Utilizing cost-effective portable equipment to enhance COVID-19 variant tracking both on-site and at a large scale.

Despite optimistic predictions on the eventual end of COVID-19 (Coronavirus Disease 2019), caution is necessary regarding the emergence of new variants to sustain a positive outlook and effectively address any potential future outbreaks. However, ongoing efforts to track COVID-19 variants are concentrated in developed countries and unique social practices and remote habitats of indigenous peoples present additional challenges. By combining small-sized equipment that is easily accessible and inexpensive, we performed SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2) whole genome sequencing and measured the sample-to-answer time and accuracy of this portable variant tracking tool. Our portable design determined the variant of SARS-CoV-2 in an infected individual within 9 hours and 15 minutes without external power or internet connection, surpassing the speed of previous portable tools. It took only 16 minutes to complete sequencing run, whole genome assembly, and lineage determination using a single standalone laptop. We then demonstrated the capability to produce 289 SARS-CoV-2 whole genome sequences in a single portable sequencing run, representing a significant improvement over an existing throughput of 96 sequences per run. We verified the accuracy of portable sequencing by comparison with two other independent sequencing methods. We showed that our high-throughput data consistently represented the circulating variants in Los Angeles, United States, when compared with publicly available sequences. Our scheme is designed to be flexible, rapid, and accurate, making it a valuable tool for large-scale surveillance operations in low- and middle-income countries as well as targeted surveys for vulnerable populations in remote locations.IMPORTANCEThere have been significant efforts to track COVID-19 (Coronavirus Disease 2019) variants, accumulating over 15 million SARS-CoV-2 sequences as of 2023. However, the distribution of global survey data is highly skewed, with nearly half of all countries having inadequate or low levels of genomic surveillance. In addition, indigenous peoples face more severe threats from COVID-19, due to their generally remote residence and unique social practices. Cost-effective portable sequencing tools have been used to investigate Ebola and Zika outbreaks. However, these tools have a sample-to-answer time of around 24 hours and require an internet connection for data transfer to an off-site cloud server. In our study, we rapidly determined COVID-19 variants using only small and inexpensive equipment, with a completion time of 9 hours and 15 minutes. Furthermore, we produced 289 near-full-length SARS-CoV-2 genome sequences from a single portable Nanopore sequencing run, representing a threefold increase in throughput compared with existing Nanopore sequencing methods.

Association between Comorbidities and Preserved Ratio Impaired Spirometry: Using the Korean National Health and Nutrition Examination Survey IV-VI.

BACKGROUND: Preserved ratio impaired spirometry (PRISm) patients have more frequent respiratory symptoms and an increased risk of mortality. However, studies on comorbidities in these patients are lacking. OBJECTIVES: We investigated the association between PRISm and comorbidities using the Korea National Health and Nutrition Examination Survey (KNHANES). METHOD: This cross-sectional study included participants aged ≥50 years from the KNHANES (2007-2015). Participants who did not undergo spirometry or performed inadequately were excluded. We classified participants into 3 groups according to spirometry: PRISm (forced expiratory volume in one second [FEV1] /forced vital capacity [FVC] ≥ 0.7 and FEV1 <80%), chronic obstructive pulmonary disease (COPD) (FEV1/ FVC <0.7), and normal. Multivariate logistic regression analyses were used to evaluate the risk of comorbidities in the PRISm group compared to that in the normal group. RESULT: The study included 17,515 participants: 12,777 (73.0%), 1,563 (8.9%), and 3,175 (18.1%) in normal, PRISm, and COPD groups, respectively. After adjustment for known risk factors of each disease, hypertension (adjusted odds ratio [95% confidence interval]; 1.31 [1.14-1.50]), diabetes (1.51 [1.29-1.78]), hypercholesterolemia (1.20 [1.04-1.37]), obesity (1.31 [1.15-1.48]), ischemic heart disease (1.58 [1.13-2.22]), chronic renal disease (2.31 [1.09-4.88]), and thyroid disease (1.41 [1.09-1.83]) risks were significantly higher in the PRISm group than in the normal group. The average number of comorbidities was 2.45 in the PRISm group, which was higher than that in the normal (2.1) and COPD (2.03) groups (p < 0.05). CONCLUSION: The number of comorbidities was significantly higher in the PRISm group than in others. Hypertension, diabetes, obesity, ischemic heart disease, chronic renal disease, and thyroid disease were associated with PRISm after adjustment for risk factors.

