Metagenomic Sequencing To Detect Respiratory Viruses in Persons under Investigation for COVID-19

The effects of sequencing strategies on Metagenomic pathogen detection using bronchoalveolar lavage fluid samples

Objectives

Metagenomic next-generation sequencing (mNGS) is a powerful tool for pathogen detection. The accuracy depends on both wet lab and dry lab procedures. The objective of our study was to assess the influence of read length and dataset size on pathogen detection.

Methods

In this study, 43 clinical BALF samples, which tested positive via clinical mNGS and were consistent with the diagnosis, were subjected to re-sequencing on the Illumina NovaSeq 6000 platform. The raw re-sequencing data, consisting of 100 million (M) paired-end 150 bp (PE150) reads, were divided into simulated datasets with eight different data sizes (5 M, 10 M, 15 M, 20 M, 30 M, 50 M, 75 M, 100 M) and five different read lengths (single-end 50 bp (SE50), SE75, SE100, PE100, and PE150). Both Kraken2 and IDseq bioinformatics pipelines were employed to analyze the previously diagnosed pathogens in the simulated data. Detection of pathogens was based on read counts ranging from 1 to 10 and RPM values ranging from 0.2 to 2.

Results

Our results revealed that increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection. However, a larger data sizes for mNGS require higher economic costs and longer turnaround time for data analysis. Our findings indicate 20 M reads being sufficient for SE75 mode to achieve high recall rates. Additionally, high nucleic acid loads in samples can lead to increased stability in pathogen detection efficiency, reducing the impact of sequencing strategies. The choice of bioinformatics pipelines had a significant impact on recall rates achieved in pathogen detection.

Conclusions

Increasing dataset sizes and read lengths can enhance the performance of mNGS in pathogen detection but increase the economic and time costs of sequencing and data analysis. Currently, the 20 M reads in SE75 mode may be the best sequencing option.

Exploring the Complexity of the Human Respiratory Virome through an In Silico Analysis of Shotgun Metagenomic Data Retrieved from Public Repositories

BACKGROUND

Respiratory viruses significantly impact global morbidity and mortality, causing more disease in humans than any other infectious agent. Beyond pathogens, various viruses and bacteria colonize the respiratory tract without causing disease, potentially influencing respiratory diseases' pathogenesis. Nevertheless, our understanding of respiratory microbiota is limited by technical constraints, predominantly focusing on bacteria and neglecting crucial populations like viruses. Despite recent efforts to improve our understanding of viral diversity in the human body, our knowledge of viral diversity associated with the human respiratory tract remains limited.

METHODS

Following a comprehensive search in bibliographic and sequencing data repositories using keyword terms, we retrieved shotgun metagenomic data from public repositories (n = 85). After manual curation, sequencing data files from 43 studies were analyzed using EVEREST (pipEline for Viral assEmbly and chaRactEriSaTion). Complete and high-quality contigs were further assessed for genomic and taxonomic characterization.

RESULTS

Viral contigs were obtained from 194 out of the 868 FASTQ files processed through EVEREST. Of the 1842 contigs that were quality assessed, 8% (n = 146) were classified as complete/high-quality genomes. Most of the identified viral contigs were taxonomically classified as bacteriophages, with taxonomic resolution ranging from the superkingdom level down to the species level. Captured contigs were spread across 25 putative families and varied between RNA and DNA viruses, including previously uncharacterized viral genomes. Of note, airway samples also contained virus(es) characteristic of the human gastrointestinal tract, which have not been previously described as part of the lung virome. Additionally, by performing a meta-analysis of the integrated datasets, ecological trends within viral populations linked to human disease states and their biogeographical distribution along the respiratory tract were observed.

CONCLUSION

By leveraging publicly available repositories of shotgun metagenomic data, the present study provides new insights into viral genomes associated with specimens from the human respiratory tract across different disease spectra. Further studies are required to validate our findings and evaluate the potential impact of these viral communities on respiratory tract physiology.

Integrative genomics important to understand host-pathogen interactions

Infectious diseases are the leading cause of morbidity and mortality worldwide. Causative pathogenic microbes readily mutate their genome and lead to outbreaks, challenging the healthcare and the medical support. Understanding how certain symptoms manifest clinically is integral for therapeutic decisions and vaccination efficacy/protection. Notably, the interaction between infecting pathogens, host response and co-presence of microbes influence the trajectories of disease progression and clinical outcome. The spectrum of observed symptomatic patients (mild, moderate and severe) and the asymptomatic infections highlight the challenges and the potential for understanding the factors driving protection/susceptibility. With the increasing repertoire of high-throughput tools, such as cutting-edge multi-omics profiling and next-generation sequencing, genetic drivers of factors linked to heterogeneous disease presentations can be investigated in tandem. However, such strategies are not without limits in terms of effectively integrating host-pathogen interactions. Nonetheless, an integrative genomics method (for example, RNA sequencing data) for exploring multiple layers of complexity in host-pathogen interactions could be another way to incorporate findings from high-throughput data. We further propose that a Holo-transcriptome-based technique to capture transcriptionally active microbial units can be used to elucidate functional microbiomes. Thus, we provide holistic perspective on investigative methodologies that can harness the same genomic data to investigate multiple seemingly independent but deeply interconnected functional domains of host-pathogen interaction that modulate disease severity and clinical outcomes.

