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2.
Cell Rep ; 43(6): 114268, 2024 May 21.
Article in English | MEDLINE | ID: mdl-38776226

ABSTRACT

We investigate the distribution and evolution of prokaryotic cell size based on a compilation of 5,380 species. Size spans four orders of magnitude, from 100 nm (Mycoplasma) to more than 1 cm (Thiomargarita); however, most species congregate heavily around the mean. The distribution approximates but is distinct from log normality. Comparative phylogenetics suggests that size is heritable, yet the phylogenetic signal is moderate, and the degree of heritability is independent of taxonomic scale (i.e., fractal). Evolutionary modeling indicates the presence of an optimal cell size to which most species gravitate. The size is equivalent to a coccus of 0.70 µm in diameter. Analyses of 1,361 species with sequenced genomes show that genomic traits contribute to size evolution moderately and synergistically. Given our results, scaling theory, and empirical evidence, we discuss potential drivers that may expand or shrink cells around the optimum and propose a stability landscape model for prokaryotic cell size.

4.
Nat Aging ; 4(4): 584-594, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38528230

ABSTRACT

Multiomics has shown promise in noninvasive risk profiling and early detection of various common diseases. In the present study, in a prospective population-based cohort with ~18 years of e-health record follow-up, we investigated the incremental and combined value of genomic and gut metagenomic risk assessment compared with conventional risk factors for predicting incident coronary artery disease (CAD), type 2 diabetes (T2D), Alzheimer disease and prostate cancer. We found that polygenic risk scores (PRSs) improved prediction over conventional risk factors for all diseases. Gut microbiome scores improved predictive capacity over baseline age for CAD, T2D and prostate cancer. Integrated risk models of PRSs, gut microbiome scores and conventional risk factors achieved the highest predictive performance for all diseases studied compared with models based on conventional risk factors alone. The present study demonstrates that integrated PRSs and gut metagenomic risk models improve the predictive value over conventional risk factors for common chronic diseases.


Subject(s)
Coronary Artery Disease , Diabetes Mellitus, Type 2 , Prostatic Neoplasms , Male , Humans , Diabetes Mellitus, Type 2/diagnosis , Prospective Studies , Risk Factors , Coronary Artery Disease/genetics , Genetic Risk Score
5.
Cell Rep ; 43(4): 113953, 2024 Apr 23.
Article in English | MEDLINE | ID: mdl-38517896

ABSTRACT

The gastrointestinal (GI) tract is innervated by intrinsic neurons of the enteric nervous system (ENS) and extrinsic neurons of the central nervous system and peripheral ganglia. The GI tract also harbors a diverse microbiome, but interactions between the ENS and the microbiome remain poorly understood. Here, we activate choline acetyltransferase (ChAT)-expressing or tyrosine hydroxylase (TH)-expressing gut-associated neurons in mice to determine effects on intestinal microbial communities and their metabolites as well as on host physiology. The resulting multi-omics datasets support broad roles for discrete peripheral neuronal subtypes in shaping microbiome structure, including modulating bile acid profiles and fungal colonization. Physiologically, activation of either ChAT+ or TH+ neurons increases fecal output, while only ChAT+ activation results in increased colonic contractility and diarrhea-like fluid secretion. These findings suggest that specific subsets of peripherally activated neurons differentially regulate the gut microbiome and GI physiology in mice without involvement of signals from the brain.


Subject(s)
Gastrointestinal Microbiome , Neurons , Animals , Gastrointestinal Microbiome/physiology , Mice , Neurons/metabolism , Choline O-Acetyltransferase/metabolism , Enteric Nervous System/physiology , Mice, Inbred C57BL , Tyrosine 3-Monooxygenase/metabolism , Male , Gastrointestinal Tract/microbiology
7.
Oncogene ; 43(15): 1127-1148, 2024 Apr.
Article in English | MEDLINE | ID: mdl-38396294

