Biology subjects

Serrana, J. M.

Publications and source records attributed to Serrana, J. M..

14 recordsLinked to original sources

bioRxiv2026

Pollutant biodegradation profile mediated by multi-trophic microbial dynamics in rivers

Microbial communities and environmental conditions are closely linked to ecosystem functions and directly govern the biodegradation of pollutants in aquatic environments. However, the role of multi-trophic interactions and their spatiotemporal dynamics in these processes remains poorly understood. Here, we examined how seasonal and spatial variations, mediated by trophic interactions within benthic microbial communities, influence their composition, functional capacity, and collective potential to degrade a diverse array of organic pollutants in rivers. By characterizing both prokaryotic (i.e., archaea and bacteria) and eukaryotic taxa (i.e., algae, fungi, protists, and metazoans), and inferring metabolic pathways, we explored the connections between community composition and pollutant degradation in wastewater-receiving rivers across four seasons. Mediation analysis revealed that multi-trophic communities mediate the total effect of environmental factors on the biodegradation of 96 organic pollutants. Prokaryotic communities explained 60% of the total environmental influence on pollutant biodegradation. Additionally, eukaryotic groups had significant indirect mediation effects, with fungal, protistan, algal, and metazoan communities responsible for 56%, 53%, 26%, and 38%, respectively. Notably, fungal and protist communities mediated approximately 83% and 73% of the environmental impacts on prokaryotic community composition, respectively. Across the two rivers studied, spatial variation (at the river and reach scales) explained more variance in community composition than seasonality over the sampled year. Our findings improve understanding of ecosystem resilience and support the development of predictive models and sustainable water management strategies in dynamic aquatic environments.

microbiology↗

bioRxiv2026

Haplotype-level metabarcoding revealed the relationship between species occurrence and population genetic structure at the catchment scale in aquatic insects

A longstanding question in ecology and evolutionary biology is understanding the evolutionary mechanisms whereby some species appear frequently while others do not. Current research examined this phenomenon through computer simulations and empirical studies involving a few species, while community-wide investigations of this relationship in natural settings remain largely unexplored. To address this, we employed haplotype-level bulk DNA metabarcoding to infer haplotypes from many aquatic insect species with varying occurrence in a catchment. We identified 891 haplotypes belonging to 200 taxonomically identified Operational Taxonomic Units (OTUs). Results showed that species with higher occurrence in the catchment had greater {gamma}-genetic diversity, a wider range of environmental conditions, and an increased probability of {beta}-species-genetic diversity correlations (SGDC). We found negative -SGDC in species with lower occurrence in the catchment. Dispersal abilities and environmental factors may influence the relationship among species occurrence, population genetic structure, and SGDC. Our findings present a novel approach to address the association of species occurrence and population genetic structure, as well as SGDC, from a community-level perspective. This has important implications for addressing biodiversity loss driven by rapid environmental changes from human activities and climate change.

