Biology subjects

Fu, B.

Publications and source records attributed to Fu, B..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

GlyTrait Brings Insights into Functional Glycosylation

Glycomics research often grapples with the interpretability and biological relevance of glycomics data. Using glycosylation derived traits are promising methods for more in-depth biological insights, yet no such bioinformatic tool exists for such task. Here, we developed GlyTrait, a Python-based framework designed to enhance glycomics analysis through the innovative calculation and interpretation of derived traits from N-glycome data. GlyTrait automates the derivation of biologically significant traits, shifting focus from mere glycan abundances to functional glycan properties such as branching and fucosylation. GlyTrait extends the well-established nomenclatures and definitions of derived traits in the N-glycomics community, allowing for fast exploration and analysis of N-glycome data effortlessly. Furthermore, with the well-designed formula grammar, custom derived traits could be materialized without any knowledge of coding. Besides, a two-step post-filtering process reduces information redundancy, maintaining only the most informative traits. Finally, subsequent statistical and interpretable machine learning analysis provide robust insights into the glycosylation patterns associated with disease states. This comprehensive approach not only improves the statistical power and sensitivity compared to traditional methods, but also enhances the interpretability of glycomics data. GlyTraits efficacy is demonstrated through the re-analysis of published glycoengineered CHO cell lines and visceral leishmaniasis patient data, alongside a newly conducted pilot study for hepatocellular carcinoma (HCC) N-glycan biomarker discovery. We are confident in GlyTraits potential to become an indispensable tool for the glycomics community. Significance StatementGlycomics data is often challenging to interpret and analyze for biological relevance. GlyTrait, a Python-based tool, addresses this by automatically calculating biologically significant traits from N-glycome data, focusing on functional properties like glycan branching and fucosylation rather than mere abundance. This tool enhances data interpretability, reduces redundancy through post-filtering, and employs statistical methods to uncover glycosylation patterns linked to diseases. Demonstrated on various published datasets, as well as a newly conducted pilot study with 165 samples for hepatocellular carcinoma N-glycan biomarker discovery, GlyTrait proves to be a powerful tool. It improves the understanding of glycosylation changes in conditions like cancer, thereby benefiting the glycomics community.

bioinformatics↗

bioRxiv2024

NSP4 mutation T492I drives rapid evolution of SARS-CoV-2 toward Omicron

T492I, a mutation encountered in SARS-CoV-2 nonstructural protein 4 (NSP4), enhances viral replication and alters nonstructural protein cleavage, causing potential evolutionary impacts. Through comprehensive comparative analyses based on evolve-and-resequence experiments of SARS-CoV-2 wild-type and Delta strains with or without T492I, we demonstrate that NSP4 T492I not only increases the mutation rate, but also accelerates the emergence of many mutations characteristic for Omicron variants. Accordingly, viral populations that evolved from ancestors with T492I, show Omicron-biased selective forces and increases in viral replication, infectivity, immune evasion capacity, potentials for cross-species transmission and receptor-binding affinity. Aside from enhanced replication, we observed stronger epistasis regarding viral replication and infectivity in T492I than in S N501Y and NSP6 {Delta}SGF; this facilitates the regulation of mutation types, which can drive fast evolution of Omicron specific mutations. Our results highlight the role of an important replication-enhancing mutation in regulating the evolutionary rates and mutational trends of SARS-CoV-2.

evolutionary biology↗

bioRxiv2024

Spatiotemporal transcriptomic profiling reveals the dynamic immunological landscape of alveolar echinococcosis

