Biology subjects

Knights, D.

Publications and source records attributed to Knights, D..

14 recordsLinked to original sources

bioRxiv2025

XTree enables memory-efficient, accurate short and long sequence alignment to millions of genomes across the tree of life

XTree is a k-mer-based aligner enabling rapid, memory-efficient alignment of sequencing reads to whole-genome reference databases with up to millions of genomes. Here, we detail XTrees performance on short and long read sequencing data and demonstrate its high accuracy across diverse bacterial, viral, and eukaryotic genomes. Benchmarking demonstrates superior and/or comparable precision and recall over existing tools, with more scalable indexing and efficient memory mapping. We additionally provide pre-indexed databases, including (1) the Genome Taxonomy Database (versions r214-r226), (2) representative GenBank fungi and protozoan genomes and (3) the Pan-Viral-Compendium, a bespoke data resource spanning 6.6 million, quality-controlled, viral genomes.

bioinformatics↗

bioRxiv2024

Sugar-rich foods exacerbate antibiotic-induced microbiome injury

Intestinal microbiota composition is implicated in several diseases; understanding the factors that influence it are key to elucidating host-commensal interactions and to designing microbiome-targeted therapies. We quantified how diet influences microbiome dynamics in hospitalized patients. We recorded 9,419 meals consumed by 173 patients undergoing hematopoietic cell transplantation and profiled the microbiome in 1,009 longitudinally collected stool samples from 158 of them. Caloric intake was correlated with fecal microbiota diversity. Bayesian inference revealed associations between intake of sweets or sugars during antibiotic exposure with microbiome disruption, as assessed by low diversity or expansion of the pathobiont Enterococcus. We validated this observation experimentally, finding that sucrose exacerbated antibiotic-induced Enterococcus expansion in mice. Taken together, our results suggest that avoiding sugar-rich foods during antibiotic treatment may reduce microbiome injury. One Sentence SummaryAnalyses of hematopoietic cell transplant patients and of mice uncover links between foods and microbiome disruption.

microbiology↗

bioRxiv2024

Assembly, stability, and dynamics of the infant gut microbiome are linked to bacterial strains and functions in mother's milk

The establishment of the gut microbiome in early life is critical for healthy infant development. Although human milk is recommended as sole nutrition for the infant, little is known about how variation in the milk microbiome shapes the microbial communities in the infant gut. Here, we quantified the similarity between the maternal milk and the infant gut microbiome using 507 metagenomic samples collected from 195 mother-infant pairs at one, three, and six months postpartum. Microbial taxonomic overlap between milk and the infant gut was driven by Bifidobacterium longum, and infant microbiomes dominated by B. longum showed greater temporal stability than those dominated by other species. We identified numerous instances of strain sharing between milk and the infant gut, involving both commensal (e.g. B. longum) and pathobiont species (e.g. K. pneumoniae). Shared strains also included typically oral species such as S. salivarius and V. parvula, suggesting possible transmission from the infants oral cavity to the mothers milk. At one month, the infant gut microbiome was enriched in biosynthetic pathways, suggesting that early colonisers might be more metabolically independent than later ones. Lastly, we observed significant overlap in antimicrobial resistance gene carriage within mother-infant pairs. Together, our results suggest that the human milk microbiome has an important role in the assembly, composition, and stability of the infant gut microbiome.

microbiology↗

bioRxiv2023

Human Cytomegalovirus in breast milk is associated with milk composition, the infant gut microbiome, and infant growth

