Self-distillation contrastive learning enables clustering-free signature extraction and mapping to multimodal single-cell atlas of multimillion scale (preprint)

Massively generated single-cell multi-omics datasets are revolutionizing biological studies of heterogenous tissues and organisms, which necessitate powerful computational methods to unleash the full potential of these tremendous data. Here, we present Concerto, stands for self-distillation contrastive learning of cell representations, a self-supervised representation learning framework optimized with asymmetric teacher-student configuration to analyze single-cell multi-omics datasets with scalability up to building 10 million-cell reference within 1.5 hour and querying 10k cells within 8 seconds. Concerto leverages dropout layer as minimal data augmentation to learn meaningful cell representations in a contrastive manner. The teacher module uses attention mechanism to aggregate contextualized gene embeddings within cellular context, while the student module uses simpler dense structure with discreate input. The learned task-agnostic representations can be adapted to a broad range of single-cell computation tasks. 1) Via supervised fine-tuning, Concerto enables automatic cell classification as well as novel cell-type discovery; 2) Attention weights provide model interpretability via automatically extracting specific molecular signatures at single-cell resolution without the needs of clustering; 3) Via source-aware training, Concerto supports efficient data integration by projecting all cells across multiple batches into a joint embedding space. 4) Via batch-aware inference or unsupervised fine-tuning, Concerto enables mapping query cells onto reference and accurately transferring annotations. Concerto can flexibly extend to multi-omics datasets simply through cross-modality summation operation to obtain unified cell embeddings. Using examples from human peripheral blood, human thymus, human pancreas, and mouse tissue atlas, Concerto shows superior performance benchmarking against other top-performing methods. We also demonstrate Concerto recapitulates detailed COVID-19 disease variation through query-to-reference mapping. Concerto can operate on all genes and represents a fully data-driven approach with minimum prior distribution assumptions, eliminating the needs of PCA-like or autoencoder-like dimensionality reduction, which significantly reforms the current best practice. Concerto is a simple, straightforward, robust, and scalable framework, offering a brand new perspective to derive cell representations and can effectively satisfy the emerging paradigm of query-to-reference mapping in the era of atlas-level single-cell multimodal analysis.

Plasma cell-free DNA promise disease monitoring and tissue injury assessment of COVID-19 (preprint)

COVID-19 is a huge threat to global health. Due to the lack of definitive etiological therapeutics currently, effective disease monitoring is of high clinical value for better healthcare and management of the large number of COVID-19 patients. In this study, we recruited 37 COVID-19 patients, collected 176 blood samples upon diagnosis and during treatment, and analyzed cell-free DNA (cfDNA) in these samples. We report gross abnormalities in cfDNA of COVID-19 patients, including elevated GC content, altered molecule size and end motif patterns. More importantly, such cfDNA characteristics reflect patient-specific physiological conditions during treatment. Further analysis on tissue origin tracing of cfDNA reveals frequent tissue injuries in COVID-19 patients, which is supported by clinical diagnoses. Hence, we demonstrate the translational merit of cfDNA as valuable analyte for effective disease monitoring, as well as tissue injury assessment in COVID-19 patients.

A Chinese host genetic study discovered type I interferons and causality of cholesterol levels and WBC counts on COVID-19 severity (preprint)

