Variant abundance estimation for SARS-CoV-2 in wastewater using RNA-Seq quantification

Effectively monitoring the spread of SARS-CoV-2 variants is essential to efforts to counter the ongoing pandemic. Wastewater monitoring of SARS-CoV-2 RNA has proven an effective and efficient technique to approximate COVID-19 case rates in the population. Predicting variant abundances from wastewater, however, is technically challenging. Here we show that by sequencing SARS-CoV-2 RNA in wastewater and applying computational techniques initially used for RNA-Seq quantification, we can estimate the abundance of variants in wastewater samples. We show by sequencing samples from wastewater and clinical isolates in Connecticut U.S.A. between January and April 2021 that the temporal dynamics of variant strains broadly correspond. We further show that this technique can be used with other wastewater sequencing techniques by expanding to samples taken across the United States in a similar timeframe. We find high variability in signal among individual samples, and limited ability to detect the presence of variants with clinical frequencies <10%; nevertheless, the overall trends match what we observed from sequencing clinical samples. Thus, while clinical sequencing remains a more sensitive technique for population surveillance, wastewater sequencing can be used to monitor trends in variant prevalence in situations where clinical sequencing is unavailable or impractical.

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Occurrence of SARS-CoV-2 RNA in Six Municipal Wastewater Treatment Plants at the Early Stage of COVID-19 Pandemic in The United States

Pathogens ◽

10.3390/pathogens10070798 ◽

2021 ◽

Vol 10 (7) ◽

pp. 798

Author(s):

Samendra P. Sherchan ◽

Shalina Shahin ◽

Jeenal Patel ◽

Lauren M. Ward ◽

Sarmila Tandukar ◽

...

Keyword(s):

United States ◽

Wastewater Treatment ◽

Municipal Wastewater ◽

Wastewater Treatment Plants ◽

Quantitative Polymerase Chain Reaction ◽

The United States ◽

Secondary Effluent ◽

Untreated Wastewater ◽

Treatment Processes ◽

Wastewater Samples

In this study, we investigated the occurrence of Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) RNA in primary influent (n = 42), secondary effluent (n = 24) and tertiary treated effluent (n = 34) collected from six wastewater treatment plants (WWTPs A–F) in Virginia (WWTP A), Florida (WWTPs B, C, and D), and Georgia (WWTPs E and F) in the United States during April–July 2020. Of the 100 wastewater samples analyzed, eight (19%) untreated wastewater samples collected from the primary influents contained SARS-CoV-2 RNA as measured by reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) assays. SARS-CoV-2 RNA were detected in influent wastewater samples collected from WWTP A (Virginia), WWTPs E and F (Georgia) and WWTP D (Florida). Secondary and tertiary effluent samples were not positive for SARS-CoV-2 RNA indicating the treatment processes in these WWTPs potentially removed SARS-CoV-2 RNA during the secondary and tertiary treatment processes. However, further studies are needed to understand the log removal values (LRVs) and transmission risks of SARS-CoV-2 RNA through analyzing wastewater samples from a wider range of WWTPs.

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Impact of the first COVID-19 shelter-in-place order in the United States on emergency department utilization, Marin County, California

10.1101/2020.07.01.20144691 ◽

2020 ◽

Author(s):

Brett R. Bayles ◽

Michaela F George ◽

Haylea Hannah ◽

Patti Culross ◽

Rochelle R. Ereman ◽

...

Keyword(s):

United States ◽

San Francisco ◽

Large Scale ◽

Temporal Dynamics ◽

The United States ◽

Emergency Department Utilization ◽

Marin County ◽

Before And After ◽

Ed Visits ◽

The Impact

Background: The first shelter-in-place (SIP) order in the United States was issued across six counties in the San Francisco Bay Area to reduce the impact of COVID-19 on critical care resources. We sought to assess the impact of this large-scale intervention on emergency departments (ED) in Marin County, California. Methods: We conducted a retrospective descriptive and trend analysis of all ED visits in Marin County, California from January 1, 2018 to May 4, 2020 to quantify the temporal dynamics of ED utilization before and after the March 17, 2020 SIP order. Results: The average number of ED visits per day decreased by 52.3% following the SIP order compared to corresponding time periods in 2018 and 2019. Both respiratory and non-respiratory visits declined, but this negative trend was most pronounced for non-respiratory admissions. Conclusions: The first SIP order to be issued in the United States in response to COVID-19 was associated with a significant reduction in ED utilization in Marin County.

