RASCL: Rapid Assessment of Selection in CLades through molecular sequence analysis.

An important unmet need revealed by the COVID-19 pandemic is the near-real-time identification of potentially fitness-altering mutations within rapidly growing SARS-CoV-2 lineages. Although powerful molecular sequence analysis methods are available to detect and characterize patterns of natural selection within modestly sized gene-sequence datasets, the computational complexity of these methods and their sensitivity to sequencing errors render them effectively inapplicable in large-scale genomic surveillance contexts. Motivated by the need to analyze new lineage evolution in near-real time using large numbers of genomes, we developed the Rapid Assessment of Selection within CLades (RASCL) pipeline. RASCL applies state of the art phylogenetic comparative methods to evaluate selective processes acting at individual codon sites and across whole genes. RASCL is scalable and produces automatically updated regular lineage-specific selection analysis reports: even for lineages that include tens or hundreds of thousands of sampled genome sequences. Key to this performance is (i) generation of automatically subsampled high quality datasets of gene/ORF sequences drawn from a selected "query" viral lineage; (ii) contextualization of these query sequences in codon alignments that include high-quality "background" sequences representative of global SARS-CoV-2 diversity; and (iii) the extensive parallelization of a suite of computationally intensive selection analysis tests. Within hours of being deployed to analyze a novel rapidly growing lineage of interest, RASCL will begin yielding JavaScript Object Notation (JSON)-formatted reports that can be either imported into third-party analysis software or explored in standard web-browsers using the premade RASCL interactive data visualization dashboard. By enabling the rapid detection of genome sites evolving under different selective regimes, RASCL is well-suited for near-real-time monitoring of the population-level selective processes that will likely underlie the emergence of future variants of concern in measurably evolving pathogens with extensive genomic surveillance.

The spatial-temporal distribution and aetiological characteristics of hand, foot, and mouth disease before and after the EV‑A71 vaccination and COVID-19 pandemic in Kunming, China, 2017–2020 (preprint)

Background: After the vaccination enterovirus 71 (EV-A71) vaccine and Corona Virus Disease 2019 (COVID-19) outbreak, the prevalence of Hand, foot, and mouth disease (HFMD) remained high and the spatial-temporal distribution of enteroviruses changed. Therefore, it is essential to define the temporal features, spatial distributions, epidemiological and aetiological characteristics of HFMD of Kunming. Methods Between 2017 and 2020, a total of 36540 HFMD children cases diagnosed with HFMD in Kunming, including 32754 enteroviruses positive clinical samples. Demographic, geographical, epidemiological and aetiological data of the cases were acquired and analyzed. Results Other enteroviruses replaced EV-A71 and the incidence of EV-A71 has decreased dramatically, while, coxsackievirus A6 (Cox A6) and coxsackievirus A16 (Cox A16) with significant outbreaks in 2018 and 2019, respectively. The major and junior peaks all extended for 2-4 months than before that vaccination EV-A71 vaccine. After the COVID-19 outbreak, Cox A6 as the predominant serotype pathogens, and only single peaks appeared in 2019 and 2020. Although the high incidence of HFMD areas were Guandu, Chenggong and Xishan, the annual incidence of different enterovirus serotype appeard in different regions. In 2017, other enteroviruses prevailed in Shilin; In 2018, Cox A16 and Cox A6 prevailed in Luquan and Shilin, respectively; In 2019, Cox A16 prevailed in Jinning; In 2020, Cox A6 and coxsackievirus A10 (Cox A10) prevailed in Luquan and Shilin, respectively. Meanwhile, the epidemic cycle of Cox A6 and Cox A16 was only 1 year, and Cox A10 and other enteroviruses were potential risk pathogens. Conclusions The spatial and temporal distribution of HFMD varies at different scales, and the incidence of different pathogens associated HFMD has obvious regional differences and seasonal trends. Therefore, the research of multivalent combined vaccines are urgently needed, while, proper preventive and protective measures could effectively control the incidence of HFMD-like diseases.

Stepwise Evolution and Exceptional Conservation of ORF1a/b Overlap in Coronaviruses.