Unique microbial diversity, community composition, and networks among Pacific Islander endocervical and vaginal microbiomes with and without Chlamydia trachomatis infection in Fiji

IMPORTANCE

Chlamydia trachomatis (Ct) is the most common sexually transmitted bacterium globally. Endocervical and vaginal microbiome interactions are rarely examined within the context of Ct or among vulnerable populations. We evaluated 258 vaginal and 92 paired endocervical samples from Fijian women using metagenomic shotgun sequencing. Over 37% of the microbiomes could not be classified into sub-community state types (subCSTs). We, therefore, developed subCSTs IV-D0, IV-D1, IV-D2, and IV-E-dominated primarily by Gardnerella vaginalis-to improve classification. Among paired microbiomes, the endocervix had a significantly higher alpha diversity and, independently, higher diversity for high-risk human papilloma virus (HPV) genotypes compared to low-risk and no HPV. Ct-infected endocervical networks had smaller clusters without interactions with potentially beneficial Lactobacillus spp. Overall, these data suggest that G. vaginalis may generate polymicrobial biofilms that predispose to and/or promote Ct and possibly HPV persistence and pathogenicity. Our findings expand on the existing repertoire of endocervical and vaginal microbiomes and fill in knowledge gaps regarding Pacific Islanders.

Viral and host factors associated with SARS-CoV-2 disease severity in Georgia, USA

While SARS-CoV-2 vaccines have shown strong efficacy, their suboptimal uptake combined with the continued emergence of new viral variants raises concerns about the ongoing and future public health impact of COVID-19. We investigated viral and host factors, including vaccination status, that were associated with SARS-CoV-2 disease severity in a setting with low vaccination rates. We analyzed clinical and demographic data from 1,957 individuals in the state of Georgia, USA, coupled with viral genome sequencing from 1,185 samples. We found no difference in disease severity between individuals infected with Delta and Omicron variants among the participants in this study, after controlling for other factors, and we found no specific mutations associated with disease severity. Compared to those who were unvaccinated, vaccinated individuals experienced less severe SARS-CoV-2 disease, and the effect was similar for both variants. Vaccination within 270 days before infection was associated with decreased odds of moderate and severe outcomes, with the strongest association observed at 91-270 days post-vaccination. Older age and underlying health conditions, especially immunosuppression and renal disease, were associated with increased disease severity. Overall, this study provides insights into the impact of vaccination status, variants/mutations, and clinical factors on disease severity in SARS-CoV-2 infection when vaccination rates are low. Understanding these associations will help refine and reinforce messaging around the crucial importance of vaccination in mitigating the severity of SARS-CoV-2 disease.

Secondary Infection Surveillance with Metagenomic Next-Generation Sequencing in COVID-19 Patients: A Cross-Sectional Study

Background

Metagenomic next-generation sequencing (mNGS) is a promising tool for improving antimicrobial therapy and infection control decision-making in complex infections. Secondary infection surveillance using mNGS in COVID-19 patients has rarely been reported.

Methods

Respiratory pathogen and antibiotic resistance prediction were evaluated by BALF mNGS for 192 hospitalized COVID-19 patients between December 2022 and February 2023.

Results

Secondary infection was confirmed in 83.3% (160/192) of the COVID-19 patients, with bacterial infections (45%, 72/160) predominating, followed by mixed bacterial and fungal infections (20%, 32/160), and fungal infections (17.5%, 28/160). The incidence of bacterial or viral secondary infection was significantly higher in patients who were admitted to the ICU, received mechanical ventilation, or developed severe pneumonia (all p<0.05). Klebsiella pneumoniae (n=30, 8.4%) was the most prevalent pathogen associated with secondary infection followed by Acinetobacter baumannii (n=29, 8.1%), Candida albicans (n=29, 8.1%), Aspergillus fumigatus (n=27, 7.6%), human herpes simplex virus type 1 (n=23, 6.4%), Staphylococcus aureus (n=20, 5.6%) and Pneumocystis jiroveci (n=14, 3.9%). The overall concordance between the resistance genes detected by mNGS and the reported phenotypic resistance in 69 samples containing five clinically important pathogens (ie, K. pneumoniae, A. baumannii, S. aureus, P. aeruginosa and E. coli) that caused secondary infection was 85.5% (59/69).

Conclusion

mNGS can detect pathogens causing secondary infection and predict antimicrobial resistance for COVID19 patients. This is crucial for initiating targeted treatment and rapidly detect unsuspected spread of multidrug-resistant pathogens.

Severe Neuroinvasive West Nile Virus in Association With Anti-CD20 Monotherapy for Multiple Sclerosis

OBJECTIVES

The objective of this study was to report on the development of neuroinvasive West Nile virus (WNV) infection in the context of anti-CD20 monotherapy for multiple sclerosis (MS).