ecology↗

bioRxiv2025

Microbial hydrocarbon degradation potential of the Baltic Sea ecosystem

BackgroundThe Baltic Sea receives petroleum hydrocarbons from various point sources. The degradation of these contaminants in the environment is typically facilitated by a variety of microorganisms that possess a range of genes and metabolic functions related to the degradation of various hydrocarbon substrates. However, our understanding of natural attenuation and the microbial capacity to degrade these contaminants within the Baltic Sea ecosystem remains limited. In this study, we compiled metagenomes from the benthic and pelagic ecosystems across the Baltic Sea to identify microorganisms and characterize their genes and metabolic functions involved in the degradation of hydrocarbon compounds. ResultsKnown hydrocarbon-degrading phyla, i.e., Pseudomonadota, Myxococcota A, Actinomycetota, and Desulfobacterota, were identified within the Baltic Sea metagenome-assembled genomes (MAGs). Notably, 80% of the MAGs exhibited multiple hydrocarbon degradation gene annotations (>10 reads per kilobase million). Aerobic degradation was the predominant pathway for hydrocarbon degradation across environmental samples. Hydrocarbon degradation gene abundances varied among samples and Baltic Sea subbasins, with long-chain alkanes and dibenzothiophene compounds being the preferred substrates. Species richness and diversity of both benthic and pelagic microorganisms positively correlated with hydrocarbon degradation gene diversity, with the pelagic ecosystem exhibiting significantly higher richness and diversity compared to the benthic ecosystem. Additionally, the composition of the hydrocarbon degradation genes across the Baltic Sea subbasins was influenced by oil spill history, with areas that experienced higher spill volumes showing lower microbial diversity, suggesting potential enrichment of specific hydrocarbon degraders. Among the environmental factors assessed, depth played a significant role in shaping the composition of genes involved in hydrocarbon degradation within the Baltic Sea. ConclusionsUsing metagenomics, we profiled the native microorganisms associated with hydrocarbon degradation in the Baltic Sea. This knowledge will aid in understanding the natural capacities of microbial communities, potentially linked to the natural attenuation of hydrocarbon pollutants in the area. Insights into microbial degradation potential can enhance predictions of petroleum pollutant persistence and accumulation, support mitigation strategies for marine pollution, and reveal the ecological resilience of native microbial communities in marine ecosystems. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=106 SRC="FIGDIR/small/657333v1_ufig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@1ba6e59org.highwire.dtl.DTLVardef@a2c000org.highwire.dtl.DTLVardef@eb7bd2org.highwire.dtl.DTLVardef@e4dce_HPS_FORMAT_FIGEXP M_FIG C_FIG

ecology↗

bioRxiv2025

Environmental drivers of the resistome across the Baltic Sea

BackgroundAntimicrobial resistance is a major global health concern, with the environment playing a key role in its emergence and spread. Understanding the relationships between environmental factors, microbial communities, and resistance mechanisms is vital for elucidating environmental resistome dynamics. In this study, we characterized the environmental resistome of the Baltic Sea and evaluated how environmental gradients and spatial variability, alongside its microbial communities and associated functional genes, influence resistome diversity and composition across geographic regions. ResultsWe analyzed the metagenomes of benthic sediments from 59 monitoring stations across a 1,150 km distance of the Baltic Sea, revealing an environmental resistome comprised of predicted antimicrobial resistance genes (ARGs) associated with resistance against 26 antibiotic classes. We observed spatial variation in its resistance profile, with higher resistome diversity in the northern regions and a decline in the dead zones and the southern areas. The combined effects of salinity and temperature gradients, alongside nutrient availability, created a complex environmental landscape that shaped the diversity and distribution of the predicted ARGs. Salinity predominantly influenced microbial communities and predicted ARG composition, leading to clear distinctions between high-saline regions and those with lower to mid-level salinity. Furthermore, our analysis suggests that microbial community composition and mobile genetic elements might be crucial in shaping ARG diversity and composition. ConclusionsWe presented that salinity and temperature were identified as the primary environmental factors influencing resistome diversity and distribution across geographic regions, with nutrient availability further shaping these patterns in the Baltic Sea. Our study also highlighted the interplay between microbial communities, resistance, and associated functional genes in the benthic ecosystem, underscoring the potential role of microbial and mobile genetic element composition in ARG distribution. Understanding how environmental factors and microbial communities modulate environmental resistomes will help predict the impact of future environmental changes on resistance mechanisms in complex aquatic ecosystems.

microbiology↗

bioRxiv2025

Systematic Metaproteomics Mapping Reveals Functional and Ecological Landscapes of Human Gut Microbiota Responses to Therapeutic Drugs

