Biology subjects

Fu, L.

Publications and source records attributed to Fu, L..

At least 73 records · Page 4Linked to original sources

bioRxiv2022

Highly specialized carbohydrate metabolism capability in Bifidobacterium strain associated with intestinal barrier maturation in early preterm infants

"Leaky gut", or high intestinal barrier permeability, is common in preterm newborns. The role of microbiota in this process remains largely uncharacterized. We employed both short- and long-read sequencing of the 16S rRNA gene and metagenomes to characterize the intestinal microbiome of a longitudinal cohort of 113 preterm infants born between 240/7-326/7 weeks of gestation. Enabled by enhanced taxonomic resolution, we found significantly increased abundance of Bifidobacterium breve and a diet rich in mothers breastmilk to be associated with intestinal barrier maturation during the first week of life. We combined these factors using genome- resolved metagenomics and identified a highly specialized genetic capability of the Bifidobacterium strains to assimilate human milk oligosaccharides and host-derived glycoproteins. Our study proposed mechanistic roles of breastmilk feeding and intestinal microbial colonization in postnatal intestinal barrier maturation; these observations are critical towards advancing therapeutics to prevent and treat hyperpermeable gut- associated conditions, including necrotizing enterocolitis. IMPORTANCEDespite improvements in neonatal intensive care, necrotizing enterocolitis (NEC) remains a leading cause of morbidity and mortality. "Leaky gut", or intestinal barrier immaturity with elevated intestinal permeability, is the proximate cause of susceptibility to NEC. Early detection and intervention to prevent leaky gut in "at-risk" preterm neonates is critical to lower the risk for potentially life-threatening complications like NEC. However, the complex interactions between the developing gut microbial community, nutrition, and intestinal barrier function, remain largely uncharacterized. In this study, we revealed the critical role of sufficient breastmilk feeding volume and specialized carbohydrate metabolism capability of Bifidobacterium in coordinated postnatal improvement of intestinal barrier. Determining the clinical and microbial biomarkers that drive the intestinal developmental disparity will inform early detection and novel therapeutic strategies to promote appropriate intestinal barrier maturation, prevent NEC and other adverse health conditions in preterm infants.

microbiology↗

bioRxiv2022

Characterization of a miniaturized ultrasound transducer customized for oral health applications

ObjectiveTo customize a miniaturized ultrasound transducer to access full-mouth B-mode, color Doppler and spectral Doppler imaging for monitoring oral health. MethodsA customized periodontal ultrasound transducer SS-19-128 (19 MHz, 128 channels) with 1.8 cm wide and 1 cm thick was developed and connected to a data acquisition (DAQ) system. B-mode, color Doppler, and spectral Doppler data could all be collected with SS-19-128. The imaging resolution and penetration capacity of SS-19-128 were characterized on phantoms. Five human subjects were recruited to demonstrate B-mode and Doppler imaging by SS-19-128. Gingival thickness was measured on 11 swine teeth by SS-19-128 for comparison to conventional transgingival probing via Bland-Altman analysis and Pearson correlation. ResultsThe axial and lateral spatial resolution at 5.5 mm depth is 102.1 m and 142.9 m, respectively. The penetration depth in a tissue-mimicking phantom is over 30 mm. In vivo B-mode imaging of all 28 teeth was demonstrated on one human subject, and imaging of tooth #18 was accessed on five human subjects. Gingival thickness measurement compared with transgingival probing showed a bias of -0.015 mm and SD of 0.031 mm, and a r = 0.9235 (P<0.0001) correlation. In vivo color and spectral Doppler imaging of the supraperiosteal artery in human gingiva was performed to generate hemodynamic information. ConclusionsThe small size of SS-19-128 offers important advantages over existing technology--more specifically, whole-mouth scanning/charting reminiscent of radiography. This is nearly a two-fold increase in the number of teeth that can be assessed versus existing transducers.

bioengineering↗

bioRxiv2022

Full-mouth photoacoustic/ultrasound imaging of the periodontal pocket with a compact intraoral transducer

