Identification of microbial community in the urban environment: The concordance between conventional culture and nanopore 16S rRNA sequencing

IntroductionMicrobes in the built environment have been implicated as a source of infectious diseases. Bacterial culture is the standard method for assessing the risk of exposure to pathogens in urban environments, but this method only accounts for <1% of the diversity of bacteria. Recently, full-length 16S rRNA gene analysis using nanopore sequencing has been applied for microbial evaluations, resulting in a rise in the development of long-read taxonomic tools for species-level classification. Regarding their comparative performance, there is, however, a lack of information.MethodsHere, we aim to analyze the concordance of the microbial community in the urban environment inferred by multiple taxonomic classifiers, including ARGpore2, Emu, Kraken2/Bracken and NanoCLUST, using our 16S-nanopore dataset generated by MegaBLAST, as well as assess their abilities to identify culturable species based on the conventional culture results.ResultsAccording to our results, NanoCLUST was preferred for 16S microbial profiling because it had a high concordance of dominant species and a similar microbial profile to MegaBLAST, whereas Kraken2/Bracken, which had similar clustering results as NanoCLUST, was also desirable. Second, for culturable species identification, Emu with the highest accuracy (81.2%) and F1 score (29%) for the detection of culturable species was suggested.DiscussionIn addition to generating datasets in complex communities for future benchmarking studies, our comprehensive evaluation of the taxonomic classifiers offers recommendations for ongoing microbial community research, particularly for complex communities using nanopore 16S rRNA sequencing

Clinical Significance of BCL2, C-MYC, and BCL6 Genetic Abnormalities, Epstein-Barr Virus Infection, CD5 Protein Expression, Germinal Center B Cell/Non-Germinal Center B-Cell Subtypes, Co-expression of MYC/BCL2 Proteins and Co-expression of MYC/BCL2/BCL6 Proteins in Diffuse Large B-Cell Lymphoma : A Clinical and Pathological Correlation Study of 120 Patients

Background: Clinical significance of germinal center B-cell (GCB) and non-GCB sub-categorization, expression of MYC, BCL2, BCL6, CD5 proteins and Epstein Barr virus encoded RNA (EBER) positivity in diffuse large B-cell lymphoma (DLBCL) remain controversial. Could these biomarkers accurately identify high risk DLBCL patients? Are MYC, BCL2 and BCL6 proteins expression feasible as baseline testing to predict c-Myc, BCL2 or BCL6 gene rearrangements? Aims: To investigate prognostic values of GCB/non-GCB sub-categorization, Double Protein Expression Lymphoma (DPL), Triple Protein Expression Lymphoma (TPL), positivity of CD5 protein and EBER in patients with DLBCL disease. To evaluate correlation between BCL2 , c-Myc and BCL6 gene rearrangements with BCL2, MYC and BCL6 proteins expression. Methods: Diagnostic tissue samples of 120 DLBCL patients between January 2012 to December 2013 from four major hospitals in Malaysia were selected. Samples were subjected to immunohistochemical staining, fluorescent in-situ hybridization (FISH) testing, and central pathological review. Pathological data were correlated with clinical characteristics and treatment outcome. Results: A total of 120 cases were analysed. Mean age of diagnosis was 54.1 years ± 14.6, 64 were males, 56 were females, mean follow up period was 25 months (ranged from 1 to 36 months). Of the 120 cases, 74.2% were non-GCB whereas 25.8% were GCB, 6.7% were EBER positive, 6.7% expressed CD5 protein, 13.3% were DPL and 40% were TPL. The prevalence of c-Myc, BCL2, BCL6 gene rearrangements were 5.8%, 5.8%, and 14.2%, respectively; and 1.6% were Double Hit Lymphoma (DHL). EBER positivity, DPL, TPL, c-Myc gene rearrangement, BCL2 gene rearrangement, extra copies of BCL2 gene and BCL6 gene rearrangement were associated with shorter median overall survival (P0.05). Overall, c-Myc, BCL2 and BCL6 gene rearrangements showed weak correlation with expression of MYC, BCL2 and BCL6 proteins (P>0.05). Fluorescent in situ hybridization is the preferred technique for prediction of treatment outcome in DLBCL patients. Conclusion: c-Myc, BCL2, and BCL6 gene rearrangements, EBER expression, DHL, TPL and IPI score are reliable risk stratification tools. MYC, BCL2 and BCL6 proteins expression are not applicable as baseline biomarkers to predict c-Myc, BCL2, and BCL6 gene rearrangements

High-Throughput In Vivo Analysis of Gene Expression in Caenorhabditis elegans

Using DNA sequences 5′ to open reading frames, we have constructed green fluorescent protein (GFP) fusions and generated spatial and temporal tissue expression profiles for 1,886 specific genes in the nematode Caenorhabditis elegans. This effort encompasses about 10% of all genes identified in this organism. GFP-expressing wild-type animals were analyzed at each stage of development from embryo to adult. We have identified 5′ DNA regions regulating expression at all developmental stages and in 38 different cell and tissue types in this organism. Among the regulatory regions identified are sequences that regulate expression in all cells, in specific tissues, in combinations of tissues, and in single cells. Most of the genes we have examined in C. elegans have human orthologs. All the images and expression pattern data generated by this project are available at WormAtlas (http://gfpweb.aecom.yu.edu/index) and through WormBase (http://www.wormbase.org)