Therapeutic compounds exert impacts on gut microbiota; however, how they affect the community functional ecology, especially as reflected at the protein level, remains largely unexplored. In this study, we systematically map metaproteomic responses of ex vivo human gut microbiota to 312 compounds, generating 4.6 million microbial protein responses, available as an interactive resource (https://shiny.imetalab.ca/MPR_Viz/). Protein-level analyses identify significant metaproteomic shifts induced by 47 compounds, with neuropharmaceuticals as the sole drug class significantly enriched among these hits. Further analyses on the community level reveal a tri-stability pattern in microbial composition and the emergence of three distinct functional states, based on a functional beta-diversity metric. Notably, neuropharmaceuticals cause particularly strong effects on the microbiomes, lowering the proteome-level functional redundancy and raising the level of antimicrobial resistance proteins, ultimately pushing the microbiome into an alternative functional state. Preliminary validation suggests that enhancing functional redundancy may contribute to maintaining microbiota resilience against neuropharmaceutical-induced antimicrobial resistance. Overall, this work establishes a comprehensive view of how drugs influence gut microbiome function and ecology at the protein level, proposes a landscape-based framework for interpreting community resilience, and highlights the need to consider protein-level and ecological responses in the evaluation of therapeutic interventions.

microbiology↗

bioRxiv2024

PhyloFunc: Phylogeny-informed Functional Distance as a New Ecological Metric for Metaproteomic Data Analysis

BackgroundBeta-diversity is a fundamental ecological metric for exploring dissimilarities between microbial communities. On the functional dimension, metaproteomics data can be used to quantify beta-diversity to understand how microbial community functional profiles vary under different environmental conditions. Conventional approaches to metaproteomic functional beta-diversity often treat protein functions as independent features, ignoring the evolutionary relationships among microbial taxa from which different proteins originate. A more informative functional distance metric that incorporates evolutionary relatedness is needed to better understand microbiome functional dissimilarities. ResultsHere, we introduce PhyloFunc, a novel functional beta-diversity metric that incorporates microbiome phylogeny to inform on metaproteomic functional distance. Leveraging the phylogenetic framework of weighted UniFrac distance, PhyloFunc innovatively utilizes branch lengths to weigh between-sample functional distances for each taxon, rather than differences in taxonomic abundance as in weighted UniFrac. Proof-of-concept using a simulated toy dataset and a real dataset from mouse inoculated with a synthetic gut microbiome and fed different diets show that PhyloFunc successfully captured functional compensatory effects between phylogenetically related taxa. We further tested a third dataset of complex human gut microbiomes treated with five different drugs to compare PhyloFuncs performance with other traditional distance methods. PCoA and machine learning-based classification algorithms revealed higher sensitivity of PhyloFunc in microbiome responses to paracetamol. We provide PhyloFunc as an open-source Python package (available at https://pydigger.com/pypi/PhyloFunc), enabling efficient calculation of functional beta-diversity distances between a pair of samples or the generation of a distance matrix for all samples within a dataset. ConclusionsUnlike traditional approaches that consider metaproteomics features as independent and unrelated, PhyloFunc acknowledges the role of phylogenetic context in shaping the functional landscape in metaproteomes. In particular, we report that PhyloFunc accounts for the functional compensatory effect of taxonomically related species. Its effectiveness, ecological relevance, and enhanced sensitivity in distinguishing group variations are demonstrated through the specific applications presented in this study.

bioinformatics↗

bioRxiv2023

Comparison of eDNA, bulk-sample metabarcoding, and morphological approaches: A case study of riverine benthic macroinvertebrate communities

Freshwater biomonitoring is essential for aquatic biodiversity conservation. Advances in high-throughput sequencing allowed parallel sequencing of community samples containing DNA from environmental samples, i.e., metabarcoding. Two approaches of DNA-based method are widely used, bulk-sample metabarcoding the use of bulk tissues such as insects and eDNA the use of environmental samples such as air, water and soil. Despite the novelty of this approach for routine freshwater biomonitoring, questions still need to be answered about its applicability and reliability due to confounding factors, e.g., sample type, laboratory technicalities, and limitations of databases. Hence, studies on direct comparisons are essential to validate the efficiency of these molecular approaches compared to the conventional morphological approach to accurately assessed biodiversity for riverine benthic macroinvertebrate biomonitoring. This study used three approaches to estimate diversity and composition of benthic macroinvertebrates. We also evaluated the relationship between benthic macroinvertebrate communities and environmental factors. We morphologically identified 8,052 individuals from 35 families, 31 genera, and 29 species. eDNA metabarcoding identified 51 families, 84 genera, and 90 species, while 37 families, 55 genera, and 107 species were detected through bulk-sample metabarcoding. We report that bulk-sample metabarcoding showed finer taxonomic resolution than other approaches. Our study highlights the use of bulk-sample metabarcoding for macroinvertebrate biodiversity assessment.