Alveolar echinococcosis (AE) is caused by the invasive growth of the metacestodes of Echinococcus multilocularis (E. multilocularis). The early diagnosis, management, and treatment of AE remains challenging. Herein, we integrated bulk RNA-seq, scRNA-seq, and ST technologies to reveal the immune characteristics both spatially and chronologically in E. multilocularis infected mouse liver. An unprecedented high-resolution spatial atlas of the E. multilocularis infection foci was obtained, revealing the pivotal role of neutrophils, Spp1+ monocyte-derived macrophages (MoMFs), and fibroblasts in AE progression. We observed continuous recruitment of neutrophils and macrophages into the infected tissues, indicating prolonged immune stimulation by the growing metacestodes. However, their spatial distribution patterns and functions changed during the infection cause. At the early infection stage, Il1bhi neutrophils aggregated in the lesion displayed the highest pattern-recognition receptor activity and may kill the metacestodes through NETosis, but their death in the infection foci might also trigger immune suppression. Meanwhile, Spp1+ MoMFs attached to the protoscoleces to clear the infection. At the late infection stage, the neutrophils failed to infiltrate into the lesion although their continuous recruitment into the infected liver. Even though the Spp1+ MoMFs enclosing the microcysts of E. multilocularis may retain their pathogen-killing ability, they may also promote fibrosis and angiogenesis through interaction with fibroblasts. The pro- and anti-inflammatory phenotype balance of these immune cells may be associated with the transition of parasite control strategy from "active killing" to "negative segregation" by the host. Our findings identify key molecular traits involved in AE development, which may benefit the treatment of echinococcosis.

immunology↗

bioRxiv2024

A chromosome-level genome assembly of the Hispid cotton rat (Sigmodon hispidus), a model for human pathogenic virus infections

BackgroundThe cotton rat (Sigmodon hispidus), a rodent species native to the Americas, has emerged as a valuable laboratory model of infections by numerous human pathogens including poliovirus and respiratory syncytial virus (RSV). ResultsHere we report the first reference assembly of the cotton rat genome organized at a chromosomal level, providing annotation of 24,878 protein-coding genes. Data from PCR-free whole genome sequencing, linked-read sequencing and RNA sequencing from pooled cotton rat tissues were analyzed to assemble and annotate this novel genome sequence. Spectral karyotyping data using fluorescent probes derived from mouse chromosomes facilitated the assignment of cotton rat orthologs to syntenic chromosomes, comprising 25 autosomes and a sex chromosome in the haploid genome. Comparative phylome analysis revealed both gains and losses of numerous genes including immune defense genes against pathogens. We identified thousands of recently retrotransposed L1 and SINE B2 elements, revealing widespread genetic innovations unique to this species. ConclusionsWe anticipate that annotation and characterization of the first chromosome-level cotton rat genome assembly as described here will enable and accelerate ongoing investigations into its host defenses against viral and other pathogens, genome biology and mammalian evolution.

genomics↗

bioRxiv2024

A Scalable Adaptive Quadratic Kernel Method for Interpretable Epistasis Analysis in Complex Traits

Our knowledge of the contribution of genetic interactions (epistasis) to variation in human complex traits remains limited, partly due to the lack of efficient, powerful, and interpretable algorithms to detect interactions. Recently proposed approaches for set-based association tests show promise in improving power to detect epistasis by examining the aggregated effects of multiple variants. Nevertheless, these methods either do not scale to large numbers of individuals available in Biobank datasets or do not provide interpretable results. We, therefore, propose QuadKAST, a scalable algorithm focused on testing pairwise interaction effects (also termed as quadratic effects) of a set of genetic variants on a trait and quantifying the proportion of phenotypic variance explained by these effects. We performed comprehensive simulations and demonstrated that QuadKAST is well-calibrated. Additionally, QuadKAST is highly sensitive in detecting loci with epistatic signal and accurate in its estimation of quadratic effects. We applied QuadKAST to 53 quantitative phenotypes measured in {approx} 300, 000 unrelated white British individuals in the UK Biobank to test for quadratic effects within each of 9, 515 protein-coding genes (after accounting for linear additive effects). We detected 32 trait-gene pairs across 17 traits that demonstrate statistically significant signals of quadratic effects ([Formula] accounting for the number of genes and traits tested). Our method enables the detailed investigation of epistasis on a large scale, offering new insights into its role and importance.