A Pre-mRNA–Associating Factor Links Endogenous siRNAs to Chromatin Regulation

In plants and fungi, small RNAs silence gene expression in the nucleus by establishing repressive chromatin states. The role of endogenous small RNAs in metazoan nuclei is largely unknown. Here we show that endogenous small interfering RNAs (endo-siRNAs) direct Histone H3 Lysine 9 methylation (H3K9me) in Caenorhabditis elegans. In addition, we report the identification and characterization of nuclear RNAi defective (nrde)-1 and nrde-4. Endo-siRNA–driven H3K9me requires the nuclear RNAi pathway including the Argonaute (Ago) NRDE-3, the conserved nuclear RNAi factor NRDE-2, as well as NRDE-1 and NRDE-4. Small RNAs direct NRDE-1 to associate with the pre-mRNA and chromatin of genes, which have been targeted by RNAi. NRDE-3 and NRDE-2 are required for the association of NRDE-1 with pre-mRNA and chromatin. NRDE-4 is required for NRDE-1/chromatin association, but not NRDE-1/pre-mRNA association. These data establish that NRDE-1 is a novel pre-mRNA and chromatin-associating factor that links small RNAs to H3K9 methylation. In addition, these results demonstrate that endo-siRNAs direct chromatin modifications via the Nrde pathway in C. elegans

Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States

Short-term probabilistic forecasts of the trajectory of the COVID-19 pandemic in the United States have served as a visible and important communication channel between the scientific modeling community and both the general public and decision-makers. Forecasting models provide specific, quantitative, and evaluable predictions that inform short-term decisions such as healthcare staffing needs, school closures, and allocation of medical supplies. Starting in April 2020, the US COVID-19 Forecast Hub (https://covid19forecasthub.org/) collected, disseminated, and synthesized tens of millions of specific predictions from more than 90 different academic, industry, and independent research groups. A multimodel ensemble forecast that combined predictions from dozens of groups every week provided the most consistently accurate probabilistic forecasts of incident deaths due to COVID-19 at the state and national level from April 2020 through October 2021. The performance of 27 individual models that submitted complete forecasts of COVID-19 deaths consistently throughout this year showed high variability in forecast skill across time, geospatial units, and forecast horizons. Two-thirds of the models evaluated showed better accuracy than a naïve baseline model. Forecast accuracy degraded as models made predictions further into the future, with probabilistic error at a 20-wk horizon three to five times larger than when predicting at a 1-wk horizon. This project underscores the role that collaboration and active coordination between governmental public-health agencies, academic modeling teams, and industry partners can play in developing modern modeling capabilities to support local, state, and federal response to outbreaks

The United States COVID-19 Forecast Hub dataset

Academic researchers, government agencies, industry groups, and individuals have produced forecasts at an unprecedented scale during the COVID-19 pandemic. To leverage these forecasts, the United States Centers for Disease Control and Prevention (CDC) partnered with an academic research lab at the University of Massachusetts Amherst to create the US COVID-19 Forecast Hub. Launched in April 2020, the Forecast Hub is a dataset with point and probabilistic forecasts of incident cases, incident hospitalizations, incident deaths, and cumulative deaths due to COVID-19 at county, state, and national, levels in the United States. Included forecasts represent a variety of modeling approaches, data sources, and assumptions regarding the spread of COVID-19. The goal of this dataset is to establish a standardized and comparable set of short-term forecasts from modeling teams. These data can be used to develop ensemble models, communicate forecasts to the public, create visualizations, compare models, and inform policies regarding COVID-19 mitigation. These open-source data are available via download from GitHub, through an online API, and through R packages

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Antibodies against endogenous retroviruses promote lung cancer immunotherapy

B cells are frequently found in the margins of solid tumours as organized follicles in ectopic lymphoid organs called tertiary lymphoid structures (TLS). Although TLS have been found to correlate with improved patient survival and response to immune checkpoint blockade (ICB), the underlying mechanisms of this association remain elusive. Here we investigate lung-resident B cell responses in patients from the TRACERx 421 (Tracking Non-Small-Cell Lung Cancer Evolution Through Therapy) and other lung cancer cohorts, and in a recently established immunogenic mouse model for lung adenocarcinoma. We find that both human and mouse lung adenocarcinomas elicit local germinal centre responses and tumour-binding antibodies, and further identify endogenous retrovirus (ERV) envelope glycoproteins as a dominant anti-tumour antibody target. ERV-targeting B cell responses are amplified by ICB in both humans and mice, and by targeted inhibition of KRAS(G12C) in the mouse model. ERV-reactive antibodies exert anti-tumour activity that extends survival in the mouse model, and ERV expression predicts the outcome of ICB in human lung adenocarcinoma. Finally, we find that effective immunotherapy in the mouse model requires CXCL13-dependent TLS formation. Conversely, therapeutic CXCL13 treatment potentiates anti-tumour immunity and synergizes with ICB. Our findings provide a possible mechanistic basis for the association of TLS with immunotherapy response