Biology subjects

Feng, J.

Publications and source records attributed to Feng, J..

At least 235 records · Page 13Linked to original sources

bioRxiv2020

Investigate the relevance of major signaling pathways in cancer survival using a biologically meaningful deep learning model

Survival analysis and prediction are important in cancer studies. In addition to the Cox proportional hazards model, recently deep learning models have been proposed to integrate the multi-omics data for survival prediction. Cancer signaling pathways are important and interpretable concepts that define the signaling cascades regulating cancer development and drug resistance. Thus, it is interesting and important to investigate the relevance to patients survival of individual signaling pathways. In this exploratory study, we propose to investigate the relevance and difference of a small set of core cancer signaling pathways in the survival analysis of cancer patients. Specifically, we built a biologically meaningful and simplified deep neural network, DeepSigSurvNet, for survival prediction. In the model, the gene expression and copy number data of 1648 genes from 46 major signaling pathways are used. We applied the model on 4 types of cancer and investigated the relevance and difference of the 46 signaling pathways among the 4 types of cancer. Interestingly, the interpretable analysis identified the distinct patterns of these signaling pathways, which are helpful to understand the relevance of the signaling pathways in terms of their association with cancer survival time. These highly relevant signaling pathways can be novel targets, combined with other essential signaling pathways inhibitors, for drug and drug combination prediction to improve cancer patients survival time.

bioinformatics↗

bioRxiv2020

Predicting Tumor Cell Response to Synergistic Drug Combinations Using a Novel Simplified Deep Learning Model

Drug combinations targeting multiple targets/pathways are believed to be able to reduce drug resistance. Computational models are essential for novel drug combination discovery. In this study, we proposed a new simplified deep learning model, DeepSignalingSynergy, for drug combination prediction. Compared with existing models that use a large number of chemical-structure and genomics features in densely connected layers, we built the model on a small set of cancer signaling pathways, which can mimic the integration of multi-omics data and drug target/mechanism in a more biological meaningful and explainable manner. The evaluation results of the model using the NCI ALMANAC drug combination screening data indicated the feasibility of drug combination prediction using a small set of signaling pathways. Interestingly, the model analysis suggested the importance of heterogeneity of the 46 signaling pathways, which indicates that some new signaling pathways should be targeted to discover novel synergistic drug combinations.

bioinformatics↗

bioRxiv2020

Seqpare: a self-consistent metric of similarity between genomic interval sets

SummarySearching genomic interval sets produced by sequencing methods has been widely and routinely performed; however, existing metrics for quantifying similarities among interval sets are inconsistent. Here we introduce Seqpare, a self-consistent and effective metric of similarity and tool for comparing sequences based on their interval sets. With this metric, the similarity of two interval sets is quantified by a single index, the ratio of their effective overlap over the union: an index of zero indicates unrelated interval sets, and an index of one means that the interval sets are identical. Analysis and tests confirm the effectiveness and self-consistency of the Seqpare metric. Availabilityhttps://github.com/deepstanding/seqpare Contactjf.xtable@gmail.com

genomics↗

bioRxiv2020

Renewable Fatty Acid Ester Production in Clostridium

Production of renewable chemicals through biological routes is considered as an urgent solution for fossil energy crisis. However, endproduct toxicity inhibits microbial performance and is a key bottleneck for biochemical production. To address this challenge, here we report an example of biosynthesis of high-value and easy-recoverable derivatives to alleviate endproduct toxicity and enhance bioproduction efficiency. By leveraging the natural pathways in solventogenic clostridia for co-producing acyl-CoAs, acids and alcohols as precursors, through rational screening for host strains and enzymes, systematic metabolic engineering-- including rational organization of ester-synthesizing enzymes inside of the cell, and elimination of putative prophages, we developed strains that can produce 20.3 g/L butyl acetate and 1.6 g/L butyl butyrate respectively, which were both the unprecedented levels in microbial hosts. Techno-economic analysis indicated a production cost of $986 per metric tonne for butyl acetate production from corn stover comparing to the market price of $1,200-1,400 per metric tonne of butyl acetate, suggesting the economic competitiveness of our developed bioprocess. Our principles of selecting the most appropriate host for specific bioproduction and engineering microbial chassis to produce high-value and easy-separable endproducts are highly applicable to other bioprocesses, and could lead to breakthroughs in biofuel/biochemical production and general bioeconomy.

