Biology subjects

Stegen, J.

Publications and source records attributed to Stegen, J..

8 recordsLinked to original sources

bioRxiv2026

Toward a global chemogeography of dissolved organic matter: a molecular trait dataset across Earth systems

Dissolved organic matter (DOM) is a central component of biogeochemical cycling, but molecular observations generated by ultrahigh-resolution mass spectrometry remain fragmented across studies, limiting quantitative comparisons among ecosystems. Here, we compile and harmonize a global dataset of DOM molecular traits comprising 3,999 samples from 337 studies published between 2005 and 2026. The dataset includes eight intensity-weighted molecular traits: hydrogen-to-carbon (H/C), oxygen-to-carbon (O/C), nitrogen-to-carbon (N/C), and sulfur-to-carbon (S/C) ratios; molecular mass; double-bond equivalents (DBE); modified aromaticity index (AImod); and nominal oxidation state of carbon (NOSC). Samples span aquatic, terrestrial, atmospheric, plant-associated, petroleum-related, and other environments, and are linked, where available, to geographic, physicochemical, nutrient, and climatic metadata. Molecular data were harmonized using common definitions and restricted to negative-mode electrospray-ionization FT-ICR MS to improve cross-study comparability. This resource enables cross-system comparisons of DOM molecular traits and supports analyses of environmental gradients, geographic coverage, and global DOM chemogeography.

ecology↗

bioRxiv2023

A functional microbiome catalog crowdsourced from North American rivers

Predicting elemental cycles and maintaining water quality under increasing anthropogenic influence requires understanding the spatial drivers of river microbiomes. However, the unifying microbial processes governing river biogeochemistry are hindered by a lack of genome-resolved functional insights and sampling across multiple rivers. Here we employed a community science effort to accelerate the sampling, sequencing, and genome-resolved analyses of river microbiomes to create the Genome Resolved Open Watersheds database (GROWdb). This resource profiled the identity, distribution, function, and expression of thousands of microbial genomes across rivers covering 90% of United States watersheds. Specifically, GROWdb encompasses 1,469 microbial species from 27 phyla, including novel lineages from 10 families and 128 genera, and defines the core river microbiome for the first time at genome level. GROWdb analyses coupled to extensive geospatial information revealed local and regional drivers of microbial community structuring, while also presenting a myriad of foundational hypotheses about ecosystem function. Building upon the previously conceived River Continuum Concept1, we layer on microbial functional trait expression, which suggests the structure and function of river microbiomes is predictable. We make GROWdb available through various collaborative cyberinfrastructures2, 3 so that it can be widely accessed across disciplines for watershed predictive modeling and microbiome-based management practices.

microbiology↗

bioRxiv2023

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems comprise less than 1% of Earths total non-glaciated area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. As a result, the relevance of microbiome interactions and the impacts they have over time on biogeochemical cycles are poorly understood. To assess how viral and microbial communities change over time, we sampled surface water and pore water compartments of the wastewater-impacted River Erpe in Germany every 3 hours over a 48-hour period resulting in 32 metagenomes paired to geochemical and metabolite measurements. We reconstructed 6,500 viral and 1,033 microbial genomes and found distinct communities associated with each river compartment. We show that 17% of our vMAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to carbon and nitrogen cycling. Together, these findings demonstrate that microbial and viral communities in surface waters of this urban river can exist as stable communities along a flowing river; and raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

microbiology↗

bioRxiv2023

Metabolic Multireactor: practical considerations for using simple oxygen sensing optodes for high-throughput batch reactor metabolism experiments

We present a system for carrying out small batch reactor microbial metabolism experiments on water and sediment samples for environmental questions. In general, it provides several advantages that can help researchers achieve impactful experiments at relatively low costs and high data quality. In particular, it allows for multiple reactors to be operated and their oxygen concentrations to be measured simultaneously, providing high throughput and high time-resolution data, which can be advantageous. Most existing literature on similar small batch-reactor metabolic studies is limited to either only a few samples, or only a few time points per sample, which can restrict the ability for researchers to learn from their experiments. The oxygen sensing system is based very directly on the work of Larsen, et al. [2011], and similar oxygen sensing technology is widely used in the literature. As such we do not delve deeply into the specifics of the fluorescent dye sensing mechanism. Instead, we focus on practical considerations. We describe the construction and operation of the calibration and experimental systems, and answer many of the questions likely to come up when other researchers choose to build and operate a similar system themselves (questions we ourselves had when we first built the system). In this way, we hope to provide an approachable and easy to use research article that can help other researchers construct and operate a similar system that can be tailored to ask their own research questions, with a minimum of confusion and missteps along the way.