ABSTRACT

In 2020, we identified cancer-specific microbial signals in The Cancer Genome Atlas (TCGA) [1]. Multiple peer-reviewed papers independently verified or extended our findings [2-12]. Given this impact, we carefully considered concerns by Gihawi et al. [13] that batch correction and database contamination with host sequences artificially created the appearance of cancer type-specific microbiomes. (1) We tested batch correction by comparing raw and Voom-SNM-corrected data per-batch, finding predictive equivalence and significantly similar features. We found consistent results with a modern microbiome-specific method (ConQuR [14]), and when restricting to taxa found in an independent, highly-decontaminated cohort. (2) Using Conterminator [15], we found low levels of human contamination in our original databases (~1% of genomes). We demonstrated that the increased detection of human reads in Gihawi et al. [13] was due to using a newer human genome reference. (3) We developed Exhaustive, a method twice as sensitive as Conterminator, to clean RefSeq. We comprehensively host-deplete TCGA with many human (pan)genome references. We repeated all analyses with this and the Gihawi et al. [13] pipeline, and found cancer type-specific microbiomes. These extensive re-analyses and updated methods validate our original conclusion that cancer type-specific microbial signatures exist in TCGA, and show they are robust to methodology.


Subject(s)
Microbiota , Neoplasms , Humans , Neoplasms/genetics , Microbiota/genetics
8.
Nat Microbiol ; 9(3): 595-613, 2024 Mar.
Article in English | MEDLINE | ID: mdl-38347104

ABSTRACT

Microbial breakdown of organic matter is one of the most important processes on Earth, yet the controls of decomposition are poorly understood. Here we track 36 terrestrial human cadavers in three locations and show that a phylogenetically distinct, interdomain microbial network assembles during decomposition despite selection effects of location, climate and season. We generated a metagenome-assembled genome library from cadaver-associated soils and integrated it with metabolomics data to identify links between taxonomy and function. This universal network of microbial decomposers is characterized by cross-feeding to metabolize labile decomposition products. The key bacterial and fungal decomposers are rare across non-decomposition environments and appear unique to the breakdown of terrestrial decaying flesh, including humans, swine, mice and cattle, with insects as likely important vectors for dispersal. The observed lockstep of microbial interactions further underlies a robust microbial forensic tool with the potential to aid predictions of the time since death.


Subject(s)
Microbial Consortia , Soil Microbiology , Mice , Humans , Animals , Swine , Cattle , Cadaver , Metagenome , Bacteria
12.
Oncol Nurs Forum ; 50(4): 461-473, 2023 06 15.
Article in English | MEDLINE | ID: mdl-37677748

ABSTRACT

OBJECTIVES: To evaluate differences in the severity of global, cancer-specific, and cumulative life stress, resilience, and common neuropsychological symptoms among four subgroups of patients with distinct chemotherapy-induced nausea (CIN) profiles. SAMPLE & SETTING: Adult patients with cancer (N = 1,343) receiving chemotherapy. METHODS & VARIABLES: Patients completed stress, resilience, and neuropsychological symptom severity measures. The Memorial Symptom Assessment Scale was used to assess CIN occurrence six times over two cycles of chemotherapy. Parametric and nonparametric statistics were used to evaluate differences among subgroups of patients with distinct CIN profiles. RESULTS: The high class had significantly higher levels of global, cancer-specific, and cumulative life stress; significantly higher levels of depression, anxiety, sleep disturbance, morning and evening fatigue, and pain; and lower levels of morning and evening energy and cognitive dysfunction. IMPLICATIONS FOR NURSING: Clinicians need to evaluate CIN occurrence across each cycle of chemotherapy and assess patients for various types of stress and common neuropsychological symptoms.


Subject(s)
Cognitive Dysfunction , Neoplasms , Adult , Humans , Anxiety/chemically induced , Cognitive Dysfunction/chemically induced , Fatigue/chemically induced , Nausea/chemically induced , Pain , Neoplasms/drug therapy
13.
Cell Rep ; 42(8): 112997, 2023 08 29.
Article in English | MEDLINE | ID: mdl-37611587

ABSTRACT

Colorectal cancer (CRC) is driven by genomic alterations in concert with dietary influences, with the gut microbiome implicated as an effector in disease development and progression. While meta-analyses have provided mechanistic insight into patients with CRC, study heterogeneity has limited causal associations. Using multi-omics studies on genetically controlled cohorts of mice, we identify diet as the major driver of microbial and metabolomic differences, with reductions in α diversity and widespread changes in cecal metabolites seen in high-fat diet (HFD)-fed mice. In addition, non-classic amino acid conjugation of the bile acid cholic acid (AA-CA) increased with HFD. We show that AA-CAs impact intestinal stem cell growth and demonstrate that Ileibacterium valens and Ruminococcus gnavus are able to synthesize these AA-CAs. This multi-omics dataset implicates diet-induced shifts in the microbiome and the metabolome in disease progression and has potential utility in future diagnostic and therapeutic developments.


