Biology subjects

Guo, B.

Publications and source records attributed to Guo, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon

An important task in the analysis of spatially resolved transcriptomics data is to identify spatially variable genes (SVGs), or genes that vary in a 2D space. Current approaches rank SVGs based on either p-values or an effect size, such as the proportion of spatial variance. However, previous work in the analysis of RNA-sequencing identified a technical bias, referred to as the "mean-variance relationship", where highly expressed genes are more likely to have a higher variance. Here, we demonstrate the mean-variance relationship in spatial transcriptomics data. Furthermore, we propose spoon, a statistical framework using Empirical Bayes techniques to remove this bias, leading to more accurate prioritization of SVGs. We demonstrate the performance of spoon in both simulated and real spatial transcriptomics data. A software implementation of our method is available at https://bioconductor.org/packages/spoon.

genomics↗

bioRxiv2024

Microbial succession, community assembly and adaptation over five years in a newly discovered deep-sea cold seep

Deep-sea cold seeps, characterized by the release of hydrocarbon-rich fluids such as methane from the seafloor, create unique ecosystems with evolving biological communities. Microorganisms serve as pioneers, initially colonizing early-stage cold seeps and providing essential matter and energy for subsequent colonizers. However, microbial succession, community assembly, and adaptation in these environments remain largely unexplored due to challenges associated with locating early-stage cold seeps. Here, we collected sediment samples from a newly discovered early-stage cold seep site, QDN-W07, in the South China Sea at varying depths over five years. We also sampled two previously reported cold seep sites, QDN-S18 and HM-ROV01, for comparative analysis. Amplicon sequencing revealed a high relative abundance of ANME-3 (up to 99%) and Methylomonadaceae (up to 83%) in surface sediments, and indicated changes in microbial community structures over time. Dispersal limitation dominated community assembly, while the contribution of homogeneous selection decreased over time, accompanied by a declined in the intensity of microbial association. Metagenomic analysis of core microbiome, comprising 172 metagenomic-assembled genomes at QDN-W07, revealed tolerance to low temperatures and oxygen. Core microbiome genomes were enriched with genes related to aerobic methane oxidation, urea metabolism, and the oxidation of sulfur, ammonia and carbon monoxide. These results indicate that core microorganisms obtain energy from the oxidation of inorganic compounds, allowing them to thrive in cold, methane-rich and unstable conditions. Overall, this study enhances our understanding of deep biosphere life, biogeochemical cycling, and the ecological management of cold seep environments.

microbiology↗

bioRxiv2024

Mapping AAV capsid sequences to functions through function-guided in silico evolution

Artificial intelligence (AI) offers significant potential to accelerate the functional engineering of adeno-associated virus (AAV) capsids in a time- and cost-efficient manner. However, existing approaches lack the ability to systematically map capsid sequences to multifunctional properties. To address this challenge, we developed ALICE, a knowledge-driven platform for in silico AAV capsid engineering that directly maps sequence to multiple functions. Our method incorporating a heuristic algorithm with contrastive learning principles, termed function-guided evolution (FE), to iteratively optimize high-performing capsid sequences generated by a naive language model toward desired functions. We elucidate FEs evolutionary mechanism, demonstrating its ability to navigate a function-guided landscape and generate capsids with tailored properties. After validating ALICEs ability to design murine-specific AAV capsids targeting Ly6a/Ly6c1 with limited training data, we developed ALICE-X by integrating a curriculum learning strategy. This upgrade facilitated exploration of sequence space beyond existing wet-lab datasets, enabling successful targeting of the human transferrin receptor 1 (hTfR1). The resulting engineered AAV variant, AAV.ALICE-H3, demonstrated improved viability, specific receptor targeting, and [~] 251-fold enhanced CNS tropism in human TFRC knock-in (hTFRC KI) mice compared to wildtype controls. This interpretable, knowledge-driven framework advances in silico AAV capsid design, offering broad applicability for translational gene therapy.