bioengineering↗

bioRxiv2020

New and improved GRAB fluorescent sensors for monitoring dopaminergic activity in vivo

The monoamine neuromodulator dopamine (DA) plays a critical role in the brain, and the ability to directly measure dopaminergic activity is essential for understanding its physiological functions. We therefore developed the first red fluorescent GPCR-activation-based DA (GRABDA) sensors and optimized versions of green fluorescent GRABDA sensors following our previous studies. In response to extracellular DA, both the red and green GRABDA sensors have a large increase in fluorescence ({Delta}F/F0 values of 150% and 340%, respectively), with subcellular resolution, subsecond kinetics, and nanomolar to submicromolar affinity. Moreover, both the red and green GRABDA sensors readily resolve evoked DA release in mouse brain slices, detect compartmental DA release in live flies with single-cell resolution, and report optogenetically elicited nigrostriatal DA release as well as mesoaccumbens dopaminergic activity during sexual behavior in freely behaving mice. Importantly, co-expressing red GRABDA with either green GRABDA or the calcium indicator GCaMP6s provides a robust tool for simultaneously tracking neuronal activity and dopaminergic signaling in distinct circuits in vivo.

neuroscience↗

bioRxiv2020

Recombinant Protein IGF1-24 Stimulates Rat Cardiomyocytes Proliferation and Repairs Myocardial Injury

Mammal cardiomyocytes lose their ability of regeneration shortly after birth. Reduced cardiomyocytes number caused by myocardial damage is unable to reverse in current clinical therapies. Therefore, it is important and urgent to find new approaches to stimulate cardiomyocytes regeneration. Here we design a recombinant protein IGF1-24 and show that it triggers cardiomyocytes proliferation in rat. 7 days after tail intravenous injection of IGF1-24, 6-7-weeks-old healthy rats showed marked improvements in cardiomyocytes proliferation. Next, we injured rats cardiac with isoproterenol and treated them with IGF1-24 injection. We found that it efficiently induced cell proliferation with significant improvements in heart histology. These results show that the recombinant IGF1-24 stimulates cardiomyocytes proliferation and can be used to achieve cardiac repair through stimulating endogenous cardiomyocyte proliferation in rats. The IGF 1-24 could be a prospective medicine to heart repair because it has high efficiency in triggering cell proliferation and it can be easily applied to heart by intravenous injection

developmental biology↗

bioRxiv2020

Development and evaluation of a loop-mediated isothermal amplification (LAMP) assay for the detection of Tomato brown rugose fruit virus (ToBRFV)

Tomato brown rugose fruit virus (ToBRFV) is a member of Tobamovirus infecting tomato and pepper. Within North America, both the United States and Mexico consider ToBRFV to be a regulated pest. In Canada, the presence of ToBRFV has been reported, but an efficient diagnostic system has not yet been established. Here, we describe the development and assessment of a loop-mediated isothermal amplification (LAMP)-based assay to detect ToBRFV. The LAMP test was efficient and robust, and results could be obtained within 35 min with an available RNA sample. Amplification was possible when either water bath or oven were used to maintain the temperature at isothermal conditions (65{degrees}C), and results could be read by visual observation of colour change. Detection limit of the LAMP was eight target RNA molecules. Under the experimental conditions tested, LAMP was as sensitive as qPCR and 100 times more sensitive than the currently used rt-PCR. We recommend this sensitive, efficient LAMP protocol to be used for routine lab testing of ToBRFV.