Periodontitis is a public issue and imaging periodontal pocket is important to evaluate periodontitis. Regular linear transducers have limitations in imaging the posterior teeth due to their geometry restrictions. Here we characterized a transducer that can image the entire human mouth including assessment of periodontal pockets via a combination of photoacoustic and ultrasound imaging. Unlike conventional transducer design, this device has a toothbrush-shaped form factor with a side-view transducer to image molars (total size: 1 x 1.9 cm). A laser diode was integrated as the light source to reduce the cost and size and facilitates clinical transition. The in vivo imaging of a molar of a periodontal patient demonstrated that the transducer could image in the posterior area of gum in vivo; the value determined by imaging was within 7% of the value measured clinically.

bioengineering↗

bioRxiv2022

Mucociliary Transport Deficiency and Disease Progression in Syrian Hamsters with SARS-CoV-2 Infection

Substantial clinical evidence supports the notion that ciliary function in the airways plays an important role in COVID-19 pathogenesis. Although ciliary damage has been observed in both in vitro and in vivo models, consequent impaired mucociliary transport (MCT) remains unknown for the intact MCT apparatus from an in vivo model of disease. Using golden Syrian hamsters, a common animal model that recapitulates human COVID-19, we quantitatively followed the time course of physiological, virological, and pathological changes upon SARS-CoV-2 infection, as well as the deficiency of the MCT apparatus using micro-optical coherence tomography, a novel method to visualize and simultaneously quantitate multiple aspects of the functional microanatomy of intact airways. Corresponding to progressive weight loss up to 7 days post-infection (dpi), viral detection and histopathological analysis in both the trachea and lung revealed steadily descending infection from the upper airways, as the main target of viral invasion, to lower airways and parenchymal lung, which are likely injured through indirect mechanisms. SARS-CoV-2 infection caused a 67% decrease in MCT rate as early as 2 dpi, largely due to diminished motile ciliation coverage, but not airway surface liquid depth, periciliary liquid depth, or cilia beat frequency of residual motile cilia. Further analysis indicated that the fewer motile cilia combined with abnormal ciliary motion of residual cilia contributed to the delayed MCT. The time course of physiological, virological, and pathological progression suggest that functional deficits of the MCT apparatus predispose to COVID-19 pathogenesis by extending viral retention and may be a risk factor for secondary infection. As a consequence, therapies directed towards the MCT apparatus deserve further investigation as a treatment modality.

microbiology↗

bioRxiv2021

pChem: a modification-centric assessment tool for the performance of chemoproteomic probes

Chemoproteomics has emerged as a key technology to expand the functional space in complex proteomes for probing fundamental biology and for discovering new small molecule-based therapies. Here we report a modification-centric computational tool termed pChem to provide a streamlined pipeline for unbiased performance assessment of chemoproteomic probes. The pipeline starts with an experimental setting for isotopically coding probe-derived modifications (PDMs) that can be automatically recognized by pChem, with masses accurately calculated and sites precisely localized. Further, pChem exports on-demand reports by scoring the profiling efficiency, modification-homogeneity and proteome-wide residue selectivity of a tested probe. The performance and robustness of pChem were benchmarked by applying it to eighteen bioorthogonal probes. Of note, the analyses reveal that the formation of unexpected PDMs can be driven by endogenous reactive metabolites (e.g., bioactive aldehydes and glutathione). Together, pChem is a powerful and user-friendly tool that aims to facilitate the development of probes for the ever-growing field of chemoproteomics.

bioinformatics↗

bioRxiv2021

Rapid visual CRISPR assay: a naked-eye colorimetric detection method for nucleic acids based on CRISPR/Cas12a and convolutional neural network

