Biology subjects

Lu, T.

Publications and source records attributed to Lu, T..

106 records · Page 6Linked to original sources

bioRxiv2021

Changes and composition of microbial community during aerobic composting of household food waste

In order to explore the effect of added bacteria on microbial community and determine the dominant bacteria in the aerobic composting process of household food waste (HFW), two groups of HFW composting experiments were conducted for 30 days. The final degradation rates of the two groups were 69.95% (group A, natural composting) and 73.52% (Group C, composting with added bacteria), respectively. 16S rRNA high-throughput sequencing was used to analyze the changes of microbial community in the composting process. As the result displays, at the classification of phylum level, the relatively abundant bacteria of two groups were Firmicutes, Proteobacteria and Cyanobacteria. At the classification of genus level, Pediococcus is the dominant bacteria of group A, which performed better in maintaining the microbial community stable in the later stage of composting, while Weissella accounted for a relatively large proportion of group C and behaved well in promoting the final degradation rate of composting. The proportion of Ochrobactrum in the early stage of group C is considerable and it is closely related to the removal of odour during composting. The relative abundance of added bacteria was always in a rather low level, suggested that the way they affect the composting process is to change the proportion of dominant bacteria in different stage of composting. This experiment provides an important reference for improving the microbial degradation efficiency of HFW. IMPORTANCEIn recent years, food waste has gradually become a global problem, the annual waste of food is as high as 1.3 billion tons. FW, especially HFW, as a high content of organic matter waste, has a pretty good recycling value. So how to deal with and recycle it efficiently, quickly and conveniently becomes more and more important. Among many treatment and recovery methods, microbial treatment (including anaerobic digestion and aerobic composting) has gradually become a research hotspot due to its advantages of low pollution and low energy consumption, and microorganisms play a crucial role in these process. In this study we use 16S rRNA high-throughput sequencing method to explore aerobic composting of HFW. The purpose of this study is to find out the dominant bacteria which can improve the degradation efficiency, remove the odor and prolong the treatment cycle, and then provide further theoretical reference for future HFW related research.

microbiology↗

bioRxiv2021

dynUGENE: an R package for uncertainty-aware gene regulatory network inference, simulation, and visualization

Methods for gene regulatory network inference focus on network architecture identification but neglect model selection and simulation. We implement an extension to the dynGENIE3 algorithm that accounts for model uncertainty as an R package, providing users with an easy to use interface for model selection and gene expression profile simulation. Source code is available at https://github.com/tianyu-lu/dynUGENE with a detailed user guide. A webserver with interactive controls is available at https://tianyulu.shinyapps.io/dynUGENE/.

bioinformatics↗

bioRxiv2020

Repulsive expansion dynamics in colony growth and patterning

Spatial expansion of a population of cells can arise from growth of microorganisms, plant cells, and mammalian cells. It underlies normal or dysfunctional tissue development and it can be exploited as the foundation for programming spatial patterns. This expansion is often driven by continuous growth and division of cells within a colony, which in turn pushes the peripheral cells outward. This process generates a repulsion velocity field at each location within the colony. Here we show that this process can be approximated as coarse-grained repulsive-expansion kinetics. This framework enables accurate and efficient simulation of growth and gene expression dynamics in radially symmetric colonies with homogenous z-directional distribution. It is robust even if cells are not spherical and vary in size. The simplicity of the resulting mathematical framework also greatly facilitates generation of mechanistic insights.

systems biology↗

bioRxiv2020

Beige adipocytes independently improve impaired glucose metabolism in the absence of brown adipose tissues in vivo

Beige adipocytes are emerging as an interesting issue in obesity and metabolism research. There is a neglected possibility that brown adipocytes are equally activated when external stimuli induce beige adipocytes. Thus, a question is whether beige adipocytes have the same functions as brown adipocytes when brown adipose tissue (BAT) is lacking. This question has not been well studied. Therefore we determine the beneficial effects of beige adipocytes upon cold challenge or CL316243 treatments in animal models of BAT ablation by surgical denervation. The data show that beige adipocytes partly contribute to impaired glucose metabolism resulting from denervated BAT. Whereas, we found that denervated BAT were activated by cold exposure and CL316243. Thus, we further used BAT-removal animal models to abolish BAT functions completely. We found that beige adipocytes upon cold challenge or CL316243 treatments independently improved impaired glucose metabolism in BAT-removal mice. The insulin signaling was activated in BAT-removal mice upon cold exposure. Whereas, both the activation of insulin signaling and up-regulation of glucose transporter expression were observed in BAT-removal mice with CL316243 treatments. The data show that beige adipocytes induced by cold exposure or CL316243 may have different mechanisms to improve impaired glucose metabolism. Beige adipocytes can also enhance energy expenditure and lipolytic activity of white adipose tissue when BAT is lacking. We provide direct evidences for the beneficial effect of beige adipocytes in glucose metabolism and energy expenditure in the absence of BAT in vivo.

