Unveiling microbial diversity: harnessing long-read sequencing technology.

Long-read sequencing has recently transformed metagenomics, enhancing strain-level pathogen characterization, enabling accurate and complete metagenome-assembled genomes, and improving microbiome taxonomic classification and profiling. These advancements are not only due to improvements in sequencing accuracy, but also happening across rapidly changing analysis methods. In this Review, we explore long-read sequencing's profound impact on metagenomics, focusing on computational pipelines for genome assembly, taxonomic characterization and variant detection, to summarize recent advancements in the field and provide an overview of available analytical methods to fully leverage long reads. We provide insights into the advantages and disadvantages of long reads over short reads and their evolution from the early days of long-read sequencing to their recent impact on metagenomics and clinical diagnostics. We further point out remaining challenges for the field such as the integration of methylation signals in sub-strain analysis and the lack of benchmarks.

Inter and intra-host diversity of RSV in hematopoietic stem cell transplant adults with normal and delayed viral clearance.

Respiratory syncytial virus (RSV) infection in immunocompromised individuals often leads to prolonged illness, progression to severe lower respiratory tract infection, and even death. How the host immune environment of the hematopoietic stem cell transplant (HCT) adults can affect viral genetic variation during an acute infection is not understood well. In the present study, we performed whole genome sequencing of RSV/A or RSV/B from samples collected longitudinally from HCT adults with normal (<14 days) and delayed (≥14 days) RSV clearance who were enrolled in a ribavirin trial. We determined the inter-host and intra-host genetic variation of RSV and the effect of mutations on putative glycosylation sites. The inter-host variation of RSV is centered in the attachment (G) and fusion (F) glycoprotein genes followed by polymerase (L) and matrix (M) genes. Interestingly, the overall genetic variation was constant between normal and delayed clearance groups for both RSV/A and RSV/B. Intra-host variation primarily occurred in the G gene followed by non-structural protein (NS1) and L genes; however, gain or loss of stop codons and frameshift mutations appeared only in the G gene and only in the delayed viral clearance group. Potential gain or loss of O-linked glycosylation sites in the G gene occurred both in RSV/A and RSV/B isolates. For RSV F gene, loss of N-linked glycosylation site occurred in three RSV/B isolates within an antigenic epitope. Both oral and aerosolized ribavirin did not cause any mutations in the L gene. In summary, prolonged viral shedding and immune deficiency resulted in RSV variation, especially in structural mutations in the G gene, possibly associated with immune evasion. Therefore, sequencing and monitoring of RSV isolates from immunocompromised patients are crucial as they can create escape mutants that can impact the effectiveness of upcoming vaccines and treatments.

Tryptophan Metabolites And Their Predicted Microbial Sources In Fecal Samples From Healthy Individuals.

Gut microbiota produce tryptophan metabolites (TMs) important to homeostasis. However, measuring TM levels in stool and determining their microbial sources can be difficult. Here, we measured TMs from the indole pathway in fecal samples from 21 healthy adults with the goal to: 1) determine fecal TM concentrations in healthy individuals; 2) link TM levels to bacterial abundance using 16S and whole genome shotgun (WGS) sequencing data; and 3) predict likely bacterial sources of TM production. Within our samples, we identified 151 genera (16S) and 592 bacterial species (WGS). Eight TMs were found in ≥17 fecal samples, including four in all persons. To our knowledge, we are the first to report fecal levels for indole-3-lactate, indole-3-propionate, and 3-indoleacrylate levels in healthy persons. Overall, indole, indole-3-acetate (IAA), and skatole accounted for 86% of the eight TMs measured. Significant correlations were found between seven TMs and 29 bacterial species.  Predicted multiple TM sources support the notion of a complex network of TM production and regulation. Further, the data suggest key roles for Collinsella aerofaciens and IAA, a metabolite reported to maintain intestinal homeostasis through enhanced barrier integrity and anti-inflammatory/antioxidant activities. These findings extend our understanding of TMs and their relationship to the microbial species that act as effectors and/or regulators in the healthy intestine and may lead to novel strategies designed to manipulate tryptophan metabolism to prevent disease and/or restore health to the dysbiotic gut.

Functional Genomics of Gastrointestinal Escherichia coli Isolated from Patients with Cancer and Diarrhea.