Microdrop Human Immunodeficiency Virus Sequencing for Incidence and Drug Resistance Surveillance.

BACKGROUND: Precise and cost-efficient human immunodeficiency virus (HIV) incidence and drug resistance surveillances are in high demand for the advancement of the 90-90-90 "treatment for all" target. METHODS: We developed microdrop HIV sequencing for the HIV incidence and drug resistance assay (HIDA), a single-blood-draw surveillance tool for incidence and drug resistance mutation (DRM) detection. We amplified full-length HIV envelope and pol gene sequences within microdroplets, and this compartmental amplification with long-read high-throughput sequencing enabled us to recover multiple unique sequences. RESULTS: We achieved greater precision in determining the stage of infection than current incidence assays, with a 1.2% false recency rate (proportion of misclassified chronic infections) and a 262-day mean duration of recent infection (average time span of recent infection classification) from 83 recently infected and 81 chronically infected individuals. Microdrop HIV sequencing demonstrated an increased capacity to detect minority variants and linked DRMs. By screening all 93 World Health Organization surveillance DRMs, we detected 6 pretreatment drug resistance mutations with 2.6%-13.2% prevalence and cross-linked mutations. CONCLUSIONS: HIDA with microdrop HIV sequencing may promote global HIV real-time surveillance by serving as a precise and high-throughput cross-sectional survey tool that can be generalized for surveillance of other pathogens.

Gut microbiome in people living with HIV is associated with impaired thiamine and folate syntheses.

People living with HIV have a high incidence of cardiovascular and neurological diseases as comorbid disorders that are commonly linked to inflammation. While microbial translocation can augment inflammation during HIV infection, functional microbiome shifts that may increase pro-inflammatory responses have not been fully characterized. In addition, defining HIV-induced microbiome changes has been complicated by high variability among individuals. Here we conducted functional annotation of previously-published 16S ribosomal RNA gene sequences of 305 HIV positive and 249 negative individuals, with adjustment for geographic region, sex, sexual behavior, and age. Metagenome profiles were inferred from these individuals' 16S data. HIV infection was associated with impaired microbial vitamin B synthesis; around half of the gene families in thiamine and folate biosynthesis pathways were significantly less abundant in the HIV positive group than the negative control. These results are consistent with the high prevalence of thiamine and folate deficiencies in HIV infections. These HIV-induced microbiota shifts have the potential to influence cardiovascular and neurocognitive diseases, given the documented associations between B-vitamin deficiencies, inflammation, and these diseases. We also observed that most essential amino acid biosynthesis pathways were downregulated in the microbiome of HIV-infected individuals. Microbial vitamin B and amino acid synthesis pathways were not significantly recovered by antiretroviral treatment when we compared 262 ART positive and 184 ART negative individuals. Our meta-analysis provides a new outlook for understanding vitamin B and amino acid deficiencies in HIV patients, suggesting that interventions for reversing HIV-induced microbiome shifts may aid in lessening the burdens of HIV comorbidities.

The Impact of Erosive Reflux Esophagitis on the Decline of Lung Function in the General Population.