cell biology↗

bioRxiv2020

Single cell plasticity and population coding stability in auditory thalamus upon associative learning

Cortical and limbic brain areas are regarded as centres for learning. However, how thalamic sensory relays participate in plasticity upon associative learning, yet support stable long-term sensory coding remains unknown. Using a miniature microscope imaging approach, we monitor the activity of populations of auditory thalamus (MGB) neurons in freely moving mice upon fear conditioning. We find that single cells exhibit mixed selectivity and heterogeneous plasticity patterns to auditory and aversive stimuli upon learning, which is conserved in amygdala-projecting MGB neurons. In contrast to individual cells, population level encoding of auditory stimuli remained stable across days. Our data identifies MGB as a site for complex neuronal plasticity in fear learning upstream of the amygdala that is in an ideal position to drive plasticity in cortical and limbic brain areas. These findings suggest that MGBs role goes beyond a sole relay function by balancing experience-dependent, diverse single cell plasticity with consistent ensemble level representations of the sensory environment to support stable auditory perception with minimal affective bias.

neuroscience↗

bioRxiv2020

Large-scale Proteomic and Phosphoproteomic Analysis of Maize Seedling Leaves During De-etiolation

De-etiolation consists of a series of developmental and physiological changes that a plant undergoes in response to light. During this process light, an important environmental signal, triggers the inhibition of mesocotyl elongation and the production of photosynthetically active chloroplasts, and etiolated leaves transition from the "sink" stage to the "source" stage. De-etiolation has been extensively studied in maize (Zea mays L). However, little is known about how this transition is regulated. In this study, we describe a quantitative proteomic and phosphoproteomic atlas of the de-etiolation process in maize. We identified 16,420 proteins and quantified 14,168. In addition, 8,746 phosphorylation sites within 3,110 proteins were identified. From the proteomic and phosphoproteomic data combined, we identified a total of 17,436 proteins, 27.6% of which are annotated protein coding genes in the Zea_mays AGPv3.28 database. Only 6% of proteins significantly changed in abundance during de-etiolation. In contrast, the phosphorylation levels of more than 25% of phosphoproteins significantly changed; these included proteins involved in gene expression and homeostatic pathways and rate-limiting enzymes involved in photosynthesis light and carbon reactions. Based on phosphoproteomic analysis, 34% (1,057) of all phosphoproteins identified in this study contained more than three phosphorylation sites, and 37 proteins contained more than 16 phosphorylation sites, which shows that multi-phosphorylation is ubiquitous during the de-etiolation process. Our results suggest that plants might preferentially regulate the level of PTMs rather than protein abundance for adapting to changing environments. The study of PTMs could thus better reveal the regulation of de-etiolation.

bioinformatics↗

bioRxiv2020

DPHL: A pan-human protein mass spectrometry library for robust biomarker discovery using Data-Independent Acquisition and Parallel Reaction Monitoring

