pTrimmer: An efficient tool to trim primers of multiplex deep sequencing data

STRsensor: a computationally efficient method for STR allele-typing from massively parallel sequencing data

Short tandem repeats (STRs) represent one of the most polymorphic variations in the human genome, finding extensive applications in forensics, population genetics and medical genetics. In contrast to the traditional capillary electrophoresis (CE) method, genotyping STRs using massive parallel sequencing technology offers enhanced sensitivity and accuracy. However, current methods are mainly designed for target sequencing with higher coverage for a specific STR locus, thereby constraining the utility of STRs in low- and medium-coverage whole genome sequencing (WGS) data. Here, we introduce STRsensor, a method designed to type STR alleles in low-coverage WGS data and target sequencing data, achieving a significant high detection ratio and accuracy. STRsensor employs two methods for STR allele-typing: the Kmers-based method and the CIGAR-based method. Furthermore, by incorporating a model for PCR stutters, STRsensor greatly enhances the accuracy of STR allele typing. With simulation data, we demonstrate that STRsensor achieves a detection ratio of 100$\%$ and an accuracy of 99.37$\%$ for a 30$\times $ WGS data, outperforming the existing methods, such as STRait Razor, STRinNGS, and HipSTR. When applied to real target sequencing data from 687 individuals, STRsensor achieves a detection ratio of 99.64$\%$ and an accuracy of 99.99$\%$. Moreover, STRsensor is a computationally efficient method that runs 79 times faster than HipSTR and 10 000 times faster than STRinNGS. STRsensor is freely available on GitHub: https://github.com/ChenHuaLab/STRsensor.

How Gut Microbiome Perturbation Caused by Antibiotic Pre-Treatments Affected the Conjugative Transfer of Antimicrobial Resistance Genes

The global spread of antimicrobial resistance genes (ARGs) poses a significant threat to public health. While antibiotics effectively treat bacterial infections, they can also induce gut dysbiosis, the severity of which varies depending on the specific antibiotic treatment used. However, it remains unclear how gut dysbiosis affects the mobility and dynamics of ARGs. To address this, mice were pre-treated with streptomycin, ampicillin, or sulfamethazine, and then orally inoculated with Salmonella enterica serovar Typhimurium and S. Heidelberg carrying a multi-drug resistance IncA/C plasmid. The streptomycin pre-treatment caused severe microbiome perturbation, promoting the high-density colonization of S. Heidelberg and S. Typhimurium, and enabling an IncA/C transfer from S. Heidelberg to S. Typhimurium and a commensal Escherichia coli. The ampicillin pre-treatment induced moderate microbiome perturbation, supporting only S. Heidelberg colonization and the IncA/C transfer to commensal E. coli. The sulfamethazine pre-treatment led to mild microbiome perturbation, favoring neither Salmonella spp. colonization nor a conjugative plasmid transfer. The degree of gut dysbiosis also influenced the enrichment or depletion of the ARGs associated with mobile plasmids or core commensal bacteria, respectively. These findings underscore the significance of pre-existing gut dysbiosis induced by various antibiotic treatments on ARG dissemination and may inform prudent antibiotic use practices.

Molecular and transcriptomic analysis of the ovary during laying and brooding stages in Zhedong white geese (Anser cygnoides domesticus)

1. This study investigates the molecular mechanisms affecting brooding in Zhedong white geese by examining differences in reproductive endocrine levels, ovarian histology and transcriptomics.2. Twenty 18-month-old Zhedong white geese were selected to examine their ovaries using histological, biochemical, molecular biological, and high-throughput sequencing techniques during the laying and brooding periods.3. The results showed that the number of atretic follicles and apoptotic cells in the ovaries increased significantly (p < 0.05), the levels of follicle-stimulating hormone, luteinising hormone, gonadotropin-releasing hormone and oestradiol decreased significantly (p < 0.05), and the level of prolactin increased significantly (p < 0.01) during the brooding stage.4. In broody geese, the expression of CASP3, CASP9, P53, BAX, and Cyt-c were considerably higher (p < 0.05), but BCL2 expression was significantly lower (p < 0.05).5. In ovarian tissues, 260 differentially expressed lncRNAs, 13 differentially expressed miRNA and 60 differentially expressed mRNA were all discovered using transcriptome sequencing analysis. Functional enrichment analysis revealed that the differentially expressed mRNA and non-coding RNA target genes were primarily involved in ECM-receptor interaction, cell adhesion, cardiac muscle contraction, mTOR signalling, and the calcium signalling pathway.6. In conclusion, follicular atrophy and apoptosis occurred in the ovaries and serum reproductive hormone levels were significantly changed during the brooding period of Zhedong white geese. COL3A1, COL1A2, GRIA1, RNF152, miR-192, and miR-194 may be important candidates for the regulation of brooding behaviour, with the mTOR signalling pathway playing a key role.

