Biology subjects

Gu, A.

Publications and source records attributed to Gu, A..

16 recordsLinked to original sources

bioRxiv2026

Nab-paclitaxel fused with the de novo designed receptor binder exhibits enhanced tumor targeting and therapeutic efficacy

Chemotherapy has been widely used in cancer treatment, but most of the chemotherapeutic drugs rely mainly on passive accumulation due to lack of target specificity, which may lead to systemic toxicity and limited clinical utility. Recent advances in artificial intelligence-based protein design provide new opportunities for developing precision therapeutics. Here we modify the albumin-bound paclitaxel (Nab-PTX), one of the most widely used drugs in chemotherapies, by applying the fusion proteins of albumin with the de novo designed protein binders targeting human EGFR or HER2. The resulting particles, EGFRmb-Nab-PTX and HER2mb-Nab-PTX, retain the similar physicochemical properties of Nab-PTX while acquiring the receptor-specific binding capacities. The in vitro assays show that both binder-modified Nab-PTX particles have increased uptake and inhibitory effects significantly in the cancer cell lines with high receptor expression levels. Furthermore, the data from a xenograft model, including tumor growth, excised tumor analysis, organ histology, and fluorescence imaging, show that the binder-modified Nab-PTX enhances tumor accumulation, improves tumor suppression, and reduces off-target toxicity compared with the conventional Nab-PTX, suggesting that they may have promising clinical potential in cancer treatment. Overall, this strategy provides an adaptable modular platform for generating albumin-based chemotherapeutic drugs with target specificities, which can be readily customized with diverse target binders to enable precise cancer therapies.

cancer biology↗

bioRxiv2025

EBV INFECTION OUTCOMES DETERMINED BY MONOCYTE AND TREG-DRIVEN IMMUNE DYNAMICS IN AN EX VIVO PBMC MODEL

Epstein-Barr virus (EBV) infects >95% of the adult population with diverse outcomes ranging from benign latency to cancers and autoimmune diseases. Immunological control of EBV infection is known to be an important determinant of EBV infection outcomes. However, species-specific viral tropism and limited infection models have impeded mechanistic insights into early host-immune control of EBV infection. Here, we use ex vivo infection of peripheral blood mononuclear cells (PBMCs), rather than routinely used B cell enriched culture systems, to study immune and viral dynamics during primary EBV infection. We combined bulk RNA sequencing, EBV transcript enrichment, and flow cytometry to characterize cellular responses across Days 1, 7-8, and 14 post-infection. Early infection triggered a monocyte-specific antiviral response marked by changes in the expression of genes associated with lipid metabolism (LIPA, lysosomal acid lipase) and chemotaxis (CCR1 and CCR2). Inhibitors of LIPA increased EBV titers during primary infection, indicating that LIPA is part of an early monocyte-driven antiviral response. At later timepoints post-infection, donor-dependent variability in lymphoblastoid cell line (LCL) outgrowth was associated with divergent immune states. Donors that failed to generate LCLs demonstrated increased frequencies of CD8+ T cells and reduced numbers of regulatory T cells (CD4CD25FOXP3). EBV transcriptomics revealed that LCL-failed donors exhibited elevated early lytic gene expression but did not establish a type III latency program. Our findings suggest that individual variations in immune cell composition and gene expression may account for differences in the immune response to EBV. These findings define temporal immune and viral signatures that predict transformation outcome and highlight intact PBMCs as a tractable model to study EBV pathogenesis in a genetically diverse, human-specific context. AUTHOR SUMMARYIndividual variation in response to Epstein-Barr virus (EBV) infection can lead to diverse pathogenic outcomes, ranging from cancers to autoimmune disease. To study this variation, we analyzed immune cell response and viral dynamics during the ex vivo primary EBV infection of peripheral blood mononuclear cells (PBMCs) from donors that either fail or succeed to generate lymphoblastoid cell lines (LCLs). Flow cytometry and RNA-seq revealed a rapid monocyte-specific antiviral response among all donors marked by genes associated with lipid metabolism (LIPA) and chemotaxis (CCR1 and CCR2). LIPA inhibition increased EBV titers during primary infection, demonstrating a functional antiviral role. At later timepoints, donor-specific differences in CD8+ T cells and Treg subsets, along with EBV gene expression, were correlated with successful LCL outgrowth. Treatment with the Treg-depleting antibody RG6292 suppressed viral transformation in donors that otherwise supported LCL outgrowth, confirming a functional role for Tregs in shaping early EBV infection outcomes. Viral transcript enrichment-seq revealed an upregulation of early lytic and failure to sustain latent gene expression correlating with failure to generate LCL. These findings highlight intact PBMCs as a tractable model to study EBV viral-host interaction in a genetically diverse, human-specific context, and that Tregs play a key determining role in viral transformation.