Human cytomegalovirus (CMV) is a highly prevalent herpesvirus that is often transmitted to the neonate via breast milk. Postnatal CMV transmission can have negative health consequences for preterm and immunocompromised infants, but any effects on healthy term infants are thought to be benign. Furthermore, the impact of CMV on the composition of the hundreds of bioactive factors in human milk has not been tested. Here, we utilize a cohort of exclusively breastfeeding full term mother-infant pairs to test for differences in the milk transcriptome and metabolome associated with CMV, and the impact of CMV in breast milk on the infant gut microbiome and infant growth. We find upregulation of the indoleamine 2,3-dioxygenase (IDO) tryptophan-to-kynurenine metabolic pathway in CMV+ milk samples, and that CMV+ milk is associated with decreased Bifidobacterium in the infant gut. Our data indicate a complex relationship between milk CMV, milk kynurenine, and infant growth; with kynurenine positively correlated, and CMV viral load negatively correlated, with infant weight-for-length at 1 month of age. These results suggest CMV transmission, CMV-related changes in milk composition, or both may be modulators of full term infant development.

genomics↗

bioRxiv2023

Human milk variation is shaped by maternal genetics and impacts the infant gut microbiome

Human milk is a complex mix of nutritional and bioactive components that provide complete nutrition for the infant. However, we lack a systematic knowledge of the factors shaping milk composition and how milk variation influences infant health. Here, we used multi-omic profiling to characterize interactions between maternal genetics, milk gene expression, milk composition, and the infant fecal microbiome in 242 exclusively breastfeeding mother-infant pairs. We identified 487 genetic loci associated with milk gene expression unique to the lactating mammary gland, including loci that impacted breast cancer risk and human milk oligosaccharide concentration. Integrative analyses uncovered connections between milk gene expression and infant gut microbiome, including an association between the expression of inflammation-related genes with IL-6 concentration in milk and the abundance of Bifidobacteria in the infant gut. Our results show how an improved understanding of the genetics and genomics of human milk connects lactation biology with maternal and infant health.

genomics↗

bioRxiv2021

Shared and disease-specific host gene-microbiome interactions across human diseases

While the gut microbiome and host gene regulation separately contribute to gastrointestinal disorders, it is unclear how the two may interact to influence host pathophysiology. Here, we developed a machine learning-based framework to jointly analyze host transcriptomic and microbiome profiles from 416 colonic mucosal samples of patients with colorectal cancer, inflammatory bowel disease, and irritable bowel syndrome. We identified potential interactions between gut microbes and host genes that are disease-specific, as well as interactions that are shared across the three diseases, involving host genes and gut microbes previously implicated in gastrointestinal inflammation, gut barrier protection, energy metabolism, and tumorigenesis. In addition, we found that mucosal gut microbes that have been associated with all three diseases, such as Streptococcus, interact with different host pathways in each disease, suggesting that similar microbes can affect host pathophysiology in a disease-specific manner through regulation of different host genes.

genomics↗

bioRxiv2020

BURST enables mathematically optimal short-read alignment for big data

One of the fundamental tasks in analyzing next-generation sequencing data is genome database search, in which DNA sequences are compared to known reference genomes for identification or annotation. Although algorithms exist for optimal database search with perfect sensitivity and specificity, these have largely been abandoned for next-generation sequencing (NGS) data in favor of faster heuristic algorithms that sacrifice alignment quality. Virtually all DNA alignment tools that are commonly used in genomic and metagenomic database search use approximate methods that sometimes report the wrong match, and sometimes fail to find a valid match when present. Here we introduce BURST, a high-throughput DNA short-read aligner that uses several new synergistic optimizations to enable provably optimal alignment in NGS datasets. BURST finds all equally good matches in the database above a specified identity threshold and can either report all of them, pick the most likely among tied matches, or provide lowest-common-ancestor taxonomic annotation among tied matches. BURST can align, disambiguate, and assign taxonomy at a rate of 1,000,000 query sequences per minute against the RefSeq v82 representative prokaryotic genome database (5,500 microbial genomes, 19GB) at 98% identity on a 32-core computer, representing a speedup of up to 20,000-fold over current optimal gapped alignment techniques. This may have broader implications for clinical applications, strain tracking, and other situations where fast, exact, extremely sensitive alignment is desired.

bioinformatics↗

bioRxiv2019

Placenta microbiome diversity is associated with maternal pre-pregnancy obesity and placenta biogeography