METHODS

This is a case series study.

RESULTS

In 2021-2022, we observed 4 cases of neuroinvasive WNV infection in our patient population of 2009 patients with MS on ocrelizumab, compared with a total of 46 cases of neuroinvasive WNV infection reported in Pennsylvania and 40 in New Jersey. Odds were 258 times that of the general population (95% confidence interval 97-691), χ2 p < 0.0001). All were women aged 41-61 years with variable disease duration, level of disability, and duration of anti-CD20 therapy. All presented in summer/early fall with fever, headache, and encephalopathy consistent with meningoencephalitis. Three patients had acute cerebellitis. Two had anterior nerve root involvement progressing to quadriparesis, and 1 developed refractory nonconvulsive status epilepticus. All required intubation and experienced significant morbidity. All had CSF pleocytosis. Two patients were WNV IgM positive in both the serum and CSF, 1 patient had positive serum IgM and CSF metagenomic next-generation sequencing (mNGS), while 1 had positive CSF mNGS with negative serum and CSF antibodies.

DISCUSSION

Neuroinvasive WNV infection can develop with anti-CD20 monotherapy in the absence of additional immunosuppression. WNV serologies may be negative in the setting of anti-CD20 treatment; in the appropriate clinical context, one should consider direct detection methods such as PCR or mNGS-based testing.

UltraSEQ, a Universal Bioinformatic Platform for Information-Based Clinical Metagenomics and Beyond

Applied metagenomics is a powerful emerging capability enabling the untargeted detection of pathogens, and its application in clinical diagnostics promises to alleviate the limitations of current targeted assays. While metagenomics offers a hypothesis-free approach to identify any pathogen, including unculturable and potentially novel pathogens, its application in clinical diagnostics has so far been limited by workflow-specific requirements, computational constraints, and lengthy expert review requirements. To address these challenges, we developed UltraSEQ, a first-of-its-kind accurate and scalable metagenomic bioinformatic tool for potential clinical diagnostics and biosurveillance utility. Here, we present the results of the evaluation of our novel UltraSEQ pipeline using an in silico-synthesized metagenome, mock microbial community data sets, and publicly available clinical data sets from samples of different infection types, including both short-read and long-read sequencing data. Our results show that UltraSEQ successfully detected all expected species across the tree of life in the in silico sample and detected all 10 bacterial and fungal species in the mock microbial community data set. For clinical data sets, even without requiring data set-specific configuration setting changes, background sample subtraction, or prior sample information, UltraSEQ achieved an overall accuracy of 91%. Furthermore, as an initial demonstration with a limited patient sample set, we show UltraSEQ's ability to provide antibiotic resistance and virulence factor genotypes that are consistent with phenotypic results. Taken together, the above-described results demonstrate that the UltraSEQ platform offers a transformative approach for microbial and metagenomic sample characterization, employing a biologically informed detection logic, deep metadata, and a flexible system architecture for the classification and characterization of taxonomic origin, gene function, and user-defined functions, including disease-causing infections. IMPORTANCE Traditional clinical microbiology-based diagnostic tests rely on targeted methods that can detect only one to a few preselected organisms or slow, culture-based methods. Although widely used today, these methods have several limitations, resulting in rates of cases of an unknown etiology of infection of >50% for several disease types. Massive developments in sequencing technologies have made it possible to apply metagenomic methods to clinical diagnostics, but current offerings are limited to a specific disease type or sequencer workflow and/or require laboratory-specific controls. The limitations associated with current clinical metagenomic offerings result from the fact that the backend bioinformatic pipelines are optimized for the specific parameters described above, resulting in an excess of unmaintained, redundant, and niche tools that lack standardization and explainable outputs. In this paper, we demonstrate that UltraSEQ uses a novel, information-based approach that enables accurate, evidence-based predictions for diagnosis as well as the functional characterization of a sample.

A CRISPR-enhanced metagenomic NGS test to improve pandemic preparedness

The lack of preparedness for detecting and responding to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pathogen (i.e., COVID-19) has caused enormous harm to public health and the economy. Testing strategies deployed on a population scale at day zero, i.e., the time of the first reported case, would be of significant value. Next-generation sequencing (NGS) has such capabilities; however, it has limited detection sensitivity for low-copy-number pathogens. Here, we leverage the CRISPR-Cas9 system to effectively remove abundant sequences not contributing to pathogen detection and show that NGS detection sensitivity of SARS-CoV-2 approaches that of RT-qPCR. The resulting sequence data can also be used for variant strain typing, co-infection detection, and individual human host response assessment, all in a single molecular and analysis workflow. This NGS work flow is pathogen agnostic and, therefore, has the potential to transform how large-scale pandemic response and focused clinical infectious disease testing are pursued in the future.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Burden of Influenza and Respiratory Syncytial Viruses in Suspected COVID-19 Patients: A Cross-Sectional and Meta-Analysis Study

