Computational tools for aptamer identification and optimization

Aptamers are single-stranded DNA or RNA oligonucleotides that can selectively bind to a specific target. They are generally obtained by SELEX, but the procedure is challenging and time-consuming. Moreover, the identified aptamers tend to be insufficient in stability, specificity, and affinity. Thus, only a handful of aptamers have entered the practical use stage. Recently, computational approaches have demonstrated a significant capacity to assist in the discovery of high-performance aptamers. This review discusses the advances achieved in several aspects of computational tools in this field, as well as the new progress in machine learning and deep learning, which are used in aptamer identification and optimization. To illustrate these computationally aided processes, aptamers selection against SARS-CoV-2 is discussed in detail as a case study. We hope that this review will aid and motivate researchers to develop and utilize more computational techniques to discover ideal aptamers effectively.

Bioinformatics analysis of the structure, function and prokaryotic expression of SARS-CoV-2 nonstructural protein

The Nsp1 protein, the main virulence factor of the virus of SARS-CoV-2, mediates viral immune escape in host cells and expands the viral infection range. Systematic bioinformatics analysis and prokaryotic expression of Nsp1 protein were performed to aid the understanding of the molecular mechanism of SARS-CoV-2 infection in host cells. Pfam, TMHMM, ProtScale, ExPASy, SignalP 4.0 and other tools were used to systematically analyze the post-translational modifications, physicochemical properties, transmembrane helix, interaction network, homology and evolutionary characteristics of Nsp1 protein. The recombinant expression vector pET-22b-Nsp1 was constructed through molecular cloning technology and expressed in a prokaryotic system. Nsp1 is composed of 180 amino acids, with a molecular weight of 19.78 kDa, an isoelectric point of 5.36 and an instability index of 28.83. It has a half-life of 30 h in mammalian reticulocytes and more than 10 h in E. coli. It has 12 potential phosphorylation sites, three potential O-glycosylation sites and no signal peptide. It is a hydrophilic protein without a transmembrane helix. Secondary structure analysis indicated that the highest proportion of structural components comprised random coils (45.00%), followed by a-helices (25.56%) and extended chains (20.56%);the lowest proportion comprised ss-turns (8.89%). Multiple sequence alignment and evolutionary analysis revealed that Bat SARS-like coronavirus WIV1 had the highest sequence identity (85.00%) with the Nsp1 protein of SARS-CoV-2. After prokaryotic expression, Nsp1 protein was found to be mainly expressed in the precipitate after centrifugation of bacterial lysate. The target protein was further identified as Nsp1 by mass spectrometry. This study provides an important reference for the expression, purification and functional analysis of SARS-CoV-2 Nsp1 protein, and further reveals the biological functions of Nsp1, thus providing a reference for research and development of related inhibitors and antiviral drugs.

Comorbidity of hepatic cystic echinococcosis with HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma. (Theme Issue: New advances in the precise diagnosis and treatment of liver cancer.) [Chinese]

Objective: To investigate the comorbidity of hepatic cystic echinococcosis with HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma, and to lay a foundation for further research on the influence of hepatic cystic echinococcosis on HBV/HCV infection, liver cirrhosis, and hepatocellular carcinoma.

Effect of training of all staff and influencing factors in Huangshi, Hubei Province during prevention and control of COVID-19 in March 2020

Objective: To understand the status of acquisition of knowledge of infection control and observe the effect of training and influencing factors in Huangshi, Hubei province during prevention and control of COVID-19.

Dramatic decline of observed atmospheric CO2 and CH4 during the COVID-19 lockdown over the Yangtze River Delta of China

The temporal variation of greenhouse gas concentrations in China during the COVID-19 lockdown in China is analyzed in this work using high resolution measurements of near surface △CO2, △CH4 and △CO concentrations above the background conditions at Lin'an (LAN), a regional background station in the Yangtze River Delta region. During the pre-lockdown observational period (IOP-1), both △CO2 and △CH4 exhibited a significant increasing trend relative to the 2011-2019 climatological mean. The reduction of △CO2, △CH4 and △CO during the lockdown observational period (IOP-2) (which also coincided with the Chinese New Year Holiday) reached up to 15.0 ppm, 14.2 ppb and 146.8 ppb, respectively, and a reduction of △CO2/△CO probably due to a dramatic reduction from industrial emissions. △CO2, △CH4 and △CO were observed to keep declining during the post-lockdown easing phase (IOP-3), which is the synthetic result of lower than normal CO2 emissions from rural regions around LAN coupled with strong uptake of the terrestrial ecosystem. Interestingly, the trend reversed to gradual increase for all species during the later easing phase (IOP-4), with △CO2/△CO constantly increasing from IOP-2 to IOP-3 and finally IOP-4, consistent with recovery in industrial emissions associated with the staged resumption of economic activity. On average, △CO2 declined sharply throughout the time of day during IOP-2 but increased gradually throughout the day during IOP-4. The findings showcase the significant role of emission reduction in accounting for the dramatic changes in measured atmospheric △CO2 and △CH4 associated with the COVID-19 lockdown and recovery.

