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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.
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Sequenciamento de Nucleotídeos em Larga Escala , Metagenoma , Metagenômica , Microbiota , Metagenômica/métodos , Metagenoma/genética , Sequenciamento de Nucleotídeos em Larga Escala/métodos , Microbiota/genética , Humanos , Análise de Sequência de DNA/métodos , Biologia Computacional/métodosRESUMO
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.
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Técnicas de Cultura de Células/métodos , Colo/metabolismo , Meios de Cultura/farmacologia , Mucosa Intestinal/metabolismo , Intestino Delgado/metabolismo , Organoides/metabolismo , Transcriptoma/efeitos dos fármacos , Calcitriol/farmacologia , Colágeno/metabolismo , Colágeno/farmacologia , Doença de Crohn/metabolismo , Doença de Crohn/patologia , Meios de Cultura/química , Combinação de Medicamentos , Escherichia coli , Infecções por Escherichia coli/metabolismo , Infecções por Escherichia coli/microbiologia , Matriz Extracelular/metabolismo , Regulação da Expressão Gênica/efeitos dos fármacos , Humanos , Laminina/metabolismo , Laminina/farmacologia , Organoides/virologia , Proteoglicanas/metabolismo , Proteoglicanas/farmacologia , RNA-Seq/métodos , Transcriptoma/genética , Viroses/metabolismo , Viroses/virologia , VírusRESUMO
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.
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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.
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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.
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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.
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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.
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Algoritmos , Variação Estrutural do Genoma , Humanos , Frequência do Gene , Alelos , Benchmarking , Sequenciamento de Nucleotídeos em Larga Escala , Genoma HumanoRESUMO
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.
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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.
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Criptosporidiose , Cryptosporidium parvum , Cryptosporidium , Criptosporidiose/epidemiologia , Criptosporidiose/genética , Criptosporidiose/parasitologia , Cryptosporidium/genética , Cryptosporidium parvum/genética , Genoma , Genômica/métodos , HumanosRESUMO
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.
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Canais Epiteliais de Sódio , Sódio , Humanos , Pressão Sanguínea/genética , Canais Epiteliais de Sódio/genética , Fenótipo , RimRESUMO
Cryptosporidium is a leading cause of childhood diarrhea in developing countries. We investigated symptomatic and asymptomatic cryptosporidiosis in 20 children less than two years of age in a semi-urban slum in southern India. All surveillance (conducted every two weeks) and diarrheal samples from 20 children (n = 1,036) with cryptosporidial diarrhea previously identified by stool microscopy were tested by polymerase chain reaction-restriction fragment length polymorphism for species and subgenotype determination. Thirty-five episodes of cryptosporidiosis were identified in 20 children, of which 25 were diarrheal. Fifteen episodes were associated with prolonged oocyst shedding. Multiple episodes of cryptosporidiosis occurred in 40% of the children. Most infections were with C. hominis, subtype Ia. Children with multiple infections had significantly lower weight-for-age and height-for-age Z scores at 24 months but had scores comparable with children with a single episode by 36 months. Multiple symptomatic Cryptosporidium infections associated with prolonged oocyst shedding occur frequently in this disease-endemic area and may contribute to the long-term effects of cryptosporidiosis on physical growth in these children.