Your browser doesn't support javascript.
Show: 20 | 50 | 100
Results 1 - 20 de 322
Filter
Add filters

Document Type
Year range
1.
Front Cell Infect Microbiol ; 11: 783961, 2021.
Article in English | MEDLINE | ID: covidwho-1630423

ABSTRACT

The global coronavirus disease 2019 (COVID-19) pandemic has demonstrated the range of disease severity and pathogen genomic diversity emanating from a singular virus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2). This diversity in disease manifestations and genomic mutations has challenged healthcare management and resource allocation during the pandemic, especially for countries such as India with a bigger population base. Here, we undertake a combinatorial approach toward scrutinizing the diagnostic and genomic diversity to extract meaningful information from the chaos of COVID-19 in the Indian context. Using methods of statistical correlation, machine learning (ML), and genomic sequencing on a clinically comprehensive patient dataset with corresponding with/without respiratory support samples, we highlight specific significant diagnostic parameters and ML models for assessing the risk of developing severe COVID-19. This information is further contextualized in the backdrop of SARS-CoV-2 genomic features in the cohort for pathogen genomic evolution monitoring. Analysis of the patient demographic features and symptoms revealed that age, breathlessness, and cough were significantly associated with severe disease; at the same time, we found no severe patient reporting absence of physical symptoms. Observing the trends in biochemical/biophysical diagnostic parameters, we noted that the respiratory rate, total leukocyte count (TLC), blood urea levels, and C-reactive protein (CRP) levels were directly correlated with the probability of developing severe disease. Out of five different ML algorithms tested to predict patient severity, the multi-layer perceptron-based model performed the best, with a receiver operating characteristic (ROC) score of 0.96 and an F1 score of 0.791. The SARS-CoV-2 genomic analysis highlighted a set of mutations with global frequency flips and future inculcation into variants of concern (VOCs) and variants of interest (VOIs), which can be further monitored and annotated for functional significance. In summary, our findings highlight the importance of SARS-CoV-2 genomic surveillance and statistical analysis of clinical data to develop a risk assessment ML model.


Subject(s)
COVID-19 , SARS-CoV-2 , Genomics , Humans , Mutation , Risk Assessment
3.
PLoS One ; 17(1): e0261014, 2022.
Article in English | MEDLINE | ID: covidwho-1622333

ABSTRACT

High viral transmission in the COVID-19 pandemic has enabled SARS-CoV-2 to acquire new mutations that may impact genome sequencing methods. The ARTIC.v3 primer pool that amplifies short amplicons in a multiplex-PCR reaction is one of the most widely used methods for sequencing the SARS-CoV-2 genome. We observed that some genomic intervals are poorly captured with ARTIC primers. To improve the genomic coverage and variant detection across these intervals, we designed long amplicon primers and evaluated the performance of a short (ARTIC) plus long amplicon (MRL) sequencing approach. Sequencing assays were optimized on VR-1986D-ATCC RNA followed by sequencing of nasopharyngeal swab specimens from fifteen COVID-19 positive patients. ARTIC data covered 94.47% of the virus genome fraction in the positive control and patient samples. Variant analysis in the ARTIC data detected 217 mutations, including 209 single nucleotide variants (SNVs) and eight insertions & deletions. On the other hand, long-amplicon data detected 156 mutations, of which 80% were concordant with ARTIC data. Combined analysis of ARTIC + MRL data improved the genomic coverage to 97.03% and identified 214 high confidence mutations. The combined final set of 214 mutations included 203 SNVs, 8 deletions and 3 insertions. Analysis showed 26 SARS-CoV-2 lineage defining mutations including 4 known variants of concern K417N, E484K, N501Y, P618H in spike gene. Hybrid analysis identified 7 nonsynonymous and 5 synonymous mutations across the genome that were either ambiguous or not called in ARTIC data. For example, G172V mutation in the ORF3a protein and A2A mutation in Membrane protein were missed by the ARTIC assay. Thus, we show that while the short amplicon (ARTIC) assay provides good genomic coverage with high throughput, complementation of poorly captured intervals with long amplicon data can significantly improve SARS-CoV-2 genomic coverage and variant detection.