BACKGROUND: The impact of reflux esophagitis on the decline of lung function has been rarely reported. This study was performed to evaluate the association between erosive reflux esophagitis and lung function changes. METHODS: We included patients with normal lung function who underwent esophagogastroduodenoscopy for health screening from a health screening center. Patients with persistent erosive reflux esophagitis on two discrete endoscopic examinations were designated as the erosive reflux esophagitis group. We also selected patients without erosive reflux esophagitis and matched them 1:4 with patients from the erosive reflux esophagitis group. We estimated annual forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) changes from baseline and compared these estimates by the linear mixed regression model. We also estimated the biannual incidence of chronic obstructive pulmonary disease (COPD). RESULTS: In total, 1,050 patients (210 patients with erosive reflux esophagitis, and 840 matched controls) were included. The median follow-up duration for spirometry was six years. In patients with erosive reflux esophagitis, mild reflux esophagitis (A grade) was most common (165 patients, 78.6%). The adjusted annual FEV1 change in patients with erosive reflux esophagitis was -51.8 mL/yr, while it decreased by 46.8 mL/yr in controls (P = 0.270). The adjusted annual FVC decline was similar between the two groups (-55.8 vs. -50.5 mL/yr, P = 0.215). The estimated COPD incidence during the follow-up period was not different between the erosive reflux esophagitis and control groups. CONCLUSION: In patients with normal lung function, the presence of erosive reflux esophagitis did not affect the annual declines in FEV1 or FVC.

HIITE: HIV-1 incidence and infection time estimator.

Motivation: Around 2.1 million new HIV-1 infections were reported in 2015, alerting that the HIV-1 epidemic remains a significant global health challenge. Precise incidence assessment strengthens epidemic monitoring efforts and guides strategy optimization for prevention programs. Estimating the onset time of HIV-1 infection can facilitate optimal clinical management and identify key populations largely responsible for epidemic spread and thereby infer HIV-1 transmission chains. Our goal is to develop a genomic assay estimating the incidence and infection time in a single cross-sectional survey setting. Results: We created a web-based platform, HIV-1 incidence and infection time estimator (HIITE), which processes envelope gene sequences using hierarchical clustering algorithms and informs the stage of infection, along with time since infection for incident cases. HIITE's performance was evaluated using 585 incident and 305 chronic specimens' envelope gene sequences collected from global cohorts including HIV-1 vaccine trial participants. HIITE precisely identified chronically infected individuals as being chronic with an error less than 1% and correctly classified 94% of recently infected individuals as being incident. Using a mixed-effect model, an incident specimen's time since infection was estimated from its single lineage diversity, showing 14% prediction error for time since infection. HIITE is the first algorithm to inform two key metrics from a single time point sequence sample. HIITE has the capacity for assessing not only population-level epidemic spread but also individual-level transmission events from a single survey, advancing HIV prevention and intervention programs. Availability and implementation: Web-based HIITE and source code of HIITE are available at http://www.hayounlee.org/software.html. Supplementary information: Supplementary data are available at Bioinformatics online.

CCMP: Software-as-a-service approach for fully-automated microbiome profiling.

Microbiome profiling holds great promise for the development of novel disease biomarkers and therapeutics. Next-generation sequencing is currently the preferred method for microbiome data collection and multiple standardized tools, packages, and pipelines have been developed for the purpose of raw data processing and microbial annotation. However, these currently available pipelines come with entry-level barriers such as high-performance hardware, software installation, and sequential command-line scripting that often deter end-users. We thus created Cloud Computing for Microbiome Profiling (CCMP, https://ccmp.usc.edu), a public cloud-based web tool which combines the analytical power of current microbiome analysis platforms with a user-friendly interface. CCMP is a free-of-charge software-as-a-service (SaaS) that simplifies user experience by enabling users to complete their analysis in a single step, uploading raw sequencing data files. Once users upload 16S ribosomal RNA gene sequence data, our pipeline performs taxonomic annotation, abundance profiling, and statistical tests to report microbiota signatures altered by diseases or experimental conditions. CCMP took a 125 gigabyte (GB) input of 16S ribosomal RNA gene sequence data from 1052 specimens in FASTQ format and reported figures and tables of taxonomic annotations, statistical tests, α and ß diversity calculations, and principal coordinate analyses within 21 h. CCMP is the first fully-automated web interface that integrates three key solutions for large-scale data analysis: cloud computing, fast file transfer technology, and microbiome analysis tools. As a reliable platform that supplies consistent microbiome analysis, CCMP will advance microbiome research by making effortful bioinformatics easily accessible to public.