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Comparative analysis of antibody- and lipid-based multiplexing methods for single-cell RNA-seq

10.1101/2020.11.16.384222 ◽

2020 ◽

Author(s):

Viacheslav Mylka ◽

Jeroen Aerts ◽

Irina Matetovici ◽

Suresh Poovathingal ◽

Niels Vandamme ◽

...

Keyword(s):

Genetic Variation ◽

Comparative Analysis ◽

Single Cell ◽

Cell Lines ◽

Clinical Studies ◽

Clinical Samples ◽

Rna Seq ◽

Batch Effects ◽

Single Cell Sequencing ◽

Single Nucleus

ABSTRACTMultiplexing of samples in single-cell RNA-seq studies allows significant reduction of experimental costs, straightforward identification of doublets, increased cell throughput, and reduction of sample-specific batch effects. Recently published multiplexing techniques using oligo-conjugated antibodies or - lipids allow barcoding sample-specific cells, a process called ‘hashing’. Here, we compare the hashing performance of TotalSeq-A and -C antibodies, custom synthesized lipids and MULTI-seq lipid hashes in four cell lines, both for single-cell RNA-seq and single-nucleus RNA-seq. Hashing efficiency was evaluated using the intrinsic genetic variation of the cell lines. Benchmarking of different hashing strategies and computational pipelines indicates that correct demultiplexing can be achieved with both lipid- and antibody-hashed human cells and nuclei, with MULTISeqDemux as the preferred demultiplexing function and antibody-based hashing as the most efficient protocol on cells. Antibody hashing was further evaluated on clinical samples using PBMCs from healthy and SARS-CoV-2 infected patients, where we demonstrate a more affordable approach for large single-cell sequencing clinical studies, while simultaneously reducing batch effects.

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Targeting Neoepitopes to Treat Solid Malignancies: Immunosurgery

Frontiers in Immunology ◽

10.3389/fimmu.2021.592031 ◽

2021 ◽

Vol 12 ◽

Author(s):

Eric de Sousa ◽

Joana R. Lérias ◽

Antonio Beltran ◽

Georgia Paraschoudi ◽

Carolina Condeço ◽

...

Keyword(s):

T Cells ◽

T Cell ◽

Human Leukocyte ◽

Immune Checkpoint Blockade ◽

Successful Outcome ◽

Clinical Samples ◽

Cancer Tissue ◽

Rna Seq ◽

Peripheral T Cells ◽

Ifn Γ

Successful outcome of immune checkpoint blockade in patients with solid cancers is in part associated with a high tumor mutational burden (TMB) and the recognition of private neoantigens by T-cells. The quality and quantity of target recognition is determined by the repertoire of ‘neoepitope’-specific T-cell receptors (TCRs) in tumor-infiltrating lymphocytes (TIL), or peripheral T-cells. Interferon gamma (IFN-γ), produced by T-cells and other immune cells, is essential for controlling proliferation of transformed cells, induction of apoptosis and enhancing human leukocyte antigen (HLA) expression, thereby increasing immunogenicity of cancer cells. TCR αβ-dependent therapies should account for tumor heterogeneity and availability of the TCR repertoire capable of reacting to neoepitopes and functional HLA pathways. Immunogenic epitopes in the tumor-stroma may also be targeted to achieve tumor-containment by changing the immune-contexture in the tumor microenvironment (TME). Non protein-coding regions of the tumor-cell genome may also contain many aberrantly expressed, non-mutated tumor-associated antigens (TAAs) capable of eliciting productive anti-tumor immune responses. Whole-exome sequencing (WES) and/or RNA sequencing (RNA-Seq) of cancer tissue, combined with several layers of bioinformatic analysis is commonly used to predict possible neoepitopes present in clinical samples. At the ImmunoSurgery Unit of the Champalimaud Centre for the Unknown (CCU), a pipeline combining several tools is used for predicting private mutations from WES and RNA-Seq data followed by the construction of synthetic peptides tailored for immunological response assessment reflecting the patient’s tumor mutations, guided by MHC typing. Subsequent immunoassays allow the detection of differential IFN-γ production patterns associated with (intra-tumoral) spatiotemporal differences in TIL or peripheral T-cells versus TIL. These bioinformatics tools, in addition to histopathological assessment, immunological readouts from functional bioassays and deep T-cell ‘adaptome’ analyses, are expected to advance discovery and development of next-generation personalized precision medicine strategies to improve clinical outcomes in cancer in the context of i) anti-tumor vaccination strategies, ii) gauging mutation-reactive T-cell responses in biological therapies and iii) expansion of tumor-reactive T-cells for the cellular treatment of patients with cancer.