Subject(s)
Genome, Viral/genetics , Genomics/methods , SARS-CoV-2/genetics , Whole Genome Sequencing/methods , COVID-19/virology , Humans , RNA, Viral/genetics , Sequence Analysis/methods
4.
Curr Microbiol ; 79(2): 48, 2022 Jan 04.
Article in English | MEDLINE | ID: covidwho-1603303

ABSTRACT

This study aimed to characterize the whole genome of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV2) isolated from an oropharyngeal swab specimen of a Pashtun Pakistani patient using next-generation sequencing. Upon comparing the SARS-CoV2 genome to the reference genome, a total of 10 genetic variants were identified. Among the 10 genetic variants, 1 missense mutation (c.1139A > G, p.Lys292Glu) in the Open Reading Frame 1ab (ORF1ab) positioned at 112 in the non-structural protein 2 (NSP2) was found to be unique. Phylogenetic analysis (n = 84) revealed that the current SARS-CoV2 genome was closely clustered with 8 Pakistani strains belonging to Punjab, Federal Capital, Azad Jammu and Kashmir (AJK), and Khyber Pakhtunkhwa (KP). In addition, the current SARS-CoV2 genome was very similar to the genome of SARS-CoV2 reported from Guam, Taiwan, India, the USA, and France. Overall, this study reports a slight mismatch in the SARS-CoV2 genome, indicating the presence of a single unique missense mutation. However, phylogenetic analysis revealed that the current SARS-CoV2 genome was closely clustered with 8 other Pakistani strains.


Subject(s)
COVID-19 , RNA, Viral , Genome, Viral , Genomics , High-Throughput Nucleotide Sequencing , Humans , Pakistan , Phylogeny , SARS-CoV-2
5.
J Pediatric Infect Dis Soc ; 10(Supplement_4): S88-S95, 2021 Dec 24.
Article in English | MEDLINE | ID: covidwho-1593724

ABSTRACT

Hospital outbreak investigations are high-stakes epidemiology. Contacts between staff and patients are numerous; environmental and community exposures are plentiful; and patients are highly vulnerable. Having the best data is paramount to understanding an outbreak in order to stop ongoing transmission and prevent future outbreaks. In the past 5 years, the high-resolution view of transmission offered by analyzing pathogen whole-genome sequencing (WGS) is increasingly part of hospital outbreak investigations. Concerns over speed and actionability, assay validation, liability, cost, and payment models lead to further opportunities for work in this area. Now accelerated by funding for COVID-19, the use of genomics in hospital outbreak investigations has firmly moved from the academic literature to more quotidian operations, with associated concerns involving regulatory affairs, data integration, and clinical interpretation. This review details past uses of WGS data in hospital-acquired infection outbreaks as well as future opportunities to increase its utility and growth in hospital infection prevention.


Subject(s)
COVID-19 , Cross Infection , Cross Infection/epidemiology , Disease Outbreaks , Genomics , Hospitals , Humans , Molecular Epidemiology , SARS-CoV-2
6.
Emerg Infect Dis ; 28(1): 247-250, 2022 01.
Article in English | MEDLINE | ID: covidwho-1581409

ABSTRACT

We sequenced ≈50% of coronavirus disease cases imported to Hong Kong during March-July 2021 and identified 70 cases caused by Delta variants of severe acute respiratory syndrome coronavirus 2. The genomic diversity detected in Hong Kong was similar to global diversity, suggesting travel hubs can play a substantial role in surveillance.


