Biology subjects

Wang, M.

Publications and source records attributed to Wang, M..

At least 361 records · Page 20Linked to original sources

bioRxiv2024

In-brain construction of receptor-based protease sensors by coupling ligand-directed chemistry and click chemistry

The chemical modification of natural proteins in living systems is highly desirable toward the cutting-edge research in chemistry-biology interface. Recent advances in bioorthogonal protein modification have enabled the production of chemically functional proteins in cultured cell systems. However, few methods are applicable in vivo because of the complexity of the three-dimensional constructs of living systems with diverse, heterogeneous cell populations and flow systems filled with tissue fluids. Here, we report a genetic engineering-free method to modify receptor proteins with various probes in the living mouse brain by combining in-brain ligand-directed chemistry with bioorthogonal click chemistry, and propose a chemical guideline for the reaction design. The rapid and selective tethering of a set of fluorescent peptides to AMPA-type glutamate receptors (AMPARs) allowed the construction of receptor-based fluorescent sensors. These probes enabled mapping of the activity of matrix metalloproteinase-9 proximal to AMPARs in the living brain to be realized with high spatial resolution. Our strategy provides new opportunities for the precise analysis of particular in vivo microenvironments that has not been able to be addressed by conventional methods. Such analysis should contribute to the understanding of the molecular basis for complicated in vivo events, such as the regulation of neuroplasticity, the most important challenge in neuroscience.

biochemistry↗

bioRxiv2024

Spatiotemporal transcriptomic maps of mouse intracerebral hemorrhage at single-cell resolution

Intracerebral hemorrhage (ICH) is a severe and widespread disease that results in high mortality and morbidity. Despite significant advances made in clinical and preclinical research, the prognosis of ICH remains poor due to an incomplete understanding of the complex pathological responses. To address this challenge, we generated single-cell resolution spatiotemporal transcriptomic maps of mouse brain 1, 3, 7, 14, and 28 days after ICH. Our analysis revealed the cellular constituents and their dynamic responses following ICH. We found changes in gene expression that are indicative of active phagocytosis and lipid processing in the lesion core and identified genes associated with brain repair at the lesion border. Persistent lipid accumulation culminated in the phenotypic transition of macrophages into foam cells. Furthermore, our results demonstrate that ICH could stimulate neural stem cells in the subventricular zone, thereby enhancing neurogenesis in this niche. This study provides a spatiotemporal molecular atlas of mouse ICH that advances the understanding of both local and global responses of brain cells to ICH and offers a valuable resource that can aid the development of novel therapies for this devastating condition.

neuroscience↗

bioRxiv2024

ADAPT: Analysis of Microbiome Differential Abundance by Pooling Tobit Models

Microbiome differential abundance analysis remains a challenging problem despite multiple methods proposed in the literature. The excessive zeros and compositionality of metagenomics data are two main challenges for differential abundance analysis. We propose a novel method called "analysis of differential abundance by pooling Tobit models" (ADAPT) to overcome these two challenges. ADAPT uniquely treats zero counts as left-censored observations to facilitate computation and enhance interpretation. ADAPT also encompasses a theoretically justified way of selecting non-differentially abundant microbiome taxa as a reference for hypothesis testing. We generate synthetic data using independent simulation frameworks to show that ADAPT has more consistent false discovery rate control and higher statistical power than competitors. We use ADAPT to analyze 16S rRNA sequencing of saliva samples and shotgun metagenomics sequencing of plaque samples collected from infants in the COHRA2 study. The results provide novel insights into the association between the oral microbiome and early childhood dental caries.

bioinformatics↗

bioRxiv2024

Hijacking a dedicated entorhinal-hippocampal extinction circuit to remove traumatic memory