To answer the increasing need for detecting and validating protein biomarkers in clinical specimens, proteomic techniques are required that support the fast, reproducible and quantitative analysis of large clinical sample cohorts. Targeted mass spectrometry techniques, specifically SRM, PRM and the massively parallel SWATH/DIA technique have emerged as a powerful method for biomarker research. For optimal performance, they require prior knowledge about the fragment ion spectra of targeted peptides. In this report, we describe a mass spectrometric (MS) pipeline and spectral resource to support data-independent acquisition (DIA) and parallel reaction monitoring (PRM) based biomarker studies. To build the spectral resource we integrated common open-source MS computational tools to assemble an open source computational workflow based on Docker. It was then applied to generate a comprehensive DIA pan-human library (DPHL) from 1,096 data dependent acquisition (DDA) MS raw files, and it comprises 242,476 unique peptide sequences from 14,782 protein groups and 10,943 SwissProt-annotated proteins expressed in 16 types of cancer samples. In particular, tissue specimens from patients with prostate cancer, cervical cancer, colorectal cancer, hepatocellular carcinoma, gastric cancer, lung adenocarcinoma, squamous cell lung carcinoma, diseased thyroid, glioblastoma multiforme, sarcoma and diffuse large B-cell lymphoma (DLBCL), as well as plasma samples from a range of hematologic malignancies were collected from multiple clinics in China, the Netherlands and Singapore and included in the resource. This extensive spectral resource was then applied to a prostate cancer cohort of 17 patients, consisting of 8 patients with prostate cancer (PCa) and 9 with benign prostate hyperplasia (BPH), respectively. Data analysis of DIA data from these samples identified differential expressions of FASN, TPP1 and SPON2 in prostate tumors. Thereafter, PRM validation was applied to a larger PCa cohort of 57 patients and the differential expressions of FASN, TPP1 and SPON2 in prostate tumors were validated. As a second application, the DPHL spectral resource was applied to a patient cohort consisting of samples from 19 DLBCL patients and 18 healthy individuals. Differential expressions of CRP, CD44 and SAA1 between DLBCL cases and healthy controls were detected by DIA-MS and confirmed by PRM. These data demonstrate that the DPHL supported that DIA-PRM MS pipeline enables robust protein biomarker discoveries.

bioinformatics↗

bioRxiv2020

Tumor Neoantigenicity Assessment with CSiN Score Incorporates Clonality and Immunogenicity to Predict Immunotherapy Outcomes

Lack of responsiveness to checkpoint inhibitors is a central problem in the modern era of cancer immunotherapy. Tumor neoantigens are critical mediators of host immune response and immunotherapy treatment efficacy. Current studies of neoantigens almost entirely focus on total neoantigen load, which simplistically treats all neoantigens equally. Besides, neoantigen loads have been linked with treatment response and prognosis only in some studies, but not others. We developed a Cauchy-Schwarz index of Neoantigens (CSiN) score to characterize the degree of concentration of immunogenic neoantigens in truncal mutations. Unlike simple neoantigen loads, CSiN incorporates the effect of both clonality and MHC-binding affinity of neoantigens when characterizing patient neoantigen profiles. By exploiting the clinical responses in 501 treated patients (mostly by checkpoint inhibitors) and the overall survival of 1,978 baseline patients, we showed that CSiN scores predict treatment response to checkpoint inhibitors and prognosis in melanoma, lung cancer, and kidney cancer patients. CSiN substantially outperforms prior genetics-based prediction methods of responsiveness. Overall, our work fulfilled an important gap in current research involving neoantigens. One Sentence SummaryThe quality of tumor neoantigens predicts response to immunotherapy

bioinformatics↗

bioRxiv2020

Overcoming Genetic Drop-outs in Variants-based Lineage Tracing from Single-cell RNA Sequencing Data

Lineage tracing provides key insights into the fates of individual cells in complex tissues. Recent works on lineage reconstruction based on the single-cell expression data are suitable for short time frames while tracing lineage based on more stable genetic markers is needed for studies that span time scales over months or years. However, variant calling from the single-cell RNA sequencing (scRNA-Seq) data suffers from "genetic drop-outs", including low coverage and allelic bias, which presents significant obstacles for lineage reconstruction. Prior studies focused only on mitochondrial (chrM) variants and need to be expanded to the whole genome to capture more variants with clearer physiological meaning. However, non-chrM variants suffer even more severe drop-outs than chrM variants, although drop-outs affect all variants. We developed strategies to overcome genetic drop-outs in scRNA-Seq-derived whole genomic variants for accurate lineage tracing, and we developed SClineger, a Bayesian Hierarchical model, to implement our approach. Our validation analyses on a series of sequencing protocols demonstrated the necessity of correction for genetic drop-outs and consideration of variants in the whole genome, and also showed the improvement that our approach provided. We showed that genetic-based lineage tracing is applicable for single-cell studies of both tumors and non-tumor tissues using our approach, and can reveal novel biological insights not afforded by expressional analyses. Interestingly, we showed that cells of various lineages grew under the spatial constraints of their respective organs during the developmental process. Overall, our work provides a powerful tool that can be applied to the large amounts of already existing scRNA-Seq data to construct the lineage histories of cells and derive new knowledge.