genetics↗

bioRxiv2024

Seminal root angle is associated with root system architecture in durum wheat

Optimal root system architecture (RSA) is critical for efficient resource capture in soils, hence being an interest in crop breeding. Seminal root angle (SRA) at the seedling stage in durum wheat has been suggested to be a good indicator of RSA. However, research on correlating such lab-based seedling root phenotyping to RSA at later phases of plant growth is limited, resulting in the importance of root trait variation seen in seedlings often being overstated. To explore the role of SRA in modifying RSA at later phases of plant growth, we assessed 11 genotypes contrasting in SRA (wide and narrow), grown in a rhizobox designed for phenotyping root systems of plants during late-tillering. Above-ground traits and root dry mass in different soil depths and across the entire soil volume were measured manually, while root architectural traits were extracted using image analysis and summarised by multiple factor analysis to describe RSA. When comparing the wide and narrow genotypes, no differences were detected for above-ground traits and total root dry mass. However, differences were observed in the allocation of root dry mass at different depths. The wide and narrow genotypes showed distinct RSAs, particularly in the upper soil (0 - 30 cm). The wide genotypes exhibited a spread-out root system with dense and thin roots, whereas the narrow genotypes had a compact root system with fewer but thicker roots. Our study demonstrated a clear difference in RSA between the wide and narrow genotypes, highlighting the association between SRA on the direction and distribution of root growth in plants at later growth stages.

plant biology↗

bioRxiv2024

Large-scale visualisation of α-synuclein oligomers in Parkinson's disease brain tissue

Parkinsons disease (PD) is a common neurodegenerative condition characterised by the presence in the brain of large intraneuronal aggregates, known as Lewy bodies and Lewy neurites, containing fibrillar -synuclein. According to the amyloid hypothesis, these large end-stage species form from smaller soluble protein assemblies, often termed oligomers, which are proposed as early drivers of pathogenesis. To date, however, this hypothesis has remained controversial, at least in part because it has not been possible to directly visualise oligomeric aggregates in human brain tissue. Therefore, their presence, abundance and distributions have remained elusive. Here, we present ASA-PD (Advanced Sensing of Aggregates - Parkinsons Disease), an imaging method to generate large-scale -synuclein oligomer maps in post-mortem human brain tissue. We combined autofluorescence suppression with single-molecule fluorescence methods, which together, enable the detection of nanoscale -synuclein aggregates. To demonstrate the utility of this platform, we captured [~]1.2 million oligomers from the anterior cingulate cortex in human post-mortem brain samples from PD and healthy control patients. Our data revealed a specific subpopulation of nanoscale oligomers that represent an early hallmark of the proteinopathy that underlies PD. We anticipate that quantitative information about oligomer distributions provided by ASA-PD will enable mechanistic studies to reveal the pathological processes caused by -synuclein aggregation.

neuroscience↗

bioRxiv2023

RASP: Optimal single fluorescent puncta detection in complex cellular backgrounds

Super-resolution and single-molecule microscopy are increasingly applied to complex biological systems. A major challenge of this approach is that fluorescent puncta must be detected in the low signal, high noise, heterogeneous background environments of cells and tissue. We present RASP, Radiality Analysis of Single Puncta, a bioimaging-segmentation method that solves this problem. RASP removes false positive puncta that other analysis methods detect, and detects features over a broad range of spatial scales: from single proteins to complex cell phenotypes. RASP outperforms the state-of-the-art in precision and speed, using image gradients to separate Gaussian-shaped objects from background. We demonstrate RASPs power by showing it can extract spatial correlations between microglia, neurons, and -synuclein oligomers in the human brain. This sensitive, computationally efficient approach enables fluorescent puncta and cellular features to be distinguished in cellular and tissue environments with a sensitivity down to the level of the single protein.

biophysics↗

bioRxiv2023

Single-cell transcriptomic analysis of immune cell dynamics in the healthy human endometrium

The microenvironment of the endometrial immune system is crucial to the success of placental implantation and healthy pregnancy. However, the functionalities of immune cells across various stages of the reproductive cycle have yet to be fully comprehended. To address this, we conducted advanced bioinformatic analyses on 230,049 high-quality single-cell transcriