Biology subjects

Hou, S.

Publications and source records attributed to Hou, S..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

A homing rescue gene drive with multiplexed gRNAs reaches high frequency in cage populations but generates functional resistance

CRISPR homing gene drive is a potent technology with considerable potential for managing populations of medically and agriculturally significant insects. It induces a bias in the inheritance of the drive allele in progeny, rapidly spreading desired genes throughout the population. Homing drives operate by Cas9 cleavage followed by homology-directed repair, copying the drive allele to the wild-type chromosome. However, resistance alleles formed by end-joining repair pose a significant obstacle to the spread of the drive. To address this challenge, we created a homing drive targeting the essential but haplosufficient hairy gene. Our strategy involves spreading the drive construct through the homing process, eliminating nonfunctional resistance, which are recessive lethal, while rescuing drive-carrying individuals with a recoded version of hairy. This strategy eliminates resistance more slowly than a previous strategy targeting haplolethal genes, but it may be easier to construct in non-model organisms. Our drive inheritance rate was moderate, and multigenerational cage studies showed quick drive spread to 96-97% of the population. However, the drive failed to reach the whole population due to the formation of functional resistance alleles, despite use of four gRNAs, a strategy that previously was successful at preventing functional resistance. Sequencing showed that these alleles had a large deletion and must have utilized an alternate start codon. The resistance allele had a modest fitness advantage over the drive in a cage study, which could prevent long-term persistence of the drive, especially if cargo genes had an additional fitness cost. Thus, revised design strategies targeting more essential regions of a target gene may often be necessary to avoid such functional resistance, even when using multiplexed gRNAs.

synthetic biology↗

bioRxiv2023

starTracer: An Accelerated Approach for Precise Marker Gene Identification in Single-Cell RNA-Seq Analysis

We introduce starTracer, a novel R package designed to enhance the specificity and efficiency of marker gene identification in single-cell RNA-seq data analysis. The package consists of two primary functional modules: "searchMarker" and "filterMarker". The "searchMarker" module, operating as an independent pipeline, exhibits superior flexibility by accepting a variety of input file types. Its primary output is a marker gene matrix, where genes are sorted by their potential to function as cluster-specific markers, with those exhibiting the greatest potential positioned at the top of the matrix for each respective cluster. In contrast, the "filterMarker" module is designed as a complementary pipeline to the Seurat "FindAllMarkers" function, providing a more accurate marker gene list for each cluster in conjunction with Seurat results. Benchmark analyses demonstrate that starTracer not only achieves excellent specificity in identifying marker genes compared to Seurat but also significantly surpasses it in processing speed. Impressively, the speed improvement ranges by 1~2 orders of magnitude compared to Seurat, as observed across three independent datasets. It is worth noting that starTracer exhibits increasing speed improvement with larger data volumes. It also excels in identifying markers in smaller clusters. Furthermore, the "filterMarker" reordering process considerably enhances Seurats marker matrix specificity. These advantages solidify starTracer as an invaluable tool for researchers working with single-cell RNA-seq data, merging robust accuracy with exceptional speed.

bioinformatics↗

bioRxiv2023

A Novel Fluorogenic Spin Probe for Real-time Monitoring of Mitochondrial Reactive Oxygen Species (mROS) Generation in an in vitro Stroke Model

The extent of oxidative damage caused by a stroke can be assessed by monitoring mitochondrial reactive oxygen species (mROS), which can further aid in early diagnosis and evaluation of treatment efficacy. Mitochondrial ROS have been identified as a potential biomarker for stroke, as they are known to cause oxidative stress and mitochondrial dysfunction in brain tissue. However, monitoring reversible mROS levels has been challenging due to the lack of appropriate probes. In this study, we developed a fluorogenic spin probe, Mito-RT-ROS, based on the rhodamine skeleton, which demonstrated good sensitivity for reversible monitoring of mROS in a physiological environment such as starvation and recovery. We also evaluated the probes efficacy in an in vitro stroke model for real-time tracking of mROS generation in a pathological setting.

neuroscience↗

bioRxiv2023

PSPire: a machine learning predictor for high-performance screening of phase-separating proteins without intrinsically disordered regions