Effective psychotherapy of post-traumatic stress disorder (PTSD) remains challenging due to the fragile nature of fear extinction, for which ventral hippocampal CA1 (vCA1) region is considered as a central hub. However, neither the core pathway nor the cellular mechanisms involved in implementing extinction are known. Here, we unveil a direct pathway, where layer 2a fan cells in the lateral entorhinal cortex (LEC) target parvalbumin-expressing interneurons (PV-INs) in the vCA1 region to propel low gamma-band synchronization of the LEC-vCA1 activity during extinction learning. Bidirectional manipulations of either hippocampal PV-INs or LEC fan cells suffice fear extinction. Gamma entrainment of vCA1 by deep brain stimulation (DBS) or noninvasive transcranial alternating current stimulation (tACS) of LEC persistently enhances the PV-IN activity in vCA1, thereby promoting fear extinction. These results demonstrate that the LEC-vCA1 pathway forms a top-down motif to empower low gamma-band oscillations that facilitate fear extinction. Finally, application of low gamma DBS and tACS to a mouse model with persistent PTSD shows potent efficacy, suggesting that the dedicated LEC-vCA1 pathway can be hijacked for therapy to remove traumatic memory trace. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=199 SRC="FIGDIR/small/593830v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@ca6768org.highwire.dtl.DTLVardef@4ae574org.highwire.dtl.DTLVardef@11e4ff5org.highwire.dtl.DTLVardef@1136cc2_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2024

Wheat Enhanced Disease Resistance EMS-Mutants Include Lesion-mimics With Adult Plant Resistance to Stripe Rust

Tetraploid durum wheat Triticum turgidum subsp. durum cv Kronos has extensive genetic variation resources, including a sequenced and cataloged ethyl methanesulfonate (EMS) mutagenized population. To utilize this allelic diversity, we screened over 2,000 mutant lines and identified over 30 enhanced disease resistance (EDR) mutants in a forward genetic field screen against stripe rust. Sixteen of the EDR lines have persistent resistance to stripe rust after four years, and several mutants showed differential disease responses against other fungal pathogens, indicating that the lines possess diverse alleles that affect multiple routes of pathogen suppression. Five of these 16 lines showed spontaneous lesion formation in the absence of pathogens. Only one showed a reduction in kernel weight under pathogen pressure, a testimony to the high mutational density that wheat can tolerate. Phenotypic selection for resistance at the adult stage identified useful EMS alleles for stripe rust resistance. The mutations in the 16 EDR lines were newly mapped to a recently released long-read Kronos genome to enhance their utility in molecular breeding for fungal resistance and for fundamental studies of plant-pathogen interactions.

plant biology↗

bioRxiv2024

Supervised fine-tuning of pre-trained antibody language models improves antigen specificity prediction

Antibodies play a crucial role in adaptive immune responses by determining B cell specificity to antigens and focusing immune function on target pathogens. Accurate prediction of antibody-antigen specificity directly from antibody sequencing data would be a great aid in understanding immune responses, guiding vaccine design, and developing antibody-based therapeutics. In this study, we present a method of supervised fine-tuning for antibody language models, which improves on previous results in binding specificity prediction to SARS-CoV-2 spike protein and influenza hemagglutinin. We perform supervised fine-tuning on four pre-trained antibody language models to predict specificity to these antigens and demonstrate that fine-tuned language model classifiers exhibit enhanced predictive accuracy compared to classifiers trained on pretrained model embeddings. The change of model attention activations after supervised fine-tuning suggested that this performance was driven by an increased model focus on the complementarity determining regions (CDRs). Application of the supervised fine-tuned models to BCR repertoire data demonstrated that these models could recognize the specific responses elicited by influenza and SARS-CoV-2 vaccination. Overall, our study highlights the benefits of supervised fine-tuning on pre-trained antibody language models as a mechanism to improve antigen specificity prediction. Author SummaryAntibodies are vigilant sentinels of our adaptive immune system that recognize and bind to targets on foreign pathogens, known as antigens. This interaction between antibody and antigen is highly specific, akin to a fitting lock and key mechanism, to ensure each antibody precisely targets its intended antigen. Recent advancements in language modeling have led to the development of antibody language model to decode specificity information in the sequences of antibodies. We introduce a method based on supervised fine-tuning, which enhances the accuracy of antibody language models in predicting antibody-antigen interactions. By training these models on large datasets of antibody sequences, we can better predict which antibodies will bind to important antigens such as those found on the surface of viruses like SARS-CoV-2 and influenza. Moreover, our study demonstrates the potential of the models to "read" B cell repertoire data and predict ongoing responses, offering new insights into how our bodies respond to vaccination. These findings have significant implications for vaccine design, as accurate prediction of antibody specificity can guide the development of more effective vaccines.

bioinformatics↗

bioRxiv2024

Mining the biosynthetic landscape of lactic acid bacteria unearths a new family of RiPPs assembled by a novel type of ThiF-like adenylyltransferases

