A near-tight lower bound on the density of forward sampling schemes.

Motivation: Sampling k-mers is a ubiquitous task in sequence analysis algorithms. Sampling schemes such as the often-used random minimizer scheme are particularly appealing as they guarantee at least one k-mer is selected out of every w consecutive k-mers. Sampling fewer k-mers often leads to an increase in efficiency of downstream methods.

Multiplexed Detection, Partitioning, and Persistence of Wild-Type and Vaccine Strains of Measles, Mumps, and Rubella Viruses in Wastewater.

Wastewater surveillance of vaccine-preventable diseases may provide early warning of outbreaks and identify areas to target for immunization. To advance wastewater monitoring of measles, mumps, and rubella viruses, we developed and validated a multiplexed RT-ddPCR assay for the detection of their RNA. Because the measles-mumps-rubella (MMR) vaccine is an attenuated live virus vaccine, we also developed an assay that distinguishes between wild-type and vaccine strains of measles in wastewater and validated it using a wastewater sample collected from a facility with an active measles outbreak.

A near-tight lower bound on the density of forward sampling schemes.

Motivation: Sampling -mers is a ubiquitous task in sequence analysis algorithms. Sampling schemes such as the often-used random minimizer scheme are particularly appealing as they guarantee at least one -mer is selected out of every consecutive -mers. Sampling fewer -mers often leads to an increase in efficiency of downstream methods.

Rapid Whole Genome Characterization of High-Risk Pathogens Using Long-Read Sequencing to Identify Potential Healthcare Transmission.

Objective: Routine use of whole genome sequencing (WGS) has been shown to help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time-intensive. In light of recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource utilization approach capable of providing accurate WGS-based comparisons of HAI pathogens within a time frame allowing for infection prevention and control (IPC) interventions.

Probiotic therapy modulates the brain-gut-liver microbiota axis in a mouse model of traumatic brain injury.

The interplay between gut microbiota and host health is crucial for maintaining the overall health of the body and brain, and it is even more crucial how changes in the bacterial profile can influence the aftermath of traumatic brain injury (TBI). We studied the effects of probiotic treatment after TBI to identify potential changes in hepatic lipid species relevant to brain function. Bioinformatic analysis of the gut microbiota indicated a significant increase in the Firmicutes/Bacteroidetes ratio in the probiotic-treated TBI group compared to sham and untreated TBI groups.

Olivar: towards automated variant aware primer design for multiplex tiled amplicon sequencing of pathogens.

Tiled amplicon sequencing has served as an essential tool for tracking the spread and evolution of pathogens. Over 15 million complete SARS-CoV-2 genomes are now publicly available, most sequenced and assembled via tiled amplicon sequencing. While computational tools for tiled amplicon design exist, they require downstream manual optimization both computationally and experimentally, which is slow and costly.

Graph-based self-supervised learning for repeat detection in metagenomic assembly.

Repetitive DNA (repeats) poses significant challenges for accurate and efficient genome assembly and sequence alignment. This is particularly true for metagenomic data, in which genome dynamics such as horizontal gene transfer, gene duplication, and gene loss/gain complicate accurate genome assembly from metagenomic communities. Detecting repeats is a crucial first step in overcoming these challenges.

Antibiotic treatment induces microbiome dysbiosis and reduction of neuroinflammation following traumatic brain injury in mice.

Background: The gut microbiome is linked to brain pathology in cases of traumatic brain injury (TBI), yet the specific bacteria that are implicated are not well characterized. To address this gap, in this study, we induced traumatic brain injury (TBI) in male C57BL/6J mice using the controlled cortical impact (CCI) injury model. After 35 days, we administered a broad-spectrum antibiotics (ABX) cocktail (ampicillin, gentamicin, metronidazole, vancomycin) through oral gavage for 2 days to diminish existing microbiota.

Reference-free structural variant detection in microbiomes via long-read co-assembly graphs.

Motivation: The study of bacterial genome dynamics is vital for understanding the mechanisms underlying microbial adaptation, growth, and their impact on host phenotype. Structural variants (SVs), genomic alterations of 50 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to the absence of clear reference genomes and the presence of mixed strains.

MethPhaser: methylation-based long-read haplotype phasing of human genomes.

The assignment of variants across haplotypes, phasing, is crucial for predicting the consequences, interaction, and inheritance of mutations and is a key step in improving our understanding of phenotype and disease. However, phasing is limited by read length and stretches of homozygosity along the genome. To overcome this limitation, we designed MethPhaser, a method that utilizes methylation signals from Oxford Nanopore Technologies to extend Single Nucleotide Variation (SNV)-based phasing.

MetaCompass: Reference-guided Assembly of Metagenomes.

Metagenomic studies have primarily relied on assembly for reconstructing genes and genomes from microbial mixtures. While reference-guided approaches have been employed in the assembly of single organisms, they have not been used in a metagenomic context. Here we describe the first effective approach for reference-guided metagenomic assembly that can complement and improve upon metagenomic assembly methods for certain organisms.

Lightweight taxonomic profiling of long-read metagenomic datasets with Lemur and Magnet.

