Biology subjects

Lu, Z.

Publications and source records attributed to Lu, Z..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Multiparametric sensing of outer membrane vesicle-derived supported lipid bilayers demonstrates the specificity of bacteriophage interactions

The use of bacteriophage, viruses that specifically infect bacteria, as antibiotics has become an area of great interest in recent years as the effectiveness of conventional antibiotics recedes. The detection of phage interactions with specific bacteria in a rapid and quantitative way is key for identifying phage of interest for novel antimicrobials. Outer membrane vesicles (OMVs) derived from gram-negative bacteria can be used to make supported lipid bilayers (SLBs) and therefore in vitro membrane models that contain naturally occurring components of the bacterial outer membrane. In this study, we used Escherichia coli OMV derived SLBs and use both fluorescent imaging and surface sensitive techniques to show their interactions with T4 phage. We also integrate these bilayers with microelectrode arrays (MEAs) functionalised with the conducting polymer PEDOT:PSS and show that the pore forming interactions of the phage with the SLBs can be monitored using electrical impedance spectroscopy. To highlight our ability to detect specific phage interactions, we also generate SLBs using OMVs derived from Citrobacter rodentium, which is resistant to T4 phage infection, and identify their lack of interaction with phage. The work presented here shows how interactions occurring between phage and these complex SLB systems can be monitored using a range of experimental techniques. We believe this approach can be used to identify phage against bacterial strains of interest, as well as more generally to monitor any pore forming structure (such as defensins) interacting with bacterial outer membranes, and thus aid in the development of next generation antimicrobials.

bioengineering↗

bioRxiv2022

scCDC: a computational method for gene-specific contamination detection and correction in single-cell and single-nucleus RNA-seq data

In droplet-based single-cell RNA-seq (scRNA-seq) and single-nucleus RNA-seq (snRNA-seq) assays, systematic contamination of ambient RNA molecules biases the estimation of genuine transcriptional levels. To correct the contamination, several computational methods have been developed. However, these methods do not distinguish the contamination-causing genes and thus either under- or over-corrected the contamination in our in-house snRNA-seq data of virgin and lactating mammary glands. Hence, we developed scCDC as the first method that specifically detects the contamination-causing genes and only corrects the expression counts of these genes. Benchmarked against existing methods on synthetic and real scRNA-seq and snRNA-seq datasets, scCDC achieved the best contamination correction accuracy with minimal data alteration. Moreover, scCDC applies to processed scRNA-seq and snRNA-seq data with empty droplets removed. In conclusion, scCDC is a flexible, accurate decontamination method that detects the contamination-causing genes, corrects the contamination, and avoids the over-correction of other genes.

bioinformatics↗

bioRxiv2022

Synthetic in vivo compartmentalisation improves metabolic flux and modulates the product profile of promiscuous enzymes

Enzyme spatial organisation and compartmentalisation are naturally evolved mechanisms for facilitating multi-step biocatalysis. We explored the synthetic in vivo co-encapsulation of two different cargo proteins in yeast using a self-assembling virus-like particle. Co-encapsulation was verified using single particle techniques for both end-to-end fusion of the cargo proteins with the encapsulation anchor at one end, and coexpression of each cargo protein with their individual anchors. The co-encapsulation of a bifunctional geranyl diphosphate/farnesyl diphosphate synthase and a bifunctional linalool/nerolidol synthase delivered nerolidol titres up to 30 times that of an unorganised free enzyme control, a remarkable improvement from a single engineering step. Interestingly, striking differences in the ratio of products (linalool and nerolidol) were observed with each spatial organisation approach. This work presents the largest reported titre fold increases from in vivo enzyme compartmentalisation and suggests that enzyme spatial organisation could be used to modulate the product profile of promiscuous enzymes.

synthetic biology↗

bioRxiv2022

Translational fusion of terpene synthases enhances metabolic flux by increasing protein stability

The end-to-end fusion of enzymes that catalyse successive steps in a reaction pathway is a metabolic engineering strategy that has been successfully applied in a variety of pathways and is particularly common in terpene bioproduction. Despite its popularity, limited work has been done to interrogate the mechanism of metabolic enhancement from enzyme fusion. We observed a remarkable >110-fold improvement in nerolidol production upon translational fusion of nerolidol synthase (a sesquiterpene synthase) to farnesyl diphosphate synthase. This delivered a titre increase from 29.6 mg/L up to 4.2 g/L nerolidol in a single engineering step. Whole-cell proteomic analysis revealed that nerolidol synthase levels in the fusion strains were greatly elevated compared to the non-fusion control. Similarly, the fusion of nerolidol synthase to non-catalytic domains also produced comparable increases in titre, which coincided with improved enzyme expression. When farnesyl diphosphate synthase was fused to other terpene synthases, we observed more modest improvements in terpene titre (1.9- and 3.8-fold), which corresponds to increases of a similar magnitude in terpene synthase expression. Therefore, increased in vivo enzyme levels - resulting from improved expression and/or stability - is likely to be a major driver of catalytic enhancement from enzyme fusion.

