COVID-19 infection dynamics revealed by SARS-CoV-2 wastewater sequencing analysis and deconvolution

The use of RNA sequencing from wastewater samples is proven to be a valuable way for estimating infection dynamics and circulating lineages of SARS-CoV-2. This approach has the advantage of being independent from patient population testing and symptomatic disease courses. However, it is equally important to develop easily accessible and scalable tools which can highlight critical changes in infection rates and dynamics over time across different locations given the sequencing data from the wastewater. Here we provide the first analysis of variant dynamics in Germany using wastewater sequencing and present PiGx SARS-CoV-2, a bit-by-bit reproducible end-to-end pipeline with comprehensive reports. To our knowledge, this is the first pipeline that includes all steps from raw-data to shareable reports, additional taxonomic analysis, deconvolution and geospatial time series analysis. Using our pipeline on a dataset of wastewater samples, from different locations across Berlin, over the time period from February 2021 to June 2021, we could reconstruct the dynamic of the Variant of Concern (VoC) B.1.1.7 (alpha). Additionally, we detected the unique signature mutation M:T26767C for the VoC B.1.617.2 (delta) and its raise in early June. We also show that SARS-CoV-2 mutation load measured from wastewater sequencing is correlated with actual case numbers and it has potential to be used in a predictive manner. All in all, our study provides additional evidence that systematic wastewater analysis using sequencing and computational methods can be used for modeling the infection dynamics of SARS-CoV-2. In addition, the results show that our tool can be used to tease out new mutations and to detect any emerging new lineages of concern before clinical detection. Our approach can support efforts for establishing continuous monitoring and early-warning projects for COVID-19 or any other infectious disease.

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Genome Sequencing of SARS-CoV-2 Allows Monitoring of Variants of Concern through Wastewater

Water ◽

10.3390/w13213018 ◽

2021 ◽

Vol 13 (21) ◽

pp. 3018

Author(s):

Malte Herold ◽

Aymeric Fouquier d′Hérouël ◽

Patrick May ◽

Francesco Delogu ◽

Anke Wienecke-Baldacchino ◽

...

Keyword(s):

Genetic Material ◽

Population Based ◽

Epidemiological Surveillance ◽

Clinical Samples ◽

Short Read ◽

Regional Clusters ◽

Subsequent Time ◽

Infection Dynamics ◽

Time Period ◽

Wastewater Samples

Monitoring SARS-CoV-2 in wastewater has shown to be an effective tool for epidemiological surveillance. More specifically, RNA levels determined with RT-qPCR have been shown to track with the infection dynamics within the population. However, the surveillance of individual lineages circulating in the population based on genomic sequencing of wastewater samples is challenging, as the genetic material constitutes a mixture of different viral haplotypes. Here, we identify specific signature mutations from individual SARS-CoV-2 lineages in wastewater samples to estimate lineages circulating in Luxembourg. We compare circulating lineages and mutations to those detected in clinical samples amongst infected individuals. We show that especially for dominant lineages, the allele frequencies of signature mutations correspond to the occurrence of particular lineages in the population. In addition, we provide evidence that regional clusters can also be discerned. We focused on the time period between November 2020 and March 2021 in which several variants of concern emerged and specifically traced the lineage B.1.1.7, which became dominant in Luxembourg during that time. During the subsequent time points, we were able to reconstruct short haplotypes, highlighting the co-occurrence of several signature mutations. Our results highlight the potential of genomic surveillance in wastewater samples based on amplicon short-read data. By extension, our work provides the basis for the early detection of novel SARS-CoV-2 variants.

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BiSulfite Bolt: A bisulfite sequencing analysis platform

GigaScience ◽

10.1093/gigascience/giab033 ◽

2021 ◽

Vol 10 (5) ◽

Author(s):

Colin Farrell ◽

Michael Thompson ◽

Anela Tosevska ◽

Adewale Oyetunde ◽

Matteo Pellegrini

Keyword(s):

