Biology subjects

Huang, J.

Publications and source records attributed to Huang, J..

At least 505 records · Page 28Linked to original sources

bioRxiv2021

A phosphorylation of RIPK3 kinase initiates an intracellular apoptotic pathway that promotes corpus luteum regression

Receptor-interacting serine/threonine-protein kinase 3 (RIPK3) normally signals to necroptosis by phosphorylating MLKL. We report here that when the cellular RIPK3 chaperone Hsp90/CDC37 level is low, RIPK3 also signals to apoptosis. The apoptotic function of RIPK3 requires phosphorylation of the serine 165/threonine 166 sites on its kinase activation loop, resulting in inactivation of RIPK3 kinase activity while gaining the ability to recruit RIPK1, FADD, and caspase-8 to form a cytosolic caspase-activating complex, thereby triggering apoptosis. We found that PGF2 induces RIPK3 expression in luteal granulosa cells in the ovary to cause luteal regression through this RIPK3-mediated apoptosis pathway. Mice carrying homozygous phosphorylation-resistant RIPK3 S165A/T166A knockin mutations failed to respond to PGF2 but retained pro-necroptotic function, whereas mice with phospho-mimicking S165D/T166E homozygous knockin mutation underwent spontaneous apoptosis in multiple RIPK3-expressing tissues and died shortly after birth. Thus, RIPK3 signals to either necroptosis or apoptosis depending on its serine 165/threonine 166 phosphorylation status.

cell biology↗

bioRxiv2021

SALTS: SURFR (small noncoding RNA) And LAGOOn (long noncoding RNA) Transcriptomics Suite

The widespread utilization of high-throughput sequencing technologies has unequivocally demonstrated that eukaryotic transcriptomes consist primarily (>98%) of non-coding RNA (ncRNA) transcripts significantly more diverse than their protein-coding counterparts. ncRNAs are typically divided into two categories based on their length. (1) ncRNAs less than 200 nucleotides (nt) long are referred as small non-coding RNAs (sncRNAs) and include microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), small nucleolar RNAs (snoRNAs), transfer ribonucleic RNAs (tRNAs), etc., and the majority of these are thought to function primarily in controlling gene expression. That said, the full repertoire of sncRNAs remains fairly poorly defined as evidenced by two entirely new classes of sncRNAs only recently being reported, i.e., snoRNA-derived RNAs (sdRNAs) and tRNA-derived fragments (tRFs). (2) ncRNAs longer than 200 nt long are known as long ncRNAs (lncRNAs). lncRNAs represent the 2nd largest transcriptional output of the cell (behind only ribosomal RNAs), and although functional roles for several lncRNAs have been reported, most lncRNAs remain largely uncharacterized due to a lack of predictive tools aimed at guiding functional characterizations. Importantly, whereas the cost of high-throughput transcriptome sequencing is now feasible for most active research programs, tools necessary for the interpretation of these sequencings typically require significant computational expertise and resources markedly hindering widespread utilization of these datasets. In light of this, we have developed a powerful new ncRNA transcriptomics suite, SALTS, which is highly accurate, markedly efficient, and extremely user-friendly. SALTS stands for SURFR (sncRNA) And LAGOOn (lncRNA) Transcriptomics Suite and offers platforms for comprehensive sncRNA and lncRNA profiling and discovery, ncRNA functional prediction, and the identification of significant differential expressions among datasets. Notably, SALTS is accessed through an intuitive Web-based interface, can be used to analyze either user-generated, standard next-generation sequencing (NGS) output file uploads (e.g., FASTQ) or existing NCBI Sequence Read Archive (SRA) data, and requires absolutely no dataset pre-processing or knowledge of library adapters/oligonucleotides. SALTS constitutes the first publically available, Web-based, comprehensive ncRNA transcriptomic NGS analysis platform designed specifically for users with no computational background, providing a much needed, powerful new resource capable of enabling more widespread ncRNA transcriptomic analyses. The SALTS WebServer is freely available online at http://salts.soc.southalabama.edu.

bioinformatics↗

bioRxiv2021

Brain transcriptional regulatory architecture and schizophrenia etiology converge between East Asian and European ancestral populations

Understanding the genetic architecture of gene expression and splicing in human brain is critical to unlocking the mechanisms of complex neuropsychiatric disorders like schizophrenia (SCZ). Large-scale brain transcriptomic studies are based primarily on populations of European (EUR) ancestry. The uniformity of mono-racial resources may limit important insights into the disease etiology. Here, we characterized brain transcriptional regulatory architecture of East Asians (EAS; n=151), identifying 3,278 expression quantitative trait loci (eQTL) and 4,726 spliceQTL (sQTL). Comparing these to PsychENCODE/BrainGVEX confirmed our hypothesis that the transcriptional regulatory architecture in EAS and EUR brains align. Furthermore, distinctive allelic frequency and linkage disequilibrium impede QTL translation and gene-expression prediction accuracy. Integration of eQTL/sQTL with genome-wide association studies reveals common and novel SCZ risk genes. Pathway-based analyses showing shared SCZ biology point to synaptic and GTPase dysfunction as a prospective pathogenesis. This study elucidates the transcriptional landscape of the EAS brain and emphasizes an essential convergence between EAS and EUR populations.

genetics↗

bioRxiv2021

Nanotraps for the containment and clearance of SARS-CoV-2

SARS-CoV-2 enters host cells through its viral spike protein binding to angiotensin-converting enzyme 2 (ACE2) receptors on the host cells. Here we show functionalized nanoparticles, termed "Nanotraps", completely inhibited SARS-CoV-2 infection by blocking the interaction between the spike protein of SARS-CoV-2 and the ACE2 of host cells. The liposomal-based Nanotrap surfaces were functionalized with either recombinant ACE2 proteins or anti-SARS-CoV-2 neutralizing antibodies and phagocytosis-specific phosphatidylserines. The Nanotraps effectively captured SARS-CoV-2 and completely blocked SARS-CoV-2 infection to ACE2-expressing human cell lines and primary lung cells; the phosphatidylserine triggered subsequent phagocytosis of the virus-bound, biodegradable Nanotraps by macrophages, leading to the clearance of pseudotyped and authentic virus in vitro. Furthermore, the Nanotraps demonstrated excellent biosafety profile in vitro and in vivo. Finally, the Nanotraps inhibited pseudotyped SARS-CoV-2 infection in live human lungs in an ex vivo lung perfusion system. In summary, Nanotraps represent a new nanomedicine for the inhibition of SARS-CoV-2 infection. HighlightsO_LINanotraps block interaction between SARS-CoV-2 spike protein and host ACE2 receptors C_LIO_LINanotraps trigger macrophages to engulf and clear virus without becoming infected C_LIO_LINanotraps showed excellent biosafety profiles in vitro and in vivo C_LIO_LINanotraps blocked infection to living human lungs in ex vivo lung perfusion system C_LI Progress and PotentialTo address the global challenge of creating treatments for SARS-CoV-2 infection, we devised a nanomedicine termed "Nanotraps" that can completely capture and eliminate the SARS-CoV-2 virus. The Nanotraps integrate protein engineering, immunology, and nanotechnology and are effective, biocompatible, safe, stable, feasible for mass production. The Nanotraps have the potential to be formulated into a nasal spray or inhaler for easy administration and direct delivery to the respiratory system, or as an oral or ocular liquid, or subcutaneous, intramuscular or intravenous injection to target different sites of SARS-CoV-2 exposure, thus offering flexibility in administration and treatment. More broadly, the highly versatile Nanotrap platform could be further developed into new vaccines and therapeutics against a broad range of diseases in infection, autoimmunity and cancer, by incorporating with different small molecule drugs, RNA, DNA, peptides, recombinant proteins, and antibodies.

bioengineering↗

bioRxiv2021

SiCEP3, a C-terminally encoded peptides from Setaria italica, promotes ABA import and signaling pathway

C-terminally encoded peptides (CEPs) are small peptides, typically post-translationally modified, and highly conserved in many species. CEPs are known to play roles in inhibition of plant growth and regulation of development, but the mechanisms are not well understood. In this study, we searched for CEP peptides in foxtail millet (Setaria italica). The 14 peptides we identified are divided into two subfamilies. The transcripts of most SiCEPs were more abundant in roots than in other tissues. SiCEP3, SiCEP4, and SiCEP5 were also expressed at high levels in panicles. Moreover, expression of all SiCEPs was induced by biotic stress and phytohormones. SiCEP3 overexpression and application of biosynthetic SiCEP3 both inhibited the growth of seedlings. In the presence of ABA, growth inhibition and ABA content of seedlings increased with the concentration of SiCEP3. Transcripts encoding two ABA transporters and one ABA receptor were induced by SiCEP3, ABA, and the two in combination. Further analysis revealed that SiCEP3 promoted ABA transport via NRT1.2 and ABCG40. In addition, SiCEP3, ABA, or the combination inhibited the kinase activities of CEP receptors CEPR1/2. Taken together, our results indicated that the CEP-CEPR module mediates ABA signaling by regulating ABCG40, NRT1.2, and PYL4 in planta. HighlightSiCEP3, a C-terminally encoded peptide, can promote ABA import and signaling pathway by inhibiting the kinase activity of its receptors under abiotic stress in Setaria italica.