immunology↗

bioRxiv2025

Meningeal macrophages exhibit diverse calcium signaling at steady-state and in response to aberrant cortical hyperexcitability in awake mice

The meninges, which envelop and protect the brain, host a dense network of resident macrophages with diverse roles in regulating homeostasis and neuroinflammation. Despite their importance, we have a limited understanding of their behavior in vivo. Many dynamic cellular functions of macrophages involve intracellular Ca2+ signaling. However, virtually nothing is known about the spatiotemporal Ca2+ dynamics of meningeal macrophages in vivo. We developed a chronic intravital two-photon imaging approach and related computational analysis tools to interrogate meningeal macrophage Ca2+ dynamics, at subcellular resolution, in a novel Pf4Cre:TIGRE2.0GCaMP6s/wt reporter mouse model. Using imaging in awake mice, we characterized Ca2+ activity in meningeal macrophages at steady state and in response to cortical spreading depolarization (CSD), an aberrant pro-inflammatory brain hyperexcitability event implicated in migraine, traumatic brain injury, and stroke. In homeostatic meninges, macrophages in the dural perivascular niche exhibited several Ca2+ dynamic features, including event duration and signal frequency spectrum, distinct from those of localized to the interstitial, non-perivascular niche. Simultaneous tracking of macrophage Ca2+ dynamics and local vasomotion revealed a subset of dural perivascular macrophages whose activity was coupled to locomotion-driven diameter fluctuations of their associated vessels. Most perivascular and non-perivascular meningeal macrophages displayed propagating intracellular Ca2+ activity and synchronized intercellular Ca2+ elevations, potentially driven by extrinsic factors. In response to CSD, the majority of perivascular and non-perivascular meningeal macrophages showed a persistent decrease in Ca2+ activity, while a smaller subset displayed Ca2+ elevations. Mechanistically, CGRP/RAMP1 signaling mediated the increase but not the decrease in CSD-mediated Ca2+ signaling. Collectively, our results highlight a previously unknown diversity of Ca2+ dynamics in meningeal macrophages at steady state and in response to an aberrant brain hyperexcitability event linked to neuroinflammation.

neuroscience↗

bioRxiv2025

Geno-pheno characterization of crop rhizospheres: An integrated Raman spectroscopy and microbiome approach in conventional and organic agriculture