SPMM: estimating infection duration of multivariant HIV-1 infections.

MOTIVATION: Illustrating how HIV-1 is transmitted and how it evolves in the following weeks is an important step for developing effective vaccination and prevention strategies. It is currently possible through DNA sequencing to account for the diverse array of viral strains within an infected individual. This provides an unprecedented opportunity to pinpoint when each patient was infected and which viruses were transmitted. RESULTS: Here we develop a mathematical tool for early HIV-1 evolution within a subject whose infection originates either from a single or multiple viral variants. The shifted Poisson mixture model (SPMM) provides a quantitative guideline for segregating viral lineages, which in turn enables us to assess when a subject was infected. The infection duration estimated by SPMM showed a statistically significant linear relationship with that by Fiebig laboratory staging (P = 0.00059) among 37 acutely infected subjects. Our tool provides a functional approach to understanding early genetic diversity, one of the most important parameters for deciphering HIV-1 transmission and predicting the rate of disease progression. AVAILABILITY AND IMPLEMENTATION: SPMM, webserver, is available at http://www.hayounlee.org/web-tools.html. CONTACT: hayoun@usc.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Analysis of Fifty Hotspot Mutations of Lung Squamous Cell Carcinoma in Never-smokers.

Smoking is the major risk factor for lung squamous cell carcinoma (SCC), although a small number of lung SCCs occurs in never-smokers. The purpose of this study was to compare 50 hotspot mutations of lung SCCs between never-smokers and smokers. We retrospectively reviewed the medical records of patients newly diagnosed with lung SCC between January 1, 2011 and December 31, 2013 in the Seoul National University Hospital. Formalin-fixed, paraffin-embedded tumor samples were used for analysis of hotspot mutations. Fifty cancer-related genes in never-smokers were compared to those in ever-smokers. Of 379 lung SCC patients, 19 (5.0%) were never-smokers. The median age of these 19 patients was 67 years (interquartile range 57-73 years), and 10 of these patients were women (52.5%). The incidence rates of stage I, II, III, and IV disease in this group were 26.4%, 5.3%, 31.6%, and 36.8%, respectively, and sequencing was performed successfully in 14 cases. In the 26 lung SCC tumor samples (12 from never-smokers and 14 from ever-smokers) sequenced using personal genome machine, the most common mutations were in TP53 (75.0%), RAS (66.7%), and STK11 (33.3%), but mutations were also found in EGFR, KIT, and PTEN. The distribution of hotspot mutations in never-smokers was similar to that in ever-smokers. There was no significant difference in overall survival between the 2 groups. The 50 hotspot mutations of lung SCC in never-smokers were similar to those of ever-smokers.

Molecular clock of HIV-1 envelope genes under early immune selection.

BACKGROUND: The molecular clock hypothesis that genes or proteins evolve at a constant rate is a key tool to reveal phylogenetic relationships among species. Using the molecular clock, we can trace an infection back to transmission using HIV-1 sequences from a single time point. Whether or not a strict molecular clock applies to HIV-1's early evolution in the presence of immune selection has not yet been fully examined. RESULTS: We identified molecular clock signatures from 1587 previously published HIV-1 full envelope gene sequences obtained since acute infection in 15 subjects. Each subject's sequence diversity linearly increased during the first 150 days post infection, with rates ranging from [Formula: see text] to [Formula: see text] with a mean of [Formula: see text] per base per day. The rate of diversification for 12 out of the 15 subjects was comparable to the neutral evolution rate. While temporal diversification was consistent with evolution patterns in the absence of selection, mutations from the founder virus were highly clustered on statistically identified selection sites, which diversified more than 65 times faster than non-selection sites. By mathematically quantifying deviations from the molecular clock under various selection scenarios, we demonstrate that the deviation from a constant clock becomes negligible as multiple escape lineages emerge. The most recent common ancestor of a virus pair from distinct escape lineages is most likely the transmitted founder virus, indicating that HIV-1 molecular dating is feasible even after the founder viruses are no longer detectable. CONCLUSIONS: The ability of HIV-1 to escape from immune surveillance in many different directions is the driving force of molecular clock persistence. This finding advances our understanding of the robustness of HIV-1's molecular clock under immune selection, implying the potential for molecular dating.

Developing high-throughput HIV incidence assay with pyrosequencing platform.

UNLABELLED: Human immunodeficiency virus (HIV) incidence is an important measure for monitoring the epidemic and evaluating the efficacy of intervention and prevention trials. This study developed a high-throughput, single-measure incidence assay by implementing a pyrosequencing platform. We devised a signal-masking bioinformatics pipeline, which yielded a process error rate of 5.8 × 10(-4) per base. The pipeline was then applied to analyze 18,434 envelope gene segments (HXB2 7212 to 7601) obtained from 12 incident and 24 chronic patients who had documented HIV-negative and/or -positive tests. The pyrosequencing data were cross-checked by using the single-genome-amplification (SGA) method to independently obtain 302 sequences from 13 patients. Using two genomic biomarkers that probe for the presence of similar sequences, the pyrosequencing platform correctly classified all 12 incident subjects (100% sensitivity) and 23 of 24 chronic subjects (96% specificity). One misclassified subject's chronic infection was correctly classified by conducting the same analysis with SGA data. The biomarkers were statistically associated across the two platforms, suggesting the assay's reproducibility and robustness. Sampling simulations showed that the biomarkers were tolerant of sequencing errors and template resampling, two factors most likely to affect the accuracy of pyrosequencing results. We observed comparable biomarker scores between AIDS and non-AIDS chronic patients (multivariate analysis of variance [MANOVA], P = 0.12), indicating that the stage of HIV disease itself does not affect the classification scheme. The high-throughput genomic HIV incidence marks a significant step toward determining incidence from a single measure in cross-sectional surveys. IMPORTANCE: Annual HIV incidence, the number of newly infected individuals within a year, is the key measure of monitoring the epidemic's rise and decline. Developing reliable assays differentiating recent from chronic infections has been a long-standing quest in the HIV community. Over the past 15 years, these assays have traditionally measured various HIV-specific antibodies, but recent technological advancements have expanded the diversity of proposed accurate, user-friendly, and financially viable tools. Here we designed a high-throughput genomic HIV incidence assay based on the signature imprinted in the HIV gene sequence population. By combining next-generation sequencing techniques with bioinformatics analysis, we demonstrated that genomic fingerprints are capable of distinguishing recently infected patients from chronically infected patients with high precision. Our high-throughput platform is expected to allow us to process many patients' samples from a single experiment, permitting the assay to be cost-effective for routine surveillance.

Portable Nanopore sequencing solution for next-generation HIV drug resistance testing.

BACKGROUND: Tackling HIV drug resistance is one of major challenges for ending AIDS epidemic, but the elevated expense of cutting-edge genomics hampers the advancement of HIV genotype testing for clinical care. METHODS: We developed a HIV genotype testing pipeline that centers on a cost-efficient portable Nanopore sequencer. Accuracy verification was conducted through comparison with parallel data obtained via fixed-site Pacbio sequencing. Our complete pol-gene sequencing strategy coupled with portable high-throughput sequencing was applied to identify drug resistance mutations across 58 samples sourced from the ART-treated Los Angeles General Medical Center Rand Schrader Clinic (LARSC) cohort (7 samples from 7 individuals) and the ART-naïve Center for HIV/AIDS Vaccine Immunology (CHAVI) cohort (51 samples from 38 individuals). RESULTS: A total of 472 HIV consensus sequences, each tagged with a unique molecular identifier, were produced from over 1.4 million bases acquired through portable Nanopore sequencing, which matched those obtained independently via Pacbio sequencing. With this desirable accuracy, we first documented the linkage of multidrug cross-resistance mutations across Integrase Strand Transfer inhibitors (INSTIs) and Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs) from an individual failing a second-generation INSTI regimen. By producing more than 500 full-length HIV pol gene sequences in a single portable sequencing run, we detected Protease Inhibitor (PI), Nucleoside Reverse Transcriptase Inhibitor (NRTI), NNRTI and INSTI resistance mutations. All drug resistance mutations identified through portable sequencing were cross-validated using fixed-site Pacbio sequencing. CONCLUSIONS: Our accurate and affordable HIV drug resistance testing solution is adaptable for both individual patient care and large-scale surveillance initiatives.