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COVID-19 In United States: Statistical Analysis and Inferences From the Empirical Data

10.21203/rs.3.rs-1084057/v1 ◽

2021 ◽

Author(s):

Nivedita Rethnakar

Keyword(s):

United States ◽

Statistical Analysis ◽

Statistical Inference ◽

Empirical Data ◽

Respiratory Diseases ◽

Temporal Dynamics ◽

The United States ◽

Mortality Statistics ◽

Race Ethnicity ◽

The Impact

Abstract This paper investigates the mortality statistics of the COVID-19 pandemic from the United States perspective. Using empirical data analysis and statistical inference tools, we bring out several exciting and important aspects of the pandemic, otherwise hidden. Specific patterns seen in demo- graphics such as race/ethnicity and age are discussed both qualitatively and quantitatively. We also study the role played by factors such as population density. Connections between COVID-19 and other respiratory diseases are also covered in detail. The temporal dynamics of the COVID-19 outbreak and the impact of vaccines in controlling the pandemic are also looked at with suf- ficient rigor. It is hoped that statistical inference such as the ones gathered in this paper would be helpful for better scientific understanding, policy prepa- ration and thus adequately preparing, should a similar situation arise in the future.

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Identification of RRM2 as a Potential Biomarker for the Diagnosis and Prognosis of Rheumatoid Arthritis

10.21203/rs.3.rs-449273/v1 ◽

2021 ◽

Author(s):

Wu Biao ◽

Yufeng Chen ◽

Junlong Zhong ◽

Shuping Zhong ◽

Bin Wang ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Mononuclear Cells ◽

Expression Profiles ◽

Clinical Samples ◽

Healthy Controls ◽

Rna Seq ◽

Hub Genes ◽

Healthy Human ◽

Bioinformatics Analyses ◽

Potential Biomarker

Abstract Background: Rheumatoid arthritis (RA) is a common autoimmune disease that can occur at any age. If treatment is delayed, RA can seriously affect the patients’ quality of life. However, there is no diagnostic criteria for RA and the positive predictive value of the current biomarkers is moderate. Objective: to identify RA-associated susceptibility genes and explore their potential as a novel biomarker for diagnosis and evaluation of the prognosis of RA.Methods: Peripheral blood mononuclear cells (PBMCs) were collected from healthy human donors and RA patients. RNA-seq analyses were performed to identify the differentially expressed genes (DEGs) between RA and control samples. The PBMCs-mRNA in DEGs were further subjected to enrichment analysis. Furthermore, the hub genes and key modules associated with RA were screened by bioinformatics analyses. Then, the expression of hub genes in RA were assessed in mRNA expression profiles. Next, real time-quantitative PCR (RT-qPCR) analyses were performed to further confirm the expression of the hub genes from the PBMCs that collected from 47 patients with RA and 40 healthy controls. Finally, we evaluated the clinical characters for the candidate mRNAs.Results: RNA-seq analyses revealed the expression of 178 mRNAs from PBMCs were disregulated between the healthy controls and the RA patients. Bioinformatics analyses revealed 10 hub mRNAs. The top 3 significant functional modules screened from PPI network functionally were involved in DNA replication origin binding, chemokine activity, etc. After validating the 10 hub mRNAs in GSE93272 dataset and clinical samples, we identified 3 candidate mRNAs, including ASPM, DTL and RRM2. Among which, RRM2 showed great capacity in discriminating between remissive RA and active RA. Significant correlations were observed between DTL and IL-8, TNF-α, between RRM2 and CDAI, DAS-28, tender joints and swollen joints, respectively. The AUC values of ASPM, DTL and RRM2 were 0.654, 0.995 and 0.990, respectively.Conclusion: We successfully identified multiple candidate mRNAs associated with RA. RRM2 showed high diagnosis efficiency with the AUC of 0.990 (sensitivity=100%, specificity=97.5%). And RRM2 severed as an additional biomarker for evaluating disease activity. The findings provided a novel candidate biomarker for diagnosis and evaluation of the prognosis of RA.