The emergence, impact, and evolution of human metapneumovirus variants from 2014 to 2021 in Spain

BACKGROUND

Human metapneumovirus (HMPV) is an important aetiologic agent of respiratory tract infection (RTI). This study aimed to describe the prevalence, genetic diversity, and evolutionary dynamics of HMPV.

METHODS

Laboratory-confirmed HMPV were characterised based on partial-coding G gene sequences with MEGA.v6.0. WGS was performed with Illumina, and evolutionary analyses with Datamonkey and Nextstrain.

RESULTS

HMPV prevalence was 2.5%, peaking in February-April and with an alternation in the predominance of HMPV-A and -B until the emergence of SARS-CoV-2, not circulating until summer and autumn-winter 2021, with a higher prevalence and with the almost only circulation of A2c_111dup. G and SH proteins were the most variable, and 70% of F protein was under negative selection. Mutation rate of HMPV genome was 6.95 ×10^-4 substitutions/site/year.

CONCLUSION

HMPV showed a significant morbidity until the emergence of SARS-CoV-2 pandemic in 2020, not circulating again until summer and autumn 2021, with a higher prevalence and with almost the only circulation of A2c_111dup, probably due to a more efficient immune evasion mechanism. The F protein showed a very conserved nature, supporting the need for steric shielding. The tMRCA showed a recent emergence of the A2c variants carrying duplications, supporting the importance of virological surveillance.

Local monitoring of SARS-CoV-2 variants in two large California counties in 2021

Coronavirus Disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continues to persist due to mutations resulting in newer, more infectious variants of concern. We aimed to leverage an ongoing private SARS-CoV-2 testing laboratory's infrastructure to monitor SARS-CoV-2 variants in two large California counties. Study enrollment was offered to adults aged 18 years or older in Los Angeles County and Riverside County who recently tested positive for SARS-CoV-2 with a polymerase chain reaction (PCR) assay. A cycle threshold value less than or equal to 30 cycles was considered a positive test for sequencing purposes. Within 5 days of study enrollment, clinician-monitored, self-collected oral fluid and anterior nares swab specimens were obtained from participants. Specimens were transported and stored at 8 °C or cooler. Samples underwent ribonucleic acid extraction, library preparation, and sequencing. SARS-CoV-2 lineages were identified using sequencing data. Participant and genomic data were analyzed using statistical tools and visualized with toolkits. The study was approved by Advarra Institutional Review Board (Pro00053729). From May 27, 2021 to September 9, 2021, 503 individuals were enrolled and underwent specimen collection. Of the 503 participants, 238 (47.3%) participants were women, 329 (63.6%) participants were vaccinated, and 221 (43.9%) participants were of Hispanic or Spanish origin. Of the cohort, 496 (98.6%) participants had symptoms at the time of collection. Among the 503 samples, 443 (88.1%) nasal specimens and 353 (70.2%) oral specimens yielded positive sequencing results. Over our study period, the prevalence of the Alpha variant of SARS-CoV-2 decreased (initially 23.1% [95% confidence interval (95% CI): 0-0.49%] to 0% [95% CI 0.0-0.0%]) as the prevalence of the Delta variant of SARS-CoV-2 increased (initially 33.3% [95% CI 0.0-100.0%] to 100.0% [95% CI 100.0-100.0%]). A strain that carried mutations of both Delta and Mu was identified. We found that outpatient SARS-CoV-2 variant surveillance could be conducted in a timely and accurate manner. The prevalence of different variants changed over time. A higher proportion of nasal specimens yielded results versus oral specimens. Timely and regional outpatient SARS-CoV-2 variant surveillance could be used for public health efforts to identify changes in SARS-CoV-2 strain epidemiology.