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are chemically diverse natural products of ribosomal origin. These peptides, which frequently act as signals or antimicrobials, are biosynthesized by conserved enzymatic machineries, making genome mining a powerful strategy for unearthing previously uncharacterized members of their class. Herein, we investigate the untapped biosynthetic potential of Lactobacillales (i.e. lactic acid bacteria) - an order of Gram-positive bacteria closely associated with human life, including pathogenic species and industrially-relevent fermenters of dairy products. Through genome mining methods, we systematically explored the distribution and diversity of ThiF-like adenylyltransferases-utilizing RiPP systems in lactic acid bacteria and identified a number of unprecedented biosynthetic gene clusters. In one of these clusters, we found a previously undescribed group of macrocyclic imide biosynthetic pathways containing multiple transporters and may be involved in potential quorum sensing (QS) system. Through in vitro assays, we determined that one such adenylyltranferase specifically catalyzes the intracyclization of its precursor peptide through macrocyclic imide formation. Incubating the enzyme with various primary amines revealed it could effectively amidate the C-terminus of the precursor peptide. This new transformation adds to the growing list of Natures peptide macrocyclization strategies and expands the impressive catalytic repertoire of the adenylyltransferase family. The diverse RiPP systems identified herein represent a vast, unexploited landscape for discovery of novel class of natural products and potential QS systems. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=68 SRC="FIGDIR/small/593846v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1cd3125org.highwire.dtl.DTLVardef@55a546org.highwire.dtl.DTLVardef@d5a325org.highwire.dtl.DTLVardef@1c9e1f3_HPS_FORMAT_FIGEXP M_FIG C_FIG (For Table of Contents use only)

biochemistry↗

bioRxiv2024

Functional and multi-omic aging rejuvenation with GLP-1R agonism

Identifying readily implementable methods that can effectively counteract aging is urgently needed for tackling age-related degenerative disorders. Here, we conducted functional assessments and deep molecular phenotyping in the aging mouse to demonstrate that glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment attenuates body-wide age-related changes. Apart from improvements in physical and cognitive performance, the age-counteracting effects are prominently evident at multiple omic levels. These span the transcriptomes and DNA methylomes of various tissues, organs and circulating white blood cells, as well as the plasma metabolome. Importantly, the beneficial effects are specific to aged mice, not young adults, and are achieved with a low dosage of GLP-1RA which has a negligible impact on food consumption and body weight. The molecular rejuvenation effects exhibit organ-specific characteristics, which are generally heavily dependent on hypothalamic GLP-1R. We benchmarked the GLP-1RA age-counteracting effects against those of mTOR inhibition, a well-established anti-aging intervention, observing a strong resemblance across the two strategies. Our findings have broad implications for understanding the mechanistic basis of the clinically observed pleiotropic effects of GLP-1RAs, the design of intervention trials for age-related diseases, and the development of anti-aging-based therapeutics.

systems biology↗

bioRxiv2024

De novo gene synthesis by an antiviral reverse transcriptase

Bacteria defend themselves from viral infection using diverse immune systems, many of which sense and target foreign nucleic acids. Defense-associated reverse transcriptase (DRT) systems provide an intriguing counterpoint to this immune strategy by instead leveraging DNA synthesis, but the identities and functions of their DNA products remain largely unknown. Here we show that DRT2 systems execute an unprecedented immunity mechanism that involves de novo gene synthesis via rolling-circle reverse transcription of a non-coding RNA (ncRNA). Unbiased profiling of RT-associated RNA and DNA ligands in DRT2-expressing cells revealed that reverse transcription generates concatenated cDNA repeats through programmed template jumping on the ncRNA. The presence of phage then triggers second-strand cDNA synthesis, leading to the production of long double-stranded DNA. Remarkably, this DNA product is efficiently transcribed, generating messenger RNAs that encode a stop codon-less, never-ending ORF (neo) whose translation causes potent growth arrest. Phylogenetic analyses and screening of diverse DRT2 homologs further revealed broad conservation of rolling-circle reverse transcription and Neo protein function. Our work highlights an elegant expansion of genome coding potential through RNA-templated gene creation, and challenges conventional paradigms of genetic information encoded along the one-dimensional axis of genomic DNA. One-Sentence SummaryBacterial reverse transcriptases synthesize extrachromosomal genes via rolling-circle amplification to confer potent antiviral immunity.

molecular biology↗

bioRxiv2024

Fast, Accurate, and Versatile Data Analysis Platform for the Quantification of Molecular Spatiotemporal Signals