As of early May 2021, the ongoing pandemic COVID-19 has caused over 160 million of infections and over 3 million deaths worldwide. Many risk factors, such as age, gender, and comorbidities, have been studied to explain the variable symptoms of infected patients. However, these effects may not fully account for the diversity in disease severity. Here, we present a comprehensive analysis of a broad range of patients laboratory and clinical assessments to investigate the genetic contributions to COVID-19 severity. By performing GWAS analysis, we discovered several concrete associations for laboratory features. Based on these findings, we performed Mendelian randomization (MR) analysis to investigate the causality of laboratory traits on disease severity. From the MR study, we identified two causal traits, cholesterol levels and WBC counts. The functional gene related to cholesterol levels is ApoE and people with particular ApoE genotype are more likely to have higher cholesterol levels, facilitating the process that SARS-CoV-2 binds on its receptor ACE2 and aggravating COVID-19 disease. The functional gene related to WBC counts is MHC system that plays a central role in the immune system. The host immune response to the SARS-CoV-2 infection greatly affects the patients severity status and clinical outcome. Additionally, our gene-based and GSEA analysis revealed interferon pathways, including type I interferon receptor binding, regulation of IFNA signaling, and SARS coronavirus and innate immunity. We hope that our work will make a contribution in studying the genetic mechanisms of disease illness and serve as useful reference for the clinical diagnosis and treatment of COVID-19.

Genomic epidemiology of SARS-CoV-2 in the United Arab Emirates reveals novel virus mutation, patterns of co-infection and tissue specific host responses (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country. Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection. Results: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with no significantly different viral loads. Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also discovered an enrichment of cytosine-to-uracil mutation among the viral population collected from the nasopharynx, that is different from the adenosine-to-inosine change previously observed in the bronchoalveolar lavage fluid samples. This observation is accompanied with an upregulation of APOBEC4, an under-studied putative cytidine-uridine editing enzyme in the infected nasopharynx. Conclusions: The genomic epidemiological and molecular biological knowledge obtained in the study provides new insights for the SARS-CoV-2 evolution and transmission. We highlight the importance of sustained surveillance of the virus mutation using genomic sequencing as a public health strategy. Keywords: SARS-CoV-2, meta-transcriptomic sequencing, novel mutations and subclades, co-infection, cyosine depletion, host RNA editing

Genomic Epidemiology of SARS-CoV-2 in the United Arab Emirates Reveals Novel Insights into the Virus Mutation, Co-Infection and Host-Dependent RNA Editing (preprint)

Background: The United Arab Emirates is a major business hub with substantial amount of international travel. Like many other countries, it was greatly affected by the COVID-19 pandemic since late January 2020, with recurring waves of infection. This study aimed at combining genomic and epidemiological data to unravel the source of SARS-CoV-2 introduction, transmission and evolution in the country.Methods: We performed meta-transcriptomic sequencing of 1,067 nasopharyngeal swab samples collected from qRT-PCR positive COVID-19 patients in Abu Dhabi, UAE, between May 9th and June 29th 2020. We investigated the genetic diversity and transmission dynamics of the viral population and analyzed the infection and transmission potential of novel genomic clusters. Within-host SARS-CoV-2 genetic variation was analyzed to determine the occurrence and prevalence of multiple infections. Finally, we evaluated innate host responses during the prolonged period of local infection.Findings: All globally known SARS-CoV-2 clades were identified within the UAE sequenced strains, with a higher occurrence of European and East Asian clades. We defined 5 subclades based on 11 unique genetic variants within the UAE strains, which were associated with higher viral loads (p<0.001). Multiple infection of different SARS-CoV-2 strains was observed for at least 5% of the patients. We also observed a host-defense mechanism via RNA editing, likely mediated by APOBEC3 rather than ADAR in nasopharyngeal samples.Interpretation: The SARS-CoV-2 epidemic in the UAE was founded by international importation followed by local transmission, leading to prevalent multiple infection and large subclade descendances. While RNA editing mechanisms mutate the viral population, newly arisen genetic variation can contribute to a heavier viral burden. Meta-transcriptomic sequencing can help to determine the transmission patterns of SARS-CoV-2.Funding: Department of Health of Abu Dhabi, UAE and National Natural Science Foundation of China.Declaration of Interests: None to declareEthics Approval Statement: The study was approved by the Abu Dhabi COVID19 Research IRB Committee (approval number DOH/CVDC/2020/1945).