The burgeoning comprehension of protein phase separation (PS) has ushered in a wealth of bioinformatics tools for the prediction of phase-separating proteins (PSPs). These tools often skew towards PSPs with a high content of intrinsically disordered regions (IDRs), thus frequently undervaluing potential PSPs without IDRs. Nonetheless, PS is not only steered by IDRs but also by the structured modular domains and interactions that arent necessarily reflected in amino acid sequences. In this work, we introduce PSPire, a unique machine learning predictor designed to incorporate both residue-level and structure-level features for the precise prediction of PSPs. Compared to current PSP predictors, PSPire shows a notable improvement in identifying PSPs without IDRs, which underscores the crucial role of non-IDR, structure-based characteristics in multivalent interactions throughout the PS process. Additionally, our biological validation experiments substantiate the predictive capacity of PSPire, with 6 out of the 8 chosen candidate PSPs confirmed to form condensates within cells. This highlights the considerable potential of structure-based models in the accurate prediction and comprehensive understanding of protein PS.

bioinformatics↗

bioRxiv2023

Gene drive and genetic sex conversion in the global agricultural pest Ceratitis capitata

Homing-based gene drives are novel interventions promising the area-wide, species-specific genetic control of harmful insect populations. Here we characterise a first set of gene drives in a tephritid agricultural pest species, the Mediterranean fruit fly Ceratitis capitata (medfly). Our results show that the medfly is highly amenable to homing-based gene drive strategies. By targeting the medfly transformer gene, we also demonstrate two different mechanisms by which CRISPR-Cas9 gene drive can be coupled to sex conversion, whereby genetic females are transformed into fertile and harmless XX males. Given this unique malleability of sex determination, we modelled gene drive interventions that couple sex conversion and female sterility and found that such approaches could be effective and tolerant of resistant allele selection in the target population. Our results open the door for developing gene drive strains for the population suppression of the medfly and related tephritid pests by co-targeting female reproduction and shifting the reproductive sex ratio towards males. They demonstrate the untapped potential for gene drives to tackle agricultural pests in an environmentally friendly and economical way.

synthetic biology↗

bioRxiv2023

Large-scale genomic rearrangements boost SCRaMbLE in Saccharomyces cerevisiae

Genomic rearrangements contribute to gene copy number alterations, disruption of protein-coding sequences and/or perturbation of cis-regulatory networks. SCRaMbLE, a Cre/loxP-based system implanted in synthetic yeast chromosomes, can effectively introduce genomic rearrangements, and is thus a potential tool to study genomic rearrangements. However, the potential of SCRaMbLE to study genomic rearrangements is currently hindered, because a strain containing all 16 synthetic chromosomes is not yet available. Here, we constructed a yeast strain, SparLox83, containing 83 loxPsym sites distributed across all 16 chromosomes, with at least two sites per chromosome. Inducing Cre recombinase expression in SparLox83 produced versatile genome-wide genomic rearrangements, including inter-chromosomal events. Moreover, SCRaMbLE of the hetero-diploid strains derived from crossing SparLox83 with strains possessing synthetic chromosome III (synIII) from the Sc2.0 project led to increased diversity of genomic rearrangements and relatively faster evolution of traits compared to a strain with only synIII. Analysis of these evolved strains demonstrates that genomic rearrangements can perturb the transcriptome and 3D genome structure and can consequently impact phenotypes. In summary, a genome with sparsely distributed loxPsym sites can serve as a powerful tool to study the consequence of genomic rearrangements and help accelerate strain engineering in Saccharomyces cerevisiae.

synthetic biology↗

bioRxiv2023

Deep learning-enhanced single-molecule spectrum imaging

Fluorescence is widely used in biological imaging and biosensing. Rich information can be revealed from the fluorescence spectrum of fluorescent molecules, such as pH, viscosity and polarity of the molecules environment, and distance between two FRET molecules. However, constructing the fluorescence spectrum of a single fluorescent molecule typically requires a significant number of photons, which can suffer from photobleaching and therefore limit its potential applications. Here we propose a deep learning-enhanced single-molecule spectrum imaging method (SpecGAN) for improving the single-molecule spectrum imaging efficiency. In SpecGAN, the photon flux required to extract a single-molecule fluorescence spectrum can be reduced by 100 times, which enables it two orders of magnitude higher temporal resolution compared to the conventional single-molecule spectrometer. The concept of SpecGAN was validated through numerical simulation and single Nile Red molecule spectrum imaging on support lipid bilayers (SLBs). With SpecGAN, the super-resolution spectrum image of the COS-7 membrane can be reconstructed with merely 12,000 frames of single-molecule localization images, which is almost half of the previously reported frame count for spectrally resolved super-resolution imaging. The low photon flux requirement and high temporal resolution of SpecGAN make it a promising tool for investigating the molecular spectrum dynamics related to biological functions or biomolecule interactions.