biochemistry↗

bioRxiv2021

Implications of sample treatment on characterization of the riverine environmental metabolome

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (-), non-SPE (-), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (-) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for microbial heterotrophic respiration. Thus, we infer that the SPE (-) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (-) and SPE (+) to adequately characterize these molecules. SynopsisWe provide data-driven sample treatment and ionization mode recommendations to researchers who aim to use high-resolution mass spectrometry to characterize environmental organic matter. Abstract Art O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

ecology↗

bioRxiv2021

ORT: A workflow linking genome-scale metabolic models with reactive transport codes

MotivationNutrient and contaminant behavior in the subsurface are governed by multiple coupled hydrobiogeochemical processes which occur across different temporal and spatial scales. Accurate description of macroscopic system behavior requires accounting for the effects of microscopic and especially microbial processes. Microbial processes mediate precipitation and dissolution and change aqueous geochemistry, all of which impacts macroscopic system behavior. As omics data describing microbial processes is increasingly affordable and available, novel methods for using this data quickly and effectively for improved ecosystem models are needed. ResultsWe propose a workflow ( Omics to Reactive Transport - ORT) for utilizing metagenomic and environmental data to describe the effect of microbiological processes in macroscopic reactive transport models. This workflow utilizes and couples two open-source software packages: KBase (a software platform for systems biology) and PFLOTRAN (a reactive transport modeling code). We describe the architecture of ORT and demonstrate an implementation using metagenomic and geochemical data from a river system. Our demonstration uses microbiological drivers of nitrification and denitrification to predict nitrogen cycling patterns which agree with those provided with generalized stoichiometries. While our example uses data from a single measurement, our workflow can be applied to spatiotemporal metagenomic datasets to allow for iterative coupling between KBASE and PFLOTRAN. Availability and ImplementationInteractive models available at https://pflotranmodeling.paf.subsurfaceinsights.com/pflotran-simple-model/. Microbiological data available at NCBI via BioProject ID PRJNA576070. ORT Python code available at https://github.com/subsurfaceinsights/ort-kbase-to-pflotran. KBase narrative available at https://narrative.kbase.us/narrative/71260 or static narrative (no login required) at https://kbase.us/n/71260/258 Contactrebecca.rubinstein@subsurfaceinsights.com or roelof.versteeg@subsurfaceinsights.com Supplementary informationSupplementary data are available online.

bioinformatics↗

bioRxiv2020

Using Community Science to Reveal the Global Chemogeography of River Metabolomes

River corridor metabolomes reflect organic matter (OM) processing that drives aquatic biogeochemical cycles. Recent work highlights the power of ultrahigh-resolution mass spectrometry for understanding metabolome composition and river corridor metabolism. However, there have been no studies on the global chemogeography of surface water and sediment metabolomes using ultrahigh-resolution techniques. Here, we describe a community science effort from the Worldwide Hydrobiogeochemistry Observation Network for Dynamic River Systems (WHONDRS) consortium to characterize global metabolomes in surface water and sediment that span multiple stream orders and biomes. We describe the distribution of key aspects of metabolomes including elemental groups, chemical classes, indices, and inferred biochemical transformations. We show that metabolomes significantly differ across surface water and sediment and that surface water metabolomes are more rich and variable. We also use inferred biochemical transformations to identify core metabolic processes shared among surface water and sediment. Finally, we observe significant spatial variation in sediment metabolites between rivers in the eastern and western portions of the contiguous United States. Our work not only provides a basis for understanding global patterns in river corridor biogeochemical cycles but also demonstrates that community science endeavors can enable global research projects that are unfeasible with traditional research models.

ecology↗

bioRxiv2020

Carbon limitation leads to thermodynamic regulation of aerobic metabolism

Organic matter (OM) metabolism in freshwater ecosystems is a critical source of uncertainty in global biogeochemical cycles, yet aquatic OM cycling remains poorly understood. Here, we present the first work to explicitly test OM thermodynamics as a key regulator of aerobic respiration, challenging long-held beliefs that organic carbon and oxygen concentrations are the primary determinants of respiration rates. We pair controlled microcosm experiments with ultrahigh-resolution OM characterization to demonstrate a clear relationship between OM thermodynamic favorability and aerobic respiration under carbon limitation. We also demonstrate a shift in the regulation of aerobic respiration from OM thermodynamics to nitrogen content when carbon is in excess, highlighting a central role for OM thermodynamics in aquatic biogeochemical cycling particularly in carbon-limited ecosystems. Our work therefore illuminates a structural gap in aquatic biogeochemical models and presents a new paradigm in which OM thermodynamics and nitrogen content interactively govern aerobic respiration.

ecology↗