Biology subjects

Bushnell, B.

Publications and source records attributed to Bushnell, B..

9 recordsLinked to original sources

bioRxiv2026

GradeBins: a comprehensive framework to augment metagenomic bin quality control

1.Metagenomic binning and single-cell assembly produce draft genomes whose completeness and contamination vary with experimental and computational choices. Comparing whole bin sets remains difficult because most quality assessment tools report per-bin metrics and operate either with ground truth labels or with inference estimates. GradeBins evaluates complete bin sets under two execution modes while producing matched per-bin and bin-set summaries. For real metagenomes, inference mode integrates bin statistics, mapping depth, taxonomy, and external quality estimates from tools such as CheckM2 and EukCC to standardize per-bin and bin-set quality reporting across Bacteria, Archaea, and Eukaryotes. For synthetic or otherwise labeled datasets, ground truth mode computes base-resolved completeness, contamination, and misbinning from labeled contigs or CAMI mappings, enabling objective benchmarking of binners, parameter choices, and experimental conditions, and calibration of inference-based estimates. Across synthetic metagenomes of 10, 50, 100, 500 and 1,000 Bacteria and Archaea, and a mixed metagenome containing also Eukaryotes, GradeBins separated binner and parameter effects using Total Score and a quality-weighted bin count, together with quality tier distributions, recovery fractions, and label-aware diagnostics. Inference-mode completeness generally tracked ground truth, whereas contamination and clean-bin rates showed mode-dependent shifts that were most pronounced in the mixed community. GradeBins added low overhead in these benchmarks, with peak memory below 8 GB and runtimes typically below 30 seconds. GradeBins enables reproducible protocol comparison, regression testing, and consistent quality reporting for genome-resolved metagenomics in both benchmarking and real-data settings. The full software package is open-source and available for download at https://bbmap.org/tools/gradebins.

microbiology↗

bioRxiv2026

Deployable high-fidelity metagenome binning at scale with QuickBin

1.Reconstructing genomes from metagenomic assemblies is foundational to microbiome research, yet metagenome binning remains constrained by a persistent trade-off between genome fidelity and deployable throughput. Many high-accuracy approaches rely on GPU-intensive workflows, marker-gene-informed postprocessing, or resource demands that limit reproducible use at catalog scale. Here we present QuickBin, a CPU-native, marker-free binning algorithm designed to recover near-complete, ultra-low-contamination metagenome-assembled genomes (MAGs) under practical compute constraints. QuickBin couples a GC-coverage spatial index (BinMap) with a hierarchical, early-exit Oracle cascade of similarity tests (scalar composition/coverage filters followed by SIMD-accelerated k-mer comparisons), invoking a compact neural network only for the small fraction of ambiguous candidate merges. Across synthetic communities evaluated by both marker-based estimates and contig-origin ground truth, QuickBin yields high recovery while maximizing the fraction of sequence assigned to uncontaminated bins. In a benchmark of 297 diverse real metagenomes, QuickBin completed all runs and recovered more MAGs meeting [≥]95% completeness and [≤]1% contamination than widely used CPU binners and compute-intensive alternatives that frequently failed to finish under standardized limits. QuickBin provides a practical path to reproducible, high-fidelity genome-resolved metagenomics at scale for downstream comparative analyses and data products that depend on low-artifact genome reconstructions. The full software package is open-source and available for download at https://bbmap.org, GitHub repo (https://github.com/bbushnell/BBTools), or Docker container (https://hub.docker.com/r/bryce911/bbtools).

microbiology↗

bioRxiv2025

Rapid terabase-scale simulation of realistic metagenomes for experimental design and pathogen detection with RandomReadsMG