bioengineering↗

bioRxiv2024

Spatial mutual nearest neighbors for spatial transcriptomics data

Mutual nearest neighbors (MNN) is a widely used computational tool to perform batch correction for single-cell RNA-sequencing data. However, in applications such as spatial transcriptomics, it fails to take into account the 2D spatial information. Here, we present spatialMNN, an algorithm that integrates multiple spatial transcriptomic samples and identifies spatial domains. Our approach begins by building a k-Nearest Neighbors (kNN) graph based on the spatial coordinates, prunes noisy edges, and identifies niches to act as anchor points for each sample. Next, we construct a MNN graph across the samples to identify similar niches. Finally, the spatialMNN graph can be partitioned using existing algorithms, such as the Louvain algorithm to predict spatial domains across the tissue samples. We demonstrate the performance of spatialMNN using large datasets, including one with N=36 10x Genomics Visium samples. We also evaluate the computing performance of spatialMNN to other popular spatial clustering methods. Our software package is available at (https://github.com/Pixel-Dream/spatialMNN).

bioinformatics↗

bioRxiv2024

Impact of biosolids amendment on the soil resistome and microbiome - a greenhouse study

The spread of antibiotic resistance poses a significant challenge to public health worldwide. Wastewater treatment utilities are reservoirs of antibiotic-resistant bacteria and antibiotic resistance genes (ARGs). This study investigates the impact of biosolids amendment on the soil microbiome, resistome, virulence factors, and ESKAPE pathogens during carrot cultivation in a replicated greenhouse study. Metagenomic sequencing revealed that biosolids amendment increased the richness of microbial genera, ARGs, and virulence factors in soil. The relative abundance of ESKAPE pathogens, including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumanii, Pseudomonas aeruginosa, and Enterobacter spp., was notably higher in biosolids-amended soils. These pathogens persisted throughout the 11-week cultivation period, raising concerns about the potential for horizontal gene transfer and the spread of antibiotic resistance. The study also identified significant co-occurrences between microbial genera and ARGs, which can suggest the possibility of the microbial taxa harboring the co-occurring ARGs. These findings highlight the importance of continued research and monitoring to ensure the safe and effective use of biosolids in agriculture.

molecular biology↗

bioRxiv2024

Ground nesting of soft eggs by extinct birds and a new parity mode switch hypothesis for the evolution of animal reproduction

Nearshore ground nesting of soft eggs by extinct birds is demonstrated here, providing a new explanation for the abundance of bird fossils in early Cretaceous lacustrine environments, where humidity conditions required for soft egg incubation would have been present. This reinforces recent findings of Archaeopteryx soft eggs near Jurassic marine environments, the possibility that wings and elongated feathers developed primarily in association with nest protection on the ground and only secondarily with flight, and the origin of flight from the ground up. Notably, soft eggs preceded rigid eggs in evolution, but both crocodiles, whose ancestors seem to have antedated bird precursors, and extant birds reproduce exclusively via hard-shelled eggs. Therefore, an explanation is in order for how reproduction via soft eggs could have occurred in the bird lineage in-between two evolutionary moments of reproduction via rigid eggs. In alternative to the commonly accepted convergent evolution of viviparity and rigid eggshells, a parity mode switch hypothesis is presented here. It postulates the existence, since the rise of animals, of an inherited ancestral parity mode switch between viviparity and oviparity. This switch would have evolved to embrace hard-shelled oviparity after rigid eggshells appeared in evolution. Commitment to a particular parity mode or eggshell type may have conditioned survival of entire animal groups, especially during major extinction events, explaining, among others, the extinction of all birds that reproduced via soft eggshells.

evolutionary biology↗

bioRxiv2024

Network nature of ligand-receptor interactions underlies disease comorbidity in the brain

Neurodegenerative disorders have overlapping symptoms and have high comorbidity rates, but this is not reflected in overlaps of risk genes. We have investigated whether ligand-receptor interactions (LRIs) are a mechanism by which distinct genes associated with disease risk can impact overlapping outcomes. We found that LRIs are likely disrupted in neurological disease and that the ligand-receptor networks associated with neurological diseases have substantial overlaps. Specifically, 96.8% of LRIs associated with disease risk are interconnected in a single LR network. These ligands and receptors are enriched for roles in inflammatory pathways and highlight the role of glia in cross-disease risk. Disruption to this LR network due to disease-associated processes (e.g. differential transcript use, protein misfolding) is likely to contribute to disease progression and risk of comorbidity. Our findings have implications for drug development, as they highlight the potential benefits and risks of pursuing cross-disease drug targets.