biophysics↗

bioRxiv2023

Active-feedback 3D single-molecule tracking using a fast-responding galvo scanning mirror

Real-time three-dimensional single-particle tracking (RT-3D-SPT) allows continuous detection of individual freely diffusing objects with high spatiotemporal precision by applying closed-loop active feedback in an optical microscope. However, the current tracking speed in RT-3D-SPT is primarily limited by the response time of control actuators, impeding long-term observation of fast diffusive objects such as single molecules. Here, we present an RT-3D-SPT system with improved tracking performance by replacing the XY piezoelectric stage with a galvo scanning mirror with an approximately five-time faster response rate (~5 kHz). Based on the previously developed 3D single-molecule active real-time tracking (3D-SMART), this new implementation with a fast-responding galvo mirror eliminates the mechanical movement of the sample and allows more rapid response to particle motion. The improved tracking performance of the galvo mirror-based implementation is verified through simulation and proof-of-principle experiments. Fluorescent nanoparticles and ~ 1 kB double-stranded DNA molecules were tracked via both the original piezoelectric stage and new galvo mirror implementations. With the new galvo-based implementation, notable increases in tracking duration, localization precision, and the degree to which the objects are locked to the center of the detection volume were observed. These results suggest faster control response elements can expand RT-3D-SPT to a broader range of chemical and biological systems.

biophysics↗

bioRxiv2023

Development of attention-based robust deep learning model for tongue diagnosis by smartphone

Compared with tongue diagnosis using tongue image analyzers, tongue diagnosis by smartphone has great advantages in convenience and cost for universal health monitoring, but its accuracy is affected by the shooting conditions of smartphones. Developing deep learning models with high accuracy and robustness to changes in the shooting environment for tongue diagnosis by smartphone and determining the influence of environmental changes on accuracy are necessary. In our study, a dataset of 9003 images was constructed after image pre-processing and labeling. Next, we developed an attention-based deep learning model (Deep Tongue) for 8 subtasks of tongue diagnosis, including the spotted tongue, teeth-marked tongue, and fissure tongue et al, which the average AUC of was 0.90, higher than the baseline model (ResNet50) by 0.10. Finally, we analyzed the objective reasons, the brightness of the environment and the hue of images, affecting the accuracy of tongue diagnosis by smartphone through a consistency experiment of direct subject inspection and tongue image inspection. Finally, we determined the influence of environmental changes on accuracy to quantify the robustness of the Deep Tongue model through simulation experiments. Overall, the Deep Tongue model achieved a higher and more stable classification accuracy of seven tongue diagnosis tasks in the complex shooting environment of the smartphone, and the classification of tongue coating (yellow/white) was found to be sensitive to the hue of the images and therefore unreliable without stricter shooting conditions and color correction.

bioinformatics↗

bioRxiv2022

St2cell: Reconstruction of in situ single-cell spatial transcriptomics by integrating high-resolution histological image.

Spatially resolved transcriptomics (SRT) has greatly expanded our understanding of the spatial patterns of gene expression in histological tissue sections. However, most currently available platforms could not provide in situ single-cell spatial transcriptomics, limiting their biological applications. Here, to in silico reconstruct SRT at the single-cell resolution, we propose St2cell which combines deep learning-based frameworks with a novel convex quadratic programming (CQP)-based model. St2cell can thoroughly leverage information in high-resolution (HR) histological images, enabling the accurate segmentation of in situ single cells and identification of their transcriptomics. Applying St2cell on various SRT datasets, we demonstrated the reliability of reconstructed transcriptomics. The single-cell resolution provided by our proposed method greatly promoted the detection of elaborate spatial architectures and further facilitated the integration with single-cell RNA-sequencing data. Moreover, in a breast cancer tissue, St2cell identified general spatial structures and co-occurrence patterns of cell types in the tumor microenvironment. St2cell is also computationally efficient and easily accessible, making it a promising tool for SRT studies.