1.Accurate simulation of metagenomic sequencing data is determinant for benchmarking new algorithms, guiding experimental design and generation of synthetic data to develop and train models for AI/ML. However, existing simulators often struggle to reproduce the uneven coverage depth patterns seen in real microbial communities, can be difficult to install, or incur long runtimes. Here we present RandomReadsMG, a fast and scalable read simulator designed to generate synthetic metagenomes with realistic, user-defined depth distributions from hundreds of genomes in a single command. The tool supports multiple abundance models and intra-genome depth variability to better mimic real data. Benchmarks show RandomReadsMG runs orders of magnitude faster than comparable software while maintaining constant memory usage for input datasets of unbounded size. We demonstrate its utility by determining pathogen detection thresholds in a complex microbiome, showcasing its value for optimizing experimental design and creating robust training data sets for bioinformatics and AI/ML. RandomReadsMG is open-source software, distributed as part of the BBTools suite. The full software package is available for download at https://sourceforge.net/projects/bbmap/. For containerized deployment, a Docker image is also available from Docker Hub at https://hub.docker.com/r/bryce911/bbtools.

microbiology↗

bioRxiv2025

Planetary-scale metagenomic search reveals new patterns of CRISPR targeting

Interactions between microbes and their mobile genetic elements (MGEs), including viruses and plasmids, are critical drivers of microbiome structures and processes. CRISPR-Cas systems are important regulators of these host-MGE interactions, but a global understanding of CRISPR loci diversity, activity, and roles across Earths biomes is still lacking. Here, we use an optimized computational approach to search short-read data and collect [~]800 million CRISPR spacers across [~]450,000 public metagenomes. From this extensive CRISPR spacer dataset, we identified 1.18 billion hits between 41 million spacers and 2.5 million viruses and plasmids. Focusing on the role of CRISPR as anti-phage defense, we observed an over-representation of prevalent and conserved spacers consistent with a positive selection pressure associated with phage targeting. Identification of sustained CRISPR targeting by microbes not expected to be viable hosts suggested that some phage genomes may frequently enter non-host microbial cells. Taken together, these results outline the extensive diversity of CRISPR loci across microbiomes, and highlight key parameters driving CRISPR targeting patterns likely to influence strain-level diversification and selection processes within microbial populations.

microbiology↗

bioRxiv2025

Tool Choice drastically Impacts CRISPR Spacer-Protospacer Detection

1CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) systems are a fundamental defense mechanism in prokaryotes, where short sequences called spacers are stored in the host genome to recognize and target exogenous genetic elements. Viromics, the study of viral communities in environmental samples, relies heavily on identifying these spacer-target interactions to understand host-virus relationships. However, the choice of sequence search tool to identify putative spacer targets is often overlooked, leading to an unknown impact of downstream inferences in virus-host analysis. Here, we utilize simulated and real datasets to compare popular sequence alignment and search tools, revealing critical differences in their ability to detect multiple matches and handle varying degrees of sequence identity between spacers and potential targets. Finally, we provide general guidelines that may inform future research regarding matching, which is a common practice in studying the complex nature of host-MGE interactions.

bioinformatics↗

bioRxiv2025

Neural sensitivity to radial frequency patterns in the visual cortex of developing macaques

Visual resolution, contrast sensitivity and form perception improve gradually with age. In nonhuman primates, the sensitivity and resolution of cells in the retina, lateral geniculate nucleus and primary visual cortex (V1) also improve, but not enough to account for the perceptual changes. So, what aspects of visual system development limit visual sensitivity in infants? Improvements in behavioral sensitivity might arise from maturation of regions downstream of V1 such as V2, V4 and pIT, which are thought to support increasingly complex perceptual abilities. We recorded the responses of populations of neurons in areas V1, V2, V4, and pIT to radial frequency patterns - a type of global form stimulus. Subjects were three young monkeys between the ages of 19 and 54 weeks, and a single adult animal. We found that neurons and neural populations in V4 reliably encoded global form in radial frequency stimuli at the earliest ages we studied, while V1 neurons do not. V2 and pIT populations also showed some degree of selectivity for these patterns at early ages, especially at higher radial frequency values. We did not find significant, systematic changes in neural decoding performance that could account for the improvement in behavioral performance over the same age range in an overlapping group of animals (Rodriguez Deliz et al., 2024). Finally, consistent with our prior behavioral results, neural populations in V4 show highest sensitivity for the higher radial frequency values which contain the highest concentration of curvature and orientation cues. SIGNIFICANCE STATEMENTInfants have remarkably limited ability to discriminate shapes. These limitations cannot be fully explained by postnatal changes in their eyes, visual thalamus, or primary visual cortex. The perception of shape requires integration of local cues across space to create global form information. We therefore examined populations of neurons in extrastriate visual cortex to learn whether information represented in these regions might limit infants abilities to process global forms. We found instead that extrastriate areas involved in global form processing function maturely early in life, by the age of 4-6 months, suggesting that infants perceptual limits are set by other aspects of brain development.