Recently there has been considerable debate in the scientific community regarding the placenta as the host of a unique microbiome. No studies have addressed the associations of clinical conditions such as maternal obesity, or localizations on the placental microbiome. We examined the placental microbiome in a multi-ethnic maternal pre-pregnant obesity cohort using controls for environmental contaminants and an optimized microbiome protocol to enrich low bacterial biomass samples. We confirmed that a distinct placenta microbiome does exist, as compared to the environmental background. The placenta microbiome consists predominantly of Lactobacillus, Enterococcus and Chryseobacterium. Moreover, the microbiome in the placentas of obese pre-pregnant mothers are less diverse when compared to those of mothers of normal pre-pregnancy weight. Lastly, microbiome richness also decreases from the maternal side to fetal side. In summary, our study reveals associations of placental microbiome with placenta biogeography and with maternal pre-pregnant obesity.

microbiology↗

bioRxiv2018

Evaluating the information content of shallow shotgun metagenomics

Although microbial communities are associated with many aspects of human, environmental, plant, and animal health, there exists no cost-effective method for precisely characterizing species and genes present in such communities. While deep whole-genome shotgun (WGS) sequencing provides the highest-level of taxonomic and functional resolution, it is often prohibitively expensive for large-scale studies. The prevailing alternative, high-throughput 16S rRNA gene amplicon sequencing (16S), often does not resolve taxonomy past the genus level and provides only moderately accurate predictions of the functional profile; thus, there is currently no widely accepted approach to affordable, high-resolution, taxonomic and functional microbiome analysis. To address this technology gap, we evaluated the information content of shallow shotgun sequencing with as low as 0.5 million sequences per sample as an alternative to 16S sequencing for large human microbiome studies. We describe a library preparation protocol enabling shallow shotgun sequencing at approximately the same per-sample cost as 16S. We analyzed multiple real and simulated biological data sets, including two novel human stool samples with ultra-deep sequencing of 2.5 billion sequences per sample, and found that shallow shotgun recovers accurate species-level taxonomic and functional profiles of the human microbiome. We recognize and discuss some of the inherent limitations of shallow shotgun sequencing, and note that 16S sequencing remains a valuable and important method for taxonomic profiling of novel environments. Although deep WGS remains the gold standard for high-resolution microbiome analysis, we recommend that researchers consider shallow shotgun sequencing as a useful alternative to 16S for large-scale human microbiome research studies.

genomics↗

bioRxiv2018

American Gut: an Open Platform for Citizen-Science Microbiome Research

Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the USA, UK, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes as compared to environmental samples, demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations, uncover new molecules and kinds of molecular communities in the human stool metabolome, and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness, and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.\n\nImportanceWe show that a citizen-science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n=1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet which we confirm with untargeted metabolomics on hundreds of samples.

microbiology↗

bioRxiv2017

Associations Between Nutrition, Gut Microbiome, and Health in A Novel Nonhuman Primate Model

Red-shanked doucs (Pygathrix nemaeus) are endangered, foregut-fermenting colobine primates which are difficult to maintain in captivity. There are critical gaps in our understanding of their natural dietary habits including consumption of leaves, unripe fruit, flowers, seeds, and other plant parts. There is also a lack of understanding of enteric adaptations, including their unique microflora. To address these knowledge gaps, we used the douc as a model to study relationships between gastrointestinal microbial community structure, diet, and health. We analyzed published fecal samples as well as detailed dietary history from doucs with four distinct lifestyles (wild, semi-wild, semi-captive, and captive) and determined gastrointestinal bacterial microbiome composition using 16S rRNA sequencing. A clear gradient of microbiome composition was revealed along an axis of natural lifestyle disruption, including significant associations with diet, health, biodiversity, and microbial function. We identified potential microbial biomarkers of douc dysbiosis, including Bacteroides and Prevotella. Our results suggest a gradient-like shift in captivity causes an attendant shift to severe gut dysbiosis, thereby resulting in gastrointestinal issues.