We describe the epidemiology and clinical characteristics of 29 patients with cancer and diarrhea in whom Enteroaggregative Escherichia coli (EAEC) was initially identified by GI BioFire panel multiplex. E. coli strains were successfully isolated from fecal cultures in 14 of 29 patients. Six of the 14 strains were identified as EAEC and 8 belonged to other diverse E. coli groups of unknown pathogenesis. We investigated these strains by their adherence to human intestinal organoids, cytotoxic responses, antibiotic resistance profile, full sequencing of their genomes, and annotation of their functional virulome. Interestingly, we discovered novel and enhanced adherence and aggregative patterns for several diarrheagenic pathotypes that were not previously seen when co-cultured with immortalized cell lines. EAEC isolates displayed exceptional adherence and aggregation to human colonoids compared not only to diverse GI E. coli , but also compared to prototype strains of other diarrheagenic E. coli . Some of the diverse E. coli strains that could not be classified as a conventional pathotype also showed an enhanced aggregative and cytotoxic response. Notably, we found a high carriage rate of antibiotic resistance genes in both EAEC strains and diverse GI E. coli isolates and observed a positive correlation between adherence to colonoids and the number of metal acquisition genes carried in both EAEC and the diverse E. coli strains. This work indicates that E. coli from cancer patients constitute strains of remarkable pathotypic and genomic divergence, including strains of unknown disease etiology with unique virulomes. Future studies will allow for the opportunity to re-define E. coli pathotypes with greater diagnostic accuracy and into more clinically relevant groupings.

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load.

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.

Longitudinal host transcriptional responses to SARS-CoV-2 infection in adults with extremely high viral load.

Current understanding of viral dynamics of SARS-CoV-2 and host responses driving the pathogenic mechanisms in COVID-19 is rapidly evolving. Here, we conducted a longitudinal study to investigate gene expression patterns during acute SARS-CoV-2 illness. Cases included SARS-CoV-2 infected individuals with extremely high viral loads early in their illness, individuals having low SARS-CoV-2 viral loads early in their infection, and individuals testing negative for SARS-CoV-2. We could identify widespread transcriptional host responses to SARS-CoV-2 infection that were initially most strongly manifested in patients with extremely high initial viral loads, then attenuating within the patient over time as viral loads decreased. Genes correlated with SARS-CoV-2 viral load over time were similarly differentially expressed across independent datasets of SARS-CoV-2 infected lung and upper airway cells, from both in vitro systems and patient samples. We also generated expression data on the human nose organoid model during SARS-CoV-2 infection. The human nose organoid-generated host transcriptional response captured many aspects of responses observed in the above patient samples, while suggesting the existence of distinct host responses to SARS-CoV-2 depending on the cellular context, involving both epithelial and cellular immune responses. Our findings provide a catalog of SARS-CoV-2 host response genes changing over time.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hemotologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

Structural variation across 138,134 samples in the TOPMed consortium.

Ever larger Structural Variant (SV) catalogs highlighting the diversity within and between populations help researchers better understand the links between SVs and disease. The identification of SVs from DNA sequence data is non-trivial and requires a balance between comprehensiveness and precision. Here we present a catalog of 355,667 SVs (59.34% novel) across autosomes and the X chromosome (50bp+) from 138,134 individuals in the diverse TOPMed consortium. We describe our methodologies for SV inference resulting in high variant quality and >90% allele concordance compared to long-read de-novo assemblies of well-characterized control samples. We demonstrate utility through significant associations between SVs and important various cardio-metabolic and hematologic traits. We have identified 690 SV hotspots and deserts and those that potentially impact the regulation of medically relevant genes. This catalog characterizes SVs across multiple populations and will serve as a valuable tool to understand the impact of SV on disease development and progression.

Ultrafast prediction of somatic structural variations by filtering out reads matched to pan-genome k-mer sets.

Variant callers typically produce massive numbers of false positives for structural variations, such as cancer-relevant copy-number alterations and fusion genes resulting from genome rearrangements. Here we describe an ultrafast and accurate detector of somatic structural variations that reduces read-mapping costs by filtering out reads matched to pan-genome k-mer sets. The detector, which we named ETCHING (for efficient detection of chromosomal rearrangements and fusion genes), reduces the number of false positives by leveraging machine-learning classifiers trained with six breakend-related features (clipped-read count, split-reads count, supporting paired-end read count, average mapping quality, depth difference and total length of clipped bases). When benchmarked against six callers on reference cell-free DNA, validated biomarkers of structural variants, matched tumour and normal whole genomes, and tumour-only targeted sequencing datasets, ETCHING was 11-fold faster than the second-fastest structural-variant caller at comparable performance and memory use. The speed and accuracy of ETCHING may aid large-scale genome projects and facilitate practical implementations in precision medicine.