1In this study, we examined phenotypic and compositional patterns in rhizosphere microbial communities across conventionally and organically managed farms to assess impacts on soil microbiomes. We employed newly developed single-cell Raman microspectroscopy (SCRS)-based community phenotypic profiling analysis with microbiome 16S rRNA gene amplicon sequencing to compare the soil microbial communities of alfalfa, carrot, corn, lettuce, potato, soybean, squash, tomato, triticale, wheat, oat, and pea grown under either conventional or organic agriculture across farms in New York State (USA). Distinct microbiome clustering patterns indicated that organic and conventional production methods imposed strong selective pressures, shaping microbial assemblages within each group more distinctly than site or plant species variations. Using SCRS-based microbial phenotyping, we identified distinct microbial adaptations in agricultural soils, with organic systems favoring lipid-accumulating phenotypes for energy storage and stress resilience in low-input environments, while higher nutrient availability in conventional systems promoted carbon-rich phenotypes, enhancing rapid carbon assimilation and biomass production. Through network analysis of ecological hub species, we identified Pseudomonas, a plant growth-promoting rhizobacteria (PGPR), along with several nitrogen-fixing prokaryotes as core members within conventional agricultural systems. In contrast, organically managed soils featured PGPR taxa from the Bacilli class and contained microorganisms carrying antibiotic resistance genes, potentially indicating the presence of antibiotic resistance genes within organic agricultural environments. Overall, we found that the novel inclusion of microbial phenotyping methods, such as SCRS, can describe unique linkages between microbiome structure and their physiology that are distinctive between conventional and organic agricultural systems. 2 ImportanceOur study successfully integrated single-cell Raman microspectroscopy and amplicon sequencing, two established techniques for analyzing microbial communities and their functions, enabling a link between genotype and phenotype to better characterize ecosystem dynamics. While few studies have explored microbial phenotypes alongside community composition to infer agricultural management differences, our research offered key insights into functional relevance of microbial communities to agricultural practices, demonstrating how management strategies influenced microbial adaptation. These findings advance microbial ecology research, demonstrating how agricultural management strategies influence microbiome structure and function, reinforcing the importance of phenotypic profiling in sustainable agriculture.

ecology↗

bioRxiv2025

GETgene-AI: A Framework for Prioritizing Actionable Cancer Drug Targets

Prioritizing actionable drug targets is a critical challenge in cancer research, where high-dimensional genomic data and the complexity of tumor biology often hinder effective prioritization. To address this, we developed GETgene-AI, a novel computational framework that integrates network-based prioritization, machine learning, and automated literature analysis to prioritize and rank potential therapeutic targets. Central to GETgene-AI is the G.E.T. strategy, which combines three data streams: mutational frequency (G List), differential expression (E List), and known drug targets (T List). These components are iteratively refined and ranked using the Biological Entity Expansion and Ranking Engine (BEERE), leveraging protein-protein interaction networks, functional annotations, and experimental evidence. Additionally, GETgene-AI incorporates GPT-4o, an advanced large language model, to automate literature-based ranking, reducing manual curation and increasing efficiency. In this study, we applied GETgene-AI to pancreatic cancer as a case study. The framework successfully prioritized high-priority targets such as PIK3CA and PRKCA, validated through experimental evidence and clinical relevance. Benchmarking against GEO2R and STRING demonstrated GETgene-AIs superior performance, achieving higher precision, recall, and efficiency in prioritizing actionable targets. Moreover, the framework mitigated false positives by deprioritizing genes lacking functional or clinical significance. While demonstrated on pancreatic cancer, the modular design of GETgene-AI enables scalability across diverse cancers and diseases. By integrating multi-omics datasets with advanced computational and AI-driven approaches, GETgene-AI provides a versatile and robust platform for accelerating cancer drug discovery. This framework bridges computational innovations with translational research to improve patient outcomes.

bioinformatics↗

bioRxiv2024

Predicting the effect of non-coding mutations on single-cell DNA methylation using deep learning

Predicting the effects of non-coding mutations on DNA methylation is crucial for advancing our understanding of gene expression, epigenetic inheritance, and its role in disease mechanisms. Current methods lack the capability to predict the impact of non-coding mutations on DNA methylation at single-cell resolution and long range, while remain challenges in tracking SNP influences throughout disease progression. Here, we introduce Methven, a deep learning-based framework designed to predict the effects of non-coding mutations on DNA methylation at single-cell resolution, to overcome the challenges. Methven integrates DNA sequences and ATAC-seq data, employing a divide-and-conquer approach to handle varying scales of SNP-CpG interactions. By leveraging a pretrained DNA language model, Methven accurately predicts both the direction and magnitude of methylation changes across a 100kbp range with a lightweight architecture. The evaluation results demonstrate the superior performance of Methven in prioritizing functional non-coding mutation, model interpretability, and its potential for revealing personalized mutation-disease associations.