Optical recording of intricate molecular dynamics is becoming an indispensable technique for biological studies, accelerated by the development of new or improved biosensors and microscopy technology. This creates major computational challenges to extract and quantify biologically meaningful spatiotemporal patterns embedded within complex and rich data sources, many of which cannot be captured with existing methods. Here, we introduce Activity Quantification and Analysis (AQuA2), a fast, accurate, and versatile data analysis platform built upon advanced machine learning techniques. It decomposes complex live imaging-based datasets into elementary signaling events, allowing accurate and unbiased quantification of molecular activities and identification of consensus functional units. We demonstrate applications across a wide range of biosensors, cell types, organs, animal models, and imaging modalities. As exemplar findings, we show how AQuA2 identified drug-dependent interactions between neurons and astroglia, and distinct sensorimotor signal propagation patterns in the mouse spinal cord.

neuroscience↗

bioRxiv2024

Diversity and ecological potentials of viral assemblages from the seamount sediments of the Northwest Pacific Ocean

Viruses are the most abundant life forms in the sea, influencing the community structure and metabolism of host cells as well as biogeochemical cycles. However, the diversity and ecological roles of viruses within seamount ecosystems, natural microbiota havens characterized by high biodiversity, remain unknown. Here, the first seamount viral genome (SMVG) dataset, based on a metagenomic analysis of twelve seamount sediment samples collected from the seamount regions of the Northwest Pacific Ocean, is established. A total of 78,069 viral operational taxonomic units (vOTUs) were found, spanning 18 viral classes and 63 viral families. The detection of sixteen viral auxiliary metabolic genes (vAMGs) suggests that viruses may participate in both the complex metabolic dynamics associated with sediment microbial communities and also biogeochemical cycles, including carbon, sulfur, metal, heme, and cobalamin cycling. vAMGs involved in the metabolism of heme, cobalamin and metals, in particular, are more often detected in seamount sediments than in trenches, cool seeps, and hydrothermal vents. This investigation of the viral communities in these seamount sediments provides new insights into the high diversity and ecological potential of the viruses and establishes a foundation for the future study of benthic viruses from deep-sea seamounts.

ecology↗

bioRxiv2024

5-HT Neurons Integrate GABA and Dopamine Inputs to Regulate Meal Initiation

Obesity is a growing global health epidemic with limited effective therapeutics. Serotonin (5-HT) is one major neurotransmitter which remains an excellent target for new weight-loss therapies, but there remains a gap in knowledge on the mechanisms involved in 5-HT produced in the dorsal Raphe nucleus (DRN) and its involvement in meal initiation. Using a closed-loop optogenetic feeding paradigm, we showed that the 5-HTDRN{lozenge}arcuate nucleus (ARH) circuit plays an important role in regulating meal initiation. Incorporating electrophysiology and ChannelRhodopsin-2-Assisted Circuit Mapping, we demonstrated that 5-HTDRN neurons receive inhibitory input partially from GABAergic neurons in the DRN, and the 5-HT response to GABAergic inputs can be enhanced by hunger. Additionally, deletion of the GABAA receptor subunit in 5-HT neurons inhibits meal initiation with no effect on the satiation process. Finally, we identified the instrumental role of dopaminergic inputs via dopamine receptor D2 in 5-HTDRN neurons in enhancing the response to GABA-induced feeding. Thus, our results indicate that 5-HTDRN neurons are inhibited by synergistic inhibitory actions of GABA and dopamine, which allows for the initiation of a meal.

neuroscience↗

bioRxiv2024

Short-Term Disruption of TGFβ Signaling in Adult Mice Renders the Aorta Vulnerable to Hypertension-Induced Dissection

Hypertension and transient increases in blood pressure from extreme exertion are risk factors for aortic dissection in patients with age-related vascular degeneration or inherited connective tissue disorders. Yet, the common experimental model of angiotensin II-induced aortopathy in mice appears independent of high blood pressure as lesions do not occur in response to an alternative vasoconstrictor, norepinephrine, and are not prevented by co-treatment with a vasodilator, hydralazine. We investigated vasoconstrictor administration to adult mice 1 week after disruption of TGF{beta} signaling in smooth muscle cells. Norepinephrine increased blood pressure and induced aortic dissection by 7 days and even within 30 minutes that was rescued by hydralazine; results were similar with angiotensin II. Changes in regulatory contractile molecule expression were not of pathological significance. Rather, reduced synthesis of extracellular matrix yielded a vulnerable aortic phenotype by decreasing medial collagen, most dynamically type XVIII, and impairing cell-matrix adhesion. We conclude that transient and sustained increases in blood pressure cause dissection in aortas rendered vulnerable by inhibition of TGF{beta}-driven extracellular matrix production by smooth muscle cells. A corollary is that medial fibrosis, a frequent feature of medial degeneration, may afford some protection against aortic dissection.