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Susceptibility of Clinical Isolates of Staphylococcus aureus to Ceftaroline

JOURNAL FOR CLINICAL AND DIAGNOSTIC RESEARCH ◽

10.7860/jcdr/2021/46121.14442 ◽

2021 ◽

Author(s):

Harsha Sreedharan ◽

KB Asha Pai

Keyword(s):

Staphylococcus Aureus ◽

Tertiary Care Hospital ◽

Methicillin Resistance ◽

Descriptive Analysis ◽

Tertiary Care ◽

The United States ◽

Clinical Isolates ◽

Diffusion Method ◽

Clinical Samples ◽

Care Hospital

Introduction: Methicillin-Resistant Staphylococcus aureus(MRSA) infection is a major global healthcare problem, the prevalence of which varies from 25-50% in India. It is known to cause Skin and Soft tissue Infections (SSI), endovascular infections, endocarditis, pneumonia, septic arthritis, osteomyelitis, and sepsis. Vancomycin is the drug of choice for treating severe MRSA infections. Ceftaroline, a fifth-generation cephalosporin has been approved by the United States Food and Drug Administration (US FDA) for treating acute bacterial SSI caused by susceptible micro-organisms including MRSA, Community acquired respiratory tract infection, MRSA bacteremia and endocarditis. Aim: To assess the susceptibility of clinical isolates of S. aureusto ceftaroline, in a Tertiary Care Hospital. Materials and Methods: This prospective study was conducted in the Department of Microbiology of a Tertiary Care Hospital over a period of two months from June 2019 to July 2019. S.aureus isolates from various clinical samples were screened for methicillin resistance by disc diffusion method using cefoxitin disc and ceftaroline susceptibility of these isolates was assessed by E-strip method. The isolates were classified as ceftaroline susceptible, Susceptibility Dose Dependent (SDD) and ceftaroline resistant respectively as per CLSI guidelines. A descriptive analysis of the data was done and the results were presented as frequencies and percentages. Results: All the S.aureus isolates were found to be susceptible to ceftaroline. Methicillin Sensitive Staphylococcus aureus(MSSA) isolates had lower Minimum Inhibitory Concentration (MIC) when compared to MRSA. The highest MIC among MRSA was 0.5 μg/mL. Conclusion: Ceftaroline can be considered as an effective alternative for treatment of infections caused by MRSA.

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Obesity, Body Image Dissatisfaction, and Sexual Dysfunction: A Narrative Review

Sexes ◽

10.3390/sexes3010002 ◽

2022 ◽

Vol 3 (1) ◽

pp. 20-39

Author(s):

Sean M. McNabney

Keyword(s):