Truvari: refined structural variant comparison preserves allelic diversity.

The fundamental challenge of multi-sample structural variant (SV) analysis such as merging and benchmarking is identifying when two SVs are the same. Common approaches for comparing SVs were developed alongside technologies which produce ill-defined boundaries. As SV detection becomes more exact, algorithms to preserve this refined signal are needed. Here, we present Truvari-an SV comparison, annotation, and analysis toolkit-and demonstrate the effect of SV comparison choices by building population-level VCFs from 36 haplotype-resolved long-read assemblies. We observe over-merging from other SV merging approaches which cause up to a 2.2× inflation of allele frequency, relative to Truvari.

Rare Variants in Genes Encoding Subunits of the Epithelial Na+ Channel Are Associated With Blood Pressure and Kidney Function.

BACKGROUND: The epithelial Na+ channel (ENaC) is intrinsically linked to fluid volume homeostasis and blood pressure. Specific rare mutations in SCNN1A, SCNN1B, and SCNN1G, genes encoding the α, ß, and γ subunits of ENaC, respectively, are associated with extreme blood pressure phenotypes. No associations between blood pressure and SCNN1D, which encodes the δ subunit of ENaC, have been reported. A small number of sequence variants in ENaC subunits have been reported to affect functional transport in vitro or blood pressure. The effects of the vast majority of rare and low-frequency ENaC variants on blood pressure are not known. METHODS: We explored the association of low frequency and rare variants in the genes encoding ENaC subunits, with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure. Using whole-genome sequencing data from 14 studies participating in the Trans-Omics in Precision Medicine Whole-Genome Sequencing Program, and sequence kernel association tests. RESULTS: We found that variants in SCNN1A and SCNN1B were associated with diastolic blood pressure and mean arterial pressure (P<0.00625). Although SCNN1D is poorly expressed in human kidney tissue, SCNN1D variants were associated with systolic blood pressure, diastolic blood pressure, mean arterial pressure, and pulse pressure (P<0.00625). ENaC variants in 2 of the 4 subunits (SCNN1B and SCNN1D) were also associated with estimated glomerular filtration rate (P<0.00625), but not with stroke. CONCLUSIONS: Our results suggest that variants in extrarenal ENaCs, in addition to ENaCs expressed in kidneys, influence blood pressure and kidney function.

Multiple Respiratory Syncytial Virus (RSV) Strains Infecting HEp-2 and A549 Cells Reveal Cell Line-Dependent Differences in Resistance to RSV Infection.

Respiratory syncytial virus (RSV) is a leading cause of pediatric acute respiratory infection worldwide. There are currently no approved vaccines or antivirals to combat RSV disease. A few transformed cell lines and two historic strains have been extensively used to study RSV. Here, we reported a thorough molecular and cell biological characterization of HEp-2 and A549 cells infected with one of four strains of RSV representing both major subgroups as well as historic and more contemporary genotypes (RSV/A/Tracy [GA1], RSV/A/Ontario [ON], RSV/B/18537 [GB1], and RSV/B/Buenos Aires [BA]) via measurements of viral replication kinetics and viral gene expression, immunofluorescence-based imaging of gross cellular morphology and cell-associated RSV, and measurements of host response, including transcriptional changes and levels of secreted cytokines and growth factors. IMPORTANCE Infection with the respiratory syncytial virus (RSV) early in life is essentially guaranteed and can lead to severe disease. Most RSV studies have involved either of two historic RSV/A strains infecting one of two cell lines, HEp-2 or A549 cells. However, RSV contains ample variation within two evolving subgroups (A and B), and HEp-2 and A549 cell lines are genetically distinct. Here, we measured viral action and host response in both HEp-2 and A549 cells infected with four RSV strains from both subgroups and representing both historic and more contemporary strains. We discovered a subgroup-dependent difference in viral gene expression and found A549 cells were more potently antiviral and more sensitive, albeit subtly, to viral variation. Our findings revealed important differences between RSV subgroups and two widely used cell lines and provided baseline data for experiments with model systems better representative of natural RSV infection.

Fully resolved assembly of Cryptosporidium parvum.