Rapid diagnosis based on naked-eye colorimetric detection remains challenging, but it could build new capacities for molecular point-of-care testing (POCT). In this study, we evaluated the performance of 16 types of single-stranded DNA-fluorophore-quencher (ssDNA-FQ) reporters for use with CRISPR/Cas12a based visual colorimetric assays. Among them, 9 ssDNA-FQ reporters were found to be suitable for direct visual colorimetric detection, with especially very strong performance using ROX-labeled reporters. We optimized the reaction concentrations of these ssDNA-FQ reporters for naked-eye read-out of assay results (no transducing component required for visualization). Subsequently, we developed a convolutional neural network algorithm standardize and to automate the analytical colorimetric assessment of images and integrated this into the MagicEye mobile phone software. A field-deployable assay platform named RApid VIsual CRISPR (RAVI-CRISPR) based on a ROX-labeled reporter with isothermal amplification and CRISPR/Cas12a targeting was established. We deployed RAVI-CRISPR in a single tube towards an instrument-less colorimetric POCT format that requires only a portable rechargeable hand warmer for incubation. The RAVI-CRISPR was successfully used for the single-copy detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and African swine fever virus (ASFV). Our study demonstrates this novel RAVI-CRISPR system for distinguishing different pathogenic nucleic acid targets with high specificity and sensitivity as the simplest-to-date platform for rapid pen-side testing.

molecular biology↗

bioRxiv2021

Thiol-based mucolytics exhibit antiviral activity against SARS-CoV-2 through allosteric disulfide disruption in the spike glycoprotein

Small molecule therapeutics targeting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have lagged far behind the development of vaccines in the fight to control the COVID-19 pandemic. Here, we show that thiol-based mucolytic agents, P2119 and P2165, potently inhibit infection by human coronaviruses, including SARS-CoV-2, and decrease the binding of spike glycoprotein to its receptor, angiotensin-converting enzyme 2 (ACE2). Proteomics and reactive cysteine profiling link the antiviral activity of repurposed mucolytic agents to the reduction of key disulfides, specifically, by disruption of the Cys379-Cys432 and Cys391-Cys525 pairs distal to the receptor binding motif (RBM) in the receptor binding domain (RBD) of the spike glycoprotein. Computational analyses provide insight into conformation changes that occur when these disulfides break or form, consistent with an allosteric role, and indicate that P2119/P2165 target a conserved hydrophobic binding pocket in the RBD with the benzyl thiol warhead pointed directly towards Cys432. These collective findings establish the vulnerability of human coronaviruses to repurposed thiol-based mucolytics and lay the groundwork for developing these compounds as a potential treatment, preventative and/or adjuvant against infection.

microbiology↗

bioRxiv2021

Insight into the ecology of vaginal bacteria through integrative analyses of metagenomic and metatranscriptomic data

Vaginal bacterial communities dominated by Lactobacillus species are associated with a reduced risk to various adverse health outcomes. However, somewhat unexpectedly many healthy women have microbiota that are not dominated by lactobacilli. To determine the factors that drive vaginal community composition we characterized the genetic composition and transcriptional activities of vaginal microbiota in healthy women. We demonstrated that the abundance of a species is not always indicative of its transcriptional activity and that impending changes in community composition can be predicted from metatranscriptomic data. Functional comparisons highlight differences in the metabolic activities of these communities, notably in their degradation of host-produced mucin but not glycogen. Degradation of mucin by communities not dominated by Lactobacillus may play a role in their association with adverse health outcomes. Finally, we show that the transcriptional activities of L. crispatus, L. iners, and G. vaginalis vary with the taxonomic composition of the communities in which they reside. Notably, L. iners and G. vaginalis both demonstrated lower expression of their cholesterol-dependent cytolysins when co-resident with Lactobacillus spp. and higher expression when co-resident with other facultative and obligate anaerobes. The pathogenic potential of these species may depend on the communities in which they reside and thus could be modulated by interventional strategies. Our results provide insight to the functional ecology of vaginal microbiota and reveal strategies for management of these ecosystems.