Data Aggregation ◽

Bisulfite Sequencing ◽

Low Complexity ◽

Sequencing Analysis ◽

Command Line ◽

Sequencing Data ◽

Bisulfite Sequencing Data ◽

Analysis Platform ◽

Python Package ◽

Bisulfite Sequencing Analysis

Abstract Background Bisulfite sequencing is commonly used to measure DNA methylation. Processing bisulfite sequencing data is often challenging owing to the computational demands of mapping a low-complexity, asymmetrical library and the lack of a unified processing toolset to produce an analysis-ready methylation matrix from read alignments. To address these shortcomings, we have developed BiSulfite Bolt (BSBolt), a fast and scalable bisulfite sequencing analysis platform. BSBolt performs a pre-alignment sequencing read assessment step to improve efficiency when handling asymmetrical bisulfite sequencing libraries. Findings We evaluated BSBolt against simulated and real bisulfite sequencing libraries. We found that BSBolt provides accurate and fast bisulfite sequencing alignments and methylation calls. We also compared BSBolt to several existing bisulfite alignment tools and found BSBolt outperforms Bismark, BSSeeker2, BISCUIT, and BWA-Meth based on alignment accuracy and methylation calling accuracy. Conclusion BSBolt offers streamlined processing of bisulfite sequencing data through an integrated toolset that offers support for simulation, alignment, methylation calling, and data aggregation. BSBolt is implemented as a Python package and command line utility for flexibility when building informatics pipelines. BSBolt is available at https://github.com/NuttyLogic/BSBolt under an MIT license.

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A METAGENOMIC ASSESSMENT OF BACTERIAL CONTAMINATION OF DUST EVENTS IN SENEGAL

International Journal of Advanced Research ◽

10.21474/ijar01/12610 ◽

2021 ◽

Vol 9 (03) ◽

pp. 509-526

Author(s):

Alioune Marone ◽

◽

Malick Mbengue ◽

Gregory Jenkins ◽

Demba Ndao Niang ◽

...

Keyword(s):

Respiratory Diseases ◽

Rrna Gene ◽

Source Population ◽

Sequencing Analysis ◽

Human Pathogens ◽

Sequencing Data ◽

Bacterial Populations ◽

African Dust ◽

Hypervariable Regions ◽

Dust Events

Previous work in the Caribbean and West Africa have shown that air samples taken during dust events contain microorganisms (bacteria, fungi, viruses), including human pathogens that can cause many respiratory diseases. To better understand the potential downstream effect of bacteria dust on human health and public ecosystems, it is important to characterize the source population. In this study, we aimed to explore the bacterial populations of African dust samples collected between 2013-2017. The dust samples were collected using the spatula method, then the hypervariable regions (V3 and V4) of the 16S rRNA gene were amplified using PCR followed byMiSeq Illumina sequencing. Analysis of the sequencing data were performed using MG-RAST. At the phylum level, the proportions of Actinobacteria (22%), Firmicutes (20%), Proteobacteria (19%), and Bacteroidetes (13%) were respectively predominant in all dust samples. At the genus level, Bacillus(16%), Pseudomonas(10%), Nocardiodes and Exiguobacterium (5%) are the most dominated genera in African dust samples collected in this study.The study showed that molecular characterization of dust microbial population remains a very efficient method, also applicable to the search for viruses and fungi in this type of sample. It is important to note that the majority of microorganisms identified in this study can cause respiratory diseases.

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Single-Cell RNA Sequencing Analysis of the Immunometabolic Rewiring and Immunopathogenesis of Coronavirus Disease 2019

Frontiers in Immunology ◽

10.3389/fimmu.2021.651656 ◽

2021 ◽

Vol 12 ◽

Author(s):

Furong Qi ◽

Wenbo Zhang ◽

Jialu Huang ◽

Lili Fu ◽

Jinfang Zhao

Keyword(s):

Single Cell ◽

Rna Sequencing ◽

Mononuclear Cells ◽

Plasma Cells ◽

Severe Disease ◽

Sequencing Analysis ◽

Sequencing Data ◽

Metabolic Remodeling ◽

Single Cell Rna Sequencing ◽

Antibody Secretion

Although immune dysfunction is a key feature of coronavirus disease 2019 (COVID-19), the metabolism-related mechanisms remain elusive. Here, by reanalyzing single-cell RNA sequencing data, we delineated metabolic remodeling in peripheral blood mononuclear cells (PBMCs) to elucidate the metabolic mechanisms that may lead to the progression of severe COVID-19. After scoring the metabolism-related biological processes and signaling pathways, we found that mono-CD14+ cells expressed higher levels of glycolysis-related genes (PKM, LDHA and PKM) and PPP-related genes (PGD and TKT) in severe patients than in mild patients. These genes may contribute to the hyperinflammation in mono-CD14+ cells of patients with severe COVID-19. The mono-CD16+ cell population in COVID-19 patients showed reduced transcription levels of genes related to lysine degradation (NSD1, KMT2E, and SETD2) and elevated transcription levels of genes involved in OXPHOS (ATP6V1B2, ATP5A1, ATP5E, and ATP5B), which may inhibit M2-like polarization. Plasma cells also expressed higher levels of the OXPHOS gene ATP13A3 in COVID-19 patients, which was positively associated with antibody secretion and survival of PCs. Moreover, enhanced glycolysis or OXPHOS was positively associated with the differentiation of memory B cells into plasmablasts or plasma cells. This study comprehensively investigated the metabolic features of peripheral immune cells and revealed that metabolic changes exacerbated inflammation in monocytes and promoted antibody secretion and cell survival in PCs in COVID-19 patients, especially those with severe disease.