microbiology↗

bioRxiv2017

BugBase Predicts Organism Level Microbiome Phenotypes

Shotgun metagenomics and marker gene amplicon sequencing can be used to directly measure or predict the functional repertoire of the microbiota en masse, but current methods do not readily estimate the functional capability of individual microorganisms. Here we present BugBase, an algorithm that predicts organism-level coverage of functional pathways as well as biologically interpretable phenotypes such as oxygen tolerance, Gram staining and pathogenic potential, within complex microbiomes using either whole-genome shotgun or marker gene sequencing data. We find BugBases organism-level pathway coverage predictions to be statistically higher powered than current bag-of-genes approaches for discerning functional changes in both host-associated and environmental microbiomes.

bioinformatics↗

bioRxiv2016

Discrete mutations in colorectal cancer correlate with defined microbial communities in the tumor microenvironment

Variation in the gut microbiome has been linked to colorectal cancer (CRC), as well as to host genetic variation. However, we do not know whether, in addition to baseline host genetics, somatic mutational profiles in CRC tumors interact with the surrounding tumor microbiome, and if so, whether these changes can be used to understand microbe-host interactions with potential functional biological relevance. Here, we characterized the association between CRC microbial communities and tumor mutations using microbiome profiling and whole-exome sequencing in 44 pairs of tumors and matched normal tissues. We found statistically significant associations between loss-of-function mutations in tumor genes and shifts in the abundances of specific sets of bacterial taxa, suggestive of potential functional interaction. This correlation allows us to statistically predict interactions between loss-of-function tumor mutations in cancer-related genes and pathways, including MAPK and Wnt signaling, solely based on the composition of the microbiome. These results can serve as a starting point for fine-grained exploration of the functional interactions between discrete alterations in tumor DNA and proximal microbial communities in CRC. In addition, these findings can lead to the development of improved microbiome-based CRC screening methods, as well as individualized microbiota-targeting therapies.\n\nAuthor summaryAlthough the gut microbiome - the collection of microorganisms that inhabit our gastrointestinal tract - has been implicated in colorectal cancer, colorectal tumors are caused by genetic mutations in host DNA. Here, we explored whether various mutations in colorectal tumors are correlated with specific changes in the bacterial communities that live in and on these tumors. We find that the genes and biological pathways that are mutated in tumors are correlated with variation in the composition of the microbiome. In fact, these changes in the microbiome are consistent enough that we can use them to statistically predict tumor mutations solely based on the microbiome. Our results may be used to understand the roles of specific microbes in CRC biology, and could also be the starting point of microbiome-based diagnostics for not only detection of CRC, but characterization of tumor mutational profiles.

cancer biology↗

bioRxiv2016

HOMINID: A framework for identifying associations between host genetic variation and microbiome composition

Recent studies have uncovered a strong effect of host genetic variation on the composition of host-associated microbiota. Here, we present HOMINID, a computational approach based on Lasso linear regression, that given host genetic variation and microbiome composition data, identifies host SNPs that are correlated with microbial taxa abundances. Using simulated data we show that HOMINID has accuracy in identifying associated SNPs, and performs better compared to existing methods. We also show that HOMINID can accurately identify the microbial taxa that are correlated with associated SNPs. Lastly, by using HOMINID on real data of human genetic variation and microbiome composition, we identified 13 human SNPs in which genetic variation is correlated with microbiome taxonomic composition across body sites. In conclusion, HOMINID is a powerful method to detect host genetic variants linked to microbiome composition, and can facilitate discovery of mechanisms controlling host-microbiome interactions.\n\nAvailability and implementationSoftware, code, tutorial, installation and setup details, and synthetic data are available in the project homepage: https://github.com/blekhmanlab/hominid.\n\nReal dataset used here is from Blekhman et al. (Blekhman et al. 2015); 16S rRNA gene sequence data and OTU tables are available on the HMP DACC website (www.hmpdacc.org), and host genetic data are deposited in dbGaP under project number phs000228.

genomics↗