ecology↗

bioRxiv2022

The influence of river discharge on gravel bar hyporheic microbial community structure and putative metabolic functions.

O_LIMicrobial communities in the hyporheic zone (HZ) are important in self-purification as the riverbed is metabolically active and responsible for the retention, storage and mineralisation of organic matter transported to the surface water. However, studies exploring HZ microbial community responses to disturbances (e.g. floods) remain scarce. C_LIO_LIHere, we characterised the microbial community structure among the three (downwelling, upwelling and intermediate) HZ points within and among gravel bars at high and low discharge levels in a dam-regulated river using 16S rRNA metabarcoding. C_LIO_LIWe observed significant dissimilarity in the microbial community at low discharge exhibiting local adaptation due to gravel bar spatial environmental heterogeneity. Moreover, the homogenisation effect resulted in similar microbial community structures among the three points within the gravel bars at high discharge. Microbial communities across adjacent gravel bars were dissimilar, potentially attributing to different bar morphologies. C_LIO_LIOur study highlights the role of spatial environmental heterogeneity in the biological processes that govern microbial community structure at three hyporheic points in gravel bars at two discharge levels. C_LIO_LIOur results are essential to understand the HZ microbial communities response to the river discharge levels. C_LI

evolutionary biology↗

bioRxiv2021

Haplotype-level metabarcoding of freshwater macroinvertebrate species: a prospective tool for population genetic analysis

The development and evaluation of DNA metabarcoding protocols for haplotype-level resolution require attention, specifically for population genetic analysis, i.e., parallel estimation of genetic diversity and dispersal patterns among multiple species present in a bulk sample. Further exploration and assessment of the laboratory and bioinformatics strategies are warranted to unlock the potential of metabarcoding-inferred population genetic analysis. Here, we assessed the inference of freshwater macroinvertebrate haplotypes from DNA metabarcoding data using mock samples with known Sanger-sequenced haplotypes. We also examined the influence of different DNA template concentrations and PCR cycles on detecting true haplotypes and the reduction of spurious haplotypes obtained from DNA metabarcoding. We tested our haplotyping strategy on a mock sample containing 20 specimens from four species with known haplotypes based on the 658-bp Folmer region of the mitochondrial cytochrome c oxidase gene. The read processing and denoising step resulted in 14 zero-radius operational taxonomic units (ZOTUs) of 421-bp length, with 12 ZOTUs having 100% match with 12 of the Sanger haplotype sequences. Quality passing reads relatively increased with increasing PCR cycles, and the relative abundance of each ZOTUs was consistent for each cycle number. This suggests that increasing the cycle number from 24 to 64 did not affect the relative abundance of quality passing filter reads of each ZOTUs. Our study demonstrated the ability of DNA metabarcoding to infer intraspecific variability while highlighting the challenges that need to be addressed before its possible applications to population genetic studies.

ecology↗

bioRxiv2021

Implications of taxonomic and numerical resolution on DNA metabarcoding-based inference of benthic macroinvertebrate responses to river restoration