microbiology↗

bioRxiv2021

Converting Muscle-mimetic Biomaterials to Cartilage-like Materials

Load-bearing tissues, such as muscle and cartilage, exhibit mechanical properties that often combine high elasticity, high toughness and fast recovery, despite their different stiffness ([~]100 kPa for muscles and one to several MPa for cartilage).1-7 The advance in protein engineering and protein mechanics has made it possible to engineer protein-based biomaterials to mimic soft load-bearing tissues, such as muscles.8-10 However, it is challenging to engineer protein biomaterials to achieve the mechanical properties exhibited by stiff tissues, such as articular cartilage,6,11 or to develop stiff synthetic extracellular matrices for cartilage stem/progenitor cell differentiation12. By employing physical entanglements13 of protein chains and force-induced protein unfolding,14,15 here we report the engineering of a highly tough and stiff protein hydrogel to mimic articular cartilage. By crosslinking an engineered artificial elastomeric protein from its unfolded state, we introduced chain entanglement into the hydrogel network. Upon renaturation, the entangled protein chain network and forced protein unfolding entailed this single network protein hydrogel with superb mechanical properties in both tensile and compression tests, showing a Youngs modulus of [~]0.7 MPa and toughness of 250 kJ/m3 in tensile testing; and [~]1.7 MPa in compressive modulus and toughness of 3.2 MJ/m3. The energy dissipation in both tensile and compression tests is reversible and the hydrogel can recovery its mechanical properties rapidly. Moreover, this hydrogel can withstand a compression stress of >60 MPa without failure, amongst the highest compressive strength achieved by a hydrogel. These properties are comparable to those of articular cartilage, making this protein hydrogel a novel cartilage-mimetic biomaterial. Our study opened up a new potential avenue towards engineering protein hydrogel-based substitute for articular cartilage, and may also help develop protein biomaterials with superb mechanical properties for applications in soft actuators and robotics.

bioengineering↗

bioRxiv2021

Bromodomain and Extraterminal Protein Inhibitor, Apabetalone (RVX-208), Reduces ACE2 Expression and Attenuates SARS-CoV-2 Infection in vitro

Effective therapeutics are urgently needed to counter infection and improve outcomes for patients suffering from COVID-19 and to combat this pandemic. Manipulation of epigenetic machinery to influence viral infectivity of host cells is a relatively unexplored area. The bromodomain and extraterminal (BET) family of epigenetic readers have been reported to modulate SARS-CoV-2 infection. Herein, we demonstrate apabetalone, the most clinical advanced BET inhibitor, downregulates expression of cell surface receptors involved in SARS-CoV-2 entry, including angiotensin-converting enzyme 2 (ACE2) and dipeptidyl-peptidase 4 (DPP4 or CD26) in SARS-CoV-2 permissive cells. Moreover, we show that apabetalone inhibits SARS-CoV-2 infection in vitro to levels comparable to antiviral agents. Taken together, our study supports further evaluation of apabetalone to treat COVID-19, either alone or in combination with emerging therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=192 SRC="FIGDIR/small/432949v1_ufig1.gif" ALT="Figure 1"> View larger version (54K): org.highwire.dtl.DTLVardef@127e6c4org.highwire.dtl.DTLVardef@9f6d3aorg.highwire.dtl.DTLVardef@bbfe3borg.highwire.dtl.DTLVardef@2ffad8_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2021

SAILER: Scalable and Accurate Invariant Representation Learning for Single-Cell ATAC-Seq Processing and Integration