The advent of long-read sequencing of microbiomes necessitates the development of new taxonomic profilers tailored to long-read shotgun metagenomic datasets. Here, we introduce Lemur and Magnet, a pair of tools optimized for lightweight and accurate taxonomic profiling for long-read shotgun metagenomic datasets. Lemur is a marker-gene-based method that leverages an EM algorithm to reduce false positive calls while preserving true positives; Magnet is a whole-genome read-mapping-based method that provides detailed presence and absence calls for bacterial genomes.

Parsnp 2.0: scalable core-genome alignment for massive microbial datasets.

Motivation: Since 2016, the number of microbial species with available reference genomes in NCBI has more than tripled. Multiple genome alignment, the process of identifying nucleotides across multiple genomes which share a common ancestor, is used as the input to numerous downstream comparative analysis methods. Parsnp is one of the few multiple genome alignment methods able to scale to the current era of genomic data; however, there has been no major release since its initial release in 2014.

Unveiling microbial diversity: harnessing long-read sequencing technology.

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.

Probiotic treatment causes sex-specific neuroprotection after traumatic brain injury in mice.

Background: Recent studies have shed light on the potential role of gut dysbiosis in shaping traumatic brain injury (TBI) outcomes. Changes in the levels and types of bacteria present might impact the immune system disturbances, neuroinflammatory responses, anxiety and depressive-like behaviors, and compromised neuroprotection mechanisms triggered by TBI.

Objective: This study aimed to investigate the effects of a daily pan-probiotic (PP) mixture in drinking water containing strains of and administered for either two or seven weeks before inducing TBI on both male and female mice.

Microbial Community Profiling Protocol with Full-length 16S rRNA Sequences and Emu.

16S rRNA targeted amplicon sequencing is an established standard for elucidating microbial community composition. While high-throughput short-read sequencing can elicit only a portion of the 16S rRNA gene due to their limited read length, third generation sequencing can read the 16S rRNA gene in its entirety and thus provide more precise taxonomic classification. Here, we present a protocol for generating full-length 16S rRNA sequences with Oxford Nanopore Technologies (ONT) and a microbial community profile with Emu.

Sensitivity and consistency of long- and short-read metagenomics and epicPCR for the detection of antibiotic resistance genes and their bacterial hosts in wastewater.

Wastewater surveillance is a powerful tool to assess the risks associated with antibiotic resistance in communities. One challenge is selecting which analytical tool to deploy to measure risk indicators, such as antibiotic resistance genes (ARGs) and their respective bacterial hosts. Although metagenomics is frequently used for analyzing ARGs, few studies have compared the performance of long-read and short-read metagenomics in identifying which bacteria harbor ARGs in wastewater.

Identification of a novel CG307 sub-clade in third-generation-cephalosporin-resistant causing invasive infections in the USA.

Despite the notable clinical impact, recent molecular epidemiology regarding third-generation-cephalosporin-resistant (3GC-R) in the USA remains limited. We performed whole-genome sequencing of 3GC-R bacteraemia isolates collected from March 2016 to May 2022 at a tertiary care cancer centre in Houston, TX, USA, using Illumina and Oxford Nanopore Technologies platforms. A comprehensive comparative genomic analysis was performed to dissect population structure, transmission dynamics and pan-genomic signatures of our 3GC-R .

Reference-free Structural Variant Detection in Microbiomes via Long-read Coassembly Graphs.

Bacterial genome dynamics are vital for understanding the mechanisms underlying microbial adaptation, growth, and their broader impact on host phenotype. Structural variants (SVs), genomic alterations of 10 base pairs or more, play a pivotal role in driving evolutionary processes and maintaining genomic heterogeneity within bacterial populations. While SV detection in isolate genomes is relatively straightforward, metagenomes present broader challenges due to absence of clear reference genomes and presence of mixed strains.

Parsnp 2.0: Scalable Core-Genome Alignment for Massive Microbial Datasets.

Motivation: Since 2016, the number of microbial species with available reference genomes in NCBI has more than tripled. Multiple genome alignment, the process of identifying nucleotides across multiple genomes which share a common ancestor, is used as the input to numerous downstream comparative analysis methods. Parsnp is one of the few multiple genome alignment methods able to scale to the current era of genomic data; however, there has been no major release since its initial release in 2014.

KombOver: Efficient k-core and K-truss based characterization of perturbations within the human gut microbiome.

The microbes present in the human gastrointestinal tract are regularly linked to human health and disease outcomes. Thanks to technological and methodological advances in recent years, metagenomic sequencing data, and computational methods designed to analyze metagenomic data, have contributed to improved understanding of the link between the human gut microbiome and disease. However, while numerous methods have been recently developed to extract quantitative and qualitative results from host-associated microbiome data, improved computational tools are still needed to track microbiome dynamics with short-read sequencing data.

The pan-microbiome profiling system Taxa4Meta identifies clinical dysbiotic features and classifies diarrheal disease.

Targeted metagenomic sequencing is an emerging strategy to survey disease-specific microbiome biomarkers for clinical diagnosis and prognosis. However, this approach often yields inconsistent or conflicting results owing to inadequate study power and sequencing bias. We introduce Taxa4Meta, a bioinformatics pipeline explicitly designed to compensate for technical and demographic bias.