Biology subjects

Chu, R. K.

Publications and source records attributed to Chu, R. K..

12 recordsLinked to original sources

bioRxiv2026

Integrated Post-Translational Modification (PTM) Proteomics Reveals Early Redox and Mitochondrial Remodeling Following Ref-1 Inhibition in Pancreatic Cancer

BackgroundApurinic/apyrimidinic endonuclease 1/redox factor-1 (Ref-1/APE1) is a central regulator of redox-dependent transcriptional signaling that promotes pancreatic ductal adenocarcinoma (PDAC) progression, therapeutic resistance, and metabolic adaptation. While pharmacologic inhibition of Ref-1 suppresses tumor growth and alters cellular metabolism, immediate molecular events linking Ref-1 inhibition to downstream cellular adaptation remain poorly understood. We therefore sought to characterize proteome-wide signaling responses induced by second-generation Ref-1 redox inhibitor, APX2014. MethodsWe applied an integrated multiplexed proteomics workflow to simultaneously quantify global protein abundance together with cysteine oxidation, phosphorylation, and lysine acetylation in Pa03C PDAC cells following acute treatment (30-120 min) with selective Ref-1 redox inhibitor APX2014. Differential post-translational modification (PTM) analysis, pathway enrichment, structural mapping of regulated sites, and functional mitochondrial substrate utilization assays were performed to define early signaling responses. ResultsAPX2014 induced rapid and extensive remodeling of PTM landscape while producing minimal changes in global protein abundance. Cysteine oxidation represented the earliest and most sustained response, accompanied by widespread phosphorylation and delayed lysine acetylation. Integrated pathway analyses identified mitochondrial translation, respiratory electron transport, TCA cycle metabolism, and mitochondrial redox homeostasis as the earliest and most consistently regulated processes. Functional mitochondrial assays confirmed impaired utilization of TCA cycle substrates following APX2014 treatment. Coordinated PTM remodeling was observed on Ref-1-associated signaling proteins, including NF-{kappa}B1 and p53, revealing simultaneous regulation of oxidation, phosphorylation, and acetylation within functionally important domains. Early redox-sensitive protein networks were also associated with subsequent disruption of mitotic organization. ConclusionsIntegrated multi-PTM proteomics reveals that pharmacologic Ref-1 redox inhibition rapidly rewires regulatory signaling networks before detectable changes in protein abundance. Our findings identify mitochondrial redox remodeling as an early consequence of Ref-1 inhibition, providing systems-level insight into how Ref-1-targeted therapies disrupt metabolic and stress-adaptive programs in pancreatic cancer. This work establishes a framework for understanding the molecular basis of Ref-1-directed therapeutics and highlights integrated PTM profiling as a powerful strategy for defining early drug response mechanisms. These findings provide a strong translational rationale for advancing next-generation Ref-1 redox inhibitors such as APX2014, developed from the first-in-class inhibitor APX3330 currently in clinical trials, and underscore the broader therapeutic potential of targeting Ref-1 redox signaling in pancreatic cancer.

cancer biology↗

bioRxiv2024

Coordinated organic and inorganic nitrogen transformations fuel soil microbial blooms and increase nitrogen retention during snowmelt

Snowmelt in high-elevation watersheds triggers a microbial bloom and crash that affects nitrogen (N) export. Predicting watershed N dynamics as snowpack declines is a challenge because the mechanisms that underlie this microbial bloom and crash are uncertain. Using a multi-omic approach, we show that the dynamic molecular properties of dissolved organic N, plus high gene expression for peptidases that recycle microbial biomass, suggested that microbial turnover provided N for biosynthesis during the microbial bloom. Amino acid fermentation by Bradyrhizobia produced organic acids that also fueled denitrification and dissimilatory nitrate reduction to ammonia (DNRA) during snowmelt. Nitrification in spring was driven by Spring-Adapted Nitrososphaerales, which utilized ammonium derived from osmolyte degradation by Winter-Adapted Solirubrobacteraceae. High DNRA gene expression after snowmelt suggested significant nitrate retention, increasing watershed N retention potential. However, declining snowfall may compromise microbial regulation of soil N retention, with implications for watershed N export.

microbiology↗

bioRxiv2024

Meta-metabolome ecology reveals that geochemistry and microbial functional potential are linked to organic matter development across seven rivers