cell biology↗

bioRxiv2021

deepManReg: a deep manifold-regularized learning model for improving phenotype prediction from multi-modal data

The biological processes from genotype to phenotype are complex involving multi-scale mechanisms. Increasing multi-modal data enables deeper understanding of underlying complex mechanisms in various phenotypes. However, integrating and interpreting such large-scale multi-modal data remains challenging, especially given highly heterogeneous, nonlinear relationships across modalities. To address this, we developed an interpretable regularized learning model, deepManReg to predict phenotypes from multi-modal data. First, deepManReg employs deep neural networks to learn cross-modal manifolds and then align multi-modal features onto a common latent space. This space aims to preserve both global consistency and local smoothness across modalities and reveal higher-order nonlinear cross-modal relationships. Second, deepManReg uses cross-modal manifolds as a feature graph to regularize the classifiers for improving phenotype predictions and also prioritizing the multi-modal features and cross-modal interactions for the phenotypes. We applied deepManReg to recent single cell multi-modal data such as Patch-seq data including transcriptomics and electrophysiology for neuronal cells in the mouse brain. We show that deepManReg significantly improves predicting cellular phenotypes and also prioritizing genes and electrophysiological features for the phenotypes. Finally, deepManReg is open-source and general for phenotype prediction from multi-modal data. deepManReg is open-source available at https://github.com/daifengwanglab/deepManReg.

bioinformatics↗

bioRxiv2021

Topological analysis of single-cell data reveals shared glial landscape of macular degeneration and neurodegenerative diseases

1One Sentence SummaryA novel topological machine learning approach applied to single-nucleus RNA sequencing from human retinas with age-related macular degeneration identifies interacting disease phase-specific glial activation states shared with Alzheimers disease and multiple sclerosis. 2 AbstractNeurodegeneration occurs in a wide range of diseases, including age-related macular degeneration (AMD), Alzheimers disease (AD), and multiple sclerosis (MS), each with distinct inciting events. To determine whether glial transcriptional states are shared across phases of degeneration, we sequenced 50,498 nuclei from the retinas of seven AMD patients and six healthy controls, generating the first single-cell transcriptomic atlas of AMD. We identified groupings of cells implicated in disease pathogenesis by applying a novel topologically-inspired machine learning approach called diffusion condensation. By calculating diffusion homology features and performing persistence analysis, diffusion condensation identified activated glial states enriched in the early phases of AMD, AD, and MS as well as an AMD-specific proangiogenic astrocyte state promoting pathogenic neovascularization in advanced AMD. Finally, by mapping the expression of disease-associated genes to glial states, we identified key signaling interactions creating hypotheses for therapeutic intervention. Our topological analysis identified an integrated disease-phase specific glial landscape that is shared across neurodegenerative conditions affecting the central nervous system.

neuroscience↗

bioRxiv2021

An epigenetic switch regulates the ontogeny of AXL positive/EGFR-TKI resistant cells by modulating miR-335 expression

Lung cancer remains the leading cause of cancer-related mortality worldwide, despite current advancements in research and therapeutics. Many patients diagnosed with lung cancer will develop resistance to chemotherapeutic agents. In the context of non-small cell lung cancers (NSCLC) harboring EGFR oncogenic mutations, augmented levels of AXL and GAS6 have been found to drive Erlotinib resistance in certain tumors with mesenchymal-like features. By studying the ontogeny of AXL-positive cells, we have identified a novel non-genetic mechanism of drug resistance based on cell-state transition. We demonstrate that AXL-positive cells are already present as a sub-population of cancer cells in Erlotinib-naive tumors and tumor-derived cell lines, and that the expression of AXL is regulated through a stochastic mechanism centered on the epigenetic regulation of miR-335. The existence of a cell-intrinsic program through which AXL-positive/Erlotinib-resistant cells emerge infers the need of treating tumors harboring EGFR-oncogenic mutations upfront with combinatorial treatments targeting both AXL-negative and AXL-positive cancer cells.

cancer biology↗

bioRxiv2021

Pan-genome Analysis in Sorghum Highlights the Extent of Genomic Variation and Sugarcane Aphid Resistance Genes