Subject(s)
COVID-19 , SARS-CoV-2 , COVID-19/diagnosis , COVID-19/epidemiology , Genomics , Hong Kong/epidemiology , Humans , Mass Screening , SARS-CoV-2/isolation & purification , Travel
7.
Cells ; 11(1)2021 12 28.
Article in English | MEDLINE | ID: covidwho-1580991

ABSTRACT

Coronavirus disease (COVID-19) spreads mainly through close contact of infected persons, but the molecular mechanisms underlying its pathogenesis and transmission remain unknown. Here, we propose a statistical physics model to coalesce all molecular entities into a cohesive network in which the roadmap of how each entity mediates the disease can be characterized. We argue that the process of how a transmitter transforms the virus into a recipient constitutes a triad unit that propagates COVID-19 along reticulate paths. Intrinsically, person-to-person transmissibility may be mediated by how genes interact transversely across transmitter, recipient, and viral genomes. We integrate quantitative genetic theory into hypergraph theory to code the main effects of the three genomes as nodes, pairwise cross-genome epistasis as edges, and high-order cross-genome epistasis as hyperedges in a series of mobile hypergraphs. Charting a genome-wide atlas of horizontally epistatic hypergraphs can facilitate the systematic characterization of the community genetic mechanisms underlying COVID-19 spread. This atlas can typically help design effective containment and mitigation strategies and screen and triage those more susceptible persons and those asymptomatic carriers who are incubation virus transmitters.


Subject(s)
COVID-19/transmission , Gene Expression Regulation , Genome, Viral/genetics , Genomics/methods , SARS-CoV-2/genetics , Algorithms , COVID-19/epidemiology , COVID-19/virology , Epistasis, Genetic , Genome-Wide Association Study/methods , Humans , Models, Genetic , Pandemics , SARS-CoV-2/pathogenicity , Virulence/genetics
8.
Front Immunol ; 12: 733539, 2021.
Article in English | MEDLINE | ID: covidwho-1572288

ABSTRACT

The response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is largely impacted by the level of virus exposure and status of the host immunity. The nature of protection shown by direct asymptomatic contacts of coronavirus disease 2019 (COVID-19)-positive patients is quite intriguing. In this study, we have characterized the antibody titer, SARS-CoV-2 surrogate virus neutralization, cytokine levels, single-cell T-cell receptor (TCR), and B-cell receptor (BCR) profiling in asymptomatic direct contacts, infected cases, and controls. We observed significant increase in antibodies with neutralizing amplitude in asymptomatic contacts along with cytokines such as Eotaxin, granulocyte-colony stimulating factor (G-CSF), interleukin 7 (IL-7), migration inhibitory factor (MIF), and macrophage inflammatory protein-1α (MIP-1α). Upon single-cell RNA (scRNA) sequencing, we explored the dynamics of the adaptive immune response in few representative asymptomatic close contacts and COVID-19-infected patients. We reported direct asymptomatic contacts to have decreased CD4+ naive T cells with concomitant increase in CD4+ memory and CD8+ Temra cells along with expanded clonotypes compared to infected patients. Noticeable proportions of class switched memory B cells were also observed in them. Overall, these findings gave an insight into the nature of protection in asymptomatic contacts.


Subject(s)
Adaptive Immunity/immunology , COVID-19/immunology , Genomics/methods , SARS-CoV-2/immunology , Single-Cell Analysis/methods , Adaptive Immunity/genetics , Adult , Antibodies, Viral/immunology , COVID-19/genetics , COVID-19/virology , Cytokines/immunology , Cytokines/metabolism , Female , Gene Expression Profiling/methods , Humans , Male , /metabolism , Middle Aged , SARS-CoV-2/physiology , Sequence Analysis, RNA/methods , T-Lymphocytes/immunology , T-Lymphocytes/metabolism , T-Lymphocytes/virology , Young Adult
9.
BMC Med Genomics ; 14(Suppl 6): 289, 2021 12 14.
Article in English | MEDLINE | ID: covidwho-1571758