bioinformatics↗

bioRxiv2022

Mapping nanoscale forces and potentials in live cells with microsecond 3D single-particle tracking

3D single-particle tracking has the potential to resolve the molecular level forces which dictate particle motion in biological systems. However, the information gleaned from 3D single-particle tracking often cannot resolve underlying nanoscale potentials due to limited spatiotemporal resolution. To this end, we introduce an active-feedback 3D tracking microscope that utilizes silver nanoparticles (AgNPs) as probes to study intricate biophysical events in live cells at the nanometer and microsecond scales. Due to this extremely high and durable scattering photon flux of the plasmonic particles, 1 MHz sampling frequency at nanometer precision in all three dimensions can be achieved over an unlimited observation times. In this work, we applied microsecond-sampling, active-feedback 3D single-particle tracking to investigate the interaction between AgNPs and nanoscale filopodium on the live-cell surface. The nanometer precision and microsecond sampling revealed that TAT peptide modified particles visit and dwell at local "hot spots" on the filopodium surface. The high sampling rate further enabled the calculation of the local forces and potentials within these nanoscale hotspots on the cylindrical surface of live cell filopodia. This study presents a promising tool to investigate intracellular biophysical events with unprecedented spatiotemporal resolution and a pipeline to study nanoscale potentials on three-dimensional cellular structures.

biophysics↗

bioRxiv2022

Real-time imaging of mitochondrial redox reveals increased mitochondrial oxidative stress associated with amyloid beta aggregates in vivo in a mouse model of Alzheimer's disease

BackgroundReactive oxidative stress is a critical player in the amyloid beta (A{beta}) toxicity that contributes to neurodegeneration in Alzheimers disease (AD). Mitochondrial damage, observed in AD, is one of the main sources of reactive oxygen species. Although A{beta} causes neuronal mitochondria-associated reactive oxidative stress in vitro, this has never been directly observed in the in vivo living brain. Here, we tested whether A{beta} plaques and soluble oligomers induce mitochondrial oxidative stress in surrounding neurons in vivo, and whether the neurotoxic effect can be abrogated using mitochondrial-targeted antioxidants. MethodsWe expressed a genetically encoded fluorescent ratiometric mitochondria-targeted reporter of oxidative stress in mouse models of the disease, and performed intravital multiphoton microscopy of neuronal mitochondria and A{beta} plaques. ResultsFor the first time, we demonstrated by direct observation exacerbated mitochondrial oxidative stress in neurons after both A{beta} plaque deposition and direct application of soluble oligomeric A{beta} onto the brain, and determined the most likely pathological sequence of events leading to oxidative stress in vivo. Oxidative stress could be inhibited by both blocking calcium influx into mitochondria and treating with the mitochondria-targeted antioxidant SS31. ConclusionsConsidering these results, mitochondria-targeted compounds hold promise as neuroprotective drugs for the prevention and/or treatment of AD.

neuroscience↗

bioRxiv2022

Transcriptomic analysis reveals hub genes and pathways in response to acetic acid stress in Kluyveromyces marxianus during high-temperature ethanol fermentation

The thermotolerant yeast Kluyveromyces marxianus has great potential for high-temperature ethanol fermentation, but it produces excess acetic acid during high-temperature fermentation, which inhibits ethanol production. The mechanisms of K. marxianuss responses to acetic acid have not been fully understood. In this study, the transcriptomic changes of K. marxianus DMKU3-1042 resulted from acetic acid stress during high-temperature ethanol fermentation were investigated based on high-throughput RNA sequencing. We identified 611 differentially expressed genes (DEGs) under acetic acid stress (fold change > 2 or < 0.5, P-adjust <0.05), with 166 up-regulated and 445 down-regulated. GO terms and pathways enriched in these DEGs were identified. Protein-protein interaction (PPI) networks were constructed based on the interactions between proteins coded by the DEGs, and hub genes and key modules in the PPI networks were identified. The results in this study indicated that during high-temperature fermentation, acetic acid stress promoted protein catabolism but repressed protein synthesis, which affected the growth and metabolism of K. marxianus and led to the decrease of ethanol production. The findings in this study provide a better understanding of the response mechanism of K. marxianus to acetic acid stress, and provide a basis for subsequent increase of ethanol production by K. marxianus.