Exploring and clearly defining the level of taxonomic identification and quantification approaches for diversity and biomonitoring studies are essential, given its potential influence on the assessment and interpretation of ecological outcomes. In this study, we evaluated the response of benthic macroinvertebrate communities to the restoration or construction of gravel bars conducted in the dam-impacted Trinity River, with the non-dam influenced tributaries serving as the reference sites. We aim to evaluate the performance of different taxonomic and numerical (i.e., abundance vs. presence/absence data) resolutions of DNA metabarcoding with consequent comparison to morphology-based identification and how it affects assessment outcomes. DNA metabarcoding detected 93% of the morphologically identified individuals and provided finer taxonomic resolution. We also detected significant correlations between morphological sample abundance, biomass, and DNA metabarcoding read abundance. We observed a relatively high and significant congruence in macroinvertebrate community structure and composition between different taxonomic and numerical resolutions of both methods, indicating a satisfactory surrogacy between the two approaches and their varying identification levels and data transformation. Additionally, the community-environmental association were significant for all datasets but showed varying significant associations against the physicochemical parameters. Furthermore, both methods identified Simulium spp. as significant indicators of the dam-impacted gravel bars. Still, only DNA metabarcoding showed significant false discovery rate proving the methods robustness compared to morphology-based identification. Our observations imply that coarser taxonomic resolution could be highly advantageous to DNA metabarcoding-based applications in situations where the lack of taxonomic information, e.g., poor reference database, might severely affect the quality of biological assessments.

ecology↗

bioRxiv2020

Sediment-associated microbial community profiling: sample pre-processing through sequential membrane filtration for 16s rDNA amplicon sequencing

Sequential membrane filtration as a pre-processing step for the isolation of microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques, e.g., 16s rDNA amplicon sequencing. Here, we assessed the impact of pre-processing sediment samples by sequential membrane filtration (from 10, 5 to 0.22 m pore size membrane filters) for 16s rDNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the quality and quantity of extracted DNA and PCR amplicons between the two methods. Although we found a significant difference in raw and quality-filtered reads, read abundance after bioinformatics processing (i.e., denoising and the chimeric-read filtering steps) were not significantly different. These results suggest that read abundance after these read processing steps were not influenced by sediment processing or lack thereof. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods absolute read abundance. More so at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). Accordingly, the diversity estimates and community composition were not significantly different between the non- and pre-processed samples. We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition. We also suggest the inclusion of sequential filters (i.e., pre- and mid-filters) in the community profiling, given the additional taxa not detected from the non-processed and the final collection filter. Our observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

microbiology↗

bioRxiv2020

Profiling the microbial community structure and functional diversity of a dam-regulated river undergoing gravel bar restoration

BackgroundRiver restoration efforts are expected to influence and change the diversity and functions of microbial communities following the recovery of habitat characteristics in the river ecosystem. The recreation or restoration of gravel bars in the Trinity River in California aims to rehabilitate the environmental heterogeneity downstream of the dam impounded channel. Here, we profiled the community composition, estimated diversity, and annotated putative metabolic functions of the sediment microbial communities to assess whether the construction and restoration of gravel bars in the Trinity River in California enhanced environmental heterogeneity, with the increase in the microbial beta diversity of these in-channel structures against the free-flowing reach of the main channel with comparison to its undisturbed tributaries. ResultsMicrobial community composition of the free-flowing (i.e., no gravel bars) communities were relatively closer regardless of dam influence, whereas the Trinity River gravel bar and tributaries gravel bar communities were highly dissimilar. Proteobacteria, Bacteroidetes, and Acidobacteria were the highly abundant sediment microbial phyla on most sites, specifically in the Trinity River gravel bar communities. Putative functional annotation of microbial taxa revealed that chemoheterotrophy and aerobic chemoheterotrophy were the most prevalent microbial processes, with the Trinity River gravel bars having relatively higher representations. The considerably large abundance of heterotrophic taxa implies that gravel bars provide suitable areas for heterotrophic microorganisms with metabolic functions contributing to the net respiration in the river. ConclusionsOur results provide supporting evidence on the positive impact of habitat restoration being conducted in the Trinity River with the non-dam influenced, undisturbed tributaries as the basis of comparison. Gravel bar recreation and restoration contributed to the increased microbial biodiversity through the restoration of environmental heterogeneity at the river scale. We provided valuable insights into the potential microbial processes in the sediment that might be contributing to the biogeochemical processes carried out by the microbial communities in the Trinity River. The significant positive correlation between the functional diversity of the identified microbial taxa and beta diversity suggests that differences in the detected metabolic functions were closely related to dissimilarities in community composition.