Non-SARS-CoV-2 respiratory viral infections, such as influenza virus (FluV) and human respiratory syncytial virus (RSV), have contributed considerably to the burden of infectious diseases in the non-COVID-19 era. While the rates of co-infection in SARS-CoV-2-positive group (SCPG) patients have been determined, the burden of other respiratory viruses in the SARS-CoV-2-negative group (SCNG) remains unclear. Here, we conducted a cross-sectional study (São José do Rio Preto county, Brazil), and we collected our data using a meta-analysis to evaluate the pooled prevalence of FluV and RSV among SCNG patients. Out of the 901 patients suspected of COVID-19, our molecular results showed positivity of FluV and RSV in the SCNG was 2% (15/733) and 0.27% (2/733), respectively. Co-infection with SARS-CoV-2 and FluV, or RSV, was identified in 1.7% of the patients (3/168). Following our meta-analysis, 28 studies were selected (n = 114,318 suspected COVID-19 patients), with a pooled prevalence of 4% (95% CI: 3-6) for FluV and 2% (95% CI: 1-3) for RSV among SCNG patients were observed. Interestingly, FluV positivity in the SCNG was four times higher (OR = 4, 95% CI: 3.6-5.4, p < 0.01) than in the SCPG. Similarly, RSV positivity was significantly associated with SCNG patients (OR = 2.9, 95% CI: 2-4, p < 0.01). For subgroup analysis, cold-like symptoms, including fever, cough, sore throat, headache, myalgia, diarrhea, and nausea/vomiting, were positively associated (p < 0.05) with the SCPG. In conclusion, these results show that the pooled prevalence of FluV and RSV were significantly higher in the SCNG than in the SCPG during the early phase of the COVID-19 pandemic.

Detection of coronaviruses in insectivorous bats of Fore-Caucasus, 2021

Coronaviruses (CoVs) pose a huge threat to public health as emerging viruses. Bat-borne CoVs are especially unpredictable in their evolution due to some unique features of bat physiology boosting the rate of mutations in CoVs, which is already high by itself compared to other viruses. Among bats, a meta-analysis of overall CoVs epizootiology identified a nucleic acid observed prevalence of 9.8% (95% CI 8.7-10.9%). The main objectives of our study were to conduct a qPCR screening of CoVs' prevalence in the insectivorous bat population of Fore-Caucasus and perform their characterization based on the metagenomic NGS of samples with detected CoV RNA. According to the qPCR screening, CoV RNA was detected in 5 samples, resulting in a 3.33% (95% CI 1.1-7.6%) prevalence of CoVs in bats from these studied locations. BetaCoVs reads were identified in raw metagenomic NGS data, however, detailed characterization was not possible due to relatively low RNA concentration in samples. Our results correspond to other studies, although a lower prevalence in qPCR studies was observed compared to other regions and countries. Further studies should require deeper metagenomic NGS investigation, as a supplementary method, which will allow detailed CoV characterization.

Outbreak of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in hospitalized hemodialysis patients: An epidemiologic and genomic investigation

We performed an epidemiological investigation and genome sequencing of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) to define the source and scope of an outbreak in a cluster of hospitalized patients. Lack of appropriate respiratory hygiene led to SARS-CoV-2 transmission to patients and healthcare workers during a single hemodialysis session, highlighting the importance of infection prevention precautions.

SARS-CoV-2 genotyping and sequencing following a simple and economical RNA extraction and storage protocol

Since the beginning of the SARS-CoV-2 pandemic, supply chain shortages have caused major disruptions in sourcing the materials needed for laboratory-based molecular assays. With increasing demand for molecular testing, these disruptions have limited testing capacity and hindered efforts to mitigate spread of the virus and new variants. Here we evaluate an economical and reliable protocol for the extraction and short-term ambient temperature storage of SARS-CoV-2 RNA. Additional objectives of the study were to evaluate RNA from this protocol for 1) detection of single nucleotide polymorphisms (SNPs) in the spike gene and 2) whole genome sequencing of SARS-CoV-2. The RNAES protocol was evaluated with residual nasopharyngeal (NP) samples collected from Emory Healthcare and Emory Student Health services. All RNAES extractions were performed in duplicate and once with a commercial extraction robot for comparison. Following extraction, eluates were immediately tested by rRT-PCR. SARS-CoV-2 RNA was successfully detected in 56/60 (93.3%) RNAES replicates, and Ct values corresponded with comparator results. Upon testing in spike SNP assays, three genotypes were identified, and all variant calls were consistent with those previously obtained after commercial extraction. Additionally, the SARS-RNAES protocol yield eluate pure enough for downstream whole genome sequencing, and results were consistent with SARS-CoV-2 whole genome sequencing of eluates matched for Ct value. With reproducible results across a range of virus concentrations, the SARS-RNAES protocol could help increase SARS-CoV-2 diagnostic testing and monitoring for emerging variants in resource-constrained communities.