ABSTRACT

BACKGROUND: Virus screening and viral genome reconstruction are urgent and crucial for the rapid identification of viral pathogens, i.e., tracing the source and understanding the pathogenesis when a viral outbreak occurs. Next-generation sequencing (NGS) provides an efficient and unbiased way to identify viral pathogens in host-associated and environmental samples without prior knowledge. Despite the availability of software, data analysis still requires human operations. A mature pipeline is urgently needed when thousands of viral pathogen and viral genome reconstruction samples need to be rapidly identified. RESULTS: In this paper, we present a rapid and accurate workflow to screen metagenomics sequencing data for viral pathogens and other compositions, as well as enable a reference-based assembler to reconstruct viral genomes. Moreover, we tested our workflow on several metagenomics datasets, including a SARS-CoV-2 patient sample with NGS data, pangolins tissues with NGS data, Middle East Respiratory Syndrome (MERS)-infected cells with NGS data, etc. Our workflow demonstrated high accuracy and efficiency when identifying target viruses from large scale NGS metagenomics data. Our workflow was flexible when working with a broad range of NGS datasets from small (kb) to large (100 Gb). This took from a few minutes to a few hours to complete each task. At the same time, our workflow automatically generates reports that incorporate visualized feedback (e.g., metagenomics data quality statistics, host and viral sequence compositions, details about each of the identified viral pathogens and their coverages, and reassembled viral pathogen sequences based on their closest references). CONCLUSIONS: Overall, our system enabled the rapid screening and identification of viral pathogens from metagenomics data, providing an important piece to support viral pathogen research during a pandemic. The visualized report contains information from raw sequence quality to a reconstructed viral sequence, which allows non-professional people to screen their samples for viruses by themselves (Additional file 1).


Subject(s)
COVID-19 Testing/methods , COVID-19/diagnosis , Computational Biology/methods , Genome, Viral , Genomics , Metagenomics , SARS-CoV-2/genetics , Algorithms , Animals , Automation , Coronavirus Infections/genetics , High-Throughput Nucleotide Sequencing , Humans , Mass Screening/methods , Pandemics , Pangolins , Reference Values , Software , Transcriptome , Workflow
10.
Methods Mol Biol ; 2401: 195-215, 2022.
Article in English | MEDLINE | ID: covidwho-1568331

ABSTRACT

The COVID-19 pandemic has hit heavily many aspects of our lives. At this time, genomic research is concerned with exploiting available datasets and knowledge to fuel discovery on this novel disease. Studies that can precisely characterize the gene expression profiles of human hosts infected by SARS-CoV-2 are of significant relevance. However, not many such experiments have yet been produced to date, nor made publicly available online. Thus, it is of paramount importance that data analysts explore all possibilities to integrate information coming from similar viruses and related diseases; interestingly, microarray gene profile experiments become extremely valuable for this purpose. This chapter reviews the aspects that should be considered when integrating transcriptomics data, considering mainly samples infected by different viruses and combining together various data types and also the extracted knowledge. It describes a series of scenarios from studies performed in literature and it suggests possible other directions of noteworthy integration.


Subject(s)
COVID-19 , Gene Expression Profiling , COVID-19/genetics , Genomics , Humans , Pandemics , Transcriptome
11.
Euro Surveill ; 26(43)2021 10.
Article in English | MEDLINE | ID: covidwho-1547185

ABSTRACT

BackgroundIn the SARS-CoV-2 pandemic, viral genomes are available at unprecedented speed, but spatio-temporal bias in genome sequence sampling precludes phylogeographical inference without additional contextual data.AimWe applied genomic epidemiology to trace SARS-CoV-2 spread on an international, national and local level, to illustrate how transmission chains can be resolved to the level of a single event and single person using integrated sequence data and spatio-temporal metadata.MethodsWe investigated 289 COVID-19 cases at a university hospital in Munich, Germany, between 29 February and 27 May 2020. Using the ARTIC protocol, we obtained near full-length viral genomes from 174 SARS-CoV-2-positive respiratory samples. Phylogenetic analyses using the Auspice software were employed in combination with anamnestic reporting of travel history, interpersonal interactions and perceived high-risk exposures among patients and healthcare workers to characterise cluster outbreaks and establish likely scenarios and timelines of transmission.ResultsWe identified multiple independent introductions in the Munich Metropolitan Region during the first weeks of the first pandemic wave, mainly by travellers returning from popular skiing areas in the Alps. In these early weeks, the rate of presumable hospital-acquired infections among patients and in particular healthcare workers was high (9.6% and 54%, respectively) and we illustrated how transmission chains can be dissected at high resolution combining virus sequences and spatio-temporal networks of human interactions.ConclusionsEarly spread of SARS-CoV-2 in Europe was catalysed by superspreading events and regional hotspots during the winter holiday season. Genomic epidemiology can be employed to trace viral spread and inform effective containment strategies.