The Trans-omics Landscape of COVID-19 (preprint)

The outbreak of coronavirus disease 2019 (COVID-19) has been causing a global health emergency. Although previous studies investigated COVID-19 at different omics levels, the molecular hallmarks of COVID-19, especially in those patients without comorbidities, have not been fully investigated. Here, we presented a trans-omics landscape for COVID-19 based on integrative analysis of genomic, transcriptomic, proteomic, metabolomic and lipidomic profiles from blood samples of 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Notably, we found neutrophils heterogeneity existed between asymptomatic and critically ill patients. Expression discordance of inflammatory cytokines at mRNA and protein levels in asymptomatic patients could possibly be explained by post-transcriptional regulation by RNA binding proteins (RBPs) and microRNAs. Neutrophils over-activation, induced arginine depletion, and tryptophan metabolites accumulation contributed to T/NK cell dysfunction in critical patients. Anti-virus interferons were gradually suppressed along with disease severity. Overall, our study systematically revealed multi-omics characteristics of COVID-19, and the data we generated could hopefully help illuminate COVID-19 pathogenesis and provide valuable clues about potential therapeutic strategies for COVID-19.

The Trans-omics Landscape of COVID-19 (preprint)

System-wide molecular characteristics of COVID-19, especially in those patients without comorbidities, have not been fully investigated. We compared extensive molecular profiles of blood samples from 231 COVID-19 patients, ranging from asymptomatic to critically ill, importantly excluding those with any comorbidities. Amongst the major findings, asymptomatic patients were characterized by highly activated anti-virus interferon, T/natural killer (NK) cell activation, and transcriptional upregulation of inflammatory cytokine mRNAs. However, given very abundant RNA binding proteins (RBPs), these cytokine mRNAs could be effectively destabilized hence preserving normal cytokine levels. In contrast, in critically ill patients, cytokine storm due to RBPs inhibition and tryptophan metabolites accumulation contributed to T/NK cell dysfunction. A machine-learning model was constructed which accurately stratified the COVID-19 severities based on their multi-omics features. Overall, our analysis provides insights into COVID-19 pathogenesis and identifies targets for intervening in treatment.

Characterization of Microbial Co-infections in the Respiratory Tract of hospitalized COVID-19 patients (preprint)

Summary Background Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of Coronavirus disease 2019 (COVID-19). However, microbial composition of the respiratory tract and other infected tissues, as well as their possible pathogenic contributions to varying degrees of disease severity in COVID-19 patients remain unclear. Method Between January 27 and February 26, 2020, serial clinical specimens (sputum, nasal and throat swab, anal swab and feces) were collected from a cohort of hospitalized COVID-19 patients, including 8 mildly and 15 severely ill patients (requiring ICU admission and mechanical ventilation), in the Guangdong province, China. Total RNA was extracted and ultra-deep metatranscriptomic sequencing was performed in combination with laboratory diagnostic assays. Co-infection rates, the prevalence and abundance of microbial communities in these COVID-19 patients were determined. Findings Notably, respiratory microbial co-infections were exclusively found in 84.6% of severely ill patients (11/13), among which viral and bacterial co-infections were detected by sequencing in 30.8% (4/13) and 69.2% (9/13) of the patients, respectively. In addition, for 23.1% (3/13) of the patients, bacterial co-infections with Burkholderia cepacia complex (BCC) and Staphylococcus epidermidis were also confirmed by bacterial culture. Further, a time-dependent, secondary infection of B. cenocepacia with expressions of multiple virulence genes in one severely ill patient was demonstrated, which might be the primary cause of his disease deterioration and death one month after ICU admission. Interpretation Our findings identified distinct patterns of co-infections with SARS-CoV-2 and various respiratory pathogenic microbes in hospitalized COVID-19 patients in relation to disease severity. Detection and tracking of BCC-associated nosocomial infections are recommended to improve the pre-emptive treatment regimen and reduce fatal outcomes of hospitalized patients infected with SARS-CoV-2. Funding National Science and Technology Major Project of China, National Major Project for Control and Prevention of Infectious Disease in China, the emergency grants for prevention and control of SARS-CoV-2 of Ministry of Science and Technology and Guangdong province, Guangdong Provincial Key Laboratory of Genome Read and Write, Guangdong Provincial Academician Workstation of BGI Synthetic Genomics, and Shenzhen Engineering Laboratory for Innovative Molecular Diagnostics.

