DataSheet_1_Primary Peripheral Epstein-Barr Virus Infection Can Lead to CNS Infection and Neuroinflammation in a Rabbit Model: Implications for Multiple Sclerosis Pathogenesis.pdf

Epstein-Barr virus (EBV) is a common herpesvirus associated with malignant and non-malignant conditions. An accumulating body of evidence supports a role for EBV in the pathogenesis of multiple sclerosis (MS), a demyelinating disease of the CNS. However, little is known about the details of the link between EBV and MS. One obstacle which has hindered research in this area has been the lack of a suitable animal model recapitulating natural infection in humans. We have recently shown that healthy rabbits are susceptible to EBV infection, and viral persistence in these animals mimics latent infection in humans. We used the rabbit model to investigate if peripheral EBV infection can lead to infection of the CNS and its potential consequences. We injected EBV intravenously in one group of animals, and phosphate-buffered saline (PBS) in another, with and without immunosuppression. Histopathological changes and viral dynamics were examined in peripheral blood, spleen, brain, and spinal cord, using a range of molecular and histopathology techniques. Our investigations uncovered important findings that could not be previously addressed. We showed that primary peripheral EBV infection can lead to the virus traversing the CNS. Cell associated, but not free virus in the plasma, correlated with CNS infection. The infected cells within the brain were found to be B-lymphocytes. Most notably, animals injected with EBV, but not PBS, developed inflammatory cellular aggregates in the CNS. The incidence of these aggregates increased in the immunosuppressed animals. The cellular aggregates contained compact clusters of macrophages surrounded by reactive astrocytes and dispersed B and T lymphocytes, but not myelinated nerve fibers. Moreover, studying EBV infection over a span of 28 days, revealed that the peak point for viral load in the periphery and CNS coincides with increased occurrence of cellular aggregates in the brain. Finally, peripheral EBV infection triggered temporal changes in the expression of latent viral transcripts and cytokines in the brain. The present study provides the first direct in vivo evidence for the role of peripheral EBV infection in CNS pathology, and highlights a unique model to dissect viral mechanisms contributing to the development of MS.</p

Detection of EBERs and EBER binding protein La in exosomal fractions.

<p>(A) RNase A treatment of purified exosomes prior to RNA extraction and RT-PCR did not abolish EBER amplification signal, suggesting that EBERs are present in exosomes and not in the extra-exosomal fraction. (B) To determine if the EBER-1 binding protein La was present in exosomes, 25 µg of exosomal protein fraction was separated by 10% SDS PAGE and immunoblotted using anti-La monoclonal antibodies. Exosomal fractions from all cell lines clearly showed presence of La protein, irrespective of whether they were EBV infected or not.</p

Reverse transcriptase PCR for EBERs on exosomal RNA.

<p>RT-PCR for (A) EBER-1 and (B) EBER-2 on the purified exosomes from EBV-positive and negative cells, gave positive amplification only in EBV infected cell lines. EBER-1 stably transfected 293T cells (293T-pHEBo-E1) were also positive for EBER-1, but the amplification signal was weaker than that seen with EBV-infected cell lines. (C) DNase treated RNA samples prior to reverse transcription consistently gave negative results, indicating that the amplification signals seen in Figure A and B were not due to DNA contamination (results shown for EBER-1 only). Positive (+) (EBER-1 or EBER-2 plasmid DNA) and negative (−) (sterile water) controls are indicated.</p

Reverse transcriptase PCR for EBERs on genomic RNA.

<p>RT- PCR was carried out on genomic RNA extracted from three EBV positive cell lines (B95-8, EBV-LCL and BL30-B95-8), 293T cells stably transfected with EBER-1 plasmid (293T-pHEBo-E1), and two EBV negative cell lines (BL30 and 293T stably cells transfected with empty plasmid (293T-pHEBo)). cDNA from these cells was subjected to 30 rounds of PCR amplification for (A) EBER-1 and (B) EBER-2 and the amplified products were visualized on a 2% agarose gel. Positive (+) (EBER-1 or EBER-2 plasmid DNA) and negative (−) (sterile water) controls are indicated. All three EBV positive cell lines showed specific amplification of EBER-1 and EBER-2. BL30 and 293T-pHEBo cells were clearly negative. Furthermore, EBER-1 specific amplification was also seen in EBER-1 transfected 293T-pHEBo-E1 cells. (C) To ensure that the EBER-amplification seen in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0099163#pone-0099163-g001" target="_blank">Figure 1A and 1B</a> was not due to EBV DNA contamination, PCR was performed for EBER-1 and EBER-2 on DNase treated RNA samples prior to reverse transcription. No amplification was seen, clearly indicating the absence of any contaminating DNA (results shown for EBER-1 only).</p

Reverse transcriptase PCR for EBERs on culture supernatants.