microbiology↗

bioRxiv2020

Lower Soil Carbon Loss Due to Persistent Microbial Adaptation to Climate Warming

Soil microbial respiration is an important source of uncertainty in projecting future climate and carbon (C) cycle feedbacks. Despite intensive studies for two decades, the magnitude, direction, and duration of such feedbacks are uncertain, and their underlying microbial mechanisms are still poorly understood. Here we examined the responses of soil respiration and microbial community structure to long-term experimental warming in a temperate grassland ecosystem. Our results indicated that the temperature sensitivity of soil microbial respiration (i.e., Q10) persistently decreased by 12.0{+/-}3.7% across 7 years of warming. Integrated metagenomic and functional analyses showed that microbial community adaptation played critical roles in regulating respiratory acclimation. Incorporating microbial functional gene abundance data into a microbially-enabled ecosystem model significantly improved the modeling performance of soil microbial respiration by 5-19%, compared to the traditional non-microbial model. Model parametric uncertainty was also reduced by 55-71% when gene abundances were used. In addition, our modeling analyses suggested that decreased temperature sensitivity could lead to considerably less heterotrophic respiration (11.6{+/-}7.5%), and hence less soil C loss. If such microbially mediated dampening effects occur generally across different spatial and temporal scales, the potential positive feedback of soil microbial respiration in response to climate warming may be less than previously predicted.

ecology↗

bioRxiv2020

The Drosophila HP1 family is associated with active gene expression across chromatin contexts

Drosophila Heterochromatin Protein 1a (HP1a) is essential for heterochromatin formation and is involved in transcriptional silencing. However, certain loci require HP1a to be transcribed properly. One model posits that HP1a acts as a transcriptional silencer within euchromatin while acting as an activator within heterochromatin. However, HP1a has been observed as an activator of a set of euchromatic genes. Therefore, it is not clear whether, or how, chromatin context informs the function of HP1 proteins. To understand the role of HP1 proteins in transcription, we examined the genome-wide binding profile of HP1a as well as two other Drosophila HP1 family members, HP1B and HP1C, to determine whether coordinated binding of these proteins is associated with specific transcriptional outcomes. We found that HP1 proteins share a majority of their endogenous binding targets. These genes are marked by active histone modifications and are expressed at higher levels than non-target genes in both heterochromatin and euchromatin. In addition, HP1 binding targets displayed increased RNA polymerase pausing compared to non-target genes. Specifically, co-localization of HP1B and HP1C was associated with the highest levels of polymerase pausing and gene expression. Analysis of HP1 null mutants suggests these proteins coordinate activity at transcription start sites (TSSs) to regulate transcription. Depletion of HP1B or HP1C alters expression of protein-coding genes bound by HP1 family members. Our data broadens understanding of the mechanism of transcriptional activation by HP1a and highlights the need to consider particular protein-protein interactions, rather than broader chromatin context, to predict impacts of HP1 at TSSs.

genomics↗

bioRxiv2020

A genetically encoded GRAB sensor for measuring serotonin dynamics in vivo

Serotonin (5-HT) is a phylogenetically conserved monoamine neurotransmitter modulating a variety of processes in the brain. To directly visualize the dynamics of 5-HT, we developed a genetically encoded GPCR-Activation-Based 5-HT (GRAB5-HT) sensor with high sensitivity, selectivity, and spatiotemporal resolution. GRAB5-HT, detected 5-HT release in multiple physiological and pathological conditions in both flies and mice, and thus provides new insights into the dynamics and mechanisms of 5-HT signaling.

neuroscience↗

bioRxiv2020

TMEM184B controls pruriceptor specification and function

Nociceptive and pruriceptive neurons in the dorsal root ganglia (DRG) convey sensations of pain and itch to the spinal cord, respectively. One subtype of mature DRG neurons, comprising about 5% of neurons in the ganglia, is responsible for sensing mediators of acute itch and atopic dermatitis, including the cytokine IL-31. How itch-sensitive (pruriceptive) neurons are specified is unclear. Here we show that Tmem184b, a gene with roles in axon degeneration and nerve terminal maintenance, is required for the expression of a large cohort of itch receptors, including those for IL-31, Leukotriene C4, and Histamine. Male and female mice lacking Tmem184b show reduced responses to IL-31, but maintain normal responses to pain and mechanical force, indicating a specific behavioral defect in pruriception. Calcium imaging experiments indicate that a reduction in IL-31 induced calcium entry is a likely contributor to this phenotype. We identify an early failure of proper Wnt-dependent transcriptional signatures and signaling components in Tmem184b mutant mice that may explain the improper DRG neuronal subtype specification. Accordingly, lentiviral re-expression of Tmem184b in mutant embryonic neurons restores Wnt signatures. Together, these data demonstrate that Tmem184b promotes adult somatosensation through developmental Wnt signaling and promotion of proper pruriceptive gene expression. Our data illuminate a new key regulatory step in the processes controlling the establishment of diversity in the somatosensory system.