Single-cell screening of SARS-CoV-2 target cells in pets, livestock, poultry and wildlife (preprint)

A few animals have been suspected to be intermediate hosts of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, a large-scale single-cell screening of SARS-CoV-2 target cells on a wide variety of animals is missing. Here, we constructed the single-cell atlas for 11 representative species in pets, livestock, poultry, and wildlife. Notably, the proportion of SARS-CoV-2 target cells in cat was found considerably higher than other species we investigated and SARS-CoV-2 target cells were detected in multiple cell types of domestic pig, implying the necessity to carefully evaluate the risk of cats during the current COVID-19 pandemic and keep pigs under surveillance for the possibility of becoming intermediate hosts in future coronavirus outbreak. Furthermore, we screened the expression patterns of receptors for 144 viruses, resulting in a comprehensive atlas of virus target cells. Taken together, our work provides a novel and fundamental strategy to screen virus target cells and susceptible species, based on single-cell transcriptomes we generated for domesticated animals and wildlife, which could function as a valuable resource for controlling current pandemics and serve as an early warning system for coping with future infectious disease threats.

Initial Study of Human Genetic Contribution to COVID-19 Severity and Susceptibility (preprint)

The COVID-19 pandemic has accounted for more than five million infections and hundreds of thousand deaths worldwide in the past six months. The patients demonstrate a great diversity in clinical and laboratory manifestations and disease severity. Nonetheless, little is known about the host genetic contribution to the observed inter-individual phenotypic variability. Here, we report the first host genetic study in China by deeply sequencing and analyzing 332 COVID-19 patients categorized by varying levels of severity from the Shenzhen Third Peoples Hospital. Upon a total of 22.2 million genetic variants, we conducted both single-variant and gene-based association tests among five severity groups including asymptomatic, mild, moderate, severe and critical ill patients after the correction of potential confounding factors. The most significant gene locus associated with severity is located in TMEM189-UBE2V1 involved in the IL-1 signaling pathway. The p.Val197Met missense variant that affects the stability of the TMPRSS2 protein displays a decreasing allele frequency among the severe patients compared to the mild and the general population. We also identified that the HLA-A*11:01, B*51:01 and C*14:02 alleles significantly predispose the worst outcome of the patients. This initial study of Chinese patients provides a comprehensive view of the genetic difference among the COVID-19 patient groups and highlighted genes and variants that may help guide targeted efforts in containing the outbreak. Limitations and advantages of the study were also reviewed to guide future international efforts on elucidating the genetic architecture of host-pathogen interaction for COVID-19 and other infectious and complex diseases.

Time-series plasma cell-free DNA analysis reveals disease severity of COVID-19 patients (preprint)

Symptoms of coronavirus disease 2019 (COVID-19) range from asymptomatic to severe pneumonia and death. Detection of individuals at high risk for critical condition is crucial for control of the disease. Herein, for the first time, we profiled and analyzed plasma cell-free DNA (cfDNA) of mild and severe COVID-19 patients. We found that in comparison between mild and severe COVID-19 patients, Interleukin-37 signaling was one of the most relevant pathways; top significantly altered genes included POTEH, FAM27C, SPATA48, which were mostly expressed in prostate and testis; adrenal glands, small intestines and liver were tissues presenting most differentially expressed genes. Our data thus revealed potential tissue involvement, provided insights into mechanism on COVID-19 progression, and highlighted utility of cfDNA as a noninvasive biomarker for disease severity inspections.