bioinformatics↗

bioRxiv2023

EMO: Predicting Non-coding Mutation-induced Up- and Down-regulation of Risk Gene Expression using Deep Learning

The challenge of understanding how alterations in non-coding DNA regulate gene expression is substantial, with far-reaching consequences for the advancement of human genetics and disease research. Accurately predicting the up- and down-regulation of gene expression quantitative trait loci (eQTLs) offers a potential avenue to accelerate the identification of associations between non-coding variants and phenotypic traits. However, current methods for predicting the impact of non-coding mutations on gene expression changes fail to predict the sign of eQTLs accurately. Additionally, the requirement for tissue-specific training models within these methods restricts their applicability, especially when extending predictive abilities to single-cell resolution. In this study, we present EMO, an innovative transformer-based pre-trained method, designed to predict the up- and down-regulation of gene expression caused by single non-coding mutations using DNA sequences and ATAC-seq data. EMO extends the effective prediction range up to 1Mbp between the non-coding mutation and the transcription start site (TSS) of the target gene. It demonstrates competitive prediction performance across various variant TSS distances and surpasses the state-of-the-art structure. To assess its effectiveness, EMO was fine-tuned using eQTLs from two brain tissues for external validation. We also evaluated EMOs transferability to single-cell resolution by fine-tuning it on eQTLs from six types of immune cells, achieving satisfactory results in each cell type (AUC > 0.860). Furthermore, EMO displayed promising potential in analyzing disease-associated eQTLs.

bioinformatics↗

bioRxiv2023

In vivo screening for toxicity-modulating drug interactions identifies antagonism that protects against ototoxicity in zebrafish

Ototoxicity is a debilitating side effect of over 150 medications with diverse mechanisms of action, many of which could be taken concurrently to treat multiple conditions. Approaches for preclinical evaluation of drug interactions that might impact ototoxicity would facilitate design of safer multi-drug regimens and mitigate unsafe polypharmacy by flagging combinations that potentially cause adverse interactions for monitoring. They may also identify protective agents that antagonize ototoxic injury. To address this need, we have developed a novel workflow that we call Parallelized Evaluation of Protection and Injury for Toxicity Assessment (PEPITA), which empowers high-throughput, semi-automated quantification of ototoxicity and otoprotection in zebrafish larvae. By applying PEPITA to characterize ototoxic drug interaction outcomes, we have discovered antagonistic interactions between macrolide and aminoglycoside antibiotics that confer protection against aminoglycoside-induced damage to lateral line hair cells in zebrafish larvae. Co-administration of either azithromycin or erythromycin in zebrafish protected against damage from a broad panel of aminoglycosides, at least in part via inhibiting drug uptake into hair cells via a mechanism independent from hair cell mechanotransduction. Conversely, combining macrolides with aminoglycosides in bacterial inhibition assays does not show antagonism of antimicrobial efficacy. The proof-of-concept otoprotective antagonism suggests that combinatorial interventions can potentially be developed to protect against other forms of toxicity without hindering on-target drug efficacy.

pharmacology and toxicology↗

bioRxiv2023

Isolation and nitrogen removal characteristics of a novel aerobic denitrifying strain Achromobacter xylosoxidans GR7397