neuroscience↗

bioRxiv2020

Two pectate lyases from Caldicellulosiruptor bescii with the same CALG domain had distinct properties on plant biomass degradation

Pectin deconstruction is the initial step in breaking the recalcitrance of plant biomass by using selected microorganisms that carry pectinolytic enzymes. Pectate lyases that cleave -1,4-galacturonosidic linkage of pectin are widely used in industries, such as paper making and fruit softening. However, reports on pectate lyases with high thermostability are few. Two pectate lyases (CbPL3 and CbPL9) from a thermophilic bacterium Caldicellulosiruptor bescii were investigated. Although these two enzymes belonged to different families of polysaccharide lyase, both were Ca2+-dependent. Similar biochemical properties were shown under optimized conditions 80 {degrees}C-85 {degrees}C and pH 8-9. However, the degradation products on pectin and polygalacturonic acids (pGA) were different, revealing the distinct mode of action. A concanavalin A-like lectin/glucanase (CALG) domain, located in the N-terminus of two CbPLs, shares 100% amino acid identity. CALG-truncated mutant of CbPL9 showed lower activities than the wild-type, whereas the CbPL3 with CALG knock-out portion was reported with enhanced activities, thereby revealing the different roles of CALG in two CbPLs. I-TASSER predicted that the CALG in two CbPLs is structurally close to the family 66 carbohydrate binding module (CBM66). Furthermore, substrate-binding assay indicated that the catalytic domains in two CbPLs had strong affinities on pectate-related substrates, but CALG showed weak interaction with a number of lignocellulosic carbohydrates, except sodium carboxymethyl cellulose and sodium alginate. Finally, scanning electron microscope analysis and total reducing sugar assay showed that the two enzymes could improve the saccharification of switchgrass. The two CbPLs are impressive sources for degradation of plant biomass. ImportanceThermophilic proteins could be implemented in diverse industrial applications. We sought to characterize two pectate lyases, CbPL3 and CbPL9, from a thermophilic bacterium Caldicellulosiruptor bescii. The two enzymes had high optimum temperature, low optimum pH, and good thermostability at evaluated temperature. A family-66 carbohydrate binding module (CBM66) was identified in two CbPLs with sharing 100% amino acid identity. Deletion of CBM66 obviously decreased the activity of CbPL9, but increase the activity and thermostability of CbPL3, suggesting the different roles of CBM66 in two enzymes. Moreover, the degradation products by two CbPLs were different. These results revealed these enzymes could represent a potential pectate lyase for applications in paper and textile industries.

biochemistry↗

bioRxiv2019

Separating overlapping bat calls with a bi-directional long short-term memory network