synthetic biology↗

bioRxiv2022

CRISPR/FnCas12a-mediated efficient multiplex and iterative genome editing in bacterial plant pathogens without donor DNA templates

CRISPR-based genome editing technology is revolutionizing prokaryotic research, but it has been rarely studied in bacterial plant pathogens. Here, we have developed a targeted genome editing method with no requirement of donor templates for convenient and efficient gene knockout in Xanthomonas oryzae pv. oryzae (Xoo), one of the most important bacterial pathogens on rice, by employing the heterogenous CRISPR/Cas12a from Francisella novicida and NHEJ proteins from Mycobacterium tuberculosis. FnCas12a nuclease generated both small and large DNA deletions at the target sites as well as it enabled multiplex genome editing, gene cluster deletion and plasmid cure in the Xoo PXO99A strain. Accordingly, a non-TAL effector-free polymutant strain PXO99AD25E, which lacks all 25 Xop genes involved in Xoo pathogenesis, has been engineered through iterative genome editing. Whole-genome sequencing analysis indicated that FnCas12a did not have a noticeable off-target effect. In addition, we revealed that these strategies are also suitable for targeted genome editing in another bacterial plant pathogen Pseudomonas syringae pv. tomato (Pst). We believe that our bacterial genome editing method will greatly expand the CRISPR study on microorganisms and advance our understanding of the physiology and pathogenesis of Xoo.

microbiology↗

bioRxiv2022

Citrus genomic resources unravel putative genetic determinants of Huanglongbing, a pathogen-triggered immune disease

Citrus is one of the most important tree crops worldwide and citrus production is threatened by Huanglongbing (HLB), a devasting citrus disease caused by Candidatus Liberibacter. HLB is a pathogen-triggered immune disease, in which the pathogen initiates systemic and chronic immune responses including the excessive production of reactive oxidative species, which subsequently lead to cell death of phloem tissues and HLB disease symptoms. Here, we identified putative genetic determinants of HLB pathogenicity by integrating citrus genomic resources to characterize the pan-genome of accessions that differ in their response to HLB. Genome-wide association mapping and analysis of allele-specific expression between susceptible, tolerant, and resistant accessions further refined candidates underlying the response to HLB. To enable these analyses we first developed a phased diploid assembly of Citrus sinensis Newhall genome and produced resequencing data for 91 citrus accessions that differ in their response to HLB. These data were combined with previous resequencing data from 356 sequenced accessions for genome-wide association mapping of the HLB response. Genes with HLB pathogenicity were associated with the host immune response, ROS production, and antioxidants. Overall, this study has provided a significant recourse of citrus genomic data and we have identified candidate genes to be further explored to understand the genetic determinants of HLB pathogenicity and to generate HLB resistant/tolerant citrus varieties.

genomics↗

bioRxiv2022

Cell division history encodes directional information of fate transitions

Single-cell RNA-sequencing (scRNA-seq) enables systematic mapping of cellular differentiation trajectories. However, inferring the cell-fate transitions under diseases or perturbations is still challenging due to the high cellular plasticity. Here, we demonstrate that monotonically expressed genes (MEGs) along cell divisions record the directions of state transitions regardless of the cellular processes. We developed a computational framework (PhyloVelo) to identify MEGs and reconstruct a novel transcriptomic velocity field by leveraging both scRNA-seq and phylogenetic information. PhyloVelo accurately recovered linear, bifurcated and convergent differentiations in simulations and C. elegans. It outperformed current approaches for delineating cellular trajectories in embryo development and tumor evolution through analysis of five CRISPR/Cas9-based lineage tracing datasets. Together, our study unveils an internal cellular clock and provides a powerful method for cellfate analysis in diverse biological contexts.

genomics↗

bioRxiv2022

A comprehensive view of cell-type-specific temporal dynamics in human and mouse brains