COVID-19 Whole-Genome Resequencing with Redundant Tiling PCR and Subtract-Based Amplicon Normalization Successfully Characterized SARS-CoV-2 Variants in Clinical Specimens

With an increasing number of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) sequences gathered worldwide, we recognize that deletion mutants and nucleotide substitutions that may affect whole-genome sequencing are accumulating. Here, we propose an additional strategy for tiling PCR for whole-genome resequencing, which can make the pipeline robust for mutations at the primer annealing site by a redundant amplicon scheme. We further demonstrated that subtracting overrepresented amplicons from the multiplex PCR products reduced the bias of the next-generation sequencing (NGS) library, resulting in decreasing required sequencing reads per sample. We applied this sequencing strategy to clinical specimens collected in Bangladesh. More than 80% out of the 304 samples were successfully sequenced. Less than 5% were ambiguous nucleotides, and several known variants were detected. With the additional strategies presented here, we believe that whole-genome resequencing of SARS-CoV-2 from clinical samples can be optimized.

Drivers of adaptive evolution during chronic SARS-CoV-2 infections

In some immunocompromised patients with chronic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, considerable adaptive evolution occurs. Some substitutions found in chronic infections are lineage-defining mutations in variants of concern (VOCs), which has led to the hypothesis that VOCs emerged from chronic infections. In this study, we searched for drivers of VOC-like emergence by consolidating sequencing results from a set of 27 chronic infections. Most substitutions in this set reflected lineage-defining VOC mutations; however, a subset of mutations associated with successful global transmission was absent from chronic infections. We further tested the ability to associate antibody evasion mutations with patient-specific and virus-specific features and found that viral rebound is strongly correlated with the emergence of antibody evasion. We found evidence for dynamic polymorphic viral populations in most patients, suggesting that a compromised immune system selects for antibody evasion in particular niches in a patient’s body. We suggest that a tradeoff exists between antibody evasion and transmissibility and that extensive monitoring of chronic infections is necessary to further understanding of VOC emergence.

Analysis of mutations that arise in chronic SARS-CoV-2 infections shows both overlap and differences with mutations present in pandemic viral variants of concern, highlighting their distinct drivers of evolution.

Association between germline pathogenic variants and breast cancer risk in Japanese women: The HERPACC study

Approximately 5%-10% of breast cancers are hereditary, caused by germline pathogenic variants (GPVs) in breast cancer predisposition genes. To date, most studies of the prevalence of GPVs and risk of breast cancer for each gene based on cases and noncancer controls have been conducted in Europe and the United States, and little information from Japanese populations is available. Furthermore, no studies considered confounding by established environmental factors and single-nucleotide polymorphisms (SNPs) identified in genome-wide association studies (GWAS) together in GPV evaluation. To evaluate the association between GPVs in nine established breast cancer predisposition genes including BRCA1/2 and breast cancer risk in Japanese women comprehensively, we conducted a case-control study within the Hospital-based Epidemiologic Research Program at Aichi Cancer Center (629 cases and 1153 controls). The associations between GPVs and the risk of breast cancer were assessed by odds ratios (OR) and 95% confidence intervals (CI) using logistic regression models adjusted for potential confounders. A total of 25 GPVs were detected among all cases (4.0%: 95% CI: 2.6-5.9), whereas four individuals carried GPVs in all controls (0.4%). The OR for breast cancer by all GPVs and by GPVs in BRCA1/2 was 12.2 (4.4-34.0, p = 1.74E-06) and 16.0 (4.2-60.9, p = 5.03E-0.5), respectively. A potential confounding with GPVs was observed for the GWAS-identified SNPs, whereas not for established environmental risk factors. In conclusion, GPVs increase the risk of breast cancer in Japanese women regardless of environmental factors and GWAS-identified SNPs. Future studies investigating interactions with environment and SNPs are warranted.