Aerobic denitrifying bacteria have the potential for engineering applications due to the efficient nitrate removal capacity from wastewater. In this study, a novel aerobic denitrifying strain was isolated and identified as Achromobacter xylosoxidans GR7397 from the activated sludge of a wastewater treatment plant, which possessed efficient nitrate removal capacity. Moreover, the denitrification capacity and properties of the strain were investigated in the presence of nitrate as the only nitrogen source. Five denitrification reductases encoding genes were harbored by strain GR7397 determined by electrophoretic analysis of PCR amplification products, consisting of periplasmic nitrate reductase (NAP), nitrate reductase (NAR), nitrite reductase (NIR), nitrous oxide reductase (NOS), and nitric oxide reductase (NOR), demonstrating that the strain has a complete denitrification metabolic pathway. The optimum denitrifying condition of strain GR7397 included sodium acetate adopted as the electron donor, COD/TN ratio at 4, pH at 8, temperature at 30{degrees}C, under which condition, the nitrate removal rate reached 14.86 mg {middle dot} L-1 {middle dot} h-1 that the [Formula] concentration decreased from 93.90 mg/L to 4.73 mg/L within 6 h with no accumulation of nitrite. In addition, the bioaugmentation performance of strain GR7397 to enhance nitrate removal was evaluated to be effective and stabilized in a sequential batch reactor (SBR). The removal rate of [Formula] was the highest during each cycle with a range of 15.48-28.56 mg{middle dot}L-1{middle dot}h-1 in the SBR with inoculating 30% of the strain concentrate. The current research demonstrated that strain GR7397 has significant potential for application in enhancing nitrogen removal in wastewater treatment.

bioengineering↗

bioRxiv2021

Embeddings of genomic region sets capture rich biological associations in lower dimensions

MotivationGenomic region sets summarize functional genomics data and define locations of interest in the genome such as regulatory regions or transcription factor binding sites. The number of publicly available region sets has increased dramatically, leading to challenges in data analysis. ResultsWe propose a new method to represent genomic region sets as vectors, or embeddings, using an adapted word2vec approach. We compared our approach to two simpler methods based on interval unions or term frequency-inverse document frequency and evaluated the methods in three ways: First, by classifying the cell line, antibody, or tissue type of the region set; second, by assessing whether similarity among embeddings can reflect simulated random perturbations of genomic regions; and third, by testing robustness of the proposed representations to different signal thresholds for calling peaks. Our word2vec-based region set embeddings reduce dimensionality from more than a hundred thousand to 100 without significant loss in classification performance. The vector representation could identify cell line, antibody, and tissue type with over 90% accuracy. We also found that the vectors could quantitatively summarize simulated random perturbations to region sets and are more robust to subsampling the data derived from different peak calling thresholds. Our evaluations demonstrate that the vectors retain useful biological information in relatively lower-dimensional spaces. We propose that vector representation of region sets is a promising approach for efficient analysis of genomic region data. Availabilityhttps://github.com/databio/regionset-embedding

bioinformatics↗

bioRxiv2021

Sensory cilia act as a specialized venue for regulated EV biogenesis and signaling

Extracellular vesicles play major roles in intercellular signaling, yet fundamental aspects of their biology remain poorly understood. Ciliary EV shedding is evolutionary conserved. Here we use super resolution, real time imaging of fluorescent-protein tagged EV cargo combined with in vivo bioassays to study signaling EVs in C. elegans. We find that neuronal sensory cilia shed the TRP polycystin-2 channel PKD-2::GFP-carrying EVs from two distinct sites - the ciliary tip and the ciliary base. Ciliary tip shedding requires distal ciliary enrichment of PKD-2 by the myristoylated coiled-coil protein CIL-7. Kinesin-3 KLP-6 and intraflagellar transport (IFT) kinesin-2 motors are also required for ciliary tip EV shedding. Blocking ciliary tip shedding results in excessive EV shedding from the base. Finally, we demonstrate that C. elegans male ciliated neurons modulate EV cargo composition in response to sensory stimulation by hermaphrodite mating partners. Overall, our study indicates that the cilium and its trafficking machinery act as a specialized venue for regulated EV biogenesis and signaling.