Progenitor cells play fundamental roles in preserving optimal organismal functions under normal, aging, and disease conditions. However, progenitor cells are incompletely characterized, especially in the brain, partly because conventional methods are restricted by inadequate throughput and resolution for deciphering cell-type-specific proliferation and differentiation dynamics in vivo. Here, we developed TrackerSci, a new technique that combines in vivo labeling of newborn cells with single-cell combinatorial indexing to profile the single-cell chromatin landscape and transcriptome of rare progenitor cells and track cellular differentiation trajectories in vivo. We applied TrackerSci to analyze the epigenetic and gene expression dynamics of newborn cells across entire mouse brains spanning three age stages and in a mouse model of Alzheimers disease. Leveraging the dataset, we identified diverse progenitor cell types less-characterized in conventional single cell analysis, and recovered their unique epigenetic signatures. We further quantified the cell-type-specific proliferation and differentiation potentials of progenitor cells, and identified the molecular programs underlying their aging-associated changes (e.g., reduced neurogenesis/oligodendrogenesis). Finally, we expanded our analysis to study progenitor cells in the aged human brain through profiling [~]800,000 single-cell transcriptomes across five anatomical regions from six aged human brains. We further explored the transcriptome signatures that are shared or divergent between human and mouse oligodendrogenesis, as well as the region-specific down-regulation of oligodendrogenesis in the human cerebellum. Together, the data provide an in-depth view of rare progenitor cells in mammalian brains. We anticipate TrackerSci will be broadly applicable to characterize cell-type-specific temporal dynamics in diverse systems.

genomics↗

bioRxiv2022

A global view of aging and Alzheimer's pathogenesis-associated cell population dynamics and molecular signatures in the human and mouse brains

Conventional single-cell genomics approaches are limited by throughput and thus may have failed to capture aspects of the molecular signatures and dynamics of rare cell types associated with aging and diseases. Here, we developed EasySci, an extensively improved single-cell combinatorial indexing strategy, for investigating the age-dependent dynamics of transcription and chromatin accessibility across diverse brain cell types. We profiled [~]1.5 million single-cell transcriptomes and [~]400,000 single-cell chromatin accessibility profiles across mouse brains spanning different ages, genotypes, and both sexes. With a novel computational framework designed for characterizing cellular subtypes based on the expression of both genes and exons, we identified > 300 cell subtypes and deciphered their underlying molecular programs and spatial locations especially for rare cell types (e.g., pinealocytes, tanycytes). Leveraging these data, we generated a global readout of age-dependent changes at cell subtype resolution, providing insights into cell types that expand (e.g., rare astrocytes and vascular leptomeningeal cells in the olfactory bulb, reactive microglia, and oligodendrocytes) or are depleted (e.g., neuronal progenitors, neuroblasts, committed oligodendrocyte precursors) as age progresses. Furthermore, we explored cell-type-specific responses to genetic perturbations associated with Alzheimers disease (AD) and identified rare cell types depleted (e.g., mt-Cytb+, mt-Rnr2+ choroid plexus epithelial cells) or enriched (e.g., Col25a1+, Ndrg1+ interbrain and midbrain neurons) in both AD models. Key findings are consistent between males and females, validated across the transcriptome, chromatin accessibility, and spatial analyses. Finally, we profiled a total of 118,240 single-nuclei transcriptomes from twenty-four post-mortem human brain samples derived from control and AD patients, revealing highly cell-type-specific and region-specific gene expression changes associated with AD pathogenesis. Critical AD-associated gene signatures were validated in both human and mice. In summary, these data comprise a rich resource for exploring cell-type-specific dynamics and the underlying molecular mechanisms in normal and pathological mammalian aging.

genomics↗

bioRxiv2022

Ten new high-quality genome assemblies for diverse bioenergy sorghum genotypes

Sorghum (Sorghum bicolor (L.) Moench) is an agriculturally and economically important staple crop that has immense potential as a bioenergy feedstock due to its relatively high productivity on marginal lands. To capitalize on and further improve sorghum as a potential source of sustainable biofuel, it is essential to understand the genomic mechanisms underlying complex traits related to yield, composition, and environmental adaptations. Expanding on a recently developed mapping population, we generated de novo genome assemblies for 10 parental genotypes from this population and identified a comprehensive set of over 24 thousand large structural variants (SVs) and over 10.5 million single nucleotide polymorphisms (SNPs).These resources can be integrated into both ongoing and future mapping and trait discovery for sorghum and its myriad uses including food, feed, bioenergy, and increasingly as a carbon dioxide removal mechanism. We show that SVs and nonsynonymous SNPs are enriched in different gene categories, emphasizing the need for long read sequencing in crop species to identify novel variation. Furthermore, we highlight SVs and SNPs occurring in genes and pathways with known associations to critical bioenergy-related phenotypes and characterize the landscape of genetic differences between sweet and cellulosic genotypes.