Full-spectrum HIV drug resistance mutation detection by high-resolution complete pol gene sequencing.

BACKGROUND: Drug resistance mutation testing is a key element for HIV clinical management, informing effective treatment regimens. However, resistance screening in current clinical practice is limited in reporting linked cross-class resistance mutations and minority variants, both of which may increase the risk of virological failure. METHODS: To address these limitations, we obtained 358 full-length pol gene sequences from 52 specimens of 20 HIV infected individuals by combining microdroplet amplification, unique molecular identifier (UMI) labeling, and long-read high-throughput sequencing. RESULTS: We conducted a rigorous assessment of the accuracy of our pipeline for precision drug resistance mutation detection, verifying that a sequencing depth of 35 high-throughput reads achieved complete, error-free pol gene sequencing. We detected 26 distinct drug resistance mutations to Protease Inhibitors (PIs), Nucleoside Reverse Transcriptase Inhibitors (NRTIs), Non-Nucleoside Reverse Transcriptase Inhibitors (NNRTIs), and Integrase Strand Transfer Inhibitors (INSTIs). We detected linked cross-class drug resistance mutations (PI+NRTI, PI+NNRTI, and NRTI+NNRTI) that confer cross-resistance to multiple drugs in different classes. Fourteen different types of minority mutations were also detected with frequencies ranging from 3.2% to 19%, and the presence of these mutations was verified by Sanger reference sequencing. We detected a putative transmitted drug resistance mutation (TDRM) in one individual that persisted for over seven months from the first sample collected at the acute stage of infection prior to seroconversion. CONCLUSIONS: Our comprehensive drug resistance mutation profiling can advance clinical practice by reporting mutation linkage and minority variants to better guide antiretroviral therapy options.

Immune cell identifier and classifier (ImmunIC) for single cell transcriptomic readouts.

Single cell RNA sequencing has a central role in immune profiling, identifying specific immune cells as disease markers and suggesting therapeutic target genes of immune cells. Immune cell-type annotation from single cell transcriptomics is in high demand for dissecting complex immune signatures from multicellular blood and organ samples. However, accurate cell type assignment from single-cell RNA sequencing data alone is complicated by a high level of gene expression heterogeneity. Many computational methods have been developed to respond to this challenge, but immune cell annotation accuracy is not highly desirable. We present ImmunIC, a simple and robust tool for immune cell identification and classification by combining marker genes with a machine learning method. With over two million immune cells and half-million non-immune cells from 66 single cell RNA sequencing studies, ImmunIC shows 98% accuracy in the identification of immune cells. ImmunIC outperforms existing immune cell classifiers, categorizing into ten immune cell types with 92% accuracy. We determine peripheral blood mononuclear cell compositions of severe COVID-19 cases and healthy controls using previously published single cell transcriptomic data, permitting the identification of immune cell-type specific differential pathways. Our publicly available tool can maximize the utility of single cell RNA profiling by functioning as a stand-alone bioinformatic cell sorter, advancing cell-type specific immune profiling for the discovery of disease-specific immune signatures and therapeutic targets.

Precision detection of recent HIV infections using high-throughput genomic incidence assay.