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Mapping ribonucleotides embedded in genomic DNA to single-nucleotide resolution using Ribose-Map

10.1101/2020.08.27.267153 ◽

2020 ◽

Author(s):

Alli L. Gombolay ◽

Francesca Storici

Keyword(s):

Computing Time ◽

Wide Distribution ◽

Sequencing Analysis ◽

Sequencing Data ◽

Single Nucleotide ◽

Genome Wide ◽

Hands On ◽

Nucleotide Resolution ◽

User Friendly ◽

Single Nucleotide Resolution

ABSTRACTRibose-Map is a user-friendly, standardized bioinformatics toolkit for the comprehensive analysis of ribonucleotide sequencing experiments. It allows researchers to map the locations of ribonucleotides in DNA to single-nucleotide resolution and identify biological signatures of ribonucleotide incorporation. In addition, it can be applied to data generated using any currently available high-throughput ribonucleotide sequencing technique, thus standardizing the analysis of ribonucleotide sequencing experiments and allowing direct comparisons of results. This protocol describes in detail how to use Ribose-Map to analyze raw ribonucleotide sequencing data, including preparing the reads for analysis, locating the genomic coordinates of ribonucleotides, exploring the genome-wide distribution of ribonucleotides, determining the nucleotide sequence context of ribonucleotides, and identifying hotspots of ribonucleotide incorporation. Ribose-Map does not require background knowledge of ribonucleotide sequencing analysis and assumes only basic command-line skills. The protocol requires less than 3 hr of computing time for most datasets and about 30 min of hands-on time.

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A Patient-Derived Glioblastoma Organoid Model Maintains Intertumoral and Intratumoral Heterogeneity for Therapeutic Testing

Neurosurgery ◽

10.1093/neuros/nyz310_640 ◽

2019 ◽

Vol 66 (Supplement_1) ◽

Author(s):

Ryan Salinas ◽

Daniel Zhang ◽

Fadi Jacob ◽

Phuong Nguyen ◽

Saad Sheikh ◽

...

Keyword(s):

Intratumoral Heterogeneity ◽

Patient Specific ◽

Molecular Heterogeneity ◽

Sequencing Analysis ◽

Sequencing Data ◽

Gene Set Enrichment ◽

Mtor Inhibition ◽

Primary Tumors ◽

Mek Inhibition ◽

Gene Set

Abstract INTRODUCTION Glioblastoma remains invariably lethal due to its aggressive and invasive nature. It has been increasingly appreciated that molecular heterogeneity between tumors and within tumors likely contributes to the lack of efficacy of numerous clinical trials. METHODS In order to maintain the inherent heterogeneity of glioblastoma, we employed a novel method to rapidly culture glioblastoma organoids (named GBOs) directly from neurosurgical resection. Cultures were generated from minced glioblastoma tissue in defined media free of serum, exogenous EGF/fibroblast growth factor (FGF), and matrigel so as to minimize selection bias. Over 30 GBO lines have been generated to date. Comprehensive histologic and sequencing analyses were performed to assess similarity to primary tumors. Leveraging clinical molecular and sequencing data, selected GBOs were treated with radiation/temozolamide, EGFR inhibition (gefitinib), MEK inhibition (trametinib), and mTOR inhibition (everolimus) for 7 d and analyzed by percent KI67+ cells following treatment. Gene set enrichment and gene ontology analysis was performed from pretreated sequencing data. RESULTS Rounded GBOs form within 2 wk and maintain high similarity to the primary tumor based upon histology as well as by sequencing analysis. Treatment with radiation/temozolamide led to a decrease in the proportion of KI67+ cells in 3 of 8 tumors with some evidence of correlative clinical radiographic response. GBO response to gefitinib treatment was specific to EGFR altered tumors and enriched for EGF related gene sets. Two GBOs had downstream NF1 mutated tumors that responded to MEK inhibition with gene set enrichment for RAS signaling. Despite resistance to other experimental treatments, 1 GBO line was found to have a PI3K mutation and responded significantly to downstream mTOR inhibition. CONCLUSION This novel culturing method of GBOs maintains both intertumoral and intratumoral heterogeneity. As clinical sequencing because increasingly prevalent, GBOs may become a valuable tool for functionally testing mutation-specific treatment strategies in a patient-specific and clinically relevant time frame.

