Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.10.13.758942

Microbial persistence beneath temporal restructuring in university wastewater metagenomes

Franco, G.·Anand, A.
View original source ↗Export metadata ↓

Abstract

Temporal changes in wastewater microbiomes can reflect shifts in microbial abundance, detectable membership, and genome recovery. We paired genome-resolved and read-based metagenomics to distinguish these signals in 25 spatially pooled university wastewater samples collected during wet and dry periods. The workflow recovered 203 wet-period and 230 dry-period metagenome-assembled genomes (MAGs). Community composition differed between periods in both MAG-derived presence/absence profiles (Jaccard PERMANOVA, R2 = 0.548, p = 0.001) and read-based relative-abundance profiles (BrayCurtis PERMANOVA, R2 = 0.167, p = 0.001). Greater dry-period read-based richness persisted after rarefaction but disappeared under more stringent abundance thresholds, indicating a substantial contribution from low-abundance detections. Of 57 period-associated core species in the MAG-derived profiles, 14 had exact species-level matches in the read-based dataset. All 14 remained detectable at >=90% prevalence in the opposite period, and 13 had higher relative abundance in the period corresponding to their MAG-based association. Continued species detection therefore accompanied changes in community composition and MAG-based representation. Perfect/Strict CARD/RGI resistance-associated annotations occurred in 94.1% of wet-period and 92.2% of dry-period MAGs and were distributed across shared-core and period-associated taxa. These findings reveal repeated detection of a matched subset of microbial taxa beneath temporal community restructuring, together with widespread resistance-associated genetic potential among recovered genomes. Combining read-based and genome-resolved profiles helps distinguish changes in detectable membership from changes in the genomic characterization available for wastewater surveillance.

Explore related subjects

microbiologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Franco, G., Anand, A.. 2026-10-14. Microbial persistence beneath temporal restructuring in university wastewater metagenomes. https://doi.org/10.64898/2026.10.13.758942

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

A droplet-to-data workflow for antimicrobial screening of complex matrices

Screening plant extracts and other complex natural matrices for antibacterial activity is complicated by optical interference and population averaging in conventional bulk assays. Droplet-based assays mitigate interference while enabling high-throughput assessment of bacterial subpopulations. However, analyzing the resulting image data involves difficult image processing, classification, and interpretation. Here, we present a democratized workflow for antimicrobial screening in complex matrices that combines a polydisperse droplet-based assay with EasyFlow 2.0 (EF2), our updated droplet image analysis platform. EF2 offers stable containerized deployment, expanded polydisperse droplet support, automated thresholding and MIC estimation, LLM-assisted data exploration, and import of other software outputs such as CellProfiler (CP) measurements and CellProfiler Analyst (CPA) classification models. As proof of concept, we applied this workflow to assess the antibacterial and aggregation-modulating effects of chemically distinct extracts of Taraxacum officinale, Rhodiola rosea, and Lonicera caerulea against Escherichia coli. Extracts were chemically characterized by HPLC-MS and evaluated using both standard 96-well plate microdilution and droplet-based assays. In total, 27,059 droplets were segmented in CP, classified into four growth phenotypes using a CPA random forest model, and analyzed in EF2. The droplet-based assay reached minimal inhibitory concentration (MIC) at lower extract concentrations than 96-well plate microdilution and revealed extract-specific aggregation effects: L. caerulea reduced E. coli aggregation, whereas T. officinale did not. R. rosea reduced growth in the 96-well plate microdilution assay, but high concentrations caused droplet gelation that prevented droplet-based analysis, showing that sample components must be checked for compatibility with droplet formation. These results illustrate that the EF2-centered workflow supports rapid, automated MIC estimation through unsupervised thresholding when labels are unavailable, and four-class aggregation phenotyping when a CPA model is supplied. This workflow offers flexible, scalable screening, potentially extendable beyond plant extracts to other complex sample matrices.

microbiology↗
bioRxiv2026

The influence of drug dosing regimen on extinction and adaptation during experimental evolution in Candida albicans

The antifungal azole drug fluconazole (FLC) is frequently prescribed for treating Candida albicans infections. Azole drugs are typically fungistatic; they inhibit cell growth rather than kill susceptible cells within a population. Therefore, fungal populations can adapt to fluconazole through increased drug resistance or increased drug tolerance (the ability of a subpopulation of susceptible cells to grow slowly at inhibitory drug concentrations). To our knowledge, no prior experiments have examined how different factors influence extinction propensity, although previous in vitro studies show that both drug concentration and strain background can influence adaptation. To determine how the drug dosing regimen, namely fluconazole concentration and transfer duration (i.e., the amount of time between transfer into fresh medium), influenced extinction and adaptation in Candida albicans, we conducted a fully factorial series of short in vitro evolution experiments. Dosing regimen significantly influenced extinction: all replicates evolved at all drug concentrations survived the 48 h and 72 h transfer experiments, yet the extinction rate increased sharply from low to high drug concentration with 24 h transfers. Increases in drug tolerance were frequent regardless of the dosing regimen. In contrast, drug resistance and growth rate both tended to decrease following evolution at higher drug concentrations. Fluconazole-evolved replicates exhibited frequent increases in cross-tolerance and decreases in cross-resistance in a panel of other azole drugs. Genome size changes were common in some strain backgrounds evolved to higher fluconazole concentrations, regardless of transfer times. Combined, our results indicate that many experimental factors can influence the trajectory of adaptation, and show that extinction in a fungistatic drug occurs readily at high drug concentrations with rapid transfers.

microbiology↗
bioRxiv2026

Abundance-weighted analysis and deep functional metagenomic selection reveals unrecognized diversity of soil-derived streptothricin acetyltransferases

Streptothricins (STCs) are broad-spectrum antibiotics under investigation for their therapeutic potential against antibiotic-resistant Gram-negative pathogens. However, the extent and diversity of genes that confer resistance to STCs, or their environmental resistome, remains largely unknown and is essentially limited to a handful of STC acetyltransferases. Here, we used a deep functional metagenomic approach to uncover previously unrecognized STC resistance determinants. A functional metagenomic library containing ca. 700 Gigabases of soil metagenomic DNA was selected for resistance to nourseothricin (NTC), a mixture of STC congeners, resulting in collection and sequencing of nearly 30,000 resistant clones. An abundance-weighted sequence analysis identified 265 acetyltransferase-like candidates spanning broad phylogenetic, taxonomic, and genomic diversity. Re-cloning and experimental testing of 18 candidates chosen to cover acetyltransferase sequence space confirmed that 10 conferred significant NTC resistance in Escherichia coli. Phylogenetic analyses identified three previously uncharacterized STC acetyltransferase lineages, designated as SatC, SatD, and SatE. Despite substantial sequence divergence from characterized streptothricin acetyltransferases (maximum amino acid identities of approximately 31% for SatC and SatD and up to 47.5% for SatE), these enzymes largely retained key residues associated with streptothricin binding and catalysis. In addition to strongly increasing NTC resistance, expression of the SatC construct in E. coli also significantly decreased susceptibility to the aminoglycoside antibiotics amikacin and kanamycin. Together, these findings reveal a substantially broader than previously known environmental repertoire of STC acetyltransferases and demonstrate how deep functional metagenomic selections, combined with abundance-weighted hit calling, phylogenetic analysis, and structural prediction, can uncover novel resistance functions.

microbiology↗