pathology↗

bioRxiv2024

Large- Scale Deep Proteomic Analysis in Alzheimer's Disease Brain Regions Across Race and Ethnicity

AbstractO_ST_ABSIntroductionC_ST_ABSAlzheimers disease (AD) is the most prevalent neurodegenerative disease, yet our comprehension predominantly relies on studies within the non-Hispanic White (NHW) population. Here we aimed to provide comprehensive insights into the proteomic landscape of AD across diverse racial and ethnic groups. MethodsDorsolateral prefrontal cortex (DLPFC) and superior temporal gyrus (STG) brain tissues were donated from multiple centers (Mayo Clinic, Emory University, Rush University, Mt. Sinai School of Medicine) and were harmonized through neuropathological evaluation, specifically adhering to the Braak staging and CERAD criteria. Among 1105 DLPFC tissue samples (998 unique individuals), 333 were from African American donors, 223 from Latino Americans, 529 from NHW donors, and the rest were from a mixed or unknown racial background. Among 280 STG tissue samples (244 unique individuals), 86 were African American, 76 Latino American, 116 NHW and the rest were mixed or unknown ethnicity. All tissues were uniformly homogenized and analyzed by tandem mass tag mass spectrometry (TMT-MS). ResultsAs a Quality control (QC) measure, proteins with more than 50% missing values were removed and iterative principal component analysis was conducted to remove outliers within brain regions. After QC, 9,180 and 9,734 proteins remained in the DLPC and STG proteome, respectively, of which approximately 9,000 proteins were shared between regions. Protein levels of microtubule-associated protein tau (MAPT) and amyloid-precursor protein (APP) demonstrated AD-related elevations in DLPFC tissues with a strong association with CERAD and Braak across racial groups. APOE4 protein levels in brain were highly concordant with APOE genotype of the individuals. DiscussionThis comprehensive region resolved large-scale proteomic dataset provides a resource for the understanding of ethnoracial-specific protein differences in AD brain.

neuroscience↗

bioRxiv2024

CRISPR-GPT: An LLM Agent for Automated Design of Gene-Editing Experiments

Performing effective gene-editing experiments requires a deep understanding of both the CRISPR technology and the biological system involved. Meanwhile, despite their versatility and promise, Large Language Models (LLMs) often lack domain-specific knowledge and struggle to accurately solve biological design problems. We present CRISPR-GPT, an LLM agent system to automate and enhance CRISPR-based gene-editing design and data analysis. CRISPR-GPT leverages the reasoning capabilities of LLMs for complex task decomposition, decision-making, and interactive human-artificial intelligence (AI) collaboration. This system incorporates domain expertise, retrieval techniques, external tools, and a specialized LLM fine-tuned with open-forum discussions among scientists. CRISPR-GPT assists users in selecting CRISPR systems, experiment planning, designing gRNAs, choosing delivery methods, drafting protocols, designing assays, and analyzing data. We showcase the potential of CRISPR-GPT by knocking-out four genes with CRISPR-Cas12a in a human lung adenocarcinoma cell line and epigenetically activating two genes using CRISPR-dCas9 in human melanoma cell line. CRISPR-GPT enables fully AI-guided gene-editing experiment design and analysis across different modalities, validating its effectiveness as an AI co-pilot in genome engineering.

bioinformatics↗

bioRxiv2024

A human forebrain organoid model reveals the essential function of GTF2IRD1-TTR-ERK axis for the neurodevelopmental deficits of Williams Syndrome