Clinicopathological and Immunological Features of Patients With New Onset Kidney Disease After Inactivated SARS-CoV-2 Vaccination: An Observational Cohort Study (preprint)

Background: The onset of various kidney diseases have been reported after COVID-19 vaccination. However, detailed clinical and pathological examination of kidney injury in patients receiving inactivated vaccines are lacking.Methods: We screened and analyzed patients with newly diagnosed kidney diseases after inactivated SARS-CoV-2 vaccination in Peking University First Hospital from January 2021 to August 2021. We obtained samples of blood, urine, and renal biopsy tissues. Clinical and laboratory information, as well as light microscopy, immunostaining and ultrastructural observation were described. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike protein and Nucleoprotein were stained using immune-fluorescence technique in the kidney biopsy samples. SARS-CoV-2 specific antibodies were tested using magnetic particle chemiluminescence immunoassay.Findings: The study group included 17 patients, including immune complex mediated kidney diseases (IgA nephropathy, membranous nephropathy and lupus nephritis), podocytopathy (minimal change disease and focal segmental glomerulosclerosis) and others (antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis, anti-GBM nephritis, acute tubulointerstitial nephritis, and thrombotic microangiopathy). Seven patients (41.18%) developed renal disease after the first dose and 10 (58.82%) after the second dose. We found no definitive evidence of SARS-CoV-2 Spike protein or Nucleoprotein deposition in the kidney biopsy samples. Serological markers implicated abnormal immune responses in predisposed individuals. Treatment and follow-up (median = 86 days) showed that biopsy diagnosis informed treatment and prognosis in all patients.Interpretation: We observed various kidney diseases following inactivated SARS-CoV-2 vaccine administration. Our findings provide an evidence against direct vaccine protein deposition as the major pathomechanism, but implicate abnormal immune responses in predisposed individuals. These findings expand our understanding of inactivated SARS-CoV-2 vaccine renal safety.Funding: This study was funded by National Natural Science Foundation of China (91742205, 82170711, 81800636, 82070733, 81625004), Clinical Medicine Plus X—Young Scholars Project of Peking University (PKU2021LCXQ017), the Fundamental Research Funds for the Central Universities, CAMS Innovation Fund for Medical Sciences (2019-I2M-5-046), Yunnan Provincial Science and Technology Department (202102AA100051 and 202003AC100010, China), and Beijing Young Scientist Program (BJJWZYJH01201910001006).Declaration of Interest: The authors declare no competing interests.Ethical Approval: This study was approved by the institutional review board of Peking University First Hospital (2021-352) and the Committee on Human Subject Research and Ethics of Yunnan University (CHSRE2021020). Written Informed Consent Form was obtained from each participant.

Novel COVID-19 phenotype definitions reveal phenotypically distinct patterns of genetic association and protective effects (preprint)

Multiple large COVID-19 genome-wide association studies (GWAS) have identified reproducible genetic associations indicating that some infection susceptibility and severity risk is heritable. Most of these studies ascertained COVID-19 cases in medical clinics and hospitals, which can lead to an overrepresentation of cases with severe outcomes, such as hospitalization, intensive care unit admission, or ventilation. Here, we demonstrate the utility and validity of deep phenotyping with self-reported outcomes in a population with a large proportion of mild and subclinical cases. Using these data, we defined eight different phenotypes related to COVID-19 outcomes: four that align with previously studied COVID-19 definitions and four novel definitions that focus on susceptibility given exposure, mild clinical manifestations, and an aggregate score of symptom severity. We assessed replication of 13 previously identified COVID-19 genetic associations with all eight phenotypes and found distinct patterns of association, most notably related to the chr3/SLC6A20/LZTFL1 and chr9/ABO regions. We then performed a discovery GWAS, which suggested some novel phenotypes may better capture protective associations and also identified a novel association in chr11/GALNT18 that reproduced in two fully independent populations.

Common genetic variants identify therapeutic targets for COVID-19 and individuals at high risk of severe disease (preprint)

The need to identify and effectively treat COVID-19 cases at highest risk for severe disease is critical. We identified seven common genetic variants (three novel) that modulate COVID-19 susceptibility and severity, implicating IFNAR2, CCHCR1, TCF19, SLC6A20 and the hyaluronan pathway as potential therapeutic targets. A high genetic burden was strongly associated with increased risk of hospitalization and severe disease among COVID-19 cases, especially among individuals with few known risk factors.