Subject(s)
COVID-19 , Cross Infection , Cross Infection/epidemiology , Genome, Viral , Genomics , Germany/epidemiology , Hospitals , Humans , Phylogeny , SARS-CoV-2
12.
J Med Virol ; 93(12): 6782-6787, 2021 12.
Article in English | MEDLINE | ID: covidwho-1544298

ABSTRACT

Sao Paulo State, currently experiences a second COVID-19 wave overwhelming the healthcare system. Due to the paucity of SARS-CoV-2 complete genome sequencing, we established a Network for Pandemic Alert of Emerging SARS-CoV-2 Variants to rapidly understand and monitor the spread of SARS-CoV-2 variants into the state. Through analysis of 210 SARS-CoV-2 complete genomes obtained from the largest regional health departments we identified cocirculation of multiple SARS-CoV-2 lineages such as B.1.1 (0.5%), B.1.1.28 (23.2%), B.1.1.7 (alpha variant, 6.2%), B.1.566 (1.4%), B.1.544 (0.5%), C.37 (0.5%) P.1 (gamma variant, 66.2%), and P.2 (zeta variant, 1.0%). Our analysis allowed also the detection, for the first time in Brazil, the South African B.1.351 (beta) variant of concern, B.1.351 (501Y.V2) (0.5%), characterized by the following mutations: ORF1ab: T265I, R724K, S1612L, K1655N, K3353R, SGF 3675_F3677del, P4715L, E5585D; spike: D80A, D215G, L242_L244del, A262D, K417N, E484K, N501Y, D614G, A701V, C1247F; ORF3a: Q57H, S171L, E: P71L; ORF7b: Y10F, N: T205I; ORF14: L52F. The most recent common ancestor of the identified strain was inferred to be mid-October to late December 2020. Our analysis demonstrated the P.1 lineage predominance and allowed the early detection of the South African strain for the first time in Brazil. We highlight the importance of SARS-CoV-2 active monitoring to ensure the rapid detection of potential variants for pandemic control and vaccination strategies. Highlights Identification of B.1.351 (beta) variant of concern in the Sao Paulo State. Dissemination of SARS-CoV-2 variants of concern and interest in the Sao Paulo State. Mutational Profile of the circulating variants of concern and interest.


Subject(s)
SARS-CoV-2/genetics , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Brazil , COVID-19/immunology , COVID-19/virology , Genomics/methods , Humans , Mutation/genetics , Mutation/immunology , SARS-CoV-2/immunology , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/immunology
13.
OMICS ; 25(11): 681-692, 2021 11.
Article in English | MEDLINE | ID: covidwho-1541502

ABSTRACT

Multiomics study designs have significantly increased understanding of complex biological systems. The multiomics literature is rapidly expanding and so is their heterogeneity. However, the intricacy and fragmentation of omics data are impeding further research. To examine current trends in multiomics field, we reviewed 52 articles from PubMed and Web of Science, which used an integrated omics approach, published between March 2006 and January 2021. From studies, data regarding investigated loci, species, omics type, and phenotype were extracted, curated, and streamlined according to standardized terminology, and summarized in a previously developed graphical summary. Evaluated studies included 21 omics types or applications of omics technology such as genomics, transcriptomics, metabolomics, epigenomics, environmental omics, and pharmacogenomics, species of various phyla including human, mouse, Arabidopsis thaliana, Saccharomyces cerevisiae, and various phenotypes, including cancer and COVID-19. In the analyzed studies, diverse methods, protocols, results, and terminology were used and accordingly, assessment of the studies was challenging. Adoption of standardized multiomics data presentation in the future will further buttress standardization of terminology and reporting of results in systems science. This shall catalyze, we suggest, innovation in both science communication and laboratory medicine by making available scientific knowledge that is easier to grasp, share, and harness toward medical breakthroughs.