neuroscience↗

bioRxiv2024

SpotSweeper: spatially-aware quality control for spatial transcriptomics

Quality control (QC) is a crucial step to ensure the reliability and accuracy of the data obtained from RNA sequencing experiments, including spatially-resolved transcriptomics (SRT). Existing QC approaches for SRT that have been adopted from single-nucleus RNA sequencing (snRNA-seq) methods are confounded by spatial biology and are inappropriate for SRT data. In addition, no methods currently exist for identifying histological tissue artifacts unique to SRT. Here, we introduce SpotSweeper, spatially-aware QC methods for identifying local outliers and regional artifacts in SRT. SpotSweeper evaluates the quality of individual spots relative to their local neighborhood, thus minimizing bias due to biological heterogeneity, and uses multiscale methods to detect regional artifacts. Using SpotSweeper on publicly available data, we identified a consistent set of Visium barcodes/spots as systematically low quality and demonstrate that SpotSweeper accurately identifies two distinct types of regional artifacts, resulting in improved downstream clustering and marker gene detection for spatial domains.

bioinformatics↗

bioRxiv2024

Multivalent Targeting of Blood-Brain Barrier LRP1 for Neurovascular Recovery Therapy for Alzheimer s Disease

The blood-brain barrier (BBB) is a highly selective permeability barrier that safeguards the central nervous system (CNS) from potentially harmful substances while regulating the transport of essential molecules. Its dysfunction is increasingly recognized as a pivotal factor in the pathogenesis of Alzheimers disease (AD), contributing to the accumulation of amyloid-{beta} (A{beta}) plaques. We propose an AD therapeutic strategy targeting the BBB low-density lipoprotein receptor-related protein 1 (LRP1). We show that a multivalent scaffold with LRP1-specific peptide modulates the A{beta} transport at the BBB. We show via detailed experimentation on AD model mice that this intervention markedly reduces A{beta} deposits and prevents cognitive decline. This study marks a new approach to drug design, combining multivalent targeting with the regulation of membrane trafficking through advanced molecular engineering. Crucially, the therapeutic effects emerge from the multivalent nature of our proposed system. Furthermore, our findings underscore the paramount significance of the BBB in AD pathogenesis, particularly emphasizing the critical role of LRP1-mediated A{beta} clearance in mitigating disease progression.

neuroscience↗

bioRxiv2024

Benchmarking and Optimization of Methods for the Detection of Identity-By-Descent in Plasmodium falciparum

Genomic surveillance is crucial for identifying at-risk populations for targeted malaria control and elimination. Identity-by-descent (IBD) is increasingly being used in Plasmodium population genomics to estimate genetic relatedness, effective population size (Ne), population structure, and signals of positive selection. Despite its potential, a thorough evaluation of IBD segment detection tools for species with high recombination rates, such as P. falciparum, remains absent. Here, we perform comprehensive benchmarking of IBD callers - probabilistic (hmmIBD, isoRelate), identity-by-state-based (hap-IBD, phased IBD) and others (Refined IBD) - using population genetic simulations tailored for high recombination, and IBD quality metrics at both the IBD segment level and the IBD-based downstream inference level. Our results demonstrate that low marker density per genetic unit, related to high recombination relative to mutation, significantly compromises the accuracy of detected IBD segments. In genomes with high recombination rates resembling P. falciparum, most IBD callers exhibit high false negative rates for shorter IBD segments, which can be partially mitigated through optimization of IBD caller parameters, especially those related to marker density. Notably, IBD detected with optimized parameters allows for more accurate capture of selection signals and population structure; IBD-based Ne inference is very sensitive to IBD detection errors, with IBD called from hmmIBD uniquely providing less biased estimates of Ne in this context. Validation with empirical data from the MalariaGEN Pf 7 database, representing different transmission settings, corroborates these findings. We conclude that context-specific evaluation and parameter optimization are essential for accurate IBD detection in high-recombining species and recommend hmmIBD for Plasmodium species, especially for quality-sensitive analyses, such as estimation of Ne. Our optimization and high-level benchmarking methods not only improve IBD segment detection in high-recombining genomes but also enhance overall genomic analysis, paving the way for more accurate genomic surveillance and targeted intervention strategies for malaria.