Molecular mechanism prediction analysis of compound Kushen injection in the treatment of COVID-19 based on network pharmacology and molecular docking

Background: As one of the eight effective traditional Chinese medicines for the treatment of atypical pneumonia, compound Kushen injection (CKI) played an important role in combating pneumonia caused by severe acute respiratory syndrome coronavirus 2 virus in China in 2003. CKI is known to inhibit inflammation, and its main chemical components, namely matrine and oxymatrine, can promote Th cells to recognize and eliminate viruses. In this study, network pharmacology and molecular docking were used to explore the mechanisms of CKI for treating coronavirus disease 2019. Methods: The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and other related literature were used to screen CKI's active ingredients in the blood. Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, Swiss Target Prediction and STITCH were used to search for potential targets of the active ingredients. The "ingredient-target" network was constructed using the Cytoscape software. The STRING online database was used to construct a target protein-protein interaction network that can be visualized and analyzed using the Cytoscape software to obtain key targets. Results: Sophocarpine, sophoridine, matrine, (+)-allomatrine, AIDS211310, and sophranol were the six active ingredients. After docking the active ingredients with severe acute respiratory syndrome coronavirus 2 3CL hydrolase and angiotensin-converting enzyme 2 (ACE2), they displayed suitable affinity, which could block viral replication and its binding to ACE2. The key targets mainly involved inflammatory factors, such as interleukin-6 (IL-6) and tumor necrosis factor (TNF). Gene Ontology enrichment analysis mainly indicated the IL-6 cytokine-mediated signaling pathway and cytokine-mediated signaling pathway. The Kyoto Encyclopedia of Genes and Genome pathway enrichment analysis mainly indicated steroid hormone biosynthesis and the TNF signaling pathway. Conclusion: The alkaloids in CKI can block viral replication and its binding to severe acute respiratory syndrome coronavirus 2 and ACE2 receptors. They regulate the IL-6-mediated signaling pathway, TNF signaling pathway, and steroid hormone biosynthesis, thereby initiating therapeutic responses against coronavirus disease 2019.

COVID-19 Susceptibility and Severity Risks in a Survey of Over 500,000 People (preprint)

The growing toll of the COVID-19 pandemic has heightened the urgency of identifying individuals most at risk of infection and severe outcomes, underscoring the need to assess susceptibility and severity patterns in large datasets. The AncestryDNA COVID-19 Study collected self-reported survey data on symptoms, outcomes, risk factors, and exposures for over 563,000 adult individuals in the U.S., including over 4,700 COVID-19 cases as measured by a self-reported positive nasal swab test. We observed significant associations between several risk factors and COVID-19 susceptibility and severity outcomes. Many of the susceptibility associations were accounted for by differences in known exposures; a notable exception was elevated susceptibility odds for males after adjusting for known exposures and age. We also leveraged the dataset to build risk models to robustly predict individualized COVID-19 susceptibility (area under the curve [AUC]=0.84) and severity outcomes including hospitalization and life-threatening critical illness amongst COVID-19 cases (AUC=0.87 and 0.90, respectively). The results highlight the value of self-reported epidemiological data at scale to provide public health insights into the evolving COVID-19 pandemic.

AncestryDNA COVID-19 Host Genetic Study Identifies Three Novel Loci (preprint)

Human infection with SARS-CoV-2, the causative agent of COVID-19, leads to a remarkably diverse spectrum of outcomes, ranging from asymptomatic to fatal. Recent reports suggest that both clinical and genetic risk factors may contribute to COVID-19 susceptibility and severity. To investigate genetic risk factors, we collected over 500,000 COVID-19 survey responses between April and May 2020 with accompanying genetic data from the AncestryDNA database. We conducted sex-stratified and meta-analyzed genome-wide association studies (GWAS) for COVID-19 susceptibility (positive nasopharyngeal swab test, ncases=2,407) and severity (hospitalization, ncases=250). The severity GWAS replicated associations with severe COVID-19 near ABO and SLC6A20 (P<0.05). Furthermore, we identified three novel loci with P<5x10-8. The strongest association was near IVNS1ABP, a gene involved in influenza virus replication, and was associated only in males. The other two novel loci harbor genes with established roles in viral replication or immunity: SRRM1 and the immunoglobulin lambda locus. We thus present new evidence that host genetic variation likely contributes to COVID-19 outcomes and demonstrate the value of large-scale, self-reported data as a mechanism to rapidly address a health crisis.