Metagenomic analysis reveals differences in the co-occurrence and abundance of viral species in SARS-CoV-2 patients with different severity of disease

Background

SARS-CoV-2 infections have a wide spectrum of clinical manifestations whose causes are not completely understood. Some human conditions predispose to severe outcome, like old age or the presence of comorbidities, but many other facets, including coinfections with other viruses, remain poorly characterized.

Methods

In this study, the eukaryotic fraction of the respiratory virome of 120 COVID-19 patients was characterized through whole metagenomic sequencing.

Results

Genetic material from respiratory viruses was detected in 25% of all samples, whereas human viruses other than SARS-CoV-2 were found in 80% of them. Samples from hospitalized and deceased patients presented a higher prevalence of different viruses when compared to ambulatory individuals. Small circular DNA viruses from the Anneloviridae (Torque teno midi virus 8, TTV-like mini virus 19 and 26) and Cycloviridae families (Human associated cyclovirus 10), Human betaherpesvirus 6, were found to be significantly more abundant in samples from deceased and hospitalized patients compared to samples from ambulatory individuals. Similarly, Rotavirus A, Measles morbillivirus and Alphapapilomavirus 10 were significantly more prevalent in deceased patients compared to hospitalized and ambulatory individuals.

Conclusions

Results show the suitability of using metagenomics to characterize a broader peripheric virological landscape of the eukaryotic virome in SARS-CoV-2 infected patients with distinct disease outcomes. Identified prevalent viruses in hospitalized and deceased patients may prove important for the targeted exploration of coinfections that may impact prognosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-022-07783-8.

Metagenomic Pathogen Sequencing in Resource-Scarce Settings: Lessons Learned and the Road Ahead

Metagenomic next-generation sequencing (mNGS) is the process of sequencing all genetic material in a biological sample. The technique is growing in popularity with myriad applications including outbreak investigation, biosurveillance, and pathogen detection in clinical samples. However, mNGS programs are costly to build and maintain, and additional obstacles faced by low- and middle-income countries (LMICs) may further widen global inequities in mNGS capacity. Over the past two decades, several important infectious disease outbreaks have highlighted the importance of establishing widespread sequencing capacity to support rapid disease detection and containment at the source. Using lessons learned from the COVID-19 pandemic, LMICs can leverage current momentum to design and build sustainable mNGS programs, which would form part of a global surveillance network crucial to the elimination of infectious diseases.

Diagnostic performance of metagenomic next-generation sequencing for the detection of pathogens in bronchoalveolar lavage fluid in patients with pulmonary infections: Systematic review and meta-analysis

BACKGROUND

The identification of pathogens in patients with pulmonary infection has always been a major challenge in medicine. Compared with sputum and throat swabs, bronchoalveolar lavage fluid (BALF) can better reflect the actual state in the lungs. However, there has not been a meta-analysis of the diagnostic efficacy of metagenomic next-generation sequencing (mNGS) in detecting pathogens in BALF from patients with pulmonary infections.

METHODS

Data sources were PubMed, Web of Science, Embase, and the China National Knowledge Infrastructure. The pooled sensitivity and specificity were estimated by using random-effects or fixed-effect models. Subgroup analysis was performed to reveal the effect of potential explanatory factors on the diagnostic performance measures.

RESULTS

The pooled sensitivity was 78% (95% confidence interval: 67-87%; I² = 92%) and the pooled specificity was 77% (95% confidence interval: 64-94%; I² = 74%) for mNGS. Subgroup analyses for the sensitivity of mNGS revealed that patients with pulmonary infections who were severely ill or immunocompromised significantly affected heterogeneity (P < 0.001). The positive detection rate of mNGS for pathogens in BALF of severely or immunocompromised pulmonary-infected patients was 92% (95% confidence interval: 78-100%).

CONCLUSION

mNGS has high diagnostic performance for BALF pathogens in patients with pulmonary infections, especially in critically ill or immunocompromised patients.

Metagenomic Shotgun Sequencing of Endocervical, Vaginal, and Rectal Samples among Fijian Women with and without Chlamydia trachomatis Reveals Disparate Microbial Populations and Function across Anatomic Sites: a Pilot Study