Subject(s)
Colorectal Neoplasms , Gastrointestinal Microbiome , Microbiota , Animals , Mice , Bile Acids and Salts , Metabolome
14.
Microbiome ; 11(1): 186, 2023 08 19.
Article in English | MEDLINE | ID: mdl-37596696

ABSTRACT

BACKGROUND: Exploring metagenomic contigs and "binning" them into metagenome-assembled genomes (MAGs) are essential for the delineation of functional and evolutionary guilds within microbial communities. Despite the advances in automated binning algorithms, their capabilities in recovering MAGs with accuracy and biological relevance are so far limited. Researchers often find that human involvement is necessary to achieve representative binning results. This manual process however is expertise demanding and labor intensive, and it deserves to be supported by software infrastructure. RESULTS: We present BinaRena, a comprehensive and versatile graphic interface dedicated to aiding human operators to explore metagenome assemblies via customizable visualization and to associate contigs with bins. Contigs are rendered as an interactive scatter plot based on various data types, including sequence metrics, coverage profiles, taxonomic assignments, and functional annotations. Various contig-level operations are permitted, such as selection, masking, highlighting, focusing, and searching. Binning plans can be conveniently edited, inspected, and compared visually or using metrics including silhouette coefficient and adjusted Rand index. Completeness and contamination of user-selected contigs can be calculated in real time. In demonstration of BinaRena's usability, we show that it facilitated biological pattern discovery, hypothesis generation, and bin refinement in a complex tropical peatland metagenome. It enabled isolation of pathogenic genomes within closely related populations from the gut microbiota of diarrheal human subjects. It significantly improved overall binning quality after curating results of automated binners using a simulated marine dataset. CONCLUSIONS: BinaRena is an installation-free, dependency-free, client-end web application that operates directly in any modern web browser, facilitating ease of deployment and accessibility for researchers of all skill levels. The program is hosted at https://github.com/qiyunlab/binarena , together with documentation, tutorials, example data, and a live demo. It effectively supports human researchers in intuitive interpretation and fine tuning of metagenomic data. Video Abstract.


Subject(s)
Metagenome , Microbiota , Humans , Metagenome/genetics , Microbiota/genetics , Algorithms , Biological Evolution , Diarrhea
15.
bioRxiv ; 2023 Jul 17.
Article in English | MEDLINE | ID: mdl-37503047

ABSTRACT

The human oral and nasal microbiota contains approximately 770 cultivable bacterial species. More than 2000 genome sequences of these bacteria can be found in the expanded Human Oral Microbiome Database (eHOMD). We developed HOMDscrape, a freely available Python software tool to programmatically retrieve and process amino acid sequences and sequence identifiers from BLAST results acquired from the eHOMD website. Using the data obtained through HOMDscrape, the phylogeny of proteins involved in bacterial flagellar motility, Type 4 pilus driven twitching motility, and Type 9 Secretion system (T9SS) driven gliding motility was constructed. A comprehensive phylogenetic analysis was conducted for all components of the rotary T9SS, a machinery responsible for secreting various enzymes, virulence factors, and enabling bacterial gliding motility. Results revealed that the T9SS outer membrane ß-barrel protein SprA of human oral microbes underwent horizontal evolution. Overall, we catalog motile microbes that inhabit the human oral microbiota and document their evolutionary connections. These results will serve as a guide for further studies exploring the impact of motility on shaping of the human oral microbiota.

16.
Front Microbiol ; 14: 1202194, 2023.
Article in English | MEDLINE | ID: mdl-37415812

ABSTRACT

Indoor home dust microbial communities, important contributors to human health, are shaped by environmental factors, including farm-related exposures. Advanced metagenomic whole genome shotgun sequencing (WGS) improves detection and characterization of microbiota in the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). We hypothesized that the improved characterization of indoor dust microbial communities by WGS will enhance detection of exposure-outcome associations. The objective of this study was to identify novel associations of environmental exposures with the dust microbiome from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria. The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium, and Pseudomonas, was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota. These findings can inform the design of future studies in environmental health.

17.
Nat Biotechnol ; 2023 Jul 27.
Article in English | MEDLINE | ID: mdl-37500913

ABSTRACT

Studies using 16S rRNA and shotgun metagenomics typically yield different results, usually attributed to PCR amplification biases. We introduce Greengenes2, a reference tree that unifies genomic and 16S rRNA databases in a consistent, integrated resource. By inserting sequences into a whole-genome phylogeny, we show that 16S rRNA and shotgun metagenomic data generated from the same samples agree in principal coordinates space, taxonomy and phenotype effect size when analyzed with the same tree.