Body Image ◽

Sexual Dysfunction ◽

Sexual Function ◽

Adult Population ◽

Body Image Dissatisfaction ◽

The United States ◽

The Body ◽

Narrative Review ◽

Health Concern ◽

Clinical Samples

With approximately two-thirds of the United States adult population classified as overweight or obese, obesity remains a critical public health concern. Obesity not only contributes to several health complications including type 2 diabetes mellitus and cardiovascular disease, but the condition is also associated with sexual dysfunction in both women and men. Despite evidence linking obesity and its concomitant pathophysiology to sexual problems, the potential roles of psychosocial factors such as body image are understudied. This narrative review evaluates the research linkages between obesity and sexual dysfunction, with particular attention to the potential effects of body image dissatisfaction. A literature search of biomedical and psychological databases was used to identify research pertaining to obesity, sexual function, and/or body image constructs. The pathophysiological effects of obesity on sexual function are well-documented in mechanistic studies and animal trials, often with corroboration in human clinical samples. However, very few studies examine obesity, body image, and sexual function in tandem. Body image dissatisfaction appears to independently impinge upon the sexual response cycle and mental health outcomes, irrespective of body weight. While obesity is often associated with negative body image appraisal, it is unclear whether these constructs exert additive, synergistic, or antagonistic effects on sexual responsivity. Additionally, overweight/obese individuals who exhibit higher levels of body image satisfaction or self-confidence appear to be protected from the deleterious effects of obesity on sexual satisfaction, at least to some extent. Greater reliance upon conceptual/theoretical models from the body image literature may better clarify the relationships between these constructs.

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Transcriptome-wide m6A detection with DART-Seq

10.21203/rs.2.12189/v1 ◽

2019 ◽

Author(s):

Kate D. Meyer

Keyword(s):

Gene Expression Regulation ◽

Preparation Method ◽

Current Knowledge ◽

Cross Reactivity ◽

High Variability ◽

Library Preparation ◽

Rna Seq ◽

Generation Sequencing ◽

Library Preparation Method

Abstract m6A is the most abundant internal mRNA modification and plays diverse roles in gene expression regulation. Much of our current knowledge about m6A has been driven by recent advances in the ability to detect this mark transcriptome-wide. Antibody-based approaches have been the method of choice for global m6A mapping studies. These methods rely on m6A antibodies to immunoprecipitate methylated RNAs, followed by next-generation sequencing to identify m6A-containing transcripts1,2. While these methods enabled the first identification of m6A sites transcriptome-wide and have dramatically improved our ability to study m6A, they suffer from several limitations. These include requirements for high amounts of input RNA, costly and time-consuming library preparation, high variability across studies, and m6A antibody cross-reactivity with other modifications. Here, we describe DART-Seq (deamination adjacent to RNA modification targets), an antibody-free method for global m6A detection. In DART-Seq, the C to U deaminating enzyme, APOBEC1, is fused to the m6A-binding YTH domain. This fusion protein is then introduced to cellular RNA either through overexpression in cells or with in vitro assays, and subsequent deamination of m6A-adjacent cytidines is then detected by RNA sequencing to identify m6A sites. DART-Seq can successfully map m6A sites throughout the transcriptome using as little as 10 nanograms of total cellular RNA, and it is compatible with any standard RNA-seq library preparation method.

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Spatiotemporal patterns of alcohol outlets and violence: A spatially heterogeneous Markov chain analysis

Environment and Planning B Urban Analytics and City Science ◽

10.1177/2399808320965569 ◽

2020 ◽

pp. 239980832096556

Author(s):

Ran Wei ◽

Tony H Grubesic ◽

Wei Kang

Keyword(s):

Markov Chain ◽

Policy Development ◽

Temporal Dynamics ◽

Local Level ◽

Public Health Problem ◽

The United States ◽

Alcohol Outlet ◽

Alcohol Outlets ◽

Spatial And Temporal Dynamics ◽

Outlet Density

Alcohol-related violence remains a serious social and public health problem in the United States. A large corpus of work suggests a positive statistical relationship between alcohol outlet density and violence. However, questions remain as to how neighborhood violence evolves in response to varying access to alcohol outlets. This paper introduces an approach for analyzing the spatial and temporal dynamics of violence and its association with alcohol outlets by embedding the evolution of assault events and outlet density within a spatially heterogeneous Markov chain framework. This framework enables the exploration of spatiotemporal dynamics of alcohol outlets and violence and controls for potentially confounding impacts and spatial heterogeneity. Using a case study at the block group level in Seattle, Washington, the results of this paper suggest that violence is spatially heterogeneous at the local level and locations with sparsely distributed alcohol outlets are less likely to see an increase in violence when compared to areas with higher densities of outlets. Further, the modeling approach helps identify locations that might “tip” into more violent conditions if more outlets were allowed to operate. This paper concludes with a brief discussion of how the methods and results can help improve the management, licensing, and policy development for alcohol outlets in a community.

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