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A LINE-1 insertion situated in the promoter of IMPG2 is associated with autosomal recessive progressive retinal atrophy in Lhasa Apso dogs

BMC Genetics ◽

10.1186/s12863-020-00911-w ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Rebekkah J. Hitti-Malin ◽

Louise M. Burmeister ◽

Sally L. Ricketts ◽

Thomas W. Lewis ◽

Louise Pettitt ◽

...

Keyword(s):

Genome Wide Association Study ◽

Retinal Disease ◽

Photoreceptor Cells ◽

Causal Variant ◽

Sequencing Analysis ◽

Sequencing Data ◽

Progressive Retinal Atrophy ◽

Dna Test ◽

A Genome ◽

The Uk

Abstract Background Canine progressive retinal atrophies are a group of hereditary retinal degenerations in dogs characterised by depletion of photoreceptor cells in the retina, which ultimately leads to blindness. PRA in the Lhasa Apso (LA) dog has not previously been clinically characterised or described in the literature, but owners in the UK are advised to have their dog examined through the British Veterinary Association/ Kennel Club/ International Sheep Dog Society (BVA/KC/ISDS) eye scheme annually, and similar schemes that are in operation in other countries. After the exclusion of 25 previously reported canine retinal mutations in LA PRA-affected dogs, we sought to identify the genetic cause of PRA in this breed. Results Analysis of whole-exome sequencing data of three PRA-affected LA and three LA without signs of PRA did not identify any exonic or splice site variants, suggesting the causal variant was non-exonic. We subsequently undertook a genome-wide association study (GWAS), which identified a 1.3 Mb disease-associated region on canine chromosome 33, followed by whole-genome sequencing analysis that revealed a long interspersed element-1 (LINE-1) insertion upstream of the IMPG2 gene. IMPG2 has previously been implicated in human retinal disease; however, until now no canine PRAs have been associated with this gene. The identification of this PRA-associated variant has enabled the development of a DNA test for this form of PRA in the breed, here termed PRA4 to distinguish it from other forms of PRA described in other breeds. This test has been used to determine the genotypes of over 900 LA dogs. A large cohort of genotyped dogs was used to estimate the allele frequency as between 0.07–0.1 in the UK LA population. Conclusions Through the use of GWAS and subsequent sequencing of a PRA case, we have identified a LINE-1 insertion in the retinal candidate gene IMPG2 that is associated with a form of PRA in the LA dog. Validation of this variant in 447 dogs of 123 breeds determined it was private to LA dogs. We envisage that, over time, the developed DNA test will offer breeders the opportunity to avoid producing dogs affected with this form of PRA.

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Synthetic Sequencing Standards: A Guide to Database Choice for Rumen Microbiota Amplicon Sequencing Analysis

Frontiers in Microbiology ◽

10.3389/fmicb.2020.606825 ◽

2020 ◽

Vol 11 ◽

Author(s):

Paul E. Smith ◽

Sinead M. Waters ◽

Ruth Gómez Expósito ◽

Hauke Smidt ◽

Ciara A. Carberry ◽

...

Keyword(s):

High Throughput Sequencing ◽

Cost Effective ◽

Amplicon Sequencing ◽

Gas Production ◽

Reference Database ◽

Specific Reference ◽

Sequencing Analysis ◽

Sequencing Data ◽

Rumen Microbiota ◽

Reference Databases

Our understanding of complex microbial communities, such as those residing in the rumen, has drastically advanced through the use of high throughput sequencing (HTS) technologies. Indeed, with the use of barcoded amplicon sequencing, it is now cost effective and computationally feasible to identify individual rumen microbial genera associated with ruminant livestock nutrition, genetics, performance and greenhouse gas production. However, across all disciplines of microbial ecology, there is currently little reporting of the use of internal controls for validating HTS results. Furthermore, there is little consensus of the most appropriate reference database for analyzing rumen microbiota amplicon sequencing data. Therefore, in this study, a synthetic rumen-specific sequencing standard was used to assess the effects of database choice on results obtained from rumen microbial amplicon sequencing. Four DADA2 reference training sets (RDP, SILVA, GTDB, and RefSeq + RDP) were compared to assess their ability to correctly classify sequences included in the rumen-specific sequencing standard. In addition, two thresholds of phylogenetic bootstrapping, 50 and 80, were applied to investigate the effect of increasing stringency. Sequence classification differences were apparent amongst the databases. For example the classification of Clostridium differed between all databases, thus highlighting the need for a consistent approach to nomenclature amongst different reference databases. It is hoped the effect of database on taxonomic classification observed in this study, will encourage research groups across various microbial disciplines to develop and routinely use their own microbiome-specific reference standard to validate analysis pipelines and database choice.