Intra-host Variation and Evolutionary Dynamics of SARS-CoV-2 Population in COVID-19 Patients (preprint)

As of middle May 2020, the causative agent of COVID-19, SARS-CoV-2, has infected over 4 million people with more than 300 thousand death as official reports1,2. The key to understanding the biology and virus-host interactions of SARS-CoV-2 requires the knowledge of mutation and evolution of this virus at both inter- and intra-host levels. However, despite quite a few polymorphic sites identified among SARS-CoV-2 populations, intra-host variant spectra and their evolutionary dynamics remain mostly unknown. Here, using deep sequencing data, we achieved and characterized consensus genomes and intra-host genomic variants from 32 serial samples collected from eight patients with COVID-19. The 32 consensus genomes revealed the coexistence of different genotypes within the same patient. We further identified 40 intra-host single nucleotide variants (iSNVs). Most (30/40) iSNVs presented in single patient, while ten iSNVs were found in at least two patients or identical to consensus variants. Comparison of allele frequencies of the iSNVs revealed genetic divergence between intra-host populations of the respiratory tract (RT) and gastrointestinal tract (GIT), mostly driven by bottleneck events among intra-host transmissions. Nonetheless, we observed a maintained viral genetic diversity within GIT, showing an increased population with accumulated mutations developed in the tissue-specific environments. The iSNVs identified here not only show spatial divergence of intra-host viral populations, but also provide new insights into the complex virus-host interactions.

Single-cell atlas of a non-human primate reveals new pathogenic mechanisms of COVID-19 (preprint)

Stopping COVID-19 is a priority worldwide. Understanding which cell types are targeted by SARS-CoV-2 virus, whether interspecies differences exist, and how variations in cell state influence viral entry is fundamental for accelerating therapeutic and preventative approaches. In this endeavor, we profiled the transcriptome of nine tissues from a Macaca fascicularis monkey at single-cell resolution. The distribution of SARS-CoV-2 facilitators, ACE2 and TMRPSS2, in different cell subtypes showed substantial heterogeneity across lung, kidney, and liver. Through co-expression analysis, we identified immunomodulatory proteins such as IDO2 and ANPEP as potential SARS-CoV-2 targets responsible for immune cell exhaustion. Furthermore, single-cell chromatin accessibility analysis of the kidney unveiled a plausible link between IL6-mediated innate immune responses aiming to protect tissue and enhanced ACE2 expression that could promote viral entry. Our work constitutes a unique resource for understanding the physiology and pathophysiology of two phylogenetically close species, which might guide in the development of therapeutic approaches in humans. Bullet pointsO_LIWe generated a single-cell transcriptome atlas of 9 monkey tissues to study COVID-19. C_LIO_LIACE2+TMPRSS2+ epithelial cells of lung, kidney and liver are targets for SARS-CoV-2. C_LIO_LIACE2 correlation analysis shows IDO2 and ANPEP as potential therapeutic opportunities. C_LIO_LIWe unveil a link between IL6, STAT transcription factors and boosted SARS-CoV-2 entry. C_LI

Multiple approaches for massively parallel sequencing of HCoV-19 genomes directly from clinical samples (preprint)

COVID-19 has caused a major epidemic worldwide, however, much is yet to be known about the epidemiology and evolution of the virus. One reason is that the challenges underneath sequencing HCoV-19 directly from clinical samples have not been completely tackled. Here we illustrate the application of amplicon and hybrid capture (capture)-based sequencing, as well as ultra-high-throughput metatranscriptomic (meta) sequencing in retrieving complete genomes, inter-individual and intra-individual variations of HCoV-19 from clinical samples covering a range of sample types and viral load. We also examine and compare the bias, sensitivity, accuracy, and other characteristics of these approaches in a comprehensive manner. This is, to date, the first work systematically implements amplicon and capture approaches in sequencing HCoV-19, as well as the first comparative study across methods. Our work offers practical solutions for genome sequencing and analyses of HCoV-19 and other emerging viruses.