Rivers receive substantial dissolved organic matter (DOM) input from the land and transport it to the ocean. As DOM travels through watersheds, it undergoes biotic and abiotic transformations that impact biogeochemical cycles and any subsequent CO2 release into the atmosphere. While recent research has increased our mechanistic knowledge of DOM composition within watersheds, DOM development across broad spatial distances and within divergent biomes is under investigated. Here, we combined DOM characterization, geochemical analyses, and shotgun metagenomics to analyze samples from seven rivers ranging from the U.S. Pacific Northwest to Berlin, Germany. Initial analyses revealed that many DOM properties were distinguished by river type (e.g., wastewater, headwater) and that geochemistry often explained variation across rivers. At a global scale, analyses rooted in meta-metabolome ecology indicated that DOM was structured overwhelmingly by deterministic selection. When controlling for scale, however, analyses indicated that ecological assembly dynamics were again partially structured by river type. Finally, microbial analyses revealed that many riverine microbes from our systems shared core metabolic functional potential while differing in peripheral capabilities in across the rivers. Further analysis of the carbon degradation potential for recovered metagenomically assembled genomes indicated that the sampled rivers had strong taxonomically conserved niche differentiation and that carbon degradation potential diversity was significantly related to organic matter diversity. Together, these results help us uncover interconnections between the development of DOM, riverine geochemistry, and microbial functional potential.

ecology↗

bioRxiv2022

One thousand soils for molecular understanding of belowground carbon cycling

While significant progress has been made in understanding global carbon (C) cycling, the mechanisms regulating belowground C fluxes and storage are still uncertain. New molecular technologies have the power to elucidate these processes, yet we have no widespread standardized implementation of molecular techniques. To address this gap, we introduce the Molecular Observation Network (MONet), a decadal vision from the Environmental Molecular Sciences Laboratory (EMSL), to develop a national network for understanding the molecular composition, physical structure, and hydraulic and biological properties of soil and water. These data are essential for advancing the next generation of multiscale Earth systems models. In this paper, we discuss the 1000 Soils Pilot for MONet, including a description of standardized sampling materials and protocols and a use case to highlight the utility of molecular-level and microstructural measurements for assessing the impacts of wildfire on soil. While the 1000 Soils Pilot generated a plethora of data, we focus on assessments of soil organic matter (SOM) chemistry via Fourier-transform ion cyclotron resonance-mass spectrometry and microstructural properties via X-ray Computed Tomography to highlight the effects of recent fire history in forested ecosystems on belowground C cycling. We observed decreases in soil respiration, microbial biomass, and potential enzyme activity in soils with high frequency burns. Additionally, the nominal oxidation state of carbon in SOM increased with burn frequency in surface soils. This results in a quantifiable shift in the molecular signature of SOM and shows that wildfire may result in oxidation of SOM and structural changes to soil pore networks that persist into deeper soils.

ecology↗

bioRxiv2022

A streamlined tandem tip-based workflow for sensitive nanoscale phosphoproteomics

Effective phosphoproteome of nanoscale sample analysis remains a daunting task, primarily due to significant sample loss associated with non-specific surface adsorption during enrichment of low stoichiometric phosphopeptide. We developed a novel tandem tip phosphoproteomics sample preparation method that is capable of sample cleanup and enrichment without additional sample transfer, and its integration with our recently developed SOP (Surfactant-assisted One-Pot sample preparation) and iBASIL (improved Boosting to Amplify Signal with Isobaric Labeling) approaches provides a streamlined workflow enabling sensitive, high-throughput nanoscale phosphoproteome measurements. This approach significantly reduces both sample loss and processing time, allowing the identification of >3,000 (>9,500) phosphopeptides from 1 (10) {micro}g of cell lysate using the label-free method without a spectral library. It also enabled precise quantification of [~]600 phosphopeptides from 100 cells sorted by FACS (single-cell level input for the enriched phosphopeptides) and [~]700 phosphopeptides from human spleen tissue voxels with a spatial resolution of 200 {micro}m (equivalent to [~]100 cells) in a high-throughput manner. The new workflow opens avenues for phosphoproteome profiling of mass-limited samples at the low nanogram level.

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

Playing with FiRE: A genome resolved view of the soil microbiome responses to high severity forest wildfire

Warming climate has increased the frequency and size of high severity wildfires in the western United States, with deleterious impacts on forest ecosystem resilience. Although forest soil microbiomes provide a myriad of ecosystem functions, little is known regarding the impact of high severity fire on microbially-mediated processes. Here, we characterized functional shifts in the soil microbiome (bacterial, fungal, and viral) across wildfire burn severity gradients one year post-fire in coniferous forests (Colorado and Wyoming, USA). We generated the Fire Responding Ecogenomic database (FiRE-db), consisting of 637 metagenome-assembled bacterial genomes, 2490 viral populations, and 2 fungal genomes complemented by 12 metatranscriptomes from soils affected by low and high-severity, and complementary marker gene sequencing and metabolomics data. Actinobacteria dominated the fraction of enriched and active taxa across burned soils. Taxa within surficial soils impacted by high severity wildfire exhibited traits including heat resistance, sporulation and fast growth that enhanced post-fire survival. Carbon cycling within this system was predicted to be influenced by microbial processing of pyrogenic compounds and turnover of dominant bacterial community members by abundant viruses. These genome-resolved analyses across trophic levels reveal the complexity of post-fire soil microbiome activity and offer opportunities for restoration strategies that specifically target these communities.