18.
Nat Biotechnol ; 2023 Jul 27.
Article in English | MEDLINE | ID: mdl-37500914

ABSTRACT

Phylogenetic trees provide a framework for organizing evolutionary histories across the tree of life and aid downstream comparative analyses such as metagenomic identification. Methods that rely on single-marker genes such as 16S rRNA have produced trees of limited accuracy with hundreds of thousands of organisms, whereas methods that use genome-wide data are not scalable to large numbers of genomes. We introduce updating trees using divide-and-conquer (uDance), a method that enables updatable genome-wide inference using a divide-and-conquer strategy that refines different parts of the tree independently and can build off of existing trees, with high accuracy and scalability. With uDance, we infer a species tree of roughly 200,000 genomes using 387 marker genes, totaling 42.5 billion amino acid residues.

19.
Nat Neurosci ; 26(7): 1208-1217, 2023 07.
Article in English | MEDLINE | ID: mdl-37365313

ABSTRACT

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by heterogeneous cognitive, behavioral and communication impairments. Disruption of the gut-brain axis (GBA) has been implicated in ASD although with limited reproducibility across studies. In this study, we developed a Bayesian differential ranking algorithm to identify ASD-associated molecular and taxa profiles across 10 cross-sectional microbiome datasets and 15 other datasets, including dietary patterns, metabolomics, cytokine profiles and human brain gene expression profiles. We found a functional architecture along the GBA that correlates with heterogeneity of ASD phenotypes, and it is characterized by ASD-associated amino acid, carbohydrate and lipid profiles predominantly encoded by microbial species in the genera Prevotella, Bifidobacterium, Desulfovibrio and Bacteroides and correlates with brain gene expression changes, restrictive dietary patterns and pro-inflammatory cytokine profiles. The functional architecture revealed in age-matched and sex-matched cohorts is not present in sibling-matched cohorts. We also show a strong association between temporal changes in microbiome composition and ASD phenotypes. In summary, we propose a framework to leverage multi-omic datasets from well-defined cohorts and investigate how the GBA influences ASD.


Subject(s)
Autism Spectrum Disorder , Gastrointestinal Microbiome , Humans , Gastrointestinal Microbiome/genetics , Brain-Gut Axis , Autism Spectrum Disorder/genetics , Autism Spectrum Disorder/metabolism , Cross-Sectional Studies , Bayes Theorem , Reproducibility of Results , Cytokines
20.
medRxiv ; 2023 Apr 12.
Article in English | MEDLINE | ID: mdl-37090637

ABSTRACT

Indoor home dust microbial communities, important contributors to human health outcomes, are shaped by environmental factors, including farm-related exposures. Detection and characterization of microbiota are influenced by sequencing methodology; however, it is unknown if advanced metagenomic whole genome shotgun sequencing (WGS) can detect novel associations between environmental exposures and the indoor built-environment dust microbiome, compared to conventional 16S rRNA amplicon sequencing (16S). This study aimed to better depict indoor dust microbial communities using WGS to investigate novel associations with environmental risk factors from the homes of 781 farmers and farm spouses enrolled in the Agricultural Lung Health Study. We examined various farm-related exposures, including living on a farm, crop versus animal production, and type of animal production, as well as non-farm exposures, including home cleanliness and indoor pets. We assessed the association of the exposures on within-sample alpha diversity and between-sample beta diversity, and the differential abundance of specific microbes by exposure. Results were compared to previous findings using 16S. We found most farm exposures were significantly positively associated with both alpha and beta diversity. Many microbes exhibited differential abundance related to farm exposures, mainly in the phyla Actinobacteria, Bacteroidetes, Firmicutes , and Proteobacteria . The identification of novel differential taxa associated with farming at the genera level, including Rhodococcus, Bifidobacterium, Corynebacterium , and Pseudomonas , was a benefit of WGS compared to 16S. Our findings indicate that characterization of dust microbiota, an important component of the indoor environment relevant to human health, is heavily influenced by sequencing techniques. WGS is a powerful tool to survey the microbial community that provides novel insights on the impact of environmental exposures on indoor dust microbiota, and should be an important consideration in designing future studies in environmental health.

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