bioinformatics↗

bioRxiv2019

Genetic and epigenetic mechanisms underpinning the adaptive radiation of Aquilegia species

Elucidating the genetic and epigenetic bases underlying species diversification is crucial to understanding the evolution and persistence of biodiversity. As a well-known horticultural plant grown worldwide, the genus Aquilegia (columbine) is also a model system in adaptive radiation research. In this study, we surveyed the genomes and DNA methylomes of ten representative Aquilegia species from the Asian, European and North American lineages. Our inferences of the phylogenies and population structure revealed clearly high genetic and DNA methylomic divergence across the three lineages. By multi-levelled genome-wide scanning, we identified candidate genes exhibiting lineage-specific genetic or epigenetic variation patterns that are signatures of inter-specific divergence. We demonstrated that these species diversification-associated genetic variations and epigenetic variabilities were partially independent but were both functionally related to various biological processes vital to adaptation, including stress tolerance, cell reproduction and DNA repair. Our study provides an exploratory overview of how the established genetic and epigenetic signatures are associated with the rapid radiation of Aquilegia species.

plant biology↗

bioRxiv2019

Bacteriological Monitoring and Evaluation of Cleaning-disinfection of Computer-related Equipment in an Obstetric and Gynecology Hospital

It is already known that computer keyboards and mouses in hospitals are contaminated with different kinds of bacteria. However, the mouse pad has been neglected with regard to both research and regular cleaning and disinfection in hospitals. In our study, we monitored and evaluated the bacteriology degrees of 74 computers keyboards, mouses and mouse pads from six departments. The results showed that before cleaning-disinfection, the contamination rate of the mouse pad ranked second following the keyboards. Enterococcus Faecium was cultured from the mouse pads. The computer-related equipment in the wards and outpatient rooms were much more contaminated than that in the operating rooms. Acinetobacter spp. was only isolated from the doctors computers. After cleaning-disinfection, 4 strains of MRSA were isolated from the keyboards and the mouses, one and 3 were cultured at day 3 and day 5 after cleaning-disinfection, respectively. One strain of Pseudomonas Aeruginosa was isolated from the mouses at day 3 after cleaning-disinfection. These demonstrated that the bacterial contamination of the mouse pads must be as emphasized as that of the keyboards and mouses. Furthermore, It is better to clean and disinfect the computer-related equipment(keyboards, mouses, mouse pads) at least once a day.

scientific communication and education↗

bioRxiv2019

A Bayesian approach to accurate and robust signature detection on LINCS L1000 data

LINCS L1000 dataset produced by L1000 assay contains numerous cellular expression data induced by large sets of perturbagens. Although it provides invaluable resources for drug discovery as well as understanding of disease mechanisms, severe noise in the dataset makes the detection of reliable gene expression signals difficult. Existing methods for the peak deconvolution, either k-means based or Gaussian mixture model, cannot reliably recover the accurate expression level of genes in many cases, thereby limiting their robust applications in biomedical studies. Here, we have developed a novel Bayes theory based deconvolution algorithm that gives unbiased likelihood estimations for peak positions and characterizes the peak with a probability based z-scores. Based on above algorithm, a pipeline is built to process raw data from L1000 assay into signatures that represent the features of perturbagen. The performance of the proposed new pipeline is rigorously evaluated using the similarity between bio-replicates and between drugs with shared targets. The results show that the new signature derived from the proposed algorithm gives a substantially more reliable and informative representation for perturbagens than existing methods. Thus, our new Bayesian-based peak deconvolution and z-score calculation method may significantly boost the performance of invaluable L1000 data in the down-stream applications such as drug repurposing, disease modeling, and gene function prediction.

bioinformatics↗

bioRxiv2019

Recruitment of mRNAs to P granules by gelation with intrinsically-disordered proteins