microbiology↗

bioRxiv2022

A kinase-independent function of cyclin-dependent kinase 6 promotes outer radial glia expansion and neocortical folding

The neocortex, the center for higher brain function, first emerged in mammals and has become massively expanded and folded in humans, constituting almost half the volume of the human brain. Primary microcephaly, a developmental disorder in which the brain is smaller than normal at birth, mainly results from the number of neurons in the neocortex being reduced because of defects in neural progenitor cells (NPCs). Outer radial glia (oRGs), NPCs that are abundant in gyrencephalic species but rare in lisencephalic species, are thought to play key roles in the expansion and folding of the neocortex. However, how oRGs expand, whether they are necessary for neocortical folding, and whether defects in oRGs cause microcephaly remain important questions in the study of brain development, evolution, and disease. Here, we show that oRG expansion in mice, ferrets, and human cerebral organoids requires cyclin-dependent kinase 6 (CDK6), the mutation of which causes primary microcephaly via an unknown mechanism. In a mouse model in which increased Hedgehog signaling expands oRGs and intermediate progenitor cells and induces neocortical folding, CDK6 loss selectively decreased oRGs and abolished neocortical folding. Remarkably, this function of CDK6 in oRG expansion did not require its kinase activity, was not shared by the highly similar CDK4 and CDK2, and was disrupted by the mutation causing microcephaly. Therefore, our results indicate that CDK6 is conserved to promote oRG expansion; that oRGs are necessary for neocortical folding; and that defects in oRG expansion may cause primary microcephaly. Significance StatementPrimary microcephaly, a disorder in which the brain is smaller than normal at birth, disproportionately affects the neocortex. Although outer radial glia (oRGs) expansion is hypothesized to be important in neocortical expansion and folding, it remains unknown whether oRGs are necessary for neocortical folding and whether defective oRGs cause microcephaly. Moreover, how oRGs expand is not well understood. A mutation in CDK6 causes microcephaly via an unknown mechanism. Here, we show that CDK6 promotes oRG expansion and neocortical folding. This function of CDK6 does not require its kinase activity but is disrupted by a mutation that causes microcephaly. Our findings show that CDK6 is conserved to expand oRGs and provide evidence that oRG defects disrupt neocortical growth and folding.

neuroscience↗

bioRxiv2022

Type One Protein Phosphatase Regulates Fixed-Carbon Starvation-Induced Autophagy by Dephosphorylating ATG13a to Facilitate ATG1a-ATG13a Formation in Arabidopsis

Autophagy, a conserved pathway which carries out the bulk degradation of cytoplasmic material in eukaryotic cells, is critical in plant physiology and development. It is tightly regulated by ATG13, a core component of ATG1 kinase complex which initiates autophagy. Although it has been reported that ATG13 is dephosphorylated immediately after nutrient starvation, the phosphatase regulating this process is poorly understood. Here, we demonstrated that the septuple mutant (topp-7m) and octuple mutant (topp-8m) of type one protein phosphatase (TOPP) exhibited significantly reduced tolerance to fixed-carbon (C) starvation due to compromised autophagy activity. Genetic analysis placed TOPP upstream of autophagy. Interestingly, ATG13a was found to be an interactor of TOPP. And TOPP directly dephosphorylated ATG13a in vitro and in vivo. Meanwhile, eighteen phosphorylation sites of ATG13a were identified by LC-MS. Mimic dephosphorylation of ATG13a at these 18 sites significantly promoted autophagy and increased the atg13ab mutant tolerance to fixed-C starvation. Further study showed that the dephosphorylation of ATG13a facilitated ATG1a-ATG13a complex formation. Consistently, the recruitment of ATG13a for ATG1a was markedly inhibited in topp-7m-1. In addition, TOPP-controlled dephosphorylation of ATG13a boosted ATG1a phosphorylation. Taken together, our study reveals the crucial role of TOPP in regulating autophagy by stimulating the formation of ATG1a-ATG13a complex through dephosphorylating ATG13a in Arabidopsis.