neuroscience↗

bioRxiv2024

Development of radial frequency pattern perception in macaque monkeys

Infant primates see poorly, and most perceptual functions mature steadily beyond early infancy. Behavioral studies on human and macaque infants show that global form perception, as measured by the ability to integrate contour information into a coherent percept, improves dramatically throughout the first several years after birth. However, it is unknown when sensitivity to curvature and shape emerges in early life. We studied the development of shape sensitivity in eighteen macaques, aged 2 months to 10 years. Using radial frequency stimuli (RFS), circular targets whose radii are modulated sinusoidally, we tested monkeys ability to discriminate RFS from circles as a function of the depth and frequency of sinusoidal modulation. We implemented a new 4-choice oddity task and compared the resulting data with that from a traditional 2-alternative task. Behavioral performance at all radial frequencies improved with age. Performance was better for higher radial frequencies, suggesting the developing visual system prioritizes processing of fine visual details that are ecologically relevant. By utilizing two complementary methods, we were able to capture a comprehensive developmental trajectory for shape perception.

neuroscience↗

bioRxiv2020

The DOE JGI Metagenome Workflow

The DOE JGI Metagenome Workflow performs metagenome data processing, including assembly, structural, functional, and taxonomic annotation, and binning of metagenomic datasets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) comparative analysis system (I. Chen, K. Chu, K. Palaniappan, M. Pillay, A. Ratner, J. Huang, M. Huntemann, N. Varghese, J. White, R. Seshadri, et al, Nucleic Acids Rsearch, 2019) and provided for download via the Joint Genome Institute (JGI) Data Portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here we describe the different tools, databases, and parameters used at different steps of the workflow, to help with interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a Workflow Description Language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl.git). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, H. Katta, A. Mojica, I Chen, and N. Kyrpides, and T. Reddy, Nucleic Acids Research, 2018). IMPORTANCEThe DOE JGI Metagenome Workflow is designed for processing metagenomic datasets starting from Illumina fastq files. It performs data pre-processing, error correction, assembly, structural and functional annotation, and binning. The results of processing are provided in several standard formats, such as fasta and gff and can be used for subsequent integration into the Integrated Microbial Genome (IMG) system where they can be compared to a comprehensive set of publicly available metagenomes. As of 7/30/2020 7,155 JGI metagenomes have been processed by the JGI Metagenome Workflow.

bioinformatics↗

bioRxiv2020

Microbial DNA on the move: sequencing based detection and analysis of transduced DNA in pure cultures and microbial communities

Horizontal gene transfer (HGT) plays a central role in microbial evolution. Our understanding of the mechanisms, frequency and taxonomic range of HGT in polymicrobial environments is limited, as we currently rely on historical HGT events inferred from genome sequencing and studies involving cultured microorganisms. We lack approaches to observe ongoing HGT in microbial communities. To address this knowledge gap, we developed a DNA sequencing based "transductomics" approach that detects and characterizes microbial DNA transferred via transduction. We validated our approach using model systems representing a range of transduction modes and show that we can detect numerous classes of transducing DNA. Additionally, we show that we can use this methodology to obtain insights into DNA transduction among all major taxonomic groups of the intestinal microbiome. This work extends the genomic toolkit for the broader study of mobile DNA within microbial communities and could be used to understand how phenotypes spread within microbiomes. Significance StatementMicrobes can rapidly evolve new capabilities by acquiring genes from other organisms through a process called horizontal gene transfer (HGT). HGT occurs via different routes, one of which is by the transfer of DNA carried by microbe infecting viruses (phages) or virus-like agents. This process is called transduction and has primarily been studied in the lab using pure cultures or indirectly in environmental communities by analyzing signatures in microbial genomes revealing past transduction events. The transductomics approach that we present here, allows for the detection and characterization of genes that are potentially transferred between microbes in complex microbial communities at the time of measurement and thus provides insights into real-time ongoing horizontal gene transfer.

microbiology↗