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Microbiome Nov 2023Inquiry of microbiota involvement in kidney stone disease (KSD) has largely focussed on potential oxalate handling abilities by gut bacteria and the increased...
BACKGROUND
Inquiry of microbiota involvement in kidney stone disease (KSD) has largely focussed on potential oxalate handling abilities by gut bacteria and the increased association with antibiotic exposure. By systematically comparing the gut, urinary, and oral microbiota of 83 stone formers (SF) and 30 healthy controls (HC), we provide a unified assessment of the bacterial contribution to KSD.
RESULTS
Amplicon and shotgun metagenomic sequencing approaches were consistent in identifying multi-site microbiota disturbances in SF relative to HC. Biomarker taxa, reduced taxonomic and functional diversity, functional replacement of core bioenergetic pathways with virulence-associated gene markers, and community network collapse defined SF, but differences between cohorts did not extend to oxalate metabolism.
CONCLUSIONS
We conclude that multi-site microbiota alteration is a hallmark of SF, and KSD treatment should consider microbial functional restoration and the avoidance of aberrant modulators such as poor diet and antibiotics where applicable to prevent stone recurrence. Video Abstract.
Topics: Humans; Kidney Calculi; Microbiota; Oxalates; Metagenome; Bacteria
PubMed: 38007438
DOI: 10.1186/s40168-023-01703-x -
Nature Communications Aug 2023Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this...
Preterm birth (PTB) is the leading cause of neonatal morbidity and mortality. The vaginal microbiome has been associated with PTB, yet the mechanisms underlying this association are not fully understood. Understanding microbial genetic adaptations to selective pressures, especially those related to the host, may yield insights into these associations. Here, we analyze metagenomic data from 705 vaginal samples collected during pregnancy from 40 women who delivered preterm spontaneously and 135 term controls from the Multi-Omic Microbiome Study-Pregnancy Initiative. We find that the vaginal microbiome of pregnancies that ended preterm exhibited unique genetic profiles. It was more genetically diverse at the species level, a result which we validate in an additional cohort, and harbored a higher richness and diversity of antimicrobial resistance genes, likely promoted by transduction. Interestingly, we find that Gardnerella species drove this higher genetic diversity, particularly during the first half of the pregnancy. We further present evidence that Gardnerella spp. underwent more frequent recombination and stronger purifying selection in genes involved in lipid metabolism. Overall, our population genetics analyses reveal associations between the vaginal microbiome and PTB and suggest that evolutionary processes acting on vaginal microbes may play a role in adverse pregnancy outcomes such as PTB.
Topics: Infant, Newborn; Pregnancy; Humans; Female; Premature Birth; Microbiota; Metagenome; Acclimatization; Biological Evolution
PubMed: 37591872
DOI: 10.1038/s41467-023-40719-7 -
Diagnostic Microbiology and Infectious... Oct 2023Microbial cell free DNA sequencing is increasingly used for diagnosis of infection but few studies describe its utility in real-world settings. We performed a...
Microbial cell free DNA sequencing is increasingly used for diagnosis of infection but few studies describe its utility in real-world settings. We performed a single-center retrospective case series of microbial cell free DNA testing using the Karius assay from 29 patient samples to define the clinical reasoning and the impact of testing. Indications fell into 3 categories, identifying a causative pathogen in patients with an infectious syndrome and negative microbiologic workup (15/29, 52%), seeking another pathogen when organisms identified by traditional diagnostics failed to explain the clinical presentation (9/29, 31%) and to "rule out" infection in patients with nonspecific symptoms and negative microbiologic workup (5/29, 17%). Clinical impact was positive in 13/29 (45%) and all were for patients with high pretest probability for infection. Impact was negative in 3/29 (10%) cases. There was no impact in 15/29 (52%) cases. Further work is needed to define the optimal timing accounting for test performance, and patient characteristics.
Topics: Humans; Cell-Free Nucleic Acids; Retrospective Studies; Sequence Analysis, DNA; High-Throughput Nucleotide Sequencing; Metagenomics
PubMed: 37467522
DOI: 10.1016/j.diagmicrobio.2023.116004 -
Journal of Clinical Microbiology Aug 2023Microbial cell-free DNA (mcfDNA) sequencing is an emerging infectious disease diagnostic tool which enables unbiased pathogen detection and quantification from plasma....