HIV incidence is a key measure for tracking disease spread and identifying populations and geographic regions where new infections are most concentrated. The HIV sequence population provides a robust signal for the stage of infection. Large-scale and high-precision HIV sequencing is crucial for effective genomic incidence surveillance. We produced 1,034 full-length envelope gene sequences from a seroconversion cohort by conducting HIV microdrop sequencing and measuring the genomic incidence assay's genome similarity index (GSI) dynamics. The measured dynamics of 9 of 12 individuals aligned with the GSI distribution estimated independently using 417 publicly available incident samples. We enhanced the capacity to identify individuals with recent infections, achieving predicted detection accuracies of 92% (89%-94%) for cases within 6 months and 81% (74%-87%) for cases within 9 months. These accuracy levels agreed with the observed detection accuracy intervals of an independent validation data set. Additionally, we produced 131 full-length envelope gene sequences from eight individuals with chronic HIV infection. This analysis confirmed a false recency rate (FRR) of 0%, which was consistent with 162 publicly available chronic samples. The mean duration of recent infection (MDRI) was 238 (209-267) days, indicating an 83% improvement in performance compared to current recent infection testing algorithms. The shifted Poisson mixture model was then used to estimate the time since infection, and the model estimates showed an 88% consistency with the days post infection derived from HIV RNA test dates and/or seroconversion dates. HIV microdrop sequencing provides unique prospects for large-scale incidence surveillance using high-throughput sequencing. IMPORTANCE Accurate identification of recently infected individuals is vital for prioritizing specific populations for interventions, reducing onward transmission risks, and optimizing public health services. However, current HIV-specific antibody-based methods have not been satisfactory in accurately identifying incident cases, hindering the use of HIV recency testing for prevention efforts and partner protection. Genomic incidence assays offer a promising alternative for identifying recent infections. In our study, we used microdroplet technologies to produce a large number of complete HIV envelope gene sequences, enabling the accurate detection of early infection signs. We assessed the dynamics of the incidence assay's metrics and compared them with statistical models. Our approach demonstrated high accuracy in identifying individuals with recent infections, achieving predicted detection rates exceeding 90% within 6 months and over 80% within 9 months of infection. This high-resolution method holds significant potential for enhancing the effectiveness of HIV incidence screening for case-based surveillance in public health initiatives.

Mathematical modeling of ultradeep sequencing data reveals that acute CD8+ T-lymphocyte responses exert strong selective pressure in simian immunodeficiency virus-infected macaques but still fail to clear founder epitope sequences.

The prominent role of antiviral cytotoxic CD8(+) T-lymphocytes (CD8-TL) in containing the acute viremia of human and simian immunodeficiency viruses (HIV-1 and SIV) has rationalized the development of T-cell-based vaccines. However, the presence of escape mutations in the acute stage of infection has raised a concern that accelerated escape from vaccine-induced CD8-TL responses might undermine vaccine efficacy. We reanalyzed previously published data of 101,822 viral genomes of three CD8-TL epitopes, Nef(103-111)RM9 (RM9), Tat(28-35)SL8 (SL8), and Gag(181-189)CM9 (CM9), sampled by ultradeep pyrosequencing from eight macaques. Multiple epitope variants appeared during the resolution of acute viremia, followed by the predominance of a single mutant epitope. By fitting a mathematical model, we estimated the first acute escape rate as 0.36 day(-1) within escape-prone epitopes, RM9 and SL8, and the chronic escape rate as 0.014 day(-1) within the CM9 epitope. Our estimate of SIV acute escape rates was found to be comparable to very early HIV-1 escape rates. The timing of the first escape was more highly correlated with the timing of the peak CD8-TL response than with the magnitude of the CD8-TL response. The transmitted epitope decayed more than 400 times faster during the acute viral decline stage than predicted by a neutral evolution model. However, the founder epitope persisted as a minor population even at the viral set point; in contrast, the majority of acute escape epitopes were completely cleared. Our results suggest that a reservoir of SIV infection is preferentially formed by virus with the transmitted epitope.

High-precision and cost-efficient sequencing for real-time COVID-19 surveillance.

