Biology subjects

Zorz, J.

Publications and source records attributed to Zorz, J..

9 recordsLinked to original sources

bioRxiv2026

Targeted Depletion of rRNAs and Tobamoviruses Enhances Viral Discovery in Wastewater Metatranscriptomes

Wastewater contains a complex mixture of nucleic acids derived from human cells, microorganisms, diets, and agricultural or industrial inputs. Metatranscriptomics has the potential to broaden the understanding of wastewater viromes, but its utility is constrained by high-abundance RNA molecules that prevent the detection of lower-abundance signals, including human pathogens. Two major sources of this interfering background signal are ribosomal RNAs (rRNAs) from various organisms, and plant-infecting tobamoviruses from human diets, which are often the most abundant RNA viruses in wastewater. These rRNA molecules and RNA genomes can account for upwards of 95% of total RNA sequences, thereby obscuring the detection of lower-abundance viruses of public health importance. This study evaluated whether combined depletion of ribosomal RNAs and genomic RNA from abundant plant tobamoviruses can improve the recovery of underrepresented viral sequences from wastewater. RNA extracts from a large municipal wastewater treatment plant in Calgary, Canada, were processed with or without probe-based depletion of rRNAs and eight abundant tobamoviruses. Metatranscriptomes revealed that depletion reduced rRNA reads by 90%. Reads assigned to tobamoviruses, which accounted for up to 25% of viral reads in untreated samples, were reduced to <2% of viral reads after depletion. This decrease in undesired RNA signal led to an order of magnitude increase in viral read signals and improved assembled viral genome quality. Furthermore, the number of reads assigned to human and animal pathogens increased 42-fold after depletion, enabling the detection of important pathogens like influenza, RSV, and hepatitis A, which were undecteable in untreated samples. Together, these findings demonstrate that targeted depletion of abundant background RNAs improves the detection of low abundance viruses, and enhances the utility of metatranscriptomic approaches for wastewater viral surveillance.

microbiology↗

bioRxiv2026

EsViritu is a sensitive and specific profiler for viral pathogen detection and genome recovery in metagenomes

Metagenomic sequencing allows for detection of any number of pathogenic viruses from a single sample without a priori knowledge of its contents. This has created a substantial opportunity to characterize pathogens in humans and their environment, but the field is held back by a lack of bioinformatics tools for taxonomic profiling and reconstructing virus genomes. The ideal profiler would simultaneously do two things: report viruses at single-read sensitivity so that ultra-low-abundance pathogens are not missed and hold near-perfect specificity so that a pathogen is never falsely reported. Here we present EsViritu, a taxonomic profiler that pairs an iterative greedy clustering algorithm and lowest-common-ancestor taxonomic refinement with a curated Virus Pathogen Database to reconstruct virus genomes and generate virome profiles directly from reads. We benchmarked EsViritu against four leading metagenomic profilers (Kraken2, Centrifuger, Metabuli, and Sylph), running each program across a full parameter sweep and against the same Virus Pathogen Database for an apples-to-apples comparison. Across synthetic positive controls, pathogen-free negative controls, and mutated mock communities, EsViritu was the most accurate tool at reconstructing community composition: it led or tied every tool on relative abundance accuracy at all taxonomic ranks and led or tied on detection across ranks. Importantly, other tools frequently report the presence of multiple related taxa when only reads for a single genome are present, but EsViritu faithfully records the correct, single taxon and genome. EsViritu achieves read-level sensitivity for sequences as low as 85% average nucleotide identity to the nearest reference and reports essentially no false positives in pathogen-free host and synthetic samples. EsViritu also returns reconstructed consensus genomes whose nucleotide identity to the nearest reference closely tracks ground truth, yielding both a profile and genomes from a single run.

bioinformatics↗

bioRxiv2026

Honey bee (Apis mellifera) gut microbiome associations with viruses and pesticides across Canadian agroecosystems