Microbial cell-free DNA (mcfDNA) sequencing is an emerging infectious disease diagnostic tool which enables unbiased pathogen detection and quantification from plasma. The Karius Test, a commercial mcfDNA sequencing assay developed by and available since 2017 from Karius, Inc. (Redwood City, CA), detects and quantifies mcfDNA as molecules/μL in plasma. The commercial sample data and results for all tests conducted from April 2018 through mid-September 2021 were evaluated for laboratory quality metrics, reported pathogens, and data from test requisition forms. A total of 18,690 reports were generated from 15,165 patients in a hospital setting among 39 states and the District of Columbia. The median time from sample receipt to reported result was 26 h (interquartile range [IQR] 25 to 28), and 96% of samples had valid test results. Almost two-thirds (65%) of patients were adults, and 29% at the time of diagnostic testing had ICD-10 codes representing a diverse array of clinical scenarios. There were 10,752 (58%) reports that yielded at least one taxon for a total of 22,792 detections spanning 701 unique microbial taxa. The 50 most common taxa detected included 36 bacteria, 9 viruses, and 5 fungi. Opportunistic fungi (374 Aspergillus spp., 258 Pneumocystis jirovecii, 196 , and 33 dematiaceous fungi) comprised 861 (4%) of all detections. Additional diagnostically challenging pathogens (247 zoonotic and vector-borne pathogens, 144 Mycobacterium spp., 80 spp., 78 systemic dimorphic fungi, 69 spp., and 57 protozoan parasites) comprised 675 (3%) of all detections. This is the largest reported cohort of patients tested using plasma mcfDNA sequencing and represents the first report of a clinical grade metagenomic test performed at scale. Data reveal new insights into the breadth and complexity of potential pathogens identified.
Topics: Adult; Humans; Fungi; Bacteria; Viruses; High-Throughput Nucleotide Sequencing; Metagenomics; Sequence Analysis, DNA
PubMed: 37439686
DOI: 10.1128/jcm.01855-22 -
Microbiology Spectrum Aug 2023Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life....
Petabases of environmental metagenomic data are publicly available, presenting an opportunity to characterize complex environments and discover novel lineages of life. Metagenome coassembly, in which many metagenomic samples from an environment are simultaneously analyzed to infer the underlying genomes' sequences, is an essential tool for achieving this goal. We applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 terabases (Tbp) of metagenome data from a tropical soil in the Luquillo Experimental Forest (LEF), Puerto Rico. The resulting coassembly yielded 39 high-quality (>90% complete, <5% contaminated, with predicted 23S, 16S, and 5S rRNA genes and ≥18 tRNAs) metagenome-assembled genomes (MAGs), including two from the candidate phylum . Another 268 medium-quality (≥50% complete, <10% contaminated) MAGs were extracted, including the candidate phyla , , and . In total, 307 medium- or higher-quality MAGs were assigned to 23 phyla, compared to 294 MAGs assigned to nine phyla in the same samples individually assembled. The low-quality (<50% complete, <10% contaminated) MAGs from the coassembly revealed a 49% complete rare biosphere microbe from the candidate phylum FCPU426 among other low-abundance microbes, an 81% complete fungal genome from the phylum Ascomycota, and 30 partial eukaryotic MAGs with ≥10% completeness, possibly representing protist lineages. A total of 22,254 viruses, many of them low abundance, were identified. Estimation of metagenome coverage and diversity indicates that we may have characterized ≥87.5% of the sequence diversity in this humid tropical soil and indicates the value of future terabase-scale sequencing and coassembly of complex environments. Petabases of reads are being produced by environmental metagenome sequencing. An essential step in analyzing these data is metagenome assembly, the computational reconstruction of genome sequences from microbial communities. "Coassembly" of metagenomic sequence data, in which multiple samples are assembled together, enables more complete detection of microbial genomes in an environment than "multiassembly," in which samples are assembled individually. To demonstrate the potential for coassembling terabases of metagenome data to drive biological discovery, we applied MetaHipMer2, a distributed metagenome assembler that runs on supercomputing clusters, to coassemble 3.4 Tbp of reads from a humid tropical soil environment. The resulting coassembly, its functional annotation, and analysis are presented here. The coassembly yielded more, and phylogenetically more diverse, microbial, eukaryotic, and viral genomes than the multiassembly of the same data. Our resource may facilitate the discovery of novel microbial biology in tropical soils and demonstrates the value of terabase-scale metagenome sequencing.
Topics: Soil; Microbiota; Bacteria; Metagenome; Genome, Viral; Metagenomics
PubMed: 37310219
DOI: 10.1128/spectrum.00200-23 -
Nature Biotechnology Nov 2023Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present...
Metagenomic assembly enables new organism discovery from microbial communities, but it can only capture few abundant organisms from most metagenomes. Here we present MetaPhlAn 4, which integrates information from metagenome assemblies and microbial isolate genomes for more comprehensive metagenomic taxonomic profiling. From a curated collection of 1.01 M prokaryotic reference and metagenome-assembled genomes, we define unique marker genes for 26,970 species-level genome bins, 4,992 of them taxonomically unidentified at the species level. MetaPhlAn 4 explains ~20% more reads in most international human gut microbiomes and >40% in less-characterized environments such as the rumen microbiome and proves more accurate than available alternatives on synthetic evaluations while also reliably quantifying organisms with no cultured isolates. Application of the method to >24,500 metagenomes highlights previously undetected species to be strong biomarkers for host conditions and lifestyles in human and mouse microbiomes and shows that even previously uncharacterized species can be genetically profiled at the resolution of single microbial strains.