COVID-19 global cases have climbed to more than 33 million, with over a million total deaths, as of September, 2020. Real-time massive SARS-CoV-2 whole genome sequencing is key to tracking chains of transmission and estimating the origin of disease outbreaks. Yet no methods have simultaneously achieved high precision, simple workflow, and low cost. We developed a high-precision, cost-efficient SARS-CoV-2 whole genome sequencing platform for COVID-19 genomic surveillance, CorvGenSurv (Coronavirus Genomic Surveillance). CorvGenSurv directly amplified viral RNA from COVID-19 patients' Nasopharyngeal/Oropharyngeal (NP/OP) swab specimens and sequenced the SARS-CoV-2 whole genome in three segments by long-read, high-throughput sequencing. Sequencing of the whole genome in three segments significantly reduced sequencing data waste, thereby preventing dropouts in genome coverage. We validated the precision of our pipeline by both control genomic RNA sequencing and Sanger sequencing. We produced near full-length whole genome sequences from individuals who were COVID-19 test positive during April to June 2020 in Los Angeles County, California, USA. These sequences were highly diverse in the G clade with nine novel amino acid mutations including NSP12-M755I and ORF8-V117F. With its readily adaptable design, CorvGenSurv grants wide access to genomic surveillance, permitting immediate public health response to sudden threats.

Comparing Inhaler Use Technique Based on Inhaler Type in Elderly Patients with Respiratory Disease.

BACKGROUND: The aim of this study was to investigate inhaler device handling in elderly patients. Inhaler devices with respect to misuse and error correction were also compared. METHODS: Inhaler use technique was assessed using standardized checklists at the first visit and 3-month follow-up visit after retraining. The primary outcome was difference in the acceptable use ratio among inhaler devices. Secondary outcomes included differences in error correction, the most common step of misuse, and factors affecting the accuracy of inhaler use. RESULTS: A total of 251 patients (mean age, 76.4 years) were included. The handling of 320 devices was assessed in the study. All patients had been trained before. However, only 24.7% of them used inhalers correctly. Proportions of acceptable use for Evohaler, Respimat, Turbuhaler, Ellipta, and Breezhaler/Handihaler were 38.7%, 50.0%, 61.4%, 60.8%, and 43.2%, respectively (p=0.026). At the second visit, the acceptable use ratio had increased. There were no significant differences among inhaler types (Evohaler, 63.9%; Respimat, 86.1%; Turbuhaler, 74.3%; Ellipta, 64.6%; and Breezhaler/Handihaler, 65.3% [p=0.129]). In multivariate analysis, body mass index, Turbuhaler, and Ellipta showed positive correlations with acceptable use of inhalers, whereas Chronic Obstructive Pulmonary Disease Assessment Test score showed a negative correlation. CONCLUSION: Although new inhalers have been developed, the accuracy of inhaler use remains low. Elderly patients showed more errors when using pressurized metered-dose inhalers than using dry powder inhalers and soft-mist inhalers. However, there were no significant differences in misuse among inhaler devices after individual training. Results of this study suggests that repeat training is more important than inhaler type.

Genomic investigation of the coronavirus disease-2019 outbreak in the Republic of Korea.

The South Korean government effectively contained the coronavirus disease-2019 (COVID-19) outbreak primarily associated with a religious group. We conducted SARS-CoV-2 whole genome sequencing of 66 cases to investigate connections among the initial South Korean cases and the religious group outbreak. We assessed the accuracy of genomic investigation by comparing the whole genome sequences with comprehensive contact tracing records. Five transmission clusters were estimated among the 15 initial cases. The six close-contact cases and two potential exposure pairs identified by contact tracing showed two or fewer nucleotide base differences. Additionally, we identified two transmission clusters that were phylogenetically distinct from the initial clusters, sharing common G11083T, G26144T, and C14805T markers. The strain closest to the two additional clusters was identified from a pair of identical sequences isolated from individuals who traveled from Wuhan to Italy. Our findings provide insights into the origins of community spread of COVID-19.