The ViReflow pipeline enables user friendly large scale viral consensus genome reconstruction

Throughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in < 10 min, with no user intervention. ViReflow’s simplicity, flexibility, and scalability make it an ideal tool for viral molecular epidemiological efforts.

SARS-CoV-2 Genome Sequences, Including One with an ORF7a Deletion, Obtained from Patients in Bangladesh

Genomic sequences from a complete SARS-CoV-2 open reading frame (ORF) were obtained from 24 patients diagnosed in May 2020 in Dhaka, Bangladesh. All sequences belonged to clade 20A or 20B, and none were variants of concern. Interestingly, one sequence showed a 161-nucleotide deletion in ORF7a.

Genome-resolved metagenomics using environmental and clinical samples

Recent advances in high-throughput sequencing technologies and computational methods have added a new dimension to metagenomic data analysis i.e. genome-resolved metagenomics. In general terms, it refers to the recovery of draft or high-quality microbial genomes and their taxonomic classification and functional annotation. In recent years, several studies have utilized the genome-resolved metagenome analysis approach and identified previously unknown microbial species from human and environmental metagenomes. In this review, we describe genome-resolved metagenome analysis as a series of four necessary steps: (i) preprocessing of the sequencing reads, (ii) de novo metagenome assembly, (iii) genome binning and (iv) taxonomic and functional analysis of the recovered genomes. For each of these four steps, we discuss the most commonly used tools and the currently available pipelines to guide the scientific community in the recovery and subsequent analyses of genomes from any metagenome sample. Furthermore, we also discuss the tools required for validation of assembly quality as well as for improving quality of the recovered genomes. We also highlight the currently available pipelines that can be used to automate the whole analysis without having advanced bioinformatics knowledge. Finally, we will highlight the most widely adapted and actively maintained tools and pipelines that can be helpful to the scientific community in decision making before they commence the analysis.

Evidence for increased breakthrough rates of SARS-CoV-2 variants of concern in BNT162b2-mRNA-vaccinated individuals

The BNT162b2 mRNA vaccine is highly effective against SARS-CoV-2. However, apprehension exists that variants of concern (VOCs) may evade vaccine protection, due to evidence of reduced neutralization of the VOCs B.1.1.7 and B.1.351 by vaccine sera in laboratory assays. We performed a matched cohort study to examine the distribution of VOCs in infections of BNT162b2 mRNA vaccinees from Clalit Health Services (Israel) using viral genomic sequencing, and hypothesized that if vaccine effectiveness against a VOC is reduced, its proportion among breakthrough cases would be higher than in unvaccinated controls. Analyzing 813 viral genome sequences from nasopharyngeal swabs, we showed that vaccinees who tested positive at least 7 days after the second dose were disproportionally infected with B.1.351, compared with controls. Those who tested positive between 2 weeks after the first dose and 6 days after the second dose were disproportionally infected by B.1.1.7. These findings suggest reduced vaccine effectiveness against both VOCs within particular time windows. Our results emphasize the importance of rigorously tracking viral variants, and of increasing vaccination to prevent the spread of VOCs.

Rapid SARS-CoV-2 variant monitoring using PCR confirmed by whole genome sequencing in a high-volume diagnostic laboratory

OBJECTIVES

The emerging SARS-CoV-2 variants of concern (VoC), B.1.1.7, B.1.351 and P.1, with increased transmission and/or immune evasion, emphasise the need for broad and rapid variant monitoring. Our high-volume laboratory introduced a PCR variant assay (Variant PCR) in January 2021 based on the protocol by Vogels et al. STUDY DESIGN: To assess whether Variant PCR could be used for rapid B.1.1.7, B.1.351 and P.1 screening, all positive SARS-CoV-2 airway samples were prospectively tested in parallel using both the Variant PCR and whole genome sequencing (WGS).

RESULTS

In total 1,642 SARS-CoV-2 positive samples from individual patients were tested within a time span of 4 weeks. For all samples with valid results from both Variant PCR and WGS, no VoC was missed by Variant PCR (totalling 399 VoC detected). Conversely, all of the samples identified as "other lineages" (i.e., "non-VoC lineages") by the Variant PCR, were confirmed by WGS.

