Biology subjects

Lind, A. L.

Publications and source records attributed to Lind, A. L..

5 recordsLinked to original sources

bioRxiv2026

Quantitative detection of gut microbial eukaryotes with EukDetect2 reveals global distribution of commensal protists and association with distinct microbial community structure

Microbial eukaryotes are prevalent members of host-associated and free-living microbial communities, but are routinely excluded from studies of these communities. Existing methods for eukaryote detection from whole metagenome sequencing are limited by contamination of eukaryotic reference genomes and incomplete taxonomic coverage. Our previously published tool EukDetect addressed these challenges using a curated database of universal BUSCO marker genes, but lacked validated quantitative abundance metrics and was built from a limited number of genomes. Here we present EukDetect2, incorporating a database containing 6,948 microbial eukaryotic genomes representing 6,594 unique species, 2,339 of which are newly added since EukDetect version 1, alongside quantitative metrics for estimating absolute and relative abundance of microbial eukaryotes. Using simulated data, we demonstrate accurate abundance estimation, no false positives from bacterial or host-derived reads, and equivalent or greater sensitivity and specificity than alternative taxonomic profiling tools across a range of microbial abundances and community compositions. Applying EukDetect2 across globally distributed human gut microbiome cohorts, we find that Blastocystis spp. and Dientamoeba fragilis are the most prevalent gut eukaryotes across cohorts, while host-associated fungi are consistently less prevalent than commensal protists. Blastocystis abundance is positively associated with a gut microbial community enriched for fiber-fermenting microbes and depleted for pro-inflammatory and industrialization-associated taxa. EukDetect2 provides sensitive, accurate, and quantitative metrics for investigating microbial eukaryotes from metagenomic samples.

microbiology↗

bioRxiv2023

Evolutionary constraint and innovation across hundreds of placental mammals

Evolutionary constraint and acceleration are powerful, cell-type agnostic measures of functional importance. Previous studies in mammals were limited by species number and reliance on human-referenced alignments. We explore the evolution of placental mammals, including humans, through reference-free whole-genome alignment of 240 species and protein-coding alignments for 428 species. We estimate 10.7% of the human genome is evolutionarily constrained. We resolve constraint to single nucleotides, pinpointing functional positions, and refine and expand by over seven-fold the catalog of ultraconserved elements. Overall, 48.5% of constrained bases are as yet unannotated, suggesting yet-to-be-discovered functional importance. Using species-level phenotypes and an updated phylogeny, we associate coding and regulatory variation with olfaction and hibernation. Focusing on biodiversity conservation, we identify genomic metrics that predict species at risk of extinction.

genomics↗

bioRxiv2020

Accurate and sensitive detection of microbial eukaryotes from metagenomic shotgun sequencing data

BackgroundMicrobial eukaryotes are found alongside bacteria and archaea in natural microbial systems, including host-associated microbiomes. While microbial eukaryotes are critical to these communities, they are challenging to study with shotgun sequencing techniques and are therefore often excluded. ResultsHere we present EukDetect, a bioinformatics method to identify eukaryotes in shotgun metagenomic sequencing data. Our approach uses a database of 521,824 universal marker genes from 241 conserved gene families, which we curated from 3,713 fungal, protist, non-vertebrate metazoan, and non-streptophyte archaeplastid genomes and transcriptomes. EukDetect has a broad taxonomic coverage of microbial eukaryotes, performs well on low-abundance and closely related species, and is resilient against bacterial contamination in eukaryotic genomes. Using EukDetect, we describe the spatial distribution of eukaryotes along the human gastrointestinal tract, showing that fungi and protists are present in the lumen and mucosa throughout the large intestine. We discover that there is a succession of eukaryotes that colonize the human gut during the first years of life, mirroring patterns of developmental succession observed in gut bacteria. By comparing DNA and RNA sequencing of paired samples from human stool, we find that many eukaryotes continue active transcription after passage through the gut, though some do not, suggesting they are dormant or nonviable. We analyze metagenomic data from the Baltic Sea and find that eukaryotes differ across locations and salinity gradients. Finally, we observe eukaryotes in Arabidopsis leaf samples, many of which are not identifiable from public protein databases. ConclusionsEukDetect provides an automated and reliable way to characterize eukaryotes in shotgun sequencing datasets from diverse microbiomes. We demonstrate that it enables discoveries that would be missed or clouded by false positives with standard shotgun sequence analysis. EukDetect will greatly advance our understanding of how microbial eukaryotes contribute to microbiomes.