Chlamydia trachomatis is a sexually transmitted pathogen and a global public health concern. Little is known about the microbial composition and function across endocervical, vaginal, and rectal microbiomes in the context of C. trachomatis infection. We evaluated the microbiomes of 10 age-matched high-risk Fijian women with and without C. trachomatis using metagenomic shotgun sequencing (MSS). Lactobacillus iners and Lactobacillus crispatus dominated the vagina and endocervix of uninfected women. Species often found in higher relative abundance in bacterial vaginosis (BV)-Mageeibacillus indolicus, Prevotella spp., Sneathia spp., Gardnerella vaginalis, and Veillonellaceae spp.-were dominant in C. trachomatis-infected women. This combination of BV pathogens was unique to Pacific Islanders compared to previously studied groups. The C. trachomatis-infected endocervix had a higher diversity of microbiota and microbial profiles that were somewhat different from those of the vagina. However, community state type III (CST-III) and CST-IV predominated, reflecting pathogenic microbiota regardless of C. trachomatis infection status. Rectal microbiomes were dominated by Prevotella and Bacteroides, although four women had unique microbiomes with Gardnerella, Akkermansia, Bifidobacterium, and Brachyspira. A high level of microbial similarity across microbiomes in two C. trachomatis-infected women suggested intragenitorectal transmission. A number of metabolic pathways in the endocervix, driven by BV pathogens and C. trachomatis to meet nutritional requirements for survival/growth, 5-fold higher than that in the vagina indicated that endocervical microbial functions are likely more diverse and complex than those in the vagina. Our novel findings provide the impetus for larger prospective studies to interrogate microbial/microbiome interactions that promote C. trachomatis infection and better define the unique genitorectal microbiomes of Pacific Islanders. IMPORTANCE Chlamydia trachomatis is the primary cause of bacterial sexually transmitted infections worldwide, with a disturbing increase in annual rates. While there is a plethora of data on healthy and pathogenic vaginal microbiomes-defining microbial profiles and associations with sexually transmitted infections (STIs)-far fewer studies have similarly examined the endocervix or rectum. Further, vulnerable populations, such as Pacific Islanders, remain underrepresented in research. We investigated the microbial composition, structure, and function of these anatomic microbiomes using metagenomic shotgun sequencing among a Fijian cohort. We found, primarily among C. trachomatis-infected women, unique microbial profiles in endocervical, vaginal, and rectal microbiomes with an increased diversity and more complex microbial pathways in endocervical than vaginal microbiomes. Similarities in microbiome composition across sites for some women suggested intragenitorectal transmission. These novel insights into genitorectal microbiomes and their purported function require prospective studies to better define Pacific Islander microbiomes and microbial/microbiome interactions that promote C. trachomatis infection.

Unrecognized introductions of SARS-CoV-2 into the US state of Georgia shaped the early epidemic

In early 2020, as diagnostic and surveillance responses for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) ramped up, attention focused primarily on returning international travelers. Here, we build on existing studies characterizing early patterns of SARS-CoV-2 spread within the USA by analyzing detailed clinical, molecular, and viral genomic data from the state of Georgia through March 2020. We find evidence for multiple early introductions into Georgia, despite relatively sparse sampling. Most sampled sequences likely stemmed from a single or small number of introductions from Asia three weeks prior to the state's first detected infection. Our analysis of sequences from domestic travelers demonstrates widespread circulation of closely related viruses in multiple US states by the end of March 2020. Our findings indicate that the exclusive focus on identifying SARS-CoV-2 in returning international travelers early in the pandemic may have led to a failure to recognize locally circulating infections for several weeks and point toward a critical need for implementing rapid, broadly targeted surveillance efforts for future pandemics.

Single-Amplicon Multiplex Real-Time Reverse Transcription-PCR with Tiled Probes To Detect SARS-CoV-2 spike Mutations Associated with Variants of Concern

To provide an accessible and inexpensive method to surveil for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mutations, we developed a multiplex real-time reverse transcription-PCR (rRT-PCR) assay, the Spike single-nucleotide polymorphism (SNP) assay, to detect specific mutations in the spike receptor binding domain. A single primer pair was designed to amplify a 348-bp region of spike, and probes were initially designed to detect K417, E484K, and N501Y. The assay was evaluated using characterized variant sample pools and residual nasopharyngeal samples. Variant calls were confirmed by SARS-CoV-2 genome sequencing in a subset of samples. Subsequently, a fourth probe was designed to detect L452R. The lower limit of 95% detection was 2.46 to 2.48 log₁₀ genome equivalents (GE)/ml for the three initial targets (∼1 to 2 GE/reaction). Among 253 residual nasopharyngeal swabs with detectable SARS-CoV-2 RNA, the Spike SNP assay was positive in 238 (94.1%) samples. All 220 samples with threshold cycle (C_T) values of <30 for the SARS-CoV-2 N2 target were detected, whereas 18/33 samples with N2 C_T values of ≥30 were detected. Spike SNP results were confirmed by sequencing in 50/50 samples (100%). Addition of the 452R probe did not affect performance for the original targets. The Spike SNP assay accurately identifies SARS-CoV-2 mutations in the receptor binding domain, and it can be quickly modified to detect new mutations that emerge.

Molecular diagnostic assays for COVID-19: an overview

The coronavirus disease 2019 (COVID-19) pandemic has highlighted the cardinal importance of rapid and accurate diagnostic assays. Since the early days of the outbreak, researchers with different scientific backgrounds across the globe have tried to fulfill the urgent need for such assays, with many assays having been approved and with others still undergoing clinical validation. Molecular diagnostic assays are a major group of tests used to diagnose COVID-19. Currently, the detection of SARS-CoV-2 RNA by reverse transcription polymerase chain reaction (RT-PCR) is the most widely used method. Other diagnostic molecular methods, including CRISPR-based assays, isothermal nucleic acid amplification methods, digital PCR, microarray assays, and next generation sequencing (NGS), are promising alternatives. In this review, we summarize the technical and clinical applications of the different COVID-19 molecular diagnostic assays and suggest directions for the implementation of such technologies in future infectious disease outbreaks.

