Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2.

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

MicrobeTrace: Retooling molecular epidemiology for rapid public health response.

Outbreak investigations use data from interviews, healthcare providers, laboratories and surveillance systems. However, integrated use of data from multiple sources requires a patchwork of software that present challenges in usability, interoperability, confidentiality, and cost. Rapid integration, visualization and analysis of data from multiple sources can guide effective public health interventions. We developed MicrobeTrace to facilitate rapid public health responses by overcoming barriers to data integration and exploration in molecular epidemiology. MicrobeTrace is a web-based, client-side, JavaScript application (https://microbetrace.cdc.gov) that runs in Chromium-based browsers and remains fully operational without an internet connection. Using publicly available data, we demonstrate the analysis of viral genetic distance networks and introduce a novel approach to minimum spanning trees that simplifies results. We also illustrate the potential utility of MicrobeTrace in support of contact tracing by analyzing and displaying data from an outbreak of SARS-CoV-2 in South Korea in early 2020. MicrobeTrace is developed and actively maintained by the Centers for Disease Control and Prevention. Users can email microbetrace@cdc.gov for support. The source code is available at https://github.com/cdcgov/microbetrace.

The next phase of SARS-CoV-2 surveillance: real-time molecular epidemiology.

The current coronavirus disease 2019 (COVID-19) pandemic is the first to apply whole-genome sequencing near to real time, with over 2 million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) whole-genome sequences generated and shared through the GISAID platform. This genomic resource informed public health decision-making throughout the pandemic; it also allowed detection of mutations that might affect virulence, pathogenesis, host range or immune escape as well as the effectiveness of SARS-CoV-2 diagnostics and therapeutics. However, genotype-to-phenotype predictions cannot be performed at the rapid pace of genomic sequencing. To prepare for the next phase of the pandemic, a systematic approach is needed to link global genomic surveillance and timely assessment of the phenotypic characteristics of novel variants, which will support the development and updating of diagnostics, vaccines, therapeutics and nonpharmaceutical interventions. This Review summarizes the current knowledge on key viral mutations and variants and looks to the next phase of surveillance of the evolving pandemic.

Next-Generation Sequencing (NGS) in COVID-19: A Tool for SARS-CoV-2 Diagnosis, Monitoring New Strains and Phylodynamic Modeling in Molecular Epidemiology.

This review discusses the current testing methodologies for COVID-19 diagnosis and explores next-generation sequencing (NGS) technology for the detection of SARS-CoV-2 and monitoring phylogenetic evolution in the current COVID-19 pandemic. The review addresses the development, fundamentals, assay quality control and bioinformatics processing of the NGS data. This article provides a comprehensive review of the obstacles and opportunities facing the application of NGS technologies for the diagnosis, surveillance, and study of SARS-CoV-2 and other infectious diseases. Further, we have contemplated the opportunities and challenges inherent in the adoption of NGS technology as a diagnostic test with real-world examples of its utility in the fight against COVID-19.

SARS-CoV-2 sequencing: The technological initiative to strengthen early warning systems for public health emergencies in Latin America and the Caribbean / [Secuenciación del SARS-CoV-2: la iniciativa tecnológica para fortalecer los sistemas de alerta temprana ante emergencias de salud pública en Latinoamérica y el Caribe].

The COVID-19 pandemic caused by SARS-CoV-2 is a public health problem on a scale unprecedented in the last 100 years, as has been the response focused on the rapid genomic characterization of SARS-CoV-2 in virtually all regions of the planet. This pandemic emerged during the era of genomic epidemiology, a science fueled by continued advances in next-generation sequencing. Since its recent appearance, genomic epidemiology included the precise identification of new lineages or species of pathogens and the reconstruction of their genetic variability in real time, evidenced in past outbreaks of influenza H1N1, MERS, and SARS. However, the global and uncontrolled scale of this pandemic created a scenario where genomic epidemiology was put into practice en masse, from the rapid identification of SARS-CoV-2 to the registration of new lineages and their active surveillance throughout the world. Prior to the COVID-19 pandemic, the availability of genomic data on circulating pathogens in several Latin America and the Caribbean countries was scarce or nil. With the arrival of SARS-CoV-2, this scenario changed significantly, although the amount of available information remains scarce and, in countries such as Colombia, Brazil, Argentina, and Chile, the genomic information of SARS-CoV-2 was obtained mainly by research groups in genomic epidemiology rather than the product of a public health surveillance policy or program. This indicates the need to establish public health policies aimed at implementing genomic epidemiology as a tool to strengthen surveillance and early warning systems against threats to public health in the region.