The honey bee (Apis mellifera) gut microbiome plays a central role in host health, yet its variation across agricultural landscapes remains poorly resolved. This study investigates how major environmental stressors, particularly pesticide exposure and RNA virus loadings, shape the honey bee gut microbiome in a large-scale field study conducted across Canada, spanning diverse agroecosystems from British Columbia to Quebec. We identify consistent associations between specific bacterial taxa and major RNA viruses, including enrichment of Serratia marcescens with SBV and depletion of Bombella intestini with BQCV. Pesticide exposure is likewise linked to reproducible shifts in key microbial taxa. Together, these findings reveal that interacting stressors jointly shape the bee gut microbiome and enable prediction of microbiome responses in agroecosystems. HighlightsDistinct associations identified between gut bacteria and major bee RNA viruses (BQCV, SBV, LSV, IAPV) Pesticide exposure is linked to reproducible shifts in key microbial taxa Combined virus-pesticide effects form coordinated clusters that predict microbiome variation and specific bacterial responses Integrated modeling demonstrates that environmental stressors can jointly explain microbiome structure beyond crop effects Graphical abstractSchematic overview of potential links between pesticide exposure and RNA virus infection and their effects on the bee gut bacterial community. Solid arrows indicate associations supported by the present study, whereas dashed arrows indicate hypothesized or unresolved interactions. Associations between the presence of specific bee RNA viruses (left) or pesticide residues (right) and changes in the relative abundance of particular gut taxa (pink {uparrow}, increased; blue {downarrow}, decreased). The pesticide subtype is indicated by the icon in the cell (leaf - herbicide, hyphae - fungicide and insect - insecticide). Several bacterial taxa showed reproducible associations with specific viral or pesticide variables, including Bombella intestini, Serratia marcescens, Melissococcus plutonius, Paenibacillus alvei, Apibacter sp. wkB309, and Gilliamella sp. A7. Abbreviations: BQCV Black queen cell virus; LSV, Lake Sinai virus; SBV, Sacbrood virus; IAPV, Israeli acute paralysis virus. (p/n/b) indicate the sample matrix in which the pesticide was detected, namely pollen, nectar, and bee tissue, respectively. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=133 SRC="FIGDIR/small/731697v1_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@cb92a4org.highwire.dtl.DTLVardef@1087045org.highwire.dtl.DTLVardef@102cabforg.highwire.dtl.DTLVardef@4ce2f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2026

Comparative Proteomics Across Tissues and Crop Agroecosystems Reveals Agricultural Stressor Responses in the Western Honey Bee

Maintaining honey bee health in crop production systems is increasingly difficult because worker bees encounter multiple chemical and biological pressures from pesticides and pathogens. How these field-realistic pressures affect molecular physiology across functionally distinct tissues remains poorly understood. Here, we tested whether tissue-resolved proteomics could separate stable tissue-specific patterns from crop-associated molecular changes. To do this, we profiled abdomen, gut, and head proteomes from honey bees collected across four Canadian crop ecosystems over two consecutive years, and integrated these data with pesticide-residue and pathogen-load measurements. Proteomic variation was structured by both tissue identity and crop environment. Tissue-specific proteomic profiles were characterized across samples, whereas crop-associated effects were detected in both years and were stronger in 2021, the second year of the study. Tissue-specific enrichment and network analyses linked the abdomen to lipid catabolism and ubiquitin-proteasome proteostasis, the gut to central carbon metabolism, membrane transport, vesicle trafficking, and cytoskeletal organization, and the head to neurosensory and mitochondrial functions, together with amino-sugar metabolism and vesicle-associated quality-control modules. Among the measured pesticide residues, boscalid was the most reproducible chemical correlate of proteomic variation, with the strongest signal in the gut. Cross-year validation associated boscalid exposure with reduced abundance of gut proteins involved in mitochondrial metabolism, protein quality control, vesicle trafficking, nutrient transport, and biosynthetic pathways. Additionally, integrated proteome-transcriptome-microbiome factor analysis further identified gut-centered components associated with measured stressor variables and linked protein-level variation to coordinated transcriptomic and microbial shifts. Independent-year validation showed that compact crop-associated protein signatures detected in 2020 were also present in 2021. Together, these results show that honey bee tissues maintain stable proteomic identities while showing tissue- and year-specific responses to pesticide and pathogen pressures encountered in crop ecosystems. The gut proteome may specifically provide a sensitive molecular indicator of pesticide-associated perturbation under field conditions.