CONCLUSIONS

The Variant PCR based on the protocol by Vogels et al., is an effective method for rapid screening for VoC, applicable for most diagnostic laboratories within a pandemic setting. WGS is still required to confirm the identity of certain variants and for continuous surveillance of emerging VoC.

A Large-Scale and Serverless Computational Approach for Improving Quality of NGS Data Supporting Big Multi-Omics Data Analyses

Various types of analyses performed over multi-omics data are driven today by next-generation sequencing (NGS) techniques that produce large volumes of DNA/RNA sequences. Although many tools allow for parallel processing of NGS data in a Big Data distributed environment, they do not facilitate the improvement of the quality of NGS data for a large scale in a simple declarative manner. Meanwhile, large sequencing projects and routine DNA/RNA sequencing associated with molecular profiling of diseases for personalized treatment require both good quality data and appropriate infrastructure for efficient storing and processing of the data. To solve the problems, we adapt the concept of Data Lake for storing and processing big NGS data. We also propose a dedicated library that allows cleaning the DNA/RNA sequences obtained with single-read and paired-end sequencing techniques. To accommodate the growth of NGS data, our solution is largely scalable on the Cloud and may rapidly and flexibly adjust to the amount of data that should be processed. Moreover, to simplify the utilization of the data cleaning methods and implementation of other phases of data analysis workflows, our library extends the declarative U-SQL query language providing a set of capabilities for data extraction, processing, and storing. The results of our experiments prove that the whole solution supports requirements for ample storage and highly parallel, scalable processing that accompanies NGS-based multi-omics data analyses.

Nanobodies from camelid mice and llamas neutralize SARS-CoV-2 variants

Since the start of the COVID-19 pandemic, SARS-CoV-2 has caused millions of deaths worldwide. Although a number of vaccines have been deployed, the continual evolution of the receptor-binding domain (RBD) of the virus has challenged their efficacy. In particular, the emerging variants B.1.1.7, B.1.351 and P.1 (first detected in the UK, South Africa and Brazil, respectively) have compromised the efficacy of sera from patients who have recovered from COVID-19 and immunotherapies that have received emergency use authorization1-3. One potential alternative to avert viral escape is the use of camelid VHHs (variable heavy chain domains of heavy chain antibody (also known as nanobodies)), which can recognize epitopes that are often inaccessible to conventional antibodies4. Here, we isolate anti-RBD nanobodies from llamas and from mice that we engineered to produce VHHs cloned from alpacas, dromedaries and Bactrian camels. We identified two groups of highly neutralizing nanobodies. Group 1 circumvents antigenic drift by recognizing an RBD region that is highly conserved in coronaviruses but rarely targeted by human antibodies. Group 2 is almost exclusively focused to the RBD-ACE2 interface and does not neutralize SARS-CoV-2 variants that carry E484K or N501Y substitutions. However, nanobodies in group 2 retain full neutralization activity against these variants when expressed as homotrimers, and-to our knowledge-rival the most potent antibodies against SARS-CoV-2 that have been produced to date. These findings suggest that multivalent nanobodies overcome SARS-CoV-2 mutations through two separate mechanisms: enhanced avidity for the ACE2-binding domain and recognition of conserved epitopes that are largely inaccessible to human antibodies. Therefore, although new SARS-CoV-2 mutants will continue to emerge, nanobodies represent promising tools to prevent COVID-19 mortality when vaccines are compromised.

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.

Full genome viral sequences inform patterns of SARS-CoV-2 spread into and within Israel

Full genome sequences are increasingly used to track the geographic spread and transmission dynamics of viral pathogens. Here, with a focus on Israel, we sequence 212 SARS-CoV-2 sequences and use them to perform a comprehensive analysis to trace the origins and spread of the virus. We find that travelers returning from the United States of America significantly contributed to viral spread in Israel, more than their proportion in incoming infected travelers. Using phylodynamic analysis, we estimate that the basic reproduction number of the virus was initially around 2.5, dropping by more than two-thirds following the implementation of social distancing measures. We further report high levels of transmission heterogeneity in SARS-CoV-2 spread, with between 2-10% of infected individuals resulting in 80% of secondary infections. Overall, our findings demonstrate the effectiveness of social distancing measures for reducing viral spread.