evolutionary biology↗

bioRxiv2024

Efficient cloning of genes for wheat yield component traits from QTLs via sequencing of the RIL population

In wheat (Triticum aestivum L.), yield component traits (YCTs) are the most important yield traits. Only several genes for YCTs have been originally cloned. The efficient cloning of genes for YCTs directly from wheat remains a challenge. Here, we proposed a strategy for cloning genes from quantitative trait loci (QTLs) by sequencing of recombinant inbred lines (RILs) (QTL-Seq-RIL). Using the TN18 x LM6 RIL population as an example, we identified 138 candidate unigenes (CUGs) for YCTs from 77 stable QTLs. The average of CUGs per QTL was 1.8, which enabled us to confirm the CUGs directly. We have confirmed seven CUGs, TaIFABPL, TaDdRp, TaRLK, TaTD, TaTFC3, TaKMT and TaSPL17, via the CRISPR/Cas9 system. Of these, six genes were found firstly to regulate YCTs in crops except for TaSPL17. Five CUGs (include TaSPL17) for which orthologous genes have been cloned previously with the same or similar agronomic functions. It is to say, 11 CUGs were preliminarily validated using a single RIL population. QTL-Seq-RIL provides an efficient method for rapid gene cloning using existing RIL populations.

plant biology↗

bioRxiv2023

Strong Positive Selection Biases Identity-By-Descent-Based Inferences of Recent Demography and Population Structure in Plasmodium falciparum

Malaria genomic surveillance often estimates parasite genetic relatedness using metrics such as Identity-By-Decent (IBD). Yet, strong positive selection stemming from antimalarial drug resistance or other interventions may bias IBD-based estimates. In this study, we utilized simulations, a true IBD inference algorithm, and empirical datasets from different malaria transmission settings to investigate the extent of such bias and explore potential correction strategies. We analyzed whole genome sequence data generated from 640 new and 4,026 publicly available Plasmodium falciparum clinical isolates. Our findings demonstrated that positive selection distorts IBD distributions, leading to underestimated effective population size and blurred population structure. Additionally, we discovered that the removal of IBD peak regions partially restored the accuracy of IBD-based inferences, with this effect contingent on the populations background genetic relatedness. Consequently, we advocate for selection correction for parasite populations undergoing strong, recent positive selection, particularly in high malaria transmission settings.

evolutionary biology↗

bioRxiv2023

Whole genome sequencing reveals autooctoploidy in the Chinese sturgeon and its evolutionary trajectories

The Order Acipenseriformes, which include sturgeons and paddlefishes, represent "living fossils" with complex genomes that are good models for understanding whole genome duplication (WGD) and ploidy evolution in fishes. Here we sequenced and assembled the first high-quality chromosome-level genome for the complex octoploid Acipenser sinensis (Chinese sturgeon), a critically endangered species that also represents a poorly understood ploidy group in Acipenseriformes. Our results show that A. sinensis is a complex autooctoploid species containing four kinds of octovalents (8 n), a hexavalent (6 n), two tetravalents (4 n), and a divalent (2 n). We propose based on an analysis taking into account delayed rediploidization that its octoploid genome composition results from two rounds of homologous whole genome duplications (WGDs), and further provide insight into the timing of its ploidy evolution. This study provides the first octoploid genome resource of Acipenseriformes for understanding ploidy composition and evolutionary trajectories of polyploidy fishes.

genomics↗

bioRxiv2023

escheR: Unified multi-dimensional visualizations with Gestalt principles

The creation of effective visualizations is a fundamental component of data analysis. In biomedical research, new challenges are emerging to visualize multi-dimensional data in a 2D space, but current data visualization tools have limited capabilities. To address this problem, we leverage Gestalt principles to improve the design and interpretability of multi-dimensional data in 2D data visualizations, layering aesthetics to display multiple variables. The proposed visualization can be applied to spatially-resolved transcriptomics data, but also broadly to data visualized in 2D space, such as embedding visualizations. We provide an open source R package escheR, which is built off of the state-of-the-art ggplot2 visualization framework and can be seamlessly integrated into genomics toolboxes and workflows. Availability and implementationThe open source R package escheR is freely available on Bioconductor (bioconductor.org/packages/escheR).