Acquiring clear and usable audio recordings is critical for acoustic analysis of animal vocalizations. Bioacoustics studies commonly face the problem of overlapping signals, but the issue is often ignored, as there is currently no satisfactory solution. This study presents a bi-directional long short-term memory (BLSTM) network to separate overlapping bat calls and reconstruct waveform audio sounds. The separation quality was evaluated using seven temporal-spectrum parameters. The applicability of this method for bat calls was assessed using six different species. In addition, clustering analysis was conducted with separated echolocation calls from each population. Results showed that all syllables in the overlapping calls were separated with high robustness across species. A comparison between the seven temporal-spectrum parameters showed no significant difference and negligible deviation between the extracted and original calls, indicating high separation quality. Clustering analysis of the separated echolocation calls also produced an accuracy of 93.8%, suggesting the reconstructed waveform sounds could be reliably used. These results suggest the proposed technique is a convenient and automated approach for separating overlapping calls using a BLSTM network. This powerful deep neural network approach has the potential to solve complex problems in bioacoustics. Author summaryIn recent years, the development of recording techniques and devices in animal acoustic experiment and population monitoring has led to a sharp increase in the volume of sound data. However, the collected sound would be overlapped because of the existence of multiple individuals, which laid restrictions on taking full advantage of experiment data. Besides, more convenient and automatic methods are needed to cope with the large datasets in animal acoustics. The echolocation calls and communication calls of bats are variable and often overlapped with each other both in the recordings from field and laboratory, which provides an excellent template for research on animal sound separation. Here, we firstly solved the problem of overlapping calls in bats successfully based on deep neural network. We built a network to separate the overlapping calls of six bat species. All the syllables in overlapping calls were separated and we found no significant difference between the separated syllables with non-overlapping syllables. We also demonstrated an instance of applying our method on species classification. Our study provides a useful and efficient model for sound data processing in acoustic research and the proposed method has the potential to be generalized to other animal species.

ecology↗

bioRxiv2019

Variation in the life history strategy of cells underlies tumor’s functional diversity

Classical r- vs. K-selection theory describes the trade-offs between high reproductive output and competitiveness and guides research in evolutionary ecology1-5. While its impact has waned in the recent past, cancer evolution may rekindle it6-10. Indeed, solid tumors are an ideal theater for r- and K-selection and, hence, a good testing ground for ideas on life-history strategy evolution11,12. In this study, we impose r- or K-selection on HeLa cells to obtain strongly proliferative r cells and highly competitive K cells. RNA-seq analysis indicates that phenotypic trade-offs in r and K cells are associated with distinct patterns of expression of genes involved in the cell cycle, adhesion, apoptosis, and contact inhibition. Both empirical observations and simulations based on an ecological competition model show that the trade-off between cell proliferation and competitiveness can evolve adaptively and rapidly in naive cell lines. It is conceivable that the contrasting selective pressure may operate in a realistic ecological setting of actual tumors. When the r and K cells are mixed in vitro, they exhibit strikingly different spatial and temporal distributions in the resultant cultures. Thanks to this niche separation, the fitness of the entire tumor increases. Our analyses of life-history trade-offs are pertinent to evolutionary ecology as well as cancer biology.

evolutionary biology↗

bioRxiv2019

In Vivo Neuroregeneration to Treat Ischemic Stroke in Adult Non-Human Primate Brains through NeuroD1 AAV-based Gene Therapy

Stroke is a leading cause of death and disability but most of the clinical trials have failed in the past, despite our increasing understanding of the molecular and pathological mechanisms underlying stroke. While many signaling pathways have been identified in the aftermath of stroke, the majority of current approaches are focusing on neural protection rather than neuroregeneration. In this study, we report an in vivo neural regeneration approach to convert brain internal reactive astrocytes into neurons through ectopic expression of a neural transcription factor NeuroD1 in adult non-human primate (NHP) brains following ischemic stroke. We demonstrate that NeuroD1 AAV-based gene therapy can convert reactive astrocytes into neurons with high efficiency (90%), but astrocytes are never depleted in the NeuroD1-expressed areas, consistent with the proliferative capability of astrocytes. The NeuroD1-mediated in vivo astrocyte-to-neuron (AtN) conversion in monkey cortex following ischemic stroke increased local neuronal density, reduced reactive microglia, and surprisingly protected parvalbumin interneurons in the converted areas. The NeuroD1 gene therapy showed a broad time window, from 10 days to 30 days following ischemic stroke, in terms of exerting its neuroregenerative and neuroprotective effects. The cortical astrocyte-converted neurons also showed Tbr1+ cortical neuron identity, similar to our earlier findings in rodent animal models. Unexpectedly, NeuroD1 expression in converted neurons showed a significant decrease after 6 months of viral infection, suggesting a potential self-regulatory mechanism of NeuroD1 in adult mature neurons of NHPs. These results suggest that in vivo cell conversion through NeuroD1-based gene therapy may be an effective approach to regenerate new neurons in adult primate brains for tissue repair.