microbiology↗

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

Disturbance Triggers Non-Linear Microbe-Environment Feedbacks

Conceptual frameworks linking microbial community membership, properties, and processes with the environment and emergent function have been proposed but remain untested. Here we refine and test a recent conceptual framework using hyporheic zone sediments exposed to wetting/drying transitions. Throughout the system we found threshold-like responses to the duration of desiccation. Membership of the putatively active community--but not the whole community--responded due to enhanced deterministic selection (an emergent community property). Concurrently, the thermodynamic properties of organic matter became less favorable for oxidation (an environmental component) and respiration decreased (a microbial process). While these responses were step functions of desiccation, we observed continuous monotonic relationships among community assembly, respiration, and organic matter thermodynamics. Placing the results in context of our conceptual framework points to previously unrecognized internal feedbacks that are initiated by disturbance, mediated by thermodynamics, and that cause the impacts of disturbance to be dependent on the history of disturbance.

ecology↗

bioRxiv2020

Ecological theory applied to environmental metabolomes reveals compositional divergence despite conserved molecular properties

Stream and river systems transport and process substantial amounts of dissolved organic matter (DOM) from terrestrial and aquatic sources to the ocean, with global biogeochemical implications. However, the underlying mechanisms affecting the spatiotemporal organization of DOM composition are under-investigated. To understand the principles governing DOM composition, we leverage the recently proposed synthesis of metacommunity ecology and metabolomics, termed meta-metabolome ecology. Applying this novel approach to a freshwater ecosystem, we demonstrated that despite similar molecular properties across metabolomes, metabolite identity significantly diverged due to environmental filtering. We refer to this phenomenon as thermodynamic redundancy, which is analogous to the ecological concept of functional redundancy. We suggest that under thermodynamic redundancy, divergent metabolomes can support equivalent biogeochemical function just as divergent ecological communities can support equivalent ecosystem function. As these analyses are performed in additional ecosystems, potentially generalizable principles, like thermodynamic redundancy, can be revealed and provide insight into DOM dynamics.

ecology↗

bioRxiv2020

Unification of Environmental Metabolomics with Metacommunity Ecology

Environmental metabolomics, enabled by high-resolution mass spectrometric techniques, have demonstrated the biogeochemical importance of the metabolites which comprise natural organic matter (NOM). However, significant gaps exist in our understanding of the spatiotemporal organization of NOM composition. We suggest that the underlying mechanisms governing NOM can be revealed by applying tools and concepts from metacommunity ecology to environmental metabolomics. After illustrating the similarities between metabolomes and ecological communities, we call this conceptual synthesis meta-metabolome ecology and demonstrate its potential utility using a freshwater mass spectrometry dataset. Specifically, we developed three relational metabolite dendrograms using combinations of molecular properties (i.e., aromaticity index, double-bond equivalents, etc.) and putative biochemical transformations. Using these dendrograms, which are similar to phylogenetic or functional trait trees in ecological communities, we illustrate potential analytical techniques by investigating relationally-informed -diversity and {beta}-diversity metrics (e.g., MPD, MNTD, UniFrac), and null model analyses (e.g., NRI, NTI, and {beta}NTI). Furthermore, we demonstrate that this synthesis allows ecological communities (e.g., microbes) and the metabolites they produce and consume using the same framework. We propose that applying this framework to a broad range of ecosystems will reveal generalizable principles that can advance our predictive capabilities regarding NOM dynamics.

ecology↗

bioRxiv2018

Dispersal limitation and thermodynamic constraints govern spatial structure of permafrost microbial communities

Understanding drivers of permafrost microbial community composition is critical for understanding permafrost microbiology and predicting ecosystem responses to thaw, however studies describing ecological controls on these communities are lacking. We hypothesize that permafrost communities are uniquely shaped by constraints imposed by prolonged freezing, and decoupled from factors that influence non-permafrost soil communities. To test this hypothesis, we characterized patterns of environmental variation and microbial community composition in permafrost across an Alaskan boreal forest landscape. We used null modeling to estimate the relative importance of selective and neutral assembly processes on community composition, and identified environmental factors influencing ecological selection through regression and structural equation modeling (SEM). Proportionally, the strongest process influencing community composition was dispersal limitation (0.36), exceeding the influence of homogenous selection (0.21), variable selection (0.16), and homogenizing dispersal (0.05). Fe(II) content was the most important factor explaining variable selection, and was significantly associated with total selection by univariate regression (R2=0.14, p=0.003). SEM supported a model in which Fe(II) content mediated influences of the Gibbs free energy of the organic matter pool and organic acid concentration on total selection. These findings reveal that the processes shaping microbial communities in permafrost are distinct from those in non-permafrost soils, as the stability of the permafrost environment imposes dispersal and thermodynamic constraints on permafrost communities. Models of permafrost community composition will need to account for these unique drivers in order to predict community characteristics across permafrost landscapes, and in efforts to understand how pre-thaw conditions will influence post-thaw ecological and biogeochemical processes.

ecology↗