cell biology↗

bioRxiv2020

Bedshift: perturbation of genomic interval sets

Functional genomics experiments, like ChIP-Seq or ATAC-Seq, produce results that are summarized as a region set. Many tools have been developed to analyze region sets, including computing similarity metrics to compare them. However, there is no way to objectively evaluate the effectiveness of region set similarity metrics. In this paper we present Bedshift, a command-line tool and Python API to generate new BED files by making random perturbations to an original BED file. Perturbed files have known similarity to the original file and are therefore useful to benchmark similarity metrics. To demonstrate, we used Bedshift to create an evaluation dataset of hundreds of perturbed files generated by shifting, adding, and dropping regions from a reference BED file. Then, we compared four similarity metrics: Jaccard score, coverage score, Euclidean distance, and cosine similarity. Our results highlight differences in behavior among these metrics, such as that Jaccard score is most sensitive to added or dropped regions, while coverage score is most sensitive to shifted regions. Together, we show that Bedshift is a useful tool for creating randomized region sets for a variety of uses. AvailabilityBSD2-licensed source code and documentation can be found at https://bedshift.databio.org.

bioinformatics↗

bioRxiv2020

CCP1, a tubulin deglutamylase, increases survival of rodent spinal cord neurons following glutamate-induced excitotoxicity

Microtubules (MTs) are cytoskeletal elements that provide structural support, establish morphology, and act as roadways for intracellular transport in cells. Neurons extend and must maintain long axons and dendrites to transmit information through the nervous system. Therefore, in neurons, the ability to independently regulate cytoskeletal stability and MT-based transport in different cellular compartments is essential. Post-translational modification of MTs is one mechanism by which neurons can regulate the cytoskeleton. The carboxypeptidase CCP1 negatively regulates post-translational glutamylation of MTs. We previously demonstrated that the CCP1 homolog in C. elegans is important for maintenance of cilia. In mammals, loss of CCP1, and the resulting hyperglutamylation of MTs, causes neurodegeneration. It has long been known that CCP1 expression is activated by neuronal injury; however, whether CCP1 plays a neuroprotective role after injury is unknown. Furthermore, it not yet clear whether CCP1 acts on ciliary MTs in spinal cord neurons. Using an in vitro model of excitotoxic neuronal injury coupled with shRNA-mediated knockdown of CCP1, we demonstrate that CCP1 protects neurons from excitotoxic death. Unexpectedly, excitotoxic injury reduced CCP1 expression in our system, and knockdown of CCP1 did not result in loss or shortening of cilia in cultured spinal cord neurons. Our results suggest that CCP1 acts on axonal and dendritic MTs to promote cytoskeletal rearrangements that support neuroregeneration and that enzymes responsible for glutamylation of MTs might be therapeutically targeted to prevent excitotoxic death after spinal cord injuries.

cell biology↗

bioRxiv2020

Mutation of NEKL-4/NEK10 and TTLL genes opposes loss of the CCPP-1 deglutamylase and prevents neuronal ciliary degeneration

Ciliary microtubules are subject to post-translational modifications that act as a "Tubulin Code" to regulate motor traffic, binding proteins and stability. In humans, loss of CCP1, a cytosolic carboxypeptidase and tubulin deglutamylating enzyme, causes infantile-onset neurodegeneration. In C. elegans, mutations in ccpp-1, the homolog of CCP1, result in progressive degeneration of neuronal cilia and loss of neuronal function. To identify genes that regulate microtubule glutamylation and ciliary integrity, we performed a forward genetic screen for suppressors of ciliary degeneration in ccpp-1 mutants. We isolated the ttll-5(my38) suppressor, a mutation in the tubulin tyrosine ligase-like glutamylase gene. We show that mutation in ttll-4, ttll-5, or ttll-11 gene suppressed the hyperglutamylation-induced loss of microtubules and kinesin-2 mislocalization in ccpp-1 cilia. We also identified the nekl-4(my31) suppressor, an allele affecting the NIMA (Never in Mitosis A)-related kinase NEKL-4/NEK10. In humans, NEK10 mutation causes bronchiectasis, an airway and mucociliary transport disorder caused by defective motile cilia. C. elegans NEKL-4 does not localize to cilia yet plays a role in regulating axonemal microtubule stability. This work defines a pathway in which glutamylation, a component of the Tubulin Code, is written by TTLL-4, TTLL-5, and TTLL-11; is erased by CCPP-1; is read by ciliary kinesins; and its downstream effects are modulated by NEKL-4 activity. Identification of regulators of microtubule glutamylation in diverse cellular contexts is important to the development of effective therapies for disorders characterized by changes in microtubule glutamylation. By identifying C. elegans genes important for neuronal and ciliary stability, our work may inform research into human ciliopathies and neurodegenerative diseases.

