Uncovering hidden genetic variations: long-read sequencing reveals new insights into tuberous sclerosis complex.

Background: Tuberous sclerosis is a multi-system disorder caused by mutations in either TSC1 or TSC2. The majority of affected patients (85%-90%) have heterozygous variants, and a smaller number (around 5%) have mosaic variants. Despite using various techniques, some patients still have "no mutation identified" (NMI). Methods: We hypothesized that the causal variants of patients with NMI may be structural variants or deep intronic variants. To investigate this, we sequenced the DNA of 26 tuberous sclerosis patients with NMI using targeted long-read sequencing. Results: We identified likely pathogenic/pathogenic variants in 13 of the cases, of which 6 were large deletions, four were InDels, two were deep intronic variants, one had retrotransposon insertion in either TSC1 or TSC2, and one was complex rearrangement. Furthermore, there was a de novo Alu element insertion with a high suspicion of pathogenicity that was classified as a variant of unknown significance. Conclusion: Our findings expand the current knowledge of known pathogenic variants related to tuberous sclerosis, particularly uncovering mosaic complex structural variations and retrotransposon insertions that have not been previously reported in tuberous sclerosis. Our findings suggest a higher prevalence of mosaicism among tuberous sclerosis patients than previously recognized. Our results indicate that long-read sequencing is a valuable approach for tuberous sclerosis cases with no mutation identified (NMI).

Effectiveness of containment strategies in preventing SARS-CoV-2 transmission.

BACKGROUND: Despite substantial resources deployed to curb SARS-CoV-2 transmission, controlling the COVID-19 pandemic has been a major challenge. New variants of the virus are frequently emerging leading to new waves of infection and re-introduction of control measures. In this study, we assessed the effectiveness of containment strategies implemented in the early phase of the pandemic. METHODS: Real-world data for COVID-19 cases was retrieved for the period Jan 1 to May 1, 2020 from a number of different sources, including PubMed, MEDLINE, Facebook, Epidemic Forecasting and Google Mobility Reports. We analyzed data for 18 countries/regions that deployed containment strategies such as travel restrictions, lockdowns, stay-at-home requests, school/public events closure, social distancing, and exposure history information management (digital contact tracing, DCT). Primary outcome measure was the change in the number of new cases over 30 days before and after deployment of a control measure. We also compared the effectiveness of centralized versus decentralized DCT. Time series data for COVID-19 were analyzed using Mann-Kendall (M-K) trend tests to investigate the impact of these measures on changes in the number of new cases. The rate of change in the number of new cases was compared using M-K z-values and Sen's slope. RESULTS: In spite of the widespread implementation of conventional strategies such as lockdowns, travel restrictions, social distancing, school closures, and stay-at-home requests, analysis revealed that these measures could not prevent the spread of the virus. However, countries which adopted DCT with centralized data storage were more likely to contain the spread. CONCLUSIONS: Centralized DCT was more effective in containing the spread of COVID-19. Early implementation of centralized DCT should be considered in future outbreaks. However, challenges such as public acceptance, data security and privacy concerns will need to be addressed.

Correction to: Involvement of gut microbiome in human health and disease: brief overview, knowledge gaps and research opportunities.

[This corrects the article DOI: 10.1186/s13099-018-0230-4.].

Involvement of gut microbiome in human health and disease: brief overview, knowledge gaps and research opportunities.

The commensal, symbiotic, and pathogenic microbial community which resides inside our body and on our skin (the human microbiome) can perturb host energy metabolism and immunity, and thus significantly influence development of a variety of human diseases. Therefore, the field has attracted unprecedented attention in the last decade. Although a large amount of data has been generated, there are still many unanswered questions and no universal agreements on how microbiome affects human health have been agreed upon. Consequently, this review was written to provide an updated overview of the rapidly expanding field, with a focus on revealing knowledge gaps and research opportunities. Specifically, the review covered animal physiology, optimal microbiome standard, health intervention by manipulating microbiome, knowledge base building by text mining, microbiota community structure and its implications in human diseases and health monitoring by analyzing microbiome in the blood. The review should enhance interest in conducting novel microbiota investigations that will further improve health and therapy.

Insights into intercontinental spread of Zika virus.

The epidemic of Zika virus (ZIKV) infection in South America has led to World Health Organization's declaration of a Public Health Emergency of International Concern. To further inform effective public health policy, an understanding of ZIKV's transmission mechanisms is crucial. To characterize the intercontinental transmission of ZIKV, we compiled and analyzed more than 250 gene sequences together with their sequence-related geographic and temporal information, sampled across 27 countries spanning from 1947 to 2016. After filtering and selecting appropriate sequences, extensive phylogenetic analyses were performed. Although phylogeographic reconstruction supported the transmission route of the virus in Africa, South-eastern Asia, Oceania and Latin America, we discovered that the Eastern Africa origin of ZIKV was disputable. On a molecular level, purifying selection was found to be largely responsible for the evolution of non-structural protein 5 and envelope protein E. Our dataset and ancestral sequences reconstruction analysis captured previously unidentified amino acid changes during evolution. Finally, based on the estimation of the time to the most recent common ancestors for the non-structural protein 5 gene, we hypothesized potential specific historic events that occurred in the 1940s and might have facilitated the spread of Zika virus from Africa to South-eastern Asia. Our findings provide new insights into the transmission characteristics of ZIKV, while further genetic and serologic studies are warranted to support the design of tailored prevention strategies.