Simultaneous detection and mutation surveillance of SARS-CoV-2 and multiple respiratory viruses by rapid field-deployable sequencing

BACKGROUND

Strategies for monitoring the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are crucial for combating the pandemic. Detection and mutation surveillance of SARS-CoV-2 and other respiratory viruses require separate and complex workflows that rely on highly specialized facilities, personnel, and reagents. To date, no method can rapidly diagnose multiple viral infections and determine variants in a high-throughput manner.

METHODS

We describe a method for multiplex isothermal amplification-based sequencing and real-time analysis of multiple viral genomes, termed nanopore sequencing of isothermal rapid viral amplification for near real-time analysis (NIRVANA). It can simultaneously detect SARS-CoV-2, influenza A, human adenovirus, and human coronavirus and monitor mutations for up to 96 samples in real time.

FINDINGS

NIRVANA showed high sensitivity and specificity for SARS-CoV-2 in 70 clinical samples with a detection limit of 20 viral RNA copies per μL of extracted nucleic acid. It also detected the influenza A co-infection in two samples. The variant analysis results of SARS-CoV-2-positive samples mirror the epidemiology of coronavirus disease 2019 (COVID-19). Additionally, NIRVANA could simultaneously detect SARS-CoV-2 and pepper mild mottle virus (PMMoV) (an omnipresent virus and water-quality indicator) in municipal wastewater samples.

CONCLUSIONS

NIRVANA provides high-confidence detection of both SARS-CoV-2 and other respiratory viruses and mutation surveillance of SARS-CoV-2 on the fly. We expect it to offer a promising solution for rapid field-deployable detection and mutational surveillance of pandemic viruses.

FUNDING

M.L. is supported by KAUST Office of Sponsored Research (BAS/1/1080-01). This work is supported by KAUST Competitive Research Grant (URF/1/3412-01-01; M.L. and J.C.I.B.) and Universidad Catolica San Antonio de Murcia (J.C.I.B.). A.M.H. is supported by Saudi Ministry of Education (project 436).

Validation of High-Sensitivity Severe Acute Respiratory Syndrome Coronavirus 2 Testing for Stool-Toward the New Normal for Fecal Microbiota Transplantation

INTRODUCTION

Mounting evidence demonstrates potential for fecal-oral transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The US Food and Drug Administration now requires SARS-CoV-2 testing of potential feces donors before the use of stool manufactured for fecal microbiota transplantation. We sought to develop and validate a high-sensitivity SARS-CoV-2 reverse transcriptase polymerase chain reaction (RT-PCR) procedure for testing stool specimens.

METHODS

A modified extraction method was used with an RT-PCR assay adapted from the Centers for Disease Control and Prevention PCR protocol for respiratory specimens. Contrived specimens were created using pre-COVID-19 banked stool specimens and spiking in known concentrations of SARS-CoV-2-specific nucleic acid. The highest transcript concentration at which 2/2 or 1/2 SARS-CoV-2 targets were detected in 9/10 replicates was defined as the dual-target limit and single-target limit of detection, respectively. The clinical performance of the assay was evaluated with stool samples collected from 17 nasopharyngeal swab RT-PCR-positive patients and 14 nasopharyngeal RT-PCR-negative patients.

RESULTS

The dual-target and single-target limit of detection were 56 copies/μL and 3 copies/μL, respectively. SARS-CoV-2 was detected at concentrations as low as 0.6 copies/μL. Clinical stool samples from known COVID-19-positive patients demonstrated the detection of SARS-CoV-2 in stool up to 29 days from symptom onset with a high agreement with nasopharyngeal swab tests (kappa statistic of 0.95, P value < 0.001).

DISCUSSION

The described RT-PCR test is a sensitive and flexible approach for the detection of SARS-CoV-2 in stool specimens. We propose an integrated screening approach that incorporates this stool test to support continuation of fecal microbiota transplantation programs.

Metagenomic diagnosis of severe psittacosis using multiple sequencing platforms

Background

Chlamydia psittaci is an avian pathogen that can cause lethal human infections. Diagnosis of C. psittaci pneumonia is often delayed due to nonspecific clinical presentations and limited laboratory diagnostic techniques.

Results

The MinION platform established the diagnosis in the shortest time, while BGISEQ-500 generated additional in-depth sequence data that included the rapid characterization of antibiotic susceptibility. Cytopathy appeared only in cell cultures of BALF. BALF yielded a higher bacterial load than sputum or blood, and may be the most suitable clinical specimen for the genomic diagnosis of severe pneumonia.

Conclusions

This study indicated that the benefits of metagenomic sequencing include rapid etiologic diagnosis of unknown infections and the provision of additional relevant information regarding antibiotic susceptibility. The continued optimization and standardization of sampling and metagenomic analysis promise to enhance the clinical utility of genomic diagnosis.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07725-9.