Williams Syndrome (WS; OMIM#194050) is a rare disorder, which is caused by the microdeletion of one copy of 25-27 genes, and WS patients display diverse neuronal deficits. Although remarkable progresses have been achieved, the mechanisms for these distinct deficits are still largely unknown. Here, we have shown that neural progenitor cells (NPCs) in WS forebrain organoids display abnormal proliferation and differentiation capabilities, and synapse formation. Genes with altered expression are related to neuronal development and neurogenesis. Single cell RNA-seq (scRNA-seq) data analysis revealed 13 clusters in healthy control and WS organoids. WS organoids show an aberrant generation of excitatory neurons. Mechanistically, the expression of transthyretin (TTR) are remarkably decreased in WS forebrain organoids. We have found that GTF2IRD1 encoded by one WS associated gene GTF2IRD1 binds to TTR promoter regions and regulates the expression of TTR. In addition, exogenous TTR can activate ERK signaling and rescue neurogenic deficits of WS forebrain organoids. Gtf2ird1 deficient mice display similar neurodevelopmental deficits as observed in WS organoids. Collectively, our study reveals critical function of GTF2IRD1 in regulating neurodevelopment of WS forebrain organoids and mice through regulating TTR-ERK pathway.

neuroscience↗

bioRxiv2024

Microbiota from young mice counteracts susceptibility to age-related gout through modulating butyric acid levels in aged mice

Gout is a prevalent form of inflammatory arthritis that occurs due to high levels of uric acid in the blood leading to the formation of urate crystals in and around the joints, particularly affecting the elderly. Recent research has provided evidence of distinct differences in the gut microbiota of patients with gout and hyperuricemia when compared to healthy individuals. However, the link between gut microbiota and age-related gout remained underexplored. Our study found that gut microbiota plays a crucial role in determining susceptibility to age-related gout. Specifically, we observed that age-related gut microbiota regulated the activation of the NLRP3 inflammasome pathway and modulated uric acid metabolism. More scrutiny highlighted the positive impact of "younger" microbiota on the gut microbiota structure of old or aged mice, enhancing butanoate metabolism and butyric acid content. Experimentation with butyrate supplementation indicated that butyric acid exerts a dual effect, inhibiting inflammation in acute gout and reducing serum uric acid levels. These insights emphasize the potential of gut microbiome rejuvenation in mitigating senile gout, unraveling the intricate dynamics between microbiota, aging, and gout. It potentially serves as a therapeutic target for senile gout-related conditions.

microbiology↗

bioRxiv2024

Insight into the Impact of Air Flow Rate on Algal-Bacterial Granules: Reactor Performance, Hydrodynamics by Computational Fluid Dynamics (CFD) and Microbial Community Analysis

Algal-bacterial granules have been drawing attention in wastewater treatment due to their rapid settling ability and efficient nutrient removal performance. This study evaluated the impact of air flow rates on nitrogen removal and the formation of algal-bacterial granules in domestic wastewater treatment. The highest nitrogen removal efficiency was achieved by operating with two separate feedings and the addition of an external carbon source. The higher air flow rate resulted in a higher nitrification rate and produced smaller and more compact granules on average. However, increasing the air flow rate did not necessarily increase extracellular polymeric substances (EPS) production. Computational Fluid Dynamics (CFD) simulations revealed that mechanical mixing was the primary source of shear force. Increasing the air flow rate from 0.2 LPM to 0.5 LPM only yielded a 12% increment in the volume-averaged strain rate. Further analysis of microbial communities showed that changes in bioreactor operation, especially sodium acetate addition and aerations, shifted the microbial community composition. The sodium acetate addition led to the increase of microbial diversity and the relative abundance of denitrifiers such as Thauera, while the aeration caused the increasing relative abundances of nitrogen-related genera (such as Nitrospira) and the decreasing relative abundances of cyanobacteria and Chlorella in the long-term operation of the photobioreactors. Moreover, the decrease in total abundance of grazers and pathogens along with the operation, including Chytridiomycetes, Sessilida, and Operculariidae, might result from the shear force and the decrease of prokaryotic species, such as Chlorella spp.. HighlightsO_LIA higher air flow rate resulted in a higher nitrification rate. C_LIO_LIShear stress, microbial composition, and carbon source affected EPS production. C_LIO_LIIncreasing the air flow rate from 0.2 to 0.5 LPM led to only 12% of the increment of shear stress. C_LIO_LIMicrobial community differed with aeration rate and carbon source. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=175 SRC="FIGDIR/small/589810v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@c6a7e1org.highwire.dtl.DTLVardef@37da84org.highwire.dtl.DTLVardef@eb362dorg.highwire.dtl.DTLVardef@31d122_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