neuroscience↗

bioRxiv2019

Plasmodiophora brassicae in its environment-effects of temperature and light on resting spore survival in soil

Clubroot caused by Plasmodiophora brassicae is an important disease on cruciferous crops worldwide. Management of clubroot has been challenging, due largely to the millions of resting spores produced within an infected root that can survive dormant in the soil for many years. This study was conducted to investigate some of the environmental conditions that may affect the survival of resting spores in the soil. Soil samples containing clubroot resting spores (1 x 107 spores g-1 soil) were stored at various temperatures for two years. Additionally, other samples were buried in soil, or kept on the soil surface in the field. The content of P. brassicae DNA and the numbers of viable spores in the samples were assessed by quantitative polymerase chain reaction (qPCR) and pathogenicity bioassays, respectively. The results indicated that 4{degrees}C, 20{degrees}C and being buried in the soil were better conditions for spore survival than were -20{degrees}C, 30{degrees}C and at the soil surface. Most of the spores kept on the soil surface were killed, suggesting the negative effect of light on spore viability. Additional experiments confirmed that ultraviolet (UV) light contributed a large negative effect on spore viability as lower pathogenicity and less DNA content were observed from the 2-and 3-hour UV light treated spores compared to the untreated control. Finally, this work demonstrated that DNA-based quantification methods such as qPCR can be poor predictors of P. brassicae disease potential due to the presence and persistence of DNA from dead spores.

microbiology↗

bioRxiv2019

Neurobehavioural characterisation and stratification of reinforcement-related behaviour

AbstractReinforcement-related cognitive processes, such as reward processing, impulsiveness and emotional processing are critical components of externalising and internalising behaviours. It is unclear to what extent each of these processes contributes to individual behavioural symptoms, how their neural substrates give rise to distinct behavioural outcomes, and if neural profiles across different reinforcement-related processes might differentiate individual behaviours. We created a statistical framework that enabled us to directly compare functional brain activation during reward anticipation, motor inhibition and viewing of emotional faces in the European IMAGEN cohort of 2000 14-year-old adolescents. We observe significant correlations and modulation of reward anticipation and motor inhibition networks in hyperactivity, impulsivity, inattention and conduct symptoms, and describe neural signatures across neuroimaging tasks that differentiate these behaviours. We thus characterise shared and distinct functional brain activation patterns that underlie different externalising symptoms and identify neural stratification markers, while accounting for clinically observed co-morbidity.

neuroscience↗

bioRxiv2019

sRNAanno --- a database repository of uniformly-annotated small RNAs in plants

Small RNAs (sRNAs) are essential regulatory molecules, including three mayor classes in plants, microRNAs (miRNAs), phased small interfering RNAs (phased siRNAs or phasiRNAs), and heterochromatic siRNAs (hc-siRNAs). Except miRNAs, the other two classes are not well-annotated and collected in public databases for most sequenced plant genomes. We performed comprehensive sRNA annotation for 138 plant species, which have fully sequenced genomes and public next-generation-sequencing (NGS) sRNA data available. The results are available via an online repository called sRNAanno (www.plantsRNAs.org). Compared to plant miRNAs deposited in miRBase, we obtained much more miRNAs, which are more complete and reliable because of consistent and high-stringent criteria used in our miRNA annotation. sRNAanno also provides free access to genomic information for >16,000 PHAS loci and >21,000,000 hc-siRNA loci annotated from these 138 plants. On the basis of Integrative Genomics Viewer (IGV), we developed a visualization tool for browsing NGS sRNA data (IGV-sRNA), which have been integrated a series of new functions compatible to specific sRNA features. To make sRNA annotation an easy task, sRNAanno also provides free service of sRNA annotation to the community. In summary, sRNAanno and IGV-sRNA are great resources to facilitate the genomic and genetic research of plant small RNAs.

genomics↗