Subject(s)
Computational Biology/trends , Genomics/trends , Metabolomics/trends , Proteomics/trends , Animals , COVID-19 , Computer Graphics , Epigenomics/trends , Gene Expression Profiling/trends , Humans , Pharmacogenetics/trends , Publications , SARS-CoV-2 , Terminology as Topic
14.
Brief Bioinform ; 22(5)2021 09 02.
Article in English | MEDLINE | ID: covidwho-1528156

ABSTRACT

The low capture rate of expressed RNAs from single-cell sequencing technology is one of the major obstacles to downstream functional genomics analyses. Recently, a number of imputation methods have emerged for single-cell transcriptome data, however, recovering missing values in very sparse expression matrices remains a substantial challenge. Here, we propose a new algorithm, WEDGE (WEighted Decomposition of Gene Expression), to impute gene expression matrices by using a biased low-rank matrix decomposition method. WEDGE successfully recovered expression matrices, reproduced the cell-wise and gene-wise correlations and improved the clustering of cells, performing impressively for applications with sparse datasets. Overall, this study shows a potent approach for imputing sparse expression matrix data, and our WEDGE algorithm should help many researchers to more profitably explore the biological meanings embedded in their single-cell RNA sequencing datasets. The source code of WEDGE has been released at https://github.com/QuKunLab/WEDGE.


Subject(s)
Algorithms , Computational Biology/methods , Gene Expression Profiling/methods , RNA-Seq/methods , Single-Cell Analysis/methods , COVID-19/blood , COVID-19/genetics , COVID-19/virology , Cluster Analysis , Computer Simulation , Genomics/methods , Humans , Leukocytes, Mononuclear/classification , Leukocytes, Mononuclear/metabolism , Reproducibility of Results , SARS-CoV-2/physiology , Severity of Illness Index
17.
PLoS Comput Biol ; 17(11): e1009560, 2021 11.
Article in English | MEDLINE | ID: covidwho-1523396

ABSTRACT

Severe acute respiratory coronavirus 2 (SARS-CoV-2), the causative agent of COVID-19, is of zoonotic origin. Evolutionary analyses assessing whether coronaviruses similar to SARS-CoV-2 infected ancestral species of modern-day animal hosts could be useful in identifying additional reservoirs of potentially dangerous coronaviruses. We reasoned that if a clade of species has been repeatedly exposed to a virus, then their proteins relevant for viral entry may exhibit adaptations that affect host susceptibility or response. We perform comparative analyses across the mammalian phylogeny of angiotensin-converting enzyme 2 (ACE2), the cellular receptor for SARS-CoV-2, in order to uncover evidence for selection acting at its binding interface with the SARS-CoV-2 spike protein. We uncover that in rodents there is evidence for adaptive amino acid substitutions at positions comprising the ACE2-spike interaction interface, whereas the variation within ACE2 proteins in primates and some other mammalian clades is not consistent with evolutionary adaptations. We also analyze aminopeptidase N (APN), the receptor for the human coronavirus 229E, a virus that causes the common cold, and find evidence for adaptation in primates. Altogether, our results suggest that the rodent and primate lineages may have had ancient exposures to viruses similar to SARS-CoV-2 and HCoV-229E, respectively.