Sorghum bicolor, one of the most important grass crops around the world, harbors a high degree of genetic diversity. We constructed chromosome-level genome assemblies for two important sorghum inbred lines, Tx2783 and RTx436. The final high-quality reference assemblies consist of 19 and 18 scaffolds, respectively, with contig N50 values of 25.6 and 20.3 Mb. Genes were annotated using evidence-based and de novo gene predictors, and RAMPAGE data demonstrate that transcription start sites were effectively captured. Together with other public sorghum genomes, BTx623, RTx430, and Rio, extensive structural variations (SVs) of various sizes were characterized using Tx2783 as a reference. Genome-wide scanning for disease resistance (R) genes revealed high levels of diversity among these five sorghum accessions. To characterize sugarcane aphid (SCA) resistance in Tx2783, we mapped the resistance region on chromosome 6 using a recombinant inbred line (RIL) population and found a SV of 191 kb containing a cluster of R genes in Tx2783. Using Tx2783 as a backbone, along with the SVs, we constructed a pan-genome to support alignment of resequencing data from 62 sorghum accessions, and then identified core and dispensable genes using this population. This study provides the first overview of the extent of genomic structural variations and R genes in the sorghum population, and reveals potential targets for breeding of SCA resistance.

genomics↗

bioRxiv2020

C1q/CTRP1 exerts neuroprotective effects in TBI rats by regulating inflammation and autophagy

ObjectiveC1q/CTRP1 is a newly discovered adiponectin protein, which is highly expressed in adipose and heart tissues. Recent studies have revealed that C1q/CTRP1 can regulate metabolism and inhibit inflammation. CTRP1 is also expressed in brain tissues and vascular cells of human and rat, and research on cerebral hemorrhage and cerebral ischemia-reperfusion injury demonstrates that the CTRP family can attenuate secondary brain injury and exert neuroprotective effects. Thus, this study was designed to explore the role of CTRP1 in traumatic brain injury (TBI) and the underlying mechanism. Main methodsRats were assigned into rCTRP1 group, vehicle group, and sham group. Modified Feeneys method was used to establish a closed traumatic brain injury model. Morris water maze was used for directional navigation, reverse searching and space exploration tests in rats. In addition, Golgi-Cox staining was utilized to visualize neurons, dendrites and dendritic spines. ELISA was conducted to detect the levels of inflammatory factors (IL-6 and TNF-). Finally, Western blot was adopted to detect the relative expression of p-mTOR and autophagy-related proteins (Beclin-1 and LC3-II). ResultsCTRP1 improved the behavioral and histopathological outcomes, inhibited the inflammatory response, activated mTOR and decreased autophagy-associated protein synthesis in TBI rats. ConclusionCTRP1 exerts neuroprotective effects in TBI rats by regulating inflammation and autophagy and has potential therapeutic properties after TBI.

pathology↗

bioRxiv2020

Single point mutations can potentially enhance infectivity of SARS-CoV-2 revealed by in silico affinity maturation and SPR assay

The RBD (receptor binding domain) of the SARS-CoV-2 virus S (spike) protein mediates the viral cell attachment and serves as a promising target for therapeutics development. Mutations on the S-RBD may alter its affinity to cell receptor and affect the potency of vaccines and antibodies. Here we used an in-silico approach to predict how mutations on RBD affect its binding affinity to hACE2 (human angiotensin-converting enzyme2). The effect of all single point mutations on the interface was predicted. SPR assay result shows that 6 out of 9 selected mutations can strengthen binding affinity. Our prediction has reasonable agreement with the previous deep mutational scan results and recently reported mutants. Our work demonstrated in silico method as a powerful tool to forecast more powerful virus mutants, which will significantly benefit for the development of broadly neutralizing vaccine and antibody.

bioinformatics↗

bioRxiv2020

Genome-wide reversal of glial and neurovascular cell transcriptomic aging signatures by GLP-1R agonism

Pharmacological reversal of brain aging is a long-sought yet challenging strategy for the prevention and treatment of age-related neurodegeneration, due to the diverse cell types and complex cellular pathways impacted by the aging process. Here, we report the genome-wide reversal of transcriptomic aging signatures in multiple major brain cell types, including glial and mural cells, by glucagon-like peptide-1 receptor (GLP-1R) agonist (GLP-1RA) treatment. The age-related expression changes reversed by GLP-1RA encompass both shared and cell type-specific functional pathways that are implicated in aging and neurodegeneration. Concomitantly, Alzheimers disease (AD)-associated transcriptomic signature in microglia that arises from aging is reduced. These results show the feasibility of reversing brain aging by pharmacological means, provide mechanistic insights into the neurological benefits of GLP-1RAs in diabetic patients, and imply that GLP-1R agonism may be a generally applicable pharmacological intervention for patients at risk of age-related neurodegeneration.

neuroscience↗

bioRxiv2020

A Systematic and Consistent Assay for High-throughput Characterization of Stalk Quality in Sugarcane by Near-infrared Spectroscopy

Stalk quality improvement is deemed a promising strategy to enhance sugarcane production. However, the lack of efficient approaches for a systematic evaluation of sugarcane germplasm limited stalk quality improvement. In this study, 628 sugarcane samples were employed to take a high-throughput assay for determining the sugarcane stalk quality. Based on the high-performance anion chromatography method, large sugarcane stalk quality variations were detected in biomass composition and the corresponding fundamental ratio values. Online and offline Near-infrared Spectroscopy (NIRS) modeling strategies were applied for multiple purpose calibration. Consequently, 25 equations were generated with the excellent determination coefficient (R2) and ratio performance deviation (RPD) values. Notably, for some observations, RPD values as high as 6.3 were observed that indicated their exceptional performance potential and prediction capacity. Hence, this study provides a feasible way for high-throughput assessment of stalk quality, permitting large-scale screening of optimal sugarcane germplasm.

plant biology↗

bioRxiv2020

Evaluation of the effect of life extension of DHEA extract from sweet potato on Caenorhabditis elegans

Products from natural sources are being used from centuries. This study investigates the potential antiaging activity of DHEA extracts from sweet potato. DHEA was extracted with the assistance of acid hydrolysis-ultrasonic, and the Caenorhabditis elegans model was used to investigate the antiaging activity. The results from the current study articulated that DHEA from sweet potato in 50 mol / L effectively prolonged the life-span of C. elegans by 13.60%, but the effect was not concentration-dependent. Besides, DHEA had no effect on the growth of E. coli OP50 and the nematode pharyngeal pump rate, indicating that DHEA didnt delay the aging of the nematode through calorie restriction. Further experiments demonstrated that DHEA would slow the growth of nematode body size, reduce the accumulation of ROS and lipofuscin of C. elegans. The expression and migration of daf-16 into the nucleus of nematode were significantly improved as well. The antiaging effect of DHEA on C. elegans may be achieved by strengthening the nematodes ability to resist oxidative stress and promoting nuclear expression of the daf-16 gene. Summary StatementThis study proved that DHEA from sweet potato can extended lifespan of Caenorhabditis elegans induced by strengthening the antioxidant capacity and promoting the nuclear expression of daf-16

biochemistry↗

bioRxiv2020

Multi-Level Attention Graph Neural Network for Clinically Interpretable Pathway-Level Biomarkers Discovery

Precision medicine, regarded as the future of healthcare, is gaining increasing attention these years. As an essential part of precision medicine, clinical omics have been successfully applied in disease diagnosis and prognosis using machine learning techniques. However, existing methods mainly make predictions based on gene-level individual features or their random combinations, none of the previous work has considered the activation of signaling pathways. Therefore, the model interpretability and accuracy are limited, and reasonable signaling pathways are yet to be discovered. In this paper, we propose a novel multi-level attention graph neural network (MLA-GNN), which applies weighted correlation network analysis (WGCNA) to format the omic data of each patient into graph-structured data, and then constructs multi-level graph features, and fuses them through a well-designed multi-level graph feature fully fusion (MGFFF) module to conduct multi-task prediction. Moreover, a novel full-gradient graph saliency mechanism is developed to make the MLA-GNN interpretable. MLA-GNN achieves state-of-the-art performance on transcriptomic data from TCGA-LGG/TCGA-GBM and proteomic data from COVID-19/non-COVID-19 patient sera. More importantly, the proposed model's decision can be interpreted in the signaling pathway level and is consistent with the clinical understanding.

bioinformatics↗

bioRxiv2020

Manifold learning analysis reveals the functionalgenomics at the cell-type level for neuronalelectrophysiology in the mouse brain