bioinformatics↗

bioRxiv2023

Antibiotic Resistance Gene Variant Sequencing is Necessary to Reveal the Complex Dynamics of Immigration from Sewers to Activated Sludge

Microbial community composition has increasingly emerged as a key determinant of antibiotic resistance gene (ARG) content. However, in activated sludge wastewater treatment plants (AS-WWTPs), a comprehensive understanding of the microbial community assembly process and its impact on the persistence of antimicrobial resistance (AMR) remains elusive. An important part of this process is the immigration dynamics (or community coalescence) between the influent and activated sludge. While the influent wastewater contains a plethora of ARGs, the persistence of a given ARG depends initially on the immigration success of the carrying population, and the possible horizontal transfer to indigenously resident populations of the WWTP. The current study utilised controlled manipulative experiments that decoupled the influent wastewater composition from the influent microbial populations to reveal the fundamental mechanisms involved in ARG immigration between sewers and AS-WWTP. A novel multiplexed amplicon sequencing approach was used to track different ARG sequence variants across the immigration interface, and droplet digital PCR was used to quantify the impact of immigration on the abundance of the targeted ARGs. Immigration caused an increase in the abundance of over 70 % of the quantified ARGs. However, monitoring of ARG sequence variants at the immigration interface revealed various immigration patterns such as (i) suppression of the indigenous mixed liquor variant by the immigrant, or conversely (ii) complete immigration failure of the influent variant. These immigration profiles are reported for the first time here and highlight the crucial information that can be gained using our novel multiplex amplicon sequencing techniques. Future studies aiming to reduce AMR in WWTPs should consider the impact of influent immigration in process optimisation and design.

microbiology↗

bioRxiv2023

Multiplexed Amplicon Sequencing Reveals High Sequence Diversity of Antibiotic Resistance Genes in Quebec Sewers

The United Nations Environment Assembly (UNEA-3) have recognised the importance of the environment in the development, spread and transmission of antimicrobial resistance (AMR) to humans and animals. Such recognition calls for wider surveillance of antimicrobial resistance genes (ARG) in wastewater and other environmental reservoirs. For ARG surveillance to be valuable to regulators, it must enable source tracking and risk assessment. Adequate surveillance also requires the processing of a large number of samples at a relatively low cost, and a low detection limit to allow quantification of the riskiest ARGs. However, current methods for tracking ARGs have various limitations. The current study presents a multiplexed targeted amplicon sequencing approach for the detection of sequence variants of ARGs in environmental samples. To demonstrate the application of this technique, wastewater samples collected from the inlet to 16 treatment plants located along a 440-km transect of the St-Lawrence river in the province of Quebec (Canada) were analysed. Among the ARGs examined, between 3 and 45 nucleic acid sequence variants were detected demonstrating the high sequence diversity that occurs within genes originating from a single sample type and the information that is missed using traditional techniques. Using the PLSDB and Comprehensive Antibiotic Resistance Database (CARD), the risk of ARG sequence variants was inferred based upon their reported mobility and detection in pathogens. Results suggest that sequence variants within a single ARG class present different risks to public health. In the future, targeted amplicon sequencing could be a valuable tool in environmental studies for both risk assessment purposes and in AMR source tracking.

microbiology↗

bioRxiv2023

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/. SummaryGeneration of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease.

neuroscience↗

bioRxiv2023

Activated Sludge Microbial Community Assembly: The Role of Influent Microbial Community Immigration

Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater, however the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilised controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analysed by harvesting wastewater biomass solids from 3 different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 25 % of the sequencing reads in the AS. By modelling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principals for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs. ImportanceIn biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. To allow future process optimisation to meet new treatment goals, we need a better understanding of factors influencing the microbial community assembly in WWTPs. This study developed a reproducible protocol to investigates the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls. We demonstrate herein that influent immigration contributed up to 25 % of the sequencing reads in the activated sludge under the studied conditions, highlighting the need to consider this process in future WWTP modelling and design.

microbiology↗