MotivationSingle-cell sequencing assay for transposase-accessible chromatin (scATAC-seq) provides new opportunities to dissect epigenomic heterogeneity and elucidate transcriptional regulatory mechanisms. However, computational modelling of scATAC-seq data is challenging due to its high dimension, extreme sparsity, complex dependencies, and high sensitivity to confounding factors from various sources. ResultsHere we propose a new deep generative model framework, named SAILER, for analysing scATAC-seq data. SAILER aims to learn a low-dimensional nonlinear latent representation of each cell that defines its intrinsic chromatin state, invariant to extrinsic confounding factors like read depth and batch effects. SAILER adopts the conventional encoder-decoder framework to learn the latent representation but imposes additional constraints to ensure the independence of the learned representations from the confounding factors. Experimental results on both simulated and real scATAC-seq datasets demonstrate that SAILER learns better and biologically more meaningful representations of cells than other methods. Its noise-free cell embeddings bring in significant benefits in downstream analyses: Clustering and imputation based on SAILER result in 6.9% and 18.5% improvements over existing methods, respectively. Moreover, because no matrix factorization is involved, SAILER can easily scale to process millions of cells. We implemented SAILER into a software package, freely available to all for large-scale scATAC-seq data analysis. AvailabilityThe software is publicly available at https://github.com/uci-cbcl/SAILER Contactjingz31@uci.edu and xhx@uci.edu

bioinformatics↗

bioRxiv2020

DOT1L Complex Regulates Transcriptional Initiation 1 in Human Cells

DOT1L, the only H3K79 methyltransferase in human cells and a homolog of the yeast Dot1, normally forms a complex with AF10, AF17 and ENL/AF9, is dysregulated in most of the cases of mixed lineage leukemia (MLL) and is believed to regulate transcriptional elongation without much evidence. Here we show that the depletion of DOT1L reduced the global occupancy without affecting the traveling ratio or the elongation rate of Pol II, suggesting it not a major elongation factor. An examination of general transcription factors (GTFs) binding revealed globally reduced TBP and TFIIA occupancies near promoters after DOT1L loss, pointing to a role in transcriptional initiation. Proteomic studies uncovered that DOT1L regulates transcriptional initiation likely by facilitating the recruitment of TFIID. Moreover, ENL, a DOT1L complex subunit with a known role in DOT1L recruitment, also regulates transcriptional initiation. Furthermore, DOT1L stimulates H2B monoubiquitination by limiting the recruitment of human SAGA complex, and the connection between Dot1/DOT1L and SAGA complex is conserved between yeast and human. These results advanced current understanding of roles of DOT1L complex in transcriptional regulation and MLL.

molecular biology↗

bioRxiv2020

New insight into bacterial iron competition: A-to-I editing in ferric enterobactin uptake

Adenosine-to-inosine (A-to-I) RNA editing, which is catalyzed by the adenosine deaminase RNA-specific family of enzymes, is a frequent post-transcriptional modification in metazoans. Research on A-to-I editing in bacteria is limited, and the importance is underestimated. In this study, we show that bacteria may use A-to-I editing as an alternative strategy to promote uptake of metabolic iron. The T408A editing event of xfeA in Xanthomonas oryzae pv. oryzicola (Xoc) senses extracytoplasmic iron and changes the hydrogen bonding network of ligand channel domains. The frequency of A-to-I RNA editing during iron-deficient conditions increased by 76.87%, which facilitated the passage of iron through the XfeA outer membrane channel. When bacteria were subjected to high iron concentrations, the percentage of A-to-I editing in xfeA decreased, which reduced iron transport via XfeA. Furthermore, A-to-I RNA editing increased expression of multiple genes in the chemotaxis pathway, including methyl-accepting chemotaxis proteins (MCPs) that sense concentrations of exogenous ferric enterobactin (Fe-Ent) at the cytoplasmic membrane. A-to-I RNA editing helps Xoc move towards an iron-rich environment and supports our contention that editing in xfeA facilitates entry of a ferric siderophore. Overall, our results reveal a new signaling mechanism that bacteria use to facilitate iron uptake and improve their competitiveness.

microbiology↗

bioRxiv2020

BMSCs differentiated into neurons, astrocytes and oligodendrocytesalleviatedthe inflammation and demyelination of EAE mice models