Animals with germ plasm assemble cytoplasmic RNA granules (germ granules) that segregate with the embryonic germ lineage. How germ granules assemble and recruit RNA is not well understood. Here we characterize the assembly and RNA composition of the germ (P) granules of C. elegans. [~]500 maternal mRNAs are recruited into P granules by a sequence independent mechanism that favors mRNAs with low ribosome coverage. Translational activation correlates temporally with P granule exit for two mRNAs that code for germ cell fate regulators. mRNAs are recruited into the granules by MEG-3, an intrinsically disordered protein that condenses with RNA to form nanoscale gels. Our observations reveal parallels between germ granules and stress granules and suggest that cytoplasmic RNA granules are reversible super-assemblies of nanoscale RNA-protein gel condensates.

cell biology↗

bioRxiv2019

SORBS2 is a susceptibility gene to arrhythmogenic right ventricular cardiomyopathy

BACKGROUNDArrhythogenic right ventricular cardiomyopathy (ARVC) is an inherited cardiomyopathy characterized by right ventricular remodeling and ventricular arrhythmia. To date, 16 ARVC causative genes have been identified from human genetic studies, accounting for about 60% of ARVC probands. Genetic basis for the remaining 40% ARVC probands remain elusive.\n\nMETHODSPrompted by a zebrafish mutagenesis screen that suggested the Sorbin and SH3 domain-containing 2 (SORBS2) ortholog as a candidate cardiomyopathy gene, we conducted detailed expressionl analysis of Sorbs2 in mice, as well as phenotypic characterization in the Sorbs2 knock-out (KO) mice. The intercalated disc (ICD) expression pattern and ARVC-like phenotypes further prompted us to conduct targeted sequencing of human patients with ARVC to search for rare variants in the SORBS2 gene.\n\nRESULTSSorbs2 is robustly expressed in the mouse heart, encoding an adhesion junction/desmosome protein that is mainly localized to the ICD. A mutation with near complete depletion of the Sorbs2 protein in mouse results in phenotypes characteristic of human ARVC, such as dilated right ventricle (RV), RV dysfunction, spontaneous ventricular tachycardia (VT), and premature death. Sorbs2 is required to maintain the structural integrity of ICD. Its absence resulted in profound cardiac electrical remodeling with impaired impulse conduction and action potential derangements. Five rare variants were identified from a cohort of 59 ARVC patients, among which two variants affect splicing.\n\nCONCLUSIONSSorbs2 KO mouse is an ARVC model and SORBS2 is a new ARVC susceptibility gene.

genetics↗

bioRxiv2018

Amygdala neuronal ensembles dynamically encode behavioral states

Internal states, including affective or homeostatic states, are important behavioral motivators. The amygdala is a key brain region involved in the regulation of motivated behaviors, yet how distinct internal states are represented in amygdala circuits is unknown. Here, by imaging somatic neural calcium dynamics in freely moving mice, we identify changes in the relative activity levels of two major, non-overlapping populations of principal neurons in the basal nucleus of the amygdala (BA) that predict switches between exploratory and non-exploratory (defensive, anxiety-like) behavioral states across different environments. Moreover, the amygdala widely broadcasts internal state information via several output pathways to larger brain networks, and sensory responses in BA occur independently of behavioral state encoding. Thus, the brain processes external stimuli and internal states in an orthogonal manner, which may facilitate rapid and flexible selection of appropriate, state-dependent behavioral responses.

neuroscience↗

bioRxiv2017

Specification of the germline by Nanos-dependent down-regulation of the somatic synMuvB transcription factor LIN-15B

The Nanos RNA-binding protein has been implicated in the specification of primordial germ cells (PGCs) in metazoans, but the underlying mechanisms remain poorly understood. We have profiled the transcriptome of PGCs lacking the nanos homologues nos-1 and nos-2 iC. elegans. nos-1nos-2 PGCs fail to silence hundreds of genes normally expressed in oocytes and somatic cells, a phenotype reminiscent of PGCs lacking the repressive PRC2 complex. The nos-1nos-2 phenotype depends on LIN-15B, a broadly expressed synMuvB class transcription factor known to antagonize PRC2 activity in somatic cells. LIN-15B is maternally-inherited by all embryonic cells and is down-regulated specifically in PGCs in a nos-1nos-2-dependent manner. Consistent with LIN-15B being a critical target of Nanos regulation, inactivation of maternal LIN-15B restores fertility to nos-1nos-2 mutants. These studies demonstrate a central role for Nanos in reprogramming the transcriptome of PGCs away from an oocyte/somatic fate by down-regulating an antagonist of PRC2 activity.

cell biology↗