<p>RNA was extracted from 1-PCR was carried out on RNA extracted from culture supernatant of EBV positive cell lines (EBV-LCL, B95-8), 293T cells stably transfected with EBER-1 (293T-pHEBo-E1) and two EBV negative cell lines (BL30 and 293T cells stably transfected with empty plasmid (293T-pHEBo)). cDNA was subjected to 30 rounds of PCR amplification for (A) EBER-1 and (B) EBER-2. Positive (+) (EBER-1 or EBER-2 plasmid DNA) and negative (−) (sterile water) controls are indicated. Both EBER-1 and EBER-2 were amplified from EBV positive cell lines (B95-8 and EBV-LCL) whilst the EBV negative cell lines BL30 and 293T-pHEBo were negative. EBER-1 transfected 293T-pHEBo-E1 also showed specific amplification.</p

Transmission electron microscopy and western blot for CD63 on exosomal fractions.

<p>Exosomes were isolated using differential ultracentrifugation and examined using transmission electron microscopy. (A) Nanovesicles with typical size (50–120 nm) and morphology resembling exosomes were observed in isolates from both EBV positive (EBV-LCL) and negative (293T) cells. (B) Western blotting for the exosomal marker CD63, confirmed the identity of these nanovesicles to be exosomes.</p

Epstein-Barr Virus-Encoded Small RNAs (EBERs) Are Present in Fractions Related to Exosomes Released by EBV-Transformed Cells

<div><p>Epstein-Barr virus (EBV) is an oncogenic herpesvirus associated with a number of human malignancies of epithelial and lymphoid origin. However, the mechanism of oncogenesis is unclear. A number of viral products, including EBV latent proteins and non-protein coding RNAs have been implicated. Recently it was reported that EBV-encoded small RNAs (EBERs) are released from EBV infected cells and they can induce biological changes in cells via signaling from toll-like receptor 3. Here, we investigated if these abundantly expressed non-protein coding EBV RNAs (EBER-1 and EBER-2) are excreted from infected cells in exosomal fractions. Using differential ultracentrifugation we isolated exosomes from three EBV positive cell lines (B95-8, EBV-LCL, BL30-B95-8), one EBER-1 transfected cell line (293T-pHEBo-E1) and two EBV-negative cell lines (BL30, 293T-pHEBo). The identity of purified exosomes was determined by electron microscopy and western blotting for CD63. The presence of EBERs in cells, culture supernatants and purified exosomal fractions was determined using RT-PCR and confirmed by sequencing. Purified exosomal fractions were also tested for the presence of the EBER-1-binding protein La, using western blotting. Both EBER-1 and EBER-2 were found to be present not only in the culture supernatants, but also in the purified exosome fractions of all EBV-infected cell lines. EBER-1 could also be detected in exosomal fractions from EBER-1 transfected 293T cells whilst the fractions from vector only transfectants were clearly negative. Furthermore, purified exosomal fractions also contained the EBER-binding protein (La), supporting the notion that EBERs are most probably released from EBV infected cells in the form of EBER-La complex in exosomes.</p></div

DataSheet_1_Complete genome sequence of Vibrio gazogenes PB1: an estuarine bacterium capable of producing prodigiosin from starch or cellulose.pdf

Vibrio is a genus of gram-negative, rod-shaped, motile bacteria commonly found in saltwater. One species in particular, Vibrio gazogenes PB1, sourced from an estuarine environment, is known to produce the secondary metabolite, prodigiosin. This high-value compound has potential uses as an antibiotic, a fungicide, and an anti-cancer agent. To further explore its metabolic and genetic features for biotechnological purposes, the complete genome sequence of V. gazogenes PB1 was determined by Illumina and Pacbio sequencing. Two chromosomes were assembled with a mean coverage of 293x. Chromosome 1 is 3.5 Mbp in size with 45.3% GC content and chromosome 2 is 1.2 Mbp in size with 45.1% GC content. The entire genome harbours 4178 genes, of which 3988 are protein-coding and 114 are RNA-coding. A total of 55 virulence-related genes, 38 antimicrobial resistance genes, 48 transposase sequences, 2 intact prophage regions, and 10 genomic islands were present within the genome. Six genes associated with the degradation of cellulose and starch were also identified within the genome. Four of them were strongly up-regulated, as confirmed by RT-qPCR, thus providing strong evidence for their involvement in starch and cellulose degradation. Quite importantly, we demonstrate for the first time that starch and cellulose is associated with the synthesis of prodigiosin in a native prodigiosin-producing bacterium. The prodigiosin titres obtained in the presence of cellulose were on par with glucose as the carbon source which lends further support in the use of V. gazogenes PB1 as a biotechnological host for prodigiosin production.</p