genomics↗

bioRxiv2022

DEED: A Dataset for Dream-related Emotion Research

Emotion is closely related to human cognition and behaviour. In recent years, scholars have conducted extensive research on emotion in waking state based on electroencephalography (EEG) and achieved certain results. However, Emotional activity continues after sleep, with a concentrated response of sleep emotions in dreams. Sleep emotions are concentrated in dreams, which can better reflect a series of real physical and psychological states of the human body. Currently, there is no publicly available dataset for the assessment of dream mood. Therefore, we present a physiological dataset Dream Emotion Evaluation Dataset (DEED) for the assessment of dream mood, which recorded EEG signals from 38 participants over 89 whole sleep nights and 533 dream segments(after exclusion of unqualified nights, those dream segments are extracted from 82 whole sleep nights). We studied the correlations between the subjective ratings and the EEG signals and brain network patterns for dream emotions. In addition, the relationship between the asymmetry of left and right brain bands and positive and negative dream emotions was studied. The machine learning algorithm was also used to classify different emotional EEG, which confirmed the validity of the dataset. In the meantime, we encourage other researchers to explore the underlying neural mechanisms involved in sleep.

neuroscience↗

bioRxiv2022

3rd-ChimeraMiner: A pipeline for integrated analysis of whole genome amplification generated chimeric sequences using long-read sequencing

Multiple displacement amplification (MDA) has become one of the most commonly used method of whole genome amplification (WGA) due to the high processivity, strand displacement capacity and high fidelity of the phi29 DNA polymerase, MDA generate vast amount of DNA with higher molecules weight (up to 100kb) and greater genome coverage. Along with the development of the sequencing platform, it is possible to sequence the MDA-amplified DNA molecules with over 20kb by long-read sequencing. However, one of the challenges is the formation of chimeras, which exist in all MDA products, and seriously interfere with the downstream analysis of the long-read sequencing data of MDA-amplified DNA. In this study, we constructed 3rd-ChimeraMiner, a chimera detection pipeline for analyzing the long-read sequencing of MDA products, recognizing chimeras, and integrating chimeras into the downstream analysis. Five sequencing data of MDA with different magnification fold were analyzed in here, the proportions of chimeras are much higher than that of next-generation sequencing reads and increase with the increase of magnification folds, ranging from 42% to over 76%. After comparing, 99.92% of recognized chimeras have been demonstrated not to exist in original genomes. After detecting chimeras by 3rd-ChimeraMiner, the full-length mapping ratio increased, means more PacBio data could be used in downstream analysis, and mean 97.77% inversions were removed after transferred chimeras into normal reads. 3rd-ChimeraMiner revealed efficiency and accuracy in discovering chimeras from long-read sequencing data of MDA, and is promising to be widely used in single-cell sequencing.

bioinformatics↗

bioRxiv2022

Integrative 4D-conformational mechanisms of single AdiC transporter molecules

To understand the mechanism of counter-transport of substrates by the amino-acid transporter AdiC, we used a state-of-the-art polarization-microscope to investigate conformation-specific changes of the emission polarization of a fluorophore attached to individual AdiC molecules. This capability enabled us to determine the lifetimes of two energetic states of each of AdiCs four conformations in the absence and presence of its two natural substrates, totaling 24 states. From these lifetimes and relative state-to-state transition frequencies, we further determined 60 rate constants of all state transitions and the 4 KD values for the two substrates to interact with both sides of AdiC, quantitatively defining a 24-state model that satisfactorily predicts previously observed transporting behaviors of AdiC. Combining this temporal information and the existing structural information, we have successfully built a fully experiment-based integrative 4D-model to capture and exhibit the complex spatiotemporal mechanisms of a facilitated counter-transport of an amino acid and its metabolite. Thus, a combination of the present method and existing structural techniques serves as an effective means to help transition structural biology, which has thus far been highly successful in the investigation of individual static structures, to an integrative form of dynamic structural biology.

biophysics↗

bioRxiv2022

Tracking multiple conformations occurring on angstrom-and-millisecond scales in single amino-acid-transporter molecules