BACKGROUND: Cryptosporidium parvum is an apicomplexan parasite commonly found across many host species with a global infection prevalence in human populations of 7.6%. Understanding its diversity and genomic makeup can help in fighting established infections and prohibiting further transmission. The basis of every genomic study is a high-quality reference genome that has continuity and completeness, thus enabling comprehensive comparative studies. FINDINGS: Here, we provide a highly accurate and complete reference genome of Cryptosporidium parvum. The assembly is based on Oxford Nanopore reads and was improved using Illumina reads for error correction. We also outline how to evaluate and choose from different assembly methods based on 2 main approaches that can be applied to other Cryptosporidium species. The assembly encompasses 8 chromosomes and includes 13 telomeres that were resolved. Overall, the assembly shows a high completion rate with 98.4% single-copy BUSCO genes. CONCLUSIONS: This high-quality reference genome of a zoonotic IIaA17G2R1 C. parvum subtype isolate provides the basis for subsequent comparative genomic studies across the Cryptosporidium clade. This will enable improved understanding of diversity, functional, and association studies.

Modeling nonsegmented negative-strand RNA virus (NNSV) transcription with ejective polymerase collisions and biased diffusion.

Infections by non-segmented negative-strand RNA viruses (NNSV) are widely thought to entail gradient gene expression from the well-established existence of a single promoter at the 3' end of the viral genome and the assumption of constant transcriptional attenuation between genes. But multiple recent studies show viral mRNA levels in infections by respiratory syncytial virus (RSV), a major human pathogen and member of NNSV, that are inconsistent with a simple gradient. Here we integrate known and newly predicted phenomena into a biophysically reasonable model of NNSV transcription. Our model succeeds in capturing published observations of respiratory syncytial virus and vesicular stomatitis virus (VSV) mRNA levels. We therefore propose a novel understanding of NNSV transcription based on the possibility of ejective polymerase-polymerase collisions and, in the case of RSV, biased polymerase diffusion.

Transmission event of SARS-CoV-2 delta variant reveals multiple vaccine breakthrough infections.

BACKGROUND: This study aims to identify the causative strain of SARS-CoV-2 in a cluster of vaccine breakthroughs. Vaccine breakthrough by a highly transmissible SARS-CoV-2 strain is a risk to global public health. METHODS: Nasopharyngeal swabs from suspected vaccine breakthrough cases were tested for SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) by qPCR (quantitative polymerase chain reaction) for Wuhan-Hu1 and alpha variant. Positive samples were then sequenced by Swift Normalase Amplicon Panels to determine the causal variant. GATK (genome analysis toolkit) variants were filtered with allele fraction ≥80 and min read depth 30x. RESULTS: Viral sequencing revealed an infection cluster of 6 vaccinated patients infected with the delta (B.1.617.2) SARS-CoV-2 variant. With no history of vaccine breakthrough, this suggests the delta variant may possess immune evasion in patients that received the Pfizer BNT162b2, Moderna mRNA-1273, and Covaxin BBV152. CONCLUSIONS: Delta variant may pose the highest risk out of any currently circulating SARS-CoV-2 variants, with previously described increased transmissibility over alpha variant and now, possible vaccine breakthrough. FUNDING: Parts of this work was supported by the National Institute of Allergy and Infectious Diseases (1U19AI144297) and Baylor College of Medicine internal funding.

Primary Infection May Be an Underlying Factor Contributing to Lethal Hemorrhagic Disease Caused by Elephant Endotheliotropic Herpesvirus 3 in African Elephants (Loxodonta africana).

Distinct but related species of elephant endotheliotropic herpesviruses (EEHVs) circulate within Asian and African elephant populations. Primary infection with EEHVs endemic among Asian elephants can cause clinical illness and lethal EEHV hemorrhagic disease (EEHV-HD). The degree to which this occurs among African elephants has not been fully established. Recent cases of EEHV-HD caused by the EEHV3 species in African elephants housed in North American zoos has heightened concern about the susceptibility of this elephant species to EEHV-HD. In this study, we utilize the luciferase immunoprecipitation system (LIPS) to generate a serological assay specific for EEHV3 in African elephants by detecting antibodies against the EEHV3 E34 protein. The results showed that the majority of tested elephants from four separate and genetically unrelated herds, including five elephants that survived clinical illness associated with EEHV3, were positive for prior infection with EEHV3. However, African elephants who succumbed to EEHV3-HD were seronegative for EEHV3 prior to lethal infection. This supports the hypothesis that fatal EEHV-HD caused by EEHV3 is associated with primary infection rather than reactivation of latent virus. Lastly, we observed that African elephants, like Asian elephants, acquire abundant anti-EEHV antibodies prenatally and that anti-EEHV3 specific antibodies were either never detected or declined to undetectable levels in those animals that died from lethal disease following EEHV3 infection. IMPORTANCE Prior to 2019, only five cases of clinical disease from EEHV infection among African elephants had been documented. Since 2019, there have been at least seven EEHV-HD cases in North American zoos, resulting in three fatalities, all associated with EEHV3. Evidence is accumulating to suggest that EEHV-associated clinical illness and death among Asian elephants is due to primary infection and may be associated with waning anti-EEHV antibody levels in young elephants. The development of the EEHV3 serological test described in this study enabled us to confirm that similar dynamics may be contributing to EEHV-HD in African elephants. The ability to screen for EEHV immune status in African elephant calves will have a major impact on managing captive African elephant herds and will provide new tools for investigating and understanding EEHV in wild populations.

