Coccidioidomycosis, or Valley fever, is caused by two species of dimorphic fungi. Based on molecular phylogenetic evidence, the genus Coccidioides contains two reciprocally monophyletic species: C. immitis and C. posadasii. However, phenotypic variation between species has not been deeply investigated. We therefore explored differences in growth rate under various conditions. A collection of 39 C. posadasii and 46 C. immitis isolates, representing the full geographical range of the two species, was screened for mycelial growth rate at 37 °C and 28 °C on solid media. The radial growth rate was measured for 16 days on yeast extract agar. A linear mixed effect model was used to compare the growth rate of C. posadasii and C. immitis at 37 °C and 28 °C, respectively. C. posadasii grew significantly faster at 37 °C, when compared to C. immitis; whereas both species had similar growth rates at 28 °C. These results indicate thermotolerance differs between these two species. As the ecological niche has not been well-described for Coccidioides spp., and disease variability between species has not been shown, the evolutionary pressure underlying the adaptation is unclear. However, this research reveals the first significant phenotypic difference between the two species that directly applies to ecological research.

As the size of reference sequence databases and high-throughput sequencing datasets continue to grow, it is becoming computationally infeasible to use traditional alignment to large genome databases for taxonomic classification of metagenomic reads. Exact matching approaches can rapidly assign taxonomy and summarize the composition of microbial communities, but they sacrifice accuracy and can lead to false positives. Full alignment tools provide higher confidence assignments and can assign sequences from genomes that diverge from reference sequences; however, full alignment tools are computationally intensive. To address this, we designed MTSv specifically for alignment-based taxonomic assignment in metagenomic analysis. This tool implements an FM-index assisted q-gram filter and SIMD accelerated Smith-Waterman algorithm to find alignments. However, unlike traditional aligners, MTSv will not attempt to make additional alignments to a TaxID once an alignment of sufficient quality has been found. This improves efficiency when many reference sequences are available per taxon. MTSv was designed to be flexible and can be modified to run on either memory or processor constrained systems. Although MTSv cannot compete with the speeds of exact k-mer matching approaches, it is reasonably fast and has higher precision than popular exact matching approaches. Because MTSv performs a full alignment it can classify reads even when the genomes share low similarity with reference sequences and provides a tool for high confidence pathogen detection with low off-target assignments to near neighbor species.

Coccidioidomycosis, or Valley fever, is caused by two species of dimorphic fungi. Based on molecular phylogenetic evidence, the genus Coccidioides contains two reciprocally monophyletic species: C. immitis and C. posadasii. However, phenotypic variation between species has not been deeply investigated. We therefore explored differences in growth rate under various conditions. A collection of 39 C. posadasii and 46 C. immitis isolates, representing the full geographical range of the two species, were screened for mycelial growth rate at 37°C and 28°C on solid media. The radial growth rate was measured over 16 days on yeast extract agar. A linear mixed effect model was used to compare the growth rate of C. posadasii and C. immitis at 37°C and 28°C respectively. C. posadasii grew significantly faster at 37°C, when compared to C. immitis; whereas both species had similar growth rates at 28°C. These results indicate thermotolerance differs between these two species. As the ecological niche has not been well-described for Coccidioides spp., and disease variability between species has not been shown, the evolutionary pressure underlying the adaptation is unclear. However, this research reveals the first significant phenotypic difference between the two species that directly applies to ecological and clinical research.

Summary: MetaTracer is a nucleotide alignment-based tool for metatranscriptomic analysis of complex bacterial communities that assigns sequence reads to both taxonomic groups and expressed genes in a single pass. Full nucleotide-level alignment improves accuracy relative to k-mer-based classifiers and preserves species-level resolution that is often lost in protein-based approaches. By retaining alignment coordinates and mapping reads directly to annotated genomic features, MetaTracer enables direct attribution of gene expression to specific microbial species. On simulated datasets, MetaTracer achieves high accuracy for both taxonomic and gene assignment. Applied to real dental plaque metatranscriptomic datasets, MetaTracer resolves species-specific transcriptional activity and detects reproducible differences in microbial gene expression between children with early childhood caries and healthy controls. Availability and implementation: MetaTracer is implemented as a Python-based workflow wrapper (metatracer v0.1.0) that depends on the mtsv-tools core engine (v2.1.0), which is written in Rust. The required functionality is supported by the v2.1.0 release of mtsv-tools. Both packages are open source under the MIT license and are available at github.com/FofanovLab/metatracer and github.com/FofanovLab/mtsv-tools. Versioned releases are archived at Zenodo (DOI: 10.5281/zenodo.18665766 and DOI: 10.5281/zenodo.18718002). Installation is supported via Bioconda. Contact: Viacheslav.Fofanov@nau.edu