Recent single-cell multi-modal data reveal multi-scale characteristics of single cells, such as transcriptomics, morphology, and electrophysiology. However, our understanding of functional genomics and gene regulation leading to various cellular characteristics remains elusive. To address this, we applied multiple machine learning methods to align gene expression and electrophysiological data of single neuronal cells in the mouse brain. We found that nonlinear manifold learning outperforms other methods. After manifold alignment, the cell clusters highly correspond to transcriptomic and morphological cell-types, suggesting a strong nonlinear relationship between gene expression and electrophysiology at the cell-type level. The aligned cells form developmental trajectories and show continuous changes of electrophysiological features, implying the underlying developmental process. We also found that the manifold-aligned cell clusters differentially expressed genes can predict many electrophysiological features. Functional enrichment and gene regulatory network analyses for those cell clusters revealed potential genome functions and molecular mechanisms from gene expression to neuronal electrophysiology.

bioinformatics↗

bioRxiv2020

A Neutralizing Antibody-Conjugated Photothermal Nanoparticle Captures and Inactivates SARS-CoV-2

The outbreak of 2019 coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has resulted in a global pandemic. Despite intensive research including several clinical trials, currently there are no completely safe or effective therapeutics to cure the disease. Here we report a strategy incorporating neutralizing antibodies conjugated on the surface of a photothermal nanoparticle to actively capture and inactivate SARS-CoV-2. The photothermal nanoparticle is comprised of a semiconducting polymer core and a biocompatible polyethylene glycol surface decorated with neutralizing antibodies. Such nanoparticles displayed efficient capture of SARS-CoV-2 pseudoviruses, excellent photothermal effect, and complete inhibition of viral entry into ACE2-expressing host cells via simultaneous blocking and inactivating of the virus. This photothermal nanoparticle is a flexible platform that can be readily adapted to other SARS-CoV-2 antibodies and extended to novel therapeutic proteins, thus providing a broad range of protection against multiple strains of SARS-CoV-2. O_FIG O_LINKSMALLFIG WIDTH=192 HEIGHT=200 SRC="FIGDIR/small/404624v1_ufig1.gif" ALT="Figure 1"> View larger version (66K): org.highwire.dtl.DTLVardef@44a5a8org.highwire.dtl.DTLVardef@d7bcd5org.highwire.dtl.DTLVardef@1ae6e70org.highwire.dtl.DTLVardef@d4a4f5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2020

Response of methanogen community to elevation of cathode potentials in the presence of magnetite

Electromethanogenesis refers to the process where methanogens utilize electrons derived from cathodes for the reduction of CO2 to CH4. Setting of low cathode potentials is essential for this process. In this study, we test if magnetite, an iron oxide mineral widespread in environment, can facilitate the adaption of methanogen community to the elevation of cathode potentials in electrochemical reactors. Two-chamber electrochemical reactors were constructed with inoculants obtained from a paddy field soil. We elevated cathode potentials stepwise from the initial -0.6 V vs standard hydrogen electrode (SHE) to -0.5 V and then to -0.4 V over the 120 days acclimation. Only weak current consumption and CH4 production were observed in the reactors without magnetite. But biocathodes were firmly developed and significant current consumption and CH4 production were recorded in the magnetite reactors. The robustness of electro-activity in the magnetite reactors was not affected with the elevation of cathode potentials from -0.6 V to -0.4 V. But, the current consumption and CH4 production were virtually halted in the reactors without magnetite when cathode potential was elevated to -0.4 V. Methanogens related to Methanospirillum were enriched on cathode surface of the magnetite reactors at -0.4 V, while Methanosarcina relatively dominated in the reactors without magnetite. Methanobacterium also increased in the magnetite reactors but stayed off electrodes in the culture medium at -0.4 V. Apparently, magnetite greatly facilitates the development of biocathodes, and it appears that with the aid of magnetite Methanospirillum spp. can adapt to high cathode potentials performing the efficient electromethanogenesis. IMPORTANCEConverting CO2 to CH4 through bioelectrochemistry is a promising approach for development of green energy biotechnology. This process however requires setting the low cathode potentials, which takes cost. In this study, we test if magnetite, a conductive iron mineral, can facilitate the adaption of methanogens to the elevation of cathode potentials. In the two-chamber reactors constructed using inoculants obtained from a paddy field soil, biocathodes were firmly developed in the presence of magnetite, whereas only weak electro-activity was observed in the reactors without magnetite. The elevation of cathode potentials did not affect the robustness of electro-activity in the magnetite reactors over the 120 days acclimation. Methanospirillum was identified as the key methanogens associated with cathode surface during the operation at relatively high potentials. The findings reported in this study shed a new light on the adaption of methanogen community to the elevated cathode potentials in the presence of magnetite.

bioengineering↗