Multiple sclerosis (MS) is a complex, progressive neuroinflammatory disease associated with autoimmunity. Currently, effective therapeutic strategy was poorly found in MS. Experimental autoimmune encephalomyelitis (EAE) is widely used to study the pathogenesis of MS. Previous studies have shown that bone marrow mesenchymal stem Cells (BMSCs) transplantation could treat EAE animal models, but the mechanism was divergent. Here, we systematically evaluated whether BMSCs can differentiate into neurons, astrocytes and oligodendrocytes to alleviate the symptoms of EAE mice. We used Immunofluorescence staining to detect MAP-2 neurons marker, GFAP astrocytes marker, and MBP oligodendrocytes marker expression to evaluate whether BMSCs can differentiate. The effect of BMSCs transplantation on inflammatory cell invasion and demyelination in EAE mice were detected by Hematoxylin-Eosin (H&E) and Luxol Fast Blue (LFB) staining. Inflammatory factors expression was detected by ELISA and RT-qPCR. Our results showed that BMSCs could be induced to differentiate into neuron cells, astrocytes and oligodendrocyte in vivo and in vitro. In addition, BMSCs transplant improved the survival rate and weight, and reduced neurological function scores and disease incidence of EAE mice. Moreover, BMSCs transplant alleviated the inflammation and demyelination of EAE mice. Finally, we found that BMSCs transplantation down-regulated the expression levels of pro-inflammatory factors TNF-, IL-1{beta} and IFN-{gamma}, and up-regulated the expression levels of anti-inflammatory factors IL-10 and TGF-{beta}. In conclusion, this study found that BMSCs could alleviate the inflammatory response and demyelination in EAE mice, which may be achieved by the differentiation of BMSCs into neurons, astrocytes and oligodendrocytes in EAE mice.

neuroscience↗

bioRxiv2020

Circular RNA as a potential biomarker for forensic age prediction using multiple machine learning models: A preliminary study

In forensic science, accurate estimation of the age of a victim or suspect can facilitate the investigators to narrow a search and aid in solving a crime. Aging is a complex process associated with various molecular regulation on DNA or RNA levels. Recent studies have shown that circular RNAs (circRNAs) upregulate globally during aging in multiple organisms such as mice and elegans because of their ability to resist degradation by exoribonucleases. In the current study, we attempted to investigate circRNAs potential capability of age prediction. Here, we identified more than 40,000 circRNAs in the blood of thirteen Chinese unrelated healthy individuals with ages of 20-62 years according to their circRNA-seq profiles. Three methods were applied to select age-related circRNAs candidates including false discovery rate, lasso regression, and support vector machine. The analysis uncovered a strong bias for circRNA upregulation during aging in human blood. A total of 28 circRNAs were chosen for further validation in 50 healthy unrelated subjects aged between 19 and 72 years by RT-qPCR and finally, 7 age-related circRNAs were chosen for final age prediction models. Several different algorithms including multivariate linear regression (MLR), regression tree, bagging regression, random forest regression (RFR), and support vector regression (SVR) were compared based on root mean square error (RMSE) and mean average error (MAE) values. Among five modeling methods, random forest regression (RFR) performed better than the others with an RMSE value of 5.072 years and an MAE value of 4.065 years (R2 = 0.902). In this preliminary study, we firstly used circRNAs as additional novel age-related biomarkers for developing forensic age estimation models. We propose that the use of circRNAs to obtain additional clues for forensic investigations and serve as aging indicators for age prediction would become a promising field of interest. Author summaryIn forensic investigations, estimation of the age of biological evidence recovered from crime scenes can provide additional information such as chronological age or the appearance of a culprit, which could give valuable investigative leads especially when there is no eyewitness available. Hence, generating an accurate model for age prediction using body fluids such as blood commonly seen at a crime scene can be of vital importance. Various molecular changes on DNA or RNA levels were discovered that they upregulated or downregulated during a persons lifetime. Although some biomarkers have been proved to be associated with aging and used to predict age, several disadvantages such as low sensitivity, prediction accuracy, instability and susceptibility of diseases or immune states, thus limiting their applicability in the field of age estimation. Here, we utilized a novel biomarker namely circular RNA (circRNA) to generate highly accurate age prediction models. We propose that circRNA is more suitable for forensic degradation samples because of its unique molecular structure. This preliminary research offers a new thought for exploring potential biomarker for age prediction.