plant biology↗

bioRxiv2021

DeepMicrobeFinder sorts metagenomes into prokaryotes, eukaryotes and viruses, with marine applications

Sequence classification reduces the complexity of metagenomes and facilitates a fundamental understanding of the structure and function of microbial communities. Binary metagenomic classifiers offer an insufficient solution because environmental metagenomes are typically derived from multiple sequence sources, including prokaryotes, eukaryotes and the viruses of both. Here we introduce a deep-learning based (as opposed to alignment-based) sequence classifier, DeepMicroClass, that classifies metagenomic contigs into five sequence classes, i.e., viruses infecting prokaryotic or eukaryotic hosts, eukaryotic or prokaryotic chromosomes, and prokaryotic plasmids. At different sequence lengths, DeepMicroClass achieved area under the receiver operating characteristic curve (AUC) scores >0.98 for most sequence classes, with the exception of distinguishing plasmids from prokaryotic chromosomes (AUC scores{approx} 0.97). By benchmarking on 20 designed datasets with variable sequence class composition, we showed that DeepMicroClass obtained average accuracy scores of [~]0.99, [~]0.97, and [~]0.99 for eukaryotic, plasmid and viral contig classification, respectively, which were significantly higher than the other state-of-the-art individual predictors. Using a 1-300 {micro}m daily time-series metagenomic dataset sampled from coastal Southern California as a case study, we showed that metagenomic read proportions recruited by eukaryotic contigs could be doubled with DeepMicroClasss classification compared to the counterparts of other alignment-based classifiers. With its inclusive modeling and unprecedented performance, we expect DeepMicroClass will be a useful addition to the toolbox of microbial ecologists, and will promote metagenomic studies of under-appreciated sequence types.

bioinformatics↗

bioRxiv2021

Estimating the maximal growth rates of eukaryotic microbes from cultures and metagenomes via codon usage patterns

Microbial eukaryotes are ubiquitous in the environment and play important roles in key ecosystem processes, including accounting for a significant portion of global primary production. Yet, our tools for assessing the functional capabilities of eukaryotic microbes in the environment are quite limited because many microbes have yet to be grown in culture. Maximum growth rate is a fundamental parameter of microbial lifestyle that reveals important information about an organisms functional role in a community. We developed and validated a genomic estimator of maximum growth rate for eukaryotic microbes, enabling the assessment of growth potential for organisms and communities directly in the environment. We produced a database of over 700 maximum growth rate predictions from genomes, transcriptomes, and metagenome-assembled genomes. By comparing the maximal growth rates of existing culture collections with environmentally-derived genomes we found that, unlike for prokaryotes, culture collections of microbial eukaryotes are only minimally biased in terms of growth potential. We then extended our tool to make community-wide estimates of growth potential from over 500 marine metagenomes, mapping growth potential across the global oceans. We found that prokaryotic and eukaryotic communities have highly correlated growth potentials near the ocean surface, but there is no correlation in their genomic potentials deeper in the water column. This suggests that fast growing eukaryotes and prokaryotes thrive under similar conditions at the ocean surface, but that there is a decoupling of these communities as resources become scarce deeper in the water column.

microbiology↗

bioRxiv2021

ARS2-directed alternative splicing mediates CD28 driven T cell glycolysis and effector function

CD8 T cell activation prompts extensive transcriptome remodeling underlying effector differentiation and function. Regulation of transcriptome composition by the mitogen-inducible nuclear cap-binding complex (CBC) adaptor protein ARS2 has critical cell type-specific consequences, including thymic T cell survival. Here we show that ARS2 was upregulated by CD28 during activation of peripheral T cells, was essential for anti-tumor immunity, and facilitated T cell activation-induced alternative splicing. The novel splicing function of ARS2 was mediated at least in part by recruitment of splicing factors to nascent transcripts including the M2 isoform of pyruvate kinase (Pkm2), a key determinant of CD8 T cell effector properties. Notably, ARS2-directed Pkm2 splicing occurred days after stimulation of PI3K-indepdendent CD28 signaling and increased glycolysis beyond levels determined by PI3K signaling during T cell priming. Thus, ARS2-directed Pkm2 splicing represents a mechanism by which CD28 drives glycolytic metabolism, allowing for optimal effector cytokine production and T cell anti-tumor immunity.

immunology↗