The Complexity of Co-Infections in the Era of COVID-19

The current frequency of COVID-19 in a pandemic era ensures that co-infections with a variety of co-pathogens will occur. Generally, there is a low rate of bonafide co-infections in early COVID-19 pulmonary infection as currently appreciated. Reports of high co-infection rates must be tempered by limitations in current diagnostic methods since amplification technologies do not necessarily confirm live pathogen and may be subject to considerable laboratory variation. Some laboratory methods may not exclude commensal microbes. Concurrent serodiagnoses have long been of concern for accuracy in these contexts. Presumed virus co-infections are not specific to COVID-19. The association of influenza viruses and SARS-CoV-2 in co-infection has been considerably variable during influenza season. Other respiratory virus co-infections have generally occurred in less than 10% of COVID-19 patients. Early COVID-19 disease is more commonly associated with bacterial co-pathogens that typically represent usual respiratory micro-organisms. Late infections, especially among severe clinical presentations, are more likely to be associated with nosocomial or opportunistic pathogens given the influence of treatments that can include antibiotics, antivirals, immunomodulating agents, blood products, immunotherapy, steroids, and invasive procedures. As anticipated, hospital care carries risk for multi-resistant bacteria. Overall, co-pathogen identification is linked with longer hospital stay, greater patient complexity, and adverse outcomes. As for other viral infections, a general reduction in the use of empiric antibiotic treatment is warranted. Further insight into co-infections with COVID-19 will contribute overall to effective antimicrobial therapies and disease control.

Infection- and vaccine-induced antibody binding and neutralization of the B.1.351 SARS-CoV-2 variant

The emergence of SARS-CoV-2 variants with mutations in the spike protein is raising concerns about the efficacy of infection- or vaccine-induced antibodies. We compared antibody binding and live virus neutralization of sera from naturally infected and Moderna-vaccinated individuals against two SARS-CoV-2 variants: B.1 containing the spike mutation D614G and the emerging B.1.351 variant containing additional spike mutations and deletions. Sera from acutely infected and convalescent COVID-19 patients exhibited a 3-fold reduction in binding antibody titers to the B.1.351 variant receptor-binding domain of the spike protein and a 3.5-fold reduction in neutralizing antibody titers against SARS-CoV-2 B.1.351 variant compared to the B.1 variant. Similar results were seen with sera from Moderna-vaccinated individuals. Despite reduced antibody titers against the B.1.351 variant, sera from infected and vaccinated individuals containing polyclonal antibodies to the spike protein could still neutralize SARS-CoV-2 B.1.351, suggesting that protective humoral immunity may be retained against this variant.

The Importance and Challenges of Identifying SARS-CoV-2 Reinfections

Reports of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfection have raised important questions about the strength and durability of the immune response to primary infection, which are key factors in predicting the course of the pandemic. Identifying reinfection requires detecting the virus at two different time points and using viral genomic data to distinguish reinfection from persistent viral carriage. This process is hindered by challenges of logistics and capacity, such as banking samples from primary infection and performing viral genome sequencing. These challenges may help to explain why very few cases have been described to date. In addition, reinfection may be a rare phenomenon, but detailed prospective studies are needed to rigorously assess its frequency. To provide context for future investigations of SARS-CoV-2 reinfection, we review 16 cases that have been published to date or are available in preprint. Reinfection occurred across demographic spectra and in patients whose initial infections were both asymptomatic/mild and moderate/severe. For cases in which severity could be compared between episodes, half of reinfections were less severe, raising the possibility of partial immune protection. Although many patients had a positive total immunoglobulin or IgG result at the time of reinfection, very little examination of their immune response was performed. Further work is needed to elucidate the frequency, determinants, and consequences of SARS-CoV-2 reinfection. Establishing the necessary frameworks for surveillance and investigation will rely heavily on clinical laboratories and clinical investigators, and we propose several considerations to guide the medical community in identifying and characterizing SARS-CoV-2 reinfections.

Reduced binding and neutralization of infection- and vaccine-induced antibodies to the B.1.351 (South African) SARS-CoV-2 variant

The emergence of SARS-CoV-2 variants with mutations in the spike protein is raising concerns about the efficacy of infection- or vaccine-induced antibodies to neutralize these variants. We compared antibody binding and live virus neutralization of sera from naturally infected and spike mRNA vaccinated individuals against a circulating SARS-CoV-2 B.1 variant and the emerging B.1.351 variant. In acutely-infected (5-19 days post-symptom onset), convalescent COVID-19 individuals (through 8 months post-symptom onset) and mRNA-1273 vaccinated individuals (day 14 post-second dose), we observed an average 4.3-fold reduction in antibody titers to the B.1.351-derived receptor binding domain of the spike protein and an average 3.5-fold reduction in neutralizing antibody titers to the SARS-CoV-2 B.1.351 variant as compared to the B.1 variant (spike D614G). However, most acute and convalescent sera from infected and all vaccinated individuals neutralize the SARS-CoV-2 B.1.351 variant, suggesting that protective immunity is retained against COVID-19.