genetics↗

bioRxiv2020

Structural basis of SARS-CoV-2 polymerase inhibition by Favipiravir

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has developed into an unprecedented global pandemic. Nucleoside analogues, such as Remdesivir and Favipiravir, can serve as the first-line broad-spectrum antiviral drugs against the newly emerging viral diseases. Recent clinical trials of these two drugs for SARS-CoV-2 treatment revealed antiviral efficacies as well as side effects with different extents1-4. As a pyrazine derivative, Favipiravir could be incorporated into the viral RNA products by mimicking both adenine and guanine nucleotides, which may further lead to mutations in progeny RNA copies due to the non-conserved base-pairing capacity5. Here, we determined the cryo-EM structure of Favipiravir bound to the replicating polymerase complex of SARS-CoV-2 in the pre-catalytic state. This structure provides a missing snapshot for visualizing the catalysis dynamics of coronavirus polymerase, and reveals an unexpected base-pairing pattern between Favipiravir and pyrimidine residues which may explain its capacity for mimicking both adenine and guanine nucleotides. These findings shed lights on the mechanism of coronavirus polymerase catalysis and provide a rational basis for developing antiviral drugs to combat the SARS-CoV-2 pandemic.

microbiology↗

bioRxiv2020

The role of cation diffusion facilitator CDF-1 in lipid metabolism in Caenorhabditis elegans

Zinc is one of the most important trace elements that plays a vital role in many biological processes, and aberrant zinc metabolism has been implicated in lipid-related metabolic diseases. Previously, we showed that zinc antagonizes iron to regulate sterol regulatory element-binding proteins and stearoyl-CoA desaturase (SREBP-SCD) pathway in lipid metabolism in model organism Caenorhabditis elegans. Here, we further identified another cation diffusion facilitator CDF-1 in addition to SUR-7 in response to zinc to regulate lipid metabolism. Inactivation of SBP-1, the only homolog of SREBPs, leads to increased zinc level but decreased lipid accumulation reversely. However, either cdf-1(n2527) or sur-7(tm6523) mutation could successfully restore the altered fatty acid profile, fat content and zinc level of sbp-1(ep79) mutant. Furthermore, we found that CDF-1/SUR-7 may function bypass SBP-1 to directly affect the conversion activity of SCD in the biosynthesis of unsaturated fatty acids and lipid accumulation. Collectively, these results consistently support the link between zinc homeostasis and lipid metabolism via SREBP-SCD axis by cation diffusion facilitators CDF-1 and SUR-7.

zoology↗

bioRxiv2020

UFold: Fast and Accurate RNA Secondary Structure Prediction with Deep Learning

MotivationFor many RNA molecules, the secondary structure is essential for the correct function of the RNA. Predicting RNA secondary structure from nucleotide sequences is a long-standing problem in genomics, but the prediction performance has reached a plateau over time. Traditional RNA secondary structure prediction algorithms are primarily based on thermodynamic models through free energy minimization, which imposes strong prior assumptions and is slow to run. ResultsHere we propose a deep learning-based method, called UFold, for RNA secondary structure prediction, trained directly on annotated data without any thermodynamic assumptions. UFold improves substantially upon previous models, with approximately 10~30% improvement over traditional thermodynamic models and 14% improvement over other learning-based methods. It achieves an F1 score of 0.91 on base pair prediction accuracy on an RNA structure prediction benchmark dataset. UFold is also fast with an inference time about 160ms per sequence up to 1600bp length. We provide an online web server that implements UFold for RNA structure prediction and is made freely available. AvailabilityAn online web server running UFold is available at https://ufold.ics.uci.edu. Code is available at https://github.com/uci-cbcl/UFold. Contactxhx@uci.edu

bioinformatics↗