Subject(s)
COVID-19/genetics , COVID-19/virology , Coronavirus Infections/genetics , Coronavirus Infections/virology , SARS-CoV-2/genetics , Adaptation, Physiological/genetics , Amino Acid Substitution , Angiotensin-Converting Enzyme 2/genetics , Angiotensin-Converting Enzyme 2/physiology , Animals , CD13 Antigens/genetics , CD13 Antigens/physiology , Common Cold/genetics , Common Cold/virology , Computational Biology , Coronavirus 229E, Human/genetics , Coronavirus 229E, Human/physiology , Evolution, Molecular , Genomics , Host Microbial Interactions/genetics , Host Microbial Interactions/physiology , Host Specificity/genetics , Host Specificity/physiology , Humans , Mammals/genetics , Mammals/virology , Phylogeny , Protein Interaction Domains and Motifs/genetics , Receptors, Virus/genetics , Receptors, Virus/physiology , SARS-CoV-2/physiology , Selection, Genetic , Spike Glycoprotein, Coronavirus/genetics , Spike Glycoprotein, Coronavirus/physiology , Virus Internalization
18.
BMC Res Notes ; 14(1): 415, 2021 Nov 17.
Article in English | MEDLINE | ID: covidwho-1523326

ABSTRACT

OBJECTIVE: To adapt 'fishplots' to describe real-time evolution of SARS-CoV-2 genomic clusters. RESULTS: This novel analysis adapted the fishplot to depict the size and duration of circulating genomic clusters over time in New South Wales, Australia. It illuminated the effectiveness of interventions on the emergence, spread and eventual elimination of clusters and distilled genomic data into clear information to inform public health action.


Subject(s)
COVID-19 , Australia , Genomics , Humans , New South Wales , SARS-CoV-2
19.
Elife ; 102021 06 01.
Article in English | MEDLINE | ID: covidwho-1513078

ABSTRACT

A voucher is a permanently preserved specimen that is maintained in an accessible collection. In genomics, vouchers serve as the physical evidence for the taxonomic identification of genome assemblies. Unfortunately, the vast majority of vertebrate genomes stored in the GenBank database do not refer to voucher specimens. Here, we urge researchers generating new genome assemblies to deposit voucher specimens in accessible, permanent research collections, and to link these vouchers to publications, public databases, and repositories. We also encourage scientists to deposit voucher specimens in order to recognize the work of local field biologists and promote a diverse and inclusive knowledge base, and we recommend best practices for voucher deposition to prevent taxonomic errors and ensure reproducibility and legality in genetic studies.


Subject(s)
Biological Specimen Banks , Databases, Genetic , Genomics , Specimen Handling , Animals , Data Accuracy , Humans , Phylogeny , Reproducibility of Results
20.
Elife ; 102021 04 27.
Article in English | MEDLINE | ID: covidwho-1513055

ABSTRACT

Dendritic cells (DCs) regulate processes ranging from antitumor and antiviral immunity to host-microbe communication at mucosal surfaces. It remains difficult, however, to genetically manipulate human DCs, limiting our ability to probe how DCs elicit specific immune responses. Here, we develop a CRISPR-Cas9 genome editing method for human monocyte-derived DCs (moDCs) that mediates knockouts with a median efficiency of >94% across >300 genes. Using this method, we perform genetic screens in moDCs, identifying mechanisms by which DCs tune responses to lipopolysaccharides from the human microbiome. In addition, we reveal donor-specific responses to lipopolysaccharides, underscoring the importance of assessing immune phenotypes in donor-derived cells, and identify candidate genes that control this specificity, highlighting the potential of our method to pinpoint determinants of inter-individual variation in immunity. Our work sets the stage for a systematic dissection of the immune signaling at the host-microbiome interface and for targeted engineering of DCs for neoantigen vaccination.


Subject(s)
CRISPR-Associated Protein 9/genetics , CRISPR-Cas Systems , Clustered Regularly Interspaced Short Palindromic Repeats , Dendritic Cells/immunology , Gene Editing , Genomics , Immunity, Innate/genetics , Bacteroides thetaiotaomicron/immunology , CRISPR-Associated Protein 9/metabolism , Cells, Cultured , Cytokines/genetics , Cytokines/metabolism , Dendritic Cells/drug effects , Dendritic Cells/metabolism , Gene Expression Regulation , Humans , Immunity, Innate/drug effects , Lipopolysaccharides/pharmacology , Phenotype , Signal Transduction , Toll-Like Receptor 4/agonists , Toll-Like Receptor 4/genetics , Toll-Like Receptor 4/metabolism
SELECTION OF CITATIONS
SEARCH DETAIL
...