Topics: Humans; Animals; Mice; Metagenome; Microbiota; Gastrointestinal Microbiome; Metagenomics; Phylogeny
PubMed: 36823356
DOI: 10.1038/s41587-023-01688-w -
The ISME Journal Jan 2024Nearly all organisms are hosts to multiple viruses that collectively appear to be the most abundant biological entities in the biosphere. With recent advances in... (Review)
Review
Nearly all organisms are hosts to multiple viruses that collectively appear to be the most abundant biological entities in the biosphere. With recent advances in metagenomics and metatranscriptomics, the known diversity of viruses substantially expanded. Comparative analysis of these viruses using advanced computational methods culminated in the reconstruction of the evolution of major groups of viruses and enabled the construction of a virus megataxonomy, which has been formally adopted by the International Committee on Taxonomy of Viruses. This comprehensive taxonomy consists of six virus realms, which are aspired to be monophyletic and assembled based on the conservation of hallmark proteins involved in capsid structure formation or genome replication. The viruses in different major taxa substantially differ in host range and accordingly in ecological niches. In this review article, we outline the latest developments in virus megataxonomy and the recent discoveries that will likely lead to reassessment of some major taxa, in particular, split of three of the current six realms into two or more independent realms. We then discuss the correspondence between virus taxonomy and the distribution of viruses among hosts and ecological niches, as well as the abundance of viruses versus cells in different habitats. The distribution of viruses across environments appears to be primarily determined by the host ranges, i.e. the virome is shaped by the composition of the biome in a given habitat, which itself is affected by abiotic factors.
Topics: Viruses; Metagenomics; Ecology; Phylogeny; Genome, Viral
PubMed: 38365236
DOI: 10.1093/ismejo/wrad042 -
American Journal of Respiratory and... Jan 2024
Topics: Humans; Respiratory Tract Infections; Metagenomics; Intensive Care Units
PubMed: 38029295
DOI: 10.1164/rccm.202311-2039ED -
Science Advances Sep 2023Dysbiosis of skin microbiota drives the progression of atopic dermatitis (AD). The contribution of bacteriophages to bacterial community compositions in normal and...
Dysbiosis of skin microbiota drives the progression of atopic dermatitis (AD). The contribution of bacteriophages to bacterial community compositions in normal and inflamed skin is unknown. Using shotgun metagenomics from skin swabs of healthy individuals and patients with AD, we found 13,586 potential viral contiguous DNA sequences, which could be combined into 164 putative viral genomes including 133 putative phages. The Shannon diversity index for the viral metagenome-assembled genomes (vMAGs) did not correlate with AD. In total, we identified 28 vMAGs that differed significantly between normal and AD skin. Quantitative polymerase chain reaction validation of three complete vMAGs revealed their independence from host bacterium abundance. Our data indicate that normal and inflamed skin harbor distinct phageomes and suggest a causative relationship between changing viral and bacterial communities as a driver of skin pathology.
Topics: Humans; Virome; Skin; Microbiota; Metagenome; Bacteria; DNA, Viral
PubMed: 37774017
DOI: 10.1126/sciadv.adg4015 -
Statistical normalization methods in microbiome data with application to microbiome cancer research.Gut Microbes Dec 2023Mounting evidence has shown that gut microbiome is associated with various cancers, including gastrointestinal (GI) tract and non-GI tract cancers. But microbiome data... (Review)
Review
Mounting evidence has shown that gut microbiome is associated with various cancers, including gastrointestinal (GI) tract and non-GI tract cancers. But microbiome data have unique characteristics and pose major challenges when using standard statistical methods causing results to be invalid or misleading. Thus, to analyze microbiome data, it not only needs appropriate statistical methods, but also requires microbiome data to be normalized prior to statistical analysis. Here, we first describe the unique characteristics of microbiome data and the challenges in analyzing them (Section 2). Then, we provide an overall review on the available normalization methods of 16S rRNA and shotgun metagenomic data along with examples of their applications in microbiome cancer research (Section 3). In Section 4, we comprehensively investigate how the normalization methods of 16S rRNA and shotgun metagenomic data are evaluated. Finally, we summarize and conclude with remarks on statistical normalization methods (Section 5). Altogether, this review aims to provide a broad and comprehensive view and remarks on the promises and challenges of the statistical normalization methods in microbiome data with microbiome cancer research examples.
Topics: RNA, Ribosomal, 16S; Gastrointestinal Microbiome; Microbiota; Metagenome; Research Design; Neoplasms
PubMed: 37622724
DOI: 10.1080/19490976.2023.2244139