La pandemia de COVID-19 causada por el SARS-CoV-2 es un problema de salud pública sin precedentes en los últimos 100 años, así como la respuesta centrada en la caracterización genómica del SARS-CoV-2 prácticamente en todas las regiones del planeta. Esta pandemia surgió durante la era de la epidemiología genómica impulsada por los continuos avances en la secuenciación de próxima generación. Desde su reciente aparición, la epidemiología genómica permitió la identificación precisa de nuevos linajes o especies de agentes patógenos y la reconstrucción de su variabilidad genética en tiempo real, lo que se hizo evidente en los brotes de influenza H1N1, MERS y SARS. Sin embargo, la escala global y descontrolada de esta pandemia ha generado una situación que obligó a utilizar de forma masiva herramientas de la epidemiología genómica como la rápida identificación del SARS-CoV-2 y el registro de nuevos linajes y su vigilancia activa en todo el mundo. Antes de la pandemia de COVID-19 la disponibilidad e datos genómicos de agentes patógenos circulantes en varios países de Latinoamérica y el Caribe era escasa o nula. Con la llegada del SARS-CoV-2 dicha situación cambió significativamente, aunque la cantidad de información disponible sigue siendo escasa y, en países como Colombia, Brasil, Argentina y Chile, la información genómica del SARS-CoV-2 provino principalmente de grupos de investigación en epidemiología genómica más que como producto de una política o programa de vigilancia en salud pública.

Revealing fine-scale spatiotemporal differences in SARS-CoV-2 introduction and spread.

Evidence-based public health approaches that minimize the introduction and spread of new SARS-CoV-2 transmission clusters are urgently needed in the United States and other countries struggling with expanding epidemics. Here we analyze 247 full-genome SARS-CoV-2 sequences from two nearby communities in Wisconsin, USA, and find surprisingly distinct patterns of viral spread. Dane County had the 12th known introduction of SARS-CoV-2 in the United States, but this did not lead to descendant community spread. Instead, the Dane County outbreak was seeded by multiple later introductions, followed by limited community spread. In contrast, relatively few introductions in Milwaukee County led to extensive community spread. We present evidence for reduced viral spread in both counties following the statewide "Safer at Home" order, which went into effect 25 March 2020. Our results suggest patterns of SARS-CoV-2 transmission may vary substantially even in nearby communities. Understanding these local patterns will enable better targeting of public health interventions.

Microbe hunting in the modern era: reflecting on a decade of microbial genomic epidemiology.

Since the first recognition that infectious microbes serve as the causes of many human diseases, physicians and scientists have sought to understand and control their spread. For the past 150+ years, these 'microbe hunters' have learned to combine epidemiological information with knowledge of the infectious agent(s). In this essay, I reflect on the evolution of microbe hunting, beginning with the history of pre-germ theory epidemiological studies, through the microbiological and molecular eras. Now in the genomic age, modern-day microbe hunters are combining pathogen whole-genome sequencing with epidemiological data to enhance epidemiological investigations, advance our understanding of the natural history of pathogens and drivers of disease, and ultimately reshape our plans and priorities for global disease control and eradication. Indeed, as we have seen during the ongoing Covid-19 pandemic, the role of microbe hunters is now more important than ever. Despite the advances already made by microbial genomic epidemiology, the field is still maturing, with many more exciting developments on the horizon.