bioinformatics↗

bioRxiv2023

Model cyanobacterial consortia reveal a consistent core microbiome independent of inoculation source or cyanobacterial host species

Cyanobacteria are integral to biogeochemical cycles, influence climate processes, and hold promise for commercial applications. In natural habitats, they form complex consortia with other microorganisms, where interspecies interactions shape their ecological roles. Although in vitro studies of these consortia have significantly advanced our understanding, they often lack the biological replication needed for robust statistical analysis of shared microbiome features and functions. Moreover, the microbiomes of many model cyanobacterial strains, which are central to our understanding of cyanobacterial biology, remain poorly characterized. Here, we expanded on existing in vitro approaches by co-culturing five well-characterized model cyanobacterial strains with microorganisms filtered from three distinct freshwater sources, generating 108 stable consortia. Metagenomic analyses revealed that, despite host and inoculum diversity, these consortia converged on a similar set of non-cyanobacterial taxa, forming a 25-species core microbiome. The large number of stable consortia in this study enabled statistical validation of both previously observed and newly identified core microbiome functionalities in micronutrient biosynthesis, metabolite transport, and anoxygenic photosynthesis. Furthermore, core species showed significant enrichment of plasmids, and functions encoded on plasmids suggested plasmid-mediated roles in symbiotic interactions. Overall, our findings uncover the potential microbiomes recruited by key model cyanobacteria, demonstrate that laboratory-enriched consortia retain many taxonomic and functional traits observed more broadly in phototroph-heterotroph assemblages, and show that model cyanobacteria can serve as robust hosts for uncovering functional roles underlying cyanobacterial community dynamics.

microbiology↗

bioRxiv2022

SituSeq: An offline protocol for rapid and remote Nanopore amplicon sequence analysis

Microbiome analysis through 16S rRNA gene sequencing is a crucial tool for understanding the microbial ecology of any habitat or ecosystem. However, workflows require large equipment, stable internet, and extensive computing power such that most of the work is performed far away from sample collection in both space and time. Performing amplicon sequencing and analysis at sample collection would have positive implications in many instances including remote fieldwork and point-of-care medical diagnoses. Here we present SituSeq, an offline and portable workflow for the sequencing and analysis of 16S rRNA gene amplicons using the Nanopore MinION and a standard laptop computer. SituSeq was validated using the same environmental DNA to sequence Nanopore 16S rRNA gene amplicons, Illumina 16S rRNA gene amplicons, and Illumina metagenomes. Comparisons revealed consistent community composition, ecological trends, and sequence identity across platforms. Correlation between the abundance of phyla in Illumina and Nanopore data sets was high (Pearsons r = 0.9), and over 70% of Illumina 16S rRNA gene sequences matched a Nanopore sequence with greater than 97% sequence identity. On board a research vessel on the open ocean, SituSeq was used to analyze amplicon sequences from deep sea sediments less than two hours after sequencing, and eight hours after sample collection. The rapidly available results informed decisions about subsequent sampling in near real-time while the offshore expedition was still underway. SituSeq is a portable and robust workflow that helps to bring the power of microbial genomics and diagnostics to many more researchers and situations.

microbiology↗

bioRxiv2022

A naturally occurring lytic bioprocess improves sustainability of phycocyanin production from cyanobacteria