Drivers of transcriptional variance in human intestinal epithelial organoids.

Human intestinal epithelial organoids (enteroids and colonoids) are tissue cultures used for understanding the physiology of the human intestinal epithelium. Here, we explored the effect on the transcriptome of common variations in culture methods, including extracellular matrix substrate, format, tissue segment, differentiation status, and patient heterogeneity. RNA-sequencing datasets from 276 experiments performed on 37 human enteroid and colonoid lines from 29 patients were aggregated from several groups in the Texas Medical Center. DESeq2 and gene set enrichment analysis (GSEA) were used to identify differentially expressed genes and enriched pathways. PERMANOVA, Pearson's correlation, and dendrogram analysis of the data originally indicated three tiers of influence of culture methods on transcriptomic variation: substrate (collagen vs. Matrigel) and format (3-D, transwell, and monolayer) had the largest effect; segment of origin (duodenum, jejunum, ileum, colon) and differentiation status had a moderate effect; and patient heterogeneity and specific experimental manipulations (e.g., pathogen infection) had the smallest effect. GSEA identified hundreds of pathways that varied between culture methods, such as IL1 cytokine signaling enriched in transwell versus monolayer cultures and E2F target genes enriched in collagen versus Matrigel cultures. The transcriptional influence of the format was furthermore validated in a synchronized experiment performed with various format-substrate combinations. Surprisingly, large differences in organoid transcriptome were driven by variations in culture methods such as format, whereas experimental manipulations such as infection had modest effects. These results show that common variations in culture conditions can have large effects on intestinal organoids and should be accounted for when designing experiments and comparing results between laboratories. Our data constitute the largest RNA-seq dataset interrogating human intestinal epithelial organoids.

Oligonucleotide capture sequencing of the SARS-CoV-2 genome and subgenomic fragments from COVID-19 individuals.

The newly emerged and rapidly spreading SARS-CoV-2 causes coronavirus disease 2019 (COVID-19). To facilitate a deeper understanding of the viral biology we developed a capture sequencing methodology to generate SARS-CoV-2 genomic and transcriptome sequences from infected patients. We utilized an oligonucleotide probe-set representing the full-length genome to obtain both genomic and transcriptome (subgenomic open reading frames [ORFs]) sequences from 45 SARS-CoV-2 clinical samples with varying viral titers. For samples with higher viral loads (cycle threshold value under 33, based on the CDC qPCR assay) complete genomes were generated. Analysis of junction reads revealed regions of differential transcriptional activity among samples. Mixed allelic frequencies along the 20kb ORF1ab gene in one sample, suggested the presence of a defective viral RNA species subpopulation maintained in mixture with functional RNA in one sample. The associated workflow is straightforward, and hybridization-based capture offers an effective and scalable approach for sequencing SARS-CoV-2 from patient samples.

Transmission event of SARS-CoV-2 Delta variant reveals multiple vaccine breakthrough infections.

Importance: Vaccine breakthrough by an emergent SARS-CoV-2 variant poses a great risk to global public health. Objective: To determine the SARS-CoV-2 variant responsible for 6 cases of vaccine breakthrough. Design: Nasopharyngeal swabs from suspected vaccine breakthrough cases were tested for SARS-CoV-2 by qPCR for Wuhan-Hu1 and Alpha variant. Positive samples were then sequenced by Swift Normalase Amplicon Panels to determine the causal variant. Setting: Transmission event occurred at events surrounding a wedding outside of Houston, TX. Two patients from India, likely transmitted the Delta variant to other guests. Participants: Following a positive SARS-CoV-2 qPCR test at a third-party site, six fully vaccinated patients were investigated. Three males and three females ranged from 53 to 69 years old. One patient suffered from diabetes while three others were classified as overweight. No significant other comorbidities were identified. None of the patients had a history of failed vaccination.