bioinformatics↗

bioRxiv2018

A robust phylogenomic timetree for biotechnologically and medically important fungi from Aspergillaceae (Eurotiomycetes, Ascomycota)

AbbreviationsNT, nucleotide; AA, amino acid; CI, credible interval; RCV, relative composition variability; IC, internode certainty; GSF, gene support frequencies; GLS, gene-wise log-likelihood scores; DVMC, degree of violation of a molecular clock\n\nThe filamentous fungal family Aspergillaceae contains > 1,000 known species, mostly in the genera Aspergillus and Penicillium. Several species are used in the food, biotechnology, and drug industries (e.g., Aspergillus oryzae, Penicillium camemberti), while others are dangerous human and plant pathogens (e.g., Aspergillus fumigatus, Penicillium digitatum). To infer a robust phylogeny and pinpoint poorly resolved branches and their likely underlying contributors, we used 81 genomes spanning the diversity of Aspergillus and Penicillium to construct a 1,668-gene data matrix. Phylogenies of the nucleotide and amino acid versions of this full data matrix as well as of five additional 834-gene data matrices constructed by subsampling the top 50% of genes according to different criteria associated with strong phylogenetic signal were generated using three different maximum likelihood schemes (i.e., gene-partitioned, unpartitioned, and coalescence). Examination of the topological agreement among these 36 phylogenies and measures of internode certainty identified 12 / 78 (15.4%) bipartitions that were incongruent and pinpoint the likely underlying contributing factors (incomplete lineage sorting, hybridization or introgression, and reconstruction artifacts associated with poor taxon sampling). Relaxed molecular clock analyses suggest that Aspergillaceae likely originated in the lower Cretaceous and the Aspergillus and Penicillium genera in the upper Cretaceous. Our results shed light on the ongoing debate on Aspergillus systematics and taxonomy and provide a robust evolutionary and temporal framework for comparative genomic analyses in Aspergillaceae. More broadly, our approach provides a general template for phylogenomic identification of resolved and contentious branches in densely genome-sequenced lineages across the tree of life.

evolutionary biology↗

bioRxiv2017

Drivers of genetic diversity in secondary metabolic gene clusters in a fungal population

Filamentous fungi produce a diverse array of secondary metabolites (SMs) critical for defense, virulence, and communication. The metabolic pathways that produce SMs are found in contiguous gene clusters in fungal genomes, an atypical arrangement for metabolic pathways in other eukaryotes. Comparative studies of filamentous fungal species have shown that SM gene clusters are often either highly divergent or uniquely present in one or a handful of species, hampering efforts to determine the genetic basis and evolutionary drivers of SM gene cluster divergence. Here we examined SM variation in 66 cosmopolitan strains of a single species, the opportunistic human pathogen Aspergillus fumigatus. Investigation of genome-wide within-species variation revealed five general types of variation in SM gene clusters: non-functional gene polymorphisms, gene gain and loss polymorphisms, whole cluster gain and loss polymorphisms, allelic polymorphisms where different alleles corresponded to distinct, non-homologous clusters, and location polymorphisms in which a cluster was found to differ in its genomic location across strains. These polymorphisms affect the function of representative A. fumigatus SM gene clusters, such as those involved in the production of gliotoxin, fumigaclavine, and helvolic acid, as well as the function of clusters with undefined products. In addition to enabling the identification of polymorphisms whose detection requires extensive genome-wide synteny conservation (e.g., mobile gene clusters and non-homologous cluster alleles), our approach also implicated multiple underlying genetic drivers, including point mutations, recombination, genomic deletion and insertion events, as well as horizontal gene transfer from distant fungi. Finally, most of the variants that we uncover within A. fumigatus have been previously hypothesized to contribute to SM gene cluster diversity across entire fungal classes and phyla. We suggest that the drivers of genetic diversity operating within a fungal species shown here are sufficient to explain SM cluster macroevolutionary patterns.

genomics↗