The programmed frameshift element (PFE) rerouting translation from ORF1a to ORF1b is essential for the propagation of coronaviruses. The combination of genomic features that make up PFE-the overlap between the two reading frames, a slippery sequence, as well as an ensemble of complex secondary structure elements-places severe constraints on this region as most possible nucleotide substitution may disrupt one or more of these elements. The vast amount of SARS-CoV-2 sequencing data generated within the past year provides an opportunity to assess the evolutionary dynamics of PFE in great detail. Here, we performed a comparative analysis of all available coronaviral genomic data available to date. We show that the overlap between ORF1a and ORF1b evolved as a set of discrete 7, 16, 22, 25, and 31 nucleotide stretches with a well-defined phylogenetic specificity. We further examined sequencing data from over 1,500,000 complete genomes and 55,000 raw read data sets to demonstrate exceptional conservation and detect signatures of selection within the PFE region.

A CRISPR-Cas12a-based specific enhancer for more sensitive detection of SARS-CoV-2 infection (preprint)

High Ct-values falling in the grey zone are frequently encountered in SARS-CoV-2 detection by real-time reverse transcription PCR (rRT-PCR) and have brought urgent challenges in diagnosis of samples with low viral load. Based on the single-stranded DNA reporter trans-cleavage activity by Cas12a upon target DNA recognition, we create a Specific Enhancer for detection of PCR-amplified Nucleic Acids (SENA) to confirm SARS-CoV-2 detection through specifically targeting its rRT-PCR amplicons. SENA is highly sensitive, with its limit of detection being at least 2 copies/reaction lower than that of the corresponding rRT-PCR, and highly specific, which identifies both false-negative and false-positive cases in clinic applications. SENA provides effective confirmation for nucleic acid amplification-based molecular diagnosis, and may immediately eliminate the uncertainty problems of rRT-PCR in SARS-CoV-2 clinic detection. One Sentence SummaryCRISPR-Cas12a-based COVID-19 diagnosis.

Cases Report of Cured Novel Coronavirus-infected Pneumonia Patients with Viral Nucleic Acid Test Positive in Fecal Specimens (preprint)

Background: The outbreak of the novel coronavirus in China (COVID-19) represents a significant and urgent threat to global health. We report here five cases of COVID-19 infection patients in our clinical practices who are medically stable and presumed to successfully “cleared” the virus after antiviral treatments. Case presentation: The clinical evaluation depends on the viral nucleic acid test in respiratory specimens by real-time PCR reverse transcription (RT-PCR) assays according to the authorized guidance. We found that the stool samples of these cured patients remain positive in RT-PCR assay while the virus is undetectable in respiratory specimens. RT-PCR molecular diagnostic assay was designed to specifically detect the presence of viral RNA. Thus, the positive result in the fecal specimens implies the existence of viable virions with the patients. Conclusions: This highlights the importance to look closely at the assessment standard of medical treatment, as well as the need for reevaluation of the criteria for the initial screening, prevention, and care of patients with this emerging infection. 

Potential Factors for Prediction of Disease Severity of COVID-19 Patients (preprint)

ObjectiveCoronavirus disease 2019 (COVID-19) is an escalating global epidemic caused by SARS-CoV-2, with a high mortality in critical patients. Effective indicators for predicting disease severity in SARS-CoV-2 infected patients are urgently needed. MethodsIn this study, 43 COVID-19 patients admitted in Chongqing Public Health Medical Center were involved. Demographic data, clinical features, and laboratory examinations were obtained through electronic medical records. Peripheral blood specimens were collected from COVID-19 patients and examined for lymphocyte subsets and cytokine profiles by flow cytometry. Potential contributing factors for prediction of disease severity were further analyzed. ResultsA total of 43 COVID-19 patients were included in this study, including 29 mild patients and 14 sever patients. Severe patients were significantly older (61.9{+/-}9.4 vs 44.4{+/-}15.9) and had higher incidence in co-infection with bacteria compared to mild group (85.7%vs27.6%). Significantly more severe patients had the clinical symptoms of anhelation (78.6%) and asthma (71.4%). For laboratory examination, 57.1% severe cases showed significant reduction in lymphocyte count. The levels of Interluekin-6 (IL6), IL10, erythrocyte sedimentation rate (ESR) and D-Dimer (D-D) were significantly higher in severe patients than mild patients, while the level of albumin (ALB) was remarkably lower in severe patients. Further analysis demonstrated that ESR, D-D, age, ALB and IL6 were the major contributing factors for distinguishing severe patients from mild patients. Moreover, ESR was identified as the most powerful factor to predict disease progression of COVID-19 patients. ConclusionAge and the levels of ESR, D-D, ALB and IL6 are closely related to the disease severity of COVID-19 patients. ESR can be used as a valuable indicator for distinguishing severe COVID-19 patients in early stage, so as to increase the survival of severe patients.