Cyanobacteria form dense multicellular communities that experience transient conditions in terms of access to light and oxygen. These systems are productive but also undergo substantial biomass turnover, supplementing heightened heterotrophic respiration and oxygen drawdown. Here we use metagenomics and metaproteomics to survey the cellular response of a mat-forming cyanobacterium undergoing mass cell lysis after exposure to dark and anoxic conditions. A lack of evidence for visral, bacterial, or eukaryotic antagonism contradicts commonly held beliefs on the causative agent for cyanobacterial death during dense growth. Instead, proteogenomics data indicated that lysis resulted from a genetically programmed response triggered by a failure to maintain osmotic pressure in the wake of severe energy limitation. Cyanobacterial DNA was rapidly degraded, yet cyanobacterial proteins remained abundant. A subset of proteins, including enzymes involved in amino acid metabolism, peptidases, toxin-antitoxin systems, and a potentially self-targeting CRISPR-Cas system, were upregulated upon lysis, indicating involvement in the programmed cell death response. We propose this natural form of programmed cell death could provide new pathways for controlling harmful algal blooms and for sustainable bioproduct production.

microbiology↗

bioRxiv2021

Geological processes mediate a subsurface microbial loop in the deep biosphere

Summary paragraphThe deep biosphere is the largest microbial habitat on Earth and features abundant bacterial endospores1,2. Whereas dormancy and survival at theoretical energy minima are hallmarks of subsurface microbial populations3, the roles of fundamental ecological processes like dispersal and selection in these environments are poorly understood4. Here we combine geophysics, geochemistry, microbiology and genomics to investigate biogeography in the subsurface, focusing on bacterial endospores in a deep-sea setting characterized by thermogenic hydrocarbon seepage. Thermophilic endospores in permanently cold seabed sediments above petroleum seep conduits were correlated with the presence of hydrocarbons, revealing geofluid-facilitated cell migration pathways originating in deep oil reservoirs. Genomes of thermophilic bacteria highlight adaptations to life in anoxic petroleum systems and reveal that these dormant populations are closely related to oil reservoir microbiomes from around the world. After transport out of the subsurface and into the deep-sea, thermophilic endospores re-enter the geosphere by sedimentation. Viable thermophilic endospores spanning the top several metres of the seabed correspond with total endospore counts that are similar to or exceed the global average. Burial of dormant cells enables their environmental selection in sedimentary formations where new petroleum systems establish, completing a geological microbial loop that circulates living biomass in and out of the deep biosphere.

microbiology↗

bioRxiv2021

CANT-HYD: A curated database of phylogeny-derived Hidden Markov Models for annotation of marker genes involved in hydrocarbon degradation

Discovery of microbial hydrocarbon degradation pathways has traditionally relied on laboratory isolation and characterization of microorganisms. Although many metabolic pathways for hydrocarbon degradation have been discovered, the absence of tools dedicated to their annotation makes it difficult to identify the relevant genes and predict the hydrocarbon degradation potential of microbial genomes and metagenomes. Furthermore, sequence homology between hydrocarbon degradation genes and genes with other functions often results in misannotation. A tool that systematically identifies hydrocarbon metabolic potential is therefore needed. We present the Calgary approach to ANnoTating HYDrocarbon degradation genes (CANT-HYD), a database containing HMMs of 37 marker genes involved in anaerobic and aerobic degradation pathways of aliphatic and aromatic hydrocarbons. Using this database, we show that hydrocarbon metabolic potential is widespread in the tree of life and identify understudied or overlooked hydrocarbon degradation potential in many phyla. We also demonstrate scalability by analyzing large metagenomic datasets for the prediction of hydrocarbon utilization in diverse environments. To the best of our knowledge, CANT-HYD is the first comprehensive tool for robust and accurate identification of marker genes associated with aerobic and anaerobic hydrocarbon degradation.

bioinformatics↗