microbiology↗

bioRxiv2019

Spatial and phylogenetic structure of DNA-species of Alpine stonefly community assemblages across seven habitats

O_LIStream ecosystems are spatially heterogeneous, with many different habitat patches distributed within a small area. The influence of this heterogeneity on the biodiversity of benthic insect communities is well documented; however, studies of the role of habitat heterogeneity in species coexistence and community assembly remain limited. Here, we investigated how habitat heterogeneity influences spatial structure (beta biodiversity) and phylogenetic structure (evolutionary processes) of benthic stonefly (Plecoptera, Insecta) communities. C_LIO_LIWe sampled 20 sites along two Alpine rivers, including seven habitats in four different reaches (headwaters, meandering, bar-braided floodplain, and lowland spring-fed). We identified 21 morphological species and delineated 52 DNA-species based on sequences from mitochondrial cox1 and nuclear ITS markers. Using DNA-species, we first analysed the patterns of variation in richness, diversity, and community composition by quantifing the contribution of each of the four reaches and seven habitats to the overall DNA-species diversity using an additive partition of species diversity analysis and distance-based redundancy analysis. Using gene-tree phylogenies, we assessed whether environmental filtering led to the co-occurrence of DNA-species using a two-step analysis to find a phylogenetic signal. C_LIO_LIThe four reaches significantly contributed to DNA-species richness; with the meandering section having the highest contribution. However, we found that habitats had an effect on DNA-species diversity, where glide, riffle and, pool influenced the spatial structure of stonefly communities possibly due to a high species turnover. C_LIO_LIAmong the habitats, the pool showed significant phylogenetic clustering, suggesting high levels of evolutionary adaptation and strong habitat filtering. This community structure may be caused by long-term stability of the habitat and the similar requirements for co-occurring species. C_LIO_LIOur study shows the importance of different habitats on the spatial and phylogenetic structure of stonefly community assemblies and sheds light on the habitat-specific diversity that may help improve conservation practices. C_LI

evolutionary biology↗

bioRxiv2018

Comparison of DNA metabarcoding and morphological identification for stream macroinvertebrate biodiversity assessment and monitoring

Conventional morphology-based identification is commonly used for routine assessment of freshwater ecosystems. However, cost and time efficient techniques such as high-throughput sequencing (HTS) based approaches may resolve the constraints encountered in conducting morphology-based surveys. Here, we characterized stream macroinvertebrate species diversity and community composition via metabarcoding and morphological analysis from environmental samples collected from the Shigenobu River Basin in Ehime Prefecture, Japan. We compared diversity metrics and assessed both approaches ability to evaluate the relationship between macroinvertebrate community and environmental variables. In total, we morphologically identified 45 taxa (3 families, six subfamilies, 31 genera, and five species) from 8,276 collected individuals from ten study sites. We detected 44 species by metabarcoding, with 35 species collapsed into 11 groups matching the morphologically identified taxa. A significant positive correlation between logged depth (number of HTS reads) and abundance of morphological taxa was observed, which implied that quantitative data can be used for subsequent analyses. Relatively higher estimates of alpha diversity were calculated from the metabarcoding data in comparison to morphology-based data. However, beta diversity estimates between metabarcoding and morphology data based on both incidence and abundance-based matrices were correlated proving that community differences between sampling sites were preserved in the molecular data. Also, both models were significant, but metabarcoding data (93%) explained a relatively higher percentage of variation in the relationship between community composition and the environmental variables than morphological data (91%). Overall, we present both the feasibility and limitations of HTS-driven estimations of taxonomic richness, community composition, and diversity metrics, and that metabarcoding was proven comparable and more sensitive against morphology-based analysis for stream macroinvertebrate biodiversity assessment and environmental monitoring.

ecology↗