The AdiC transporter facilitates the movement of arginine and its metabolite across the membrane of pathogenic enterobacteria, enabling them to evade a hosts highly acidic gastric defense barrier to reach the intestines. Like other transporters, AdiC undergoes a series of necessary conformational changes. Detection of these changes, which occur on angstrom-and- millisecond scales, remains extremely challenging. Here, using a high-resolution polarization-microscopic method, we have successfully resolved AdiCs four conformations by monitoring the emission-polarization changes of a fluorophore attached to an -helix that adopts conformation-specific orientations and, furthermore, quantified their probabilities in a series of arginine concentrations. The KD values determined for arginine in four individual conformations are statistically comparable to the previously reported overall KD determined using isothermal titration calorimetry. This demonstrated strong resolving power of the present polarization-microscopy method will enable an acquisition of the quantitative information required for understanding the expected complex conformational mechanism underlying the transporters function, as well as those of other membrane proteins.

biophysics↗

bioRxiv2022

Utilizing artificial intelligence system to build the digital structural proteome of reef-building corals

Reef-building corals play an important role in the marine ecosystem, and analyzing their proteomes from a structural perspective will exert positive effects on exploring their biology. Here we integrated mass spectrometry with newly published ColabFold to obtain digital structural proteomes of dominant reef-building corals. 8,382 proteins co-expressed in A. muricata, M. foliosa and P. verrucosa were identified, then 8,166 of them got predicted structures after around 4,060 GPU hours of computation. The resulting dataset covers 83.6% of residues with a confident prediction, while 25.9% have very high confidence. Our work provides insight-worthy predictions for coral research, confirms the reliability of ColabFold in practice, and is expected to be a reference case in the impending high-throughput era of structural proteomics.

bioinformatics↗

bioRxiv2022

Cytomulate: Accurate and Efficient Simulation of CyTOF data

Recently, many analysis tools have been devised to offer insights into data generated via Cytometry by time-of-flight (CyTOF). However, objective evaluations of these methods remain absent as most evaluations are conducted against real data where the ground truth is generally unknown. In this paper, we develop Cytomulate, a reproducible and accurate simulation algorithm of CyTOF data, which could serve as a foundation for future method development and evaluation. We demonstrate that Cytomulate can capture various characteristics of CyTOF data and is superior in learning overall data distributions than single-cell RNA-seq-oriented methods such as scDesign2, Splatter and generative models like LAMBDA.

bioinformatics↗

bioRxiv2022

Pan-genome inversion index reveals evolutionary insights into the subpopulation structure of Asian rice (Oryza sativa)

Understanding and exploiting genetic diversity is a key factor for the productive and stable production of rice. Utilizing 16 high-quality genomes that represent the subpopulation structure of Asian rice (O. sativa), plus the genomes of two close relatives (O. rufipogon and O. punctata), we built a pan-genome inversion index of 1,054 non-redundant inversions that span an average of [~] 14% of the O. sativa cv. Nipponbare reference genome sequence. Using this index we estimated an inversion rate of 1,100 inversions per million years in Asian rice, which is 37 to 73 times higher than previously estimated for plants. Detailed analyses of these inversions showed evidence of their effects on gene regulation, recombination rate, linkage disequilibrium and agronomic trait performance. Our study uncovers the prevalence and scale of large inversions ([≥] 100 kb) across the pan-genome of Asian rice, and hints at their largely unexplored role in functional biology and crop performance.

genomics↗

bioRxiv2022

Intrinsic RNA targeting constrains the utility of CRISPR-Cas13 systems

CRISPR-Cas13 systems have been adapted as versatile toolkits for RNA-related applications. Here we systematically evaluate the performance of several popular Cas13 family effectors (Cas13a, Cas13b and Cas13d) under lentiviral vectors and reveal surprisingly differential defects and characteristics of these systems. Using RNA immunoprecipitation sequencing, transcriptome profiling, biochemistry analysis, high-throughput CRISPR-Cas13 screening and machine learning approaches, we determine that each Cas13 system has its intrinsic RNA targets in mammalian cells. Viral process-related host genes can be targeted by Cas13 and affect production of fertile lentiviral particles, thereby restricting the utility of lentiviral Cas13 systems. Multiple RNase activities of Cas13 are involved in endogenous RNA targeting. Unlike target-induced nonspecific collateral effect, intrinsic RNA cleavage can be specific, target-independent and dynamically tuned by varied states of Cas13 nucleases. Our work provides guidance on appropriate use of lentiviral Cas13 systems and further raises cautions about intrinsic RNA targeting during Cas13-based basic and therapeutic applications.

molecular biology↗