A simulated measurement for COVID-19 pandemic using the effective reproductive number on an empirical portion of population: Epidemiological models

COVID-19 as a global pandemic has had an unprecedented impact on the entire world. Projecting the future spread of the virus in relation to its characteristics for a specific suite of countries against a temporal trend can provide public health guidance to governments and organizations. Therefore, this paper presented an epidemiological comparison of the traditional SEIR model with an extended and modified version of the same model by splitting the infected compartment into asymptomatic mild and symptomatic severe. We then exposed our derived layered model into two distinct case studies with variations in mitigation strategies and non-pharmaceutical interventions (NPIs) as a matter of benchmarking and comparison. We focused on exploring the United Arab Emirates (a small yet urban centre (where clear sequential stages NPIs were implemented). Further, we concentrated on extending the models by utilizing the effective reproductive number (Rt) estimated against time, a more realistic than the static R0, to assess the potential impact of NPIs within each case study. Compared to the traditional SEIR model, the results supported the modified model as being more sensitive in terms of peaks of simulated cases and flattening determinations

Additional file 3 of Mapping age- and sex-specific HIV prevalence in adults in sub-Saharan Africa, 2000–2018

Additional file 3: Supplemental figures.Figure S1. Prevalence of male circumcision. Figure S2. Prevalence of signs and symptoms of sexually transmitted infections. Figure S3. Prevalence of marriage or living as married. Figure S4. Prevalence of partner living elsewhere among females. Figure S5. Prevalence of condom use during most recent sexual encounter. Figure S6. Prevalence of sexual activity among young females. Figure S7. Prevalence of multiple partners among males in the past year. Figure S8. Prevalence of multiple partners among females in the past year. Figure S9. HIV prevalence predictions from the boosted regression tree model. Figure S10. HIV prevalence predictions from the generalized additive model. Figure S11. HIV prevalence predictions from the lasso regression model. Figure S12. Modeling regions. Figure S13. Age- and sex-specific vs. adult prevalence modeling. Figure S14. Data sensitivity. Figure S15. Model specification validation. Figure S16. Modeled and re-aggregated adult prevalence comparison. Figure S17. HIV prevalence raking factors for males. Figure S18. HIV prevalence raking factors for females. Figure S19. Age-specific HIV prevalence in males, 2000. Figure S20. Age-specific HIV prevalence in females, 2000. Figure S21. Age-specific HIV prevalence in males, 2005. Figure S22. Age-specific HIV prevalence in females, 2005. Figure S23. Age-specific HIV prevalence in males, 2010. Figure S24. Age-specific HIV prevalence in females, 2010. Figure S25. Age-specific HIV prevalence in males, 2018. Figure S26. Age-specific HIV prevalence in females, 2018. Figure S27. Age-specific uncertainty interval range estimates in males, 2000. Figure S28. Age-specific uncertainty interval range estimates in females, 2000. Figure S29. Age-specific uncertainty interval range estimates in males, 2005. Figure S30. Age-specific uncertainty interval range estimates in females, 2005. Figure S31. Age-specific uncertainty interval range estimates in males, 2010. Figure S32. Age-specific uncertainty interval range estimates in females, 2010. Figure S33. Age-specific uncertainty interval range estimates in males, 2018. Figure S34. Age-specific uncertainty interval range estimates in females, 2018. Figure S35. Change in HIV prevalence in males, 2000-2005. Figure S36. Change in HIV prevalence in females, 2000-2005. Figure S37. Change in HIV prevalence in males, 2005-2010. Figure S38. Change in HIV prevalence in females, 2005-2010. Figure S39. Change in HIV prevalence in males, 2010-2018. Figure S40. Change in HIV prevalence in females, 2010-2018. Figure S41. Space mesh for geostatistical models