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RNA sequencing analysis for profiling activation of cancer-associated molecular pathways.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e13032 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e13032-e13032 ◽

Cited By ~ 2

Author(s):

Anton Buzdin ◽

Andrew Garazha ◽

Maxim Sorokin ◽

Alex Glusker ◽

Alexey Aleshin ◽

...

Keyword(s):

Gene Expression ◽

Original Data ◽

Tissue Expression ◽

Molecular Pathways ◽

Sequencing Analysis ◽

Rna Seq ◽

Sequencing Data ◽

Healthy Human ◽

Tissue Samples ◽

Normal Tissues

e13032 Background: Intracellular molecular pathways (IMPs) control all major events in the living cell. They are considered hotspots in contemporary oncology because knowledge of IMPs activation is essential for understanding mechanisms of molecular pathogenesis in oncology. Profiling IMPs requires RNA-seq data for tumors and for a collection of reference normal tissues. However, there is a shortage now in such profiles for normal tissues from healthy human donors, uniformly profiled in a single series of experiments. Access to the largest dataset of normal profiles GTEx is only partly available through the dbGaP. In TCGA database, norms are adjacent to surgically removed tumors and may be affected by tumor-linked growth factors, inflammation and altered vascularization. ENCODE datasets were for the autopsies of normal tissues, but they can’t form statistically significant reference groups. Methods: Tissue samples representing 20 organs were taken from post-mortal human healthy donors killed in road accidents no later than 36 hours after death, blood samples were taken from healthy volunteers. Gene expression was profiled in RNA-seq experiments using the same reagents, equipment and protocols. Bioinformatic algorithms for IMP analysis were developed and validated using experimental and public gene expression datasets. Results: From original sequencing data we constructed the biggest fully open reference expression database of normal human tissues including 465 profiles termed Oncobox Atlas of Normal Tissue Expression (ANTE, original data: GSE120795). We next developed a method termed Oncobox for interrogating activation of IMPs in human cancers. It includes modules of expression data harmonization and comparison and an algorithm for automatic annotation of molecular pathways. The Oncobox system enables accurate scoring of thousands molecular pathways using RNA-seq data. Oncobox pathway analysis is also applicable for quantitative proteomics and microRNA data in oncology. Conclusions: The Oncobox system can be used for a plethora of applications in cancer research including finding differentially regulated genes and IMPs, and for discovery of new pathway-related diagnostic and prognostic biomarkers.

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Epidemiological and Molecular Characterization of an Invasive Group A Streptococcusemm32.2 Outbreak

Journal of Clinical Microbiology ◽

10.1128/jcm.00191-17 ◽

2017 ◽

Vol 55 (6) ◽

pp. 1837-1846 ◽

Cited By ~ 8

Author(s):

Jennifer E. Cornick ◽

Anmol M. Kiran ◽

Roberto Vivancos ◽

Jon Van Aartsen ◽

Jenny Clarke ◽

...

Keyword(s):

Group A Streptococcus ◽

Adult Population ◽

Sequencing Analysis ◽

Invasive Group ◽

Disadvantaged Population ◽

Specific Subset ◽

Time Period ◽

Case Comparison ◽

Group A

ABSTRACTAnemm32.2 invasive group A streptococcus (iGAS) outbreak occurred in Liverpool from January 2010 to September 2012. This genotype had not previously been identified in Liverpool, but was responsible for 32% (14/44) of all iGAS cases reported during this time period. We performed a case-case comparison ofemm32.2 iGAS cases with non-emm32.2 control iGAS cases identified in the Liverpool population over the same time period to assess patient risk factors foremm32.2 iGAS infection. Theemm32.2 iGAS cases were confined to the adult population. We show that homelessness, intravenous drug use, and alcohol abuse predisposed patients toemm32.2 iGAS disease; however, no obvious epidemiological linkage between the patients withemm32.2 iGAS could be identified. Comparative whole-genome sequencing analysis ofemm32.2 iGAS and non-emm32.2 control isolates was also performed to identify pathogen factors which might have driven the outbreak. We identified 19 genes, five of which had previously been implicated in virulence, which were present in all of theemm32.2 iGAS isolates but not present in any of the non-emm32.2 control isolates. We report that a novelemm32.2 genotype emerged in Liverpool in 2010 and identified a specific subset of genes, which could have allowed this novelemm32.2 genotype to persist in a disadvantaged population in the region over a 3-year period.

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