message-passing algorithm, and L = 1, L = 2, and L = 3 distance parameters. Here we show the 10-plasmid controls 10P-A, 10P-D and 10P-G. Additional 10-plasmid controls are shown in S4 Fig.</p

10-plasmid controls preparation.

10-plasmid controls preparation.</p