genetics↗

bioRxiv2020

Sensory-evoked extracellular vesicle release and targeting

Extracellular vesicles (EVs) are emerging as a universal means of cell-to-cell communication and hold great potential in diagnostics and regenerative therapies [1]. An urgent need in the field is a fundamental understanding of physiological mechanisms driving EV generation and function. Ciliary EVs act as signaling devices in Chlamydomonas and C. elegans [2-4]. Mammalian cilia shed EVs to eliminate unwanted receptors [5] or to retract cilia before entering the cell cycle [6]. Here we used our established C. elegans model to study sensory-evoked ciliary EV release and targeting using a fluorescently labeled EV cargo polycystin-2 (PKD-2). In C. elegans and mammals, the Autosomal Dominant Polycystic Kidney Disease (ADPKD) gene products polycystin-1 and polycystin-2 localize to cilia and EVs, act in the same genetic pathway, and function in a sensory capacity, suggesting ancient conservation [7]. We find that males deposit PKD-2-carrying EVs onto the vulva of the hermaphrodite during mating. We also show that mechanical stimulation triggers release of PKD-2-carrying EVs from cilia. To our knowledge this is the first report of mechanoresponsive nature of the ciliary EV release and of ciliary EV directional transfer from one animal to another animal. Since the polycystins are evolutionarily conserved ciliary EV cargoes, our findings suggest that similar mechanisms for EV release and targeting may occur in other systems and biological contexts.

cell biology↗

bioRxiv2019

Impact of Influent Carbon to Phosphorus Ratio on Performance and Phenotypic Dynamics in Enhanced Biological Phosphorus Removal (EBPR) System - Insights into Carbon Distribution, Intracellular Polymer Stoichiometry and Pathways Shifts

This study investigated the impact of influent carbon to phosphorus (P) ratio on the variation in P-removal performance and associated intracellular polymers dynamics in key functionally relevant microbial populations, namely, PAOs and GAOs, at both individual and populations levels, in laboratory scale sequencing batch reactor-EBPR systems. Significant variations and dynamics were evidenced for the formation, utilization and stoichiometry of intracellular polymers, namely polyphosphate, glycogen and Polyhydroxyalkanoates in PAOs and GAOs in the EBPR systems that were operated with influent C/P ranged from 20 to 50, presumably as results of phylogenetic diversity changes and, or metabolic functions shifts in these two populations at different influent C/P ratios. Single cell Raman micro-spectroscopy enabled quantification of differentiated polymer inclusion levels in PAOs and GAOs and, showed that as the influent rbCOD/P ratio increases, the excessive carbon beyond stoichiometric requirement for PAOs would be diverted into GAOs. Our results also evidenced that when condition becomes more P limiting at higher rbCOD/P ratios, both energy and reducing power generation required for acetate uptake and PHB formation might shift from relying on both polyP hydrolysis and glycolysis pathway, to more enhancement and dependence on glycolysis in addition to partial/reverse TCA cycle. These findings provided new insights into the metabolic elasticity of PAOs and GAOs and their population-level parameters for mechanistic EBPR modeling. This study also demonstrated the potential of application of single cell Raman micro-spectroscopy method as a powerful tool for studying phenotypic dynamics in ecological systems such as EBPR.\n\n\n\nO_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=97 SRC=\"FIGDIR/small/671081v1_ufig1.gif\" ALT=\"Figure 1\">\nView larger version (37K):\norg.highwire.dtl.DTLVardef@13227d5org.highwire.dtl.DTLVardef@1d52d42org.highwire.dtl.DTLVardef@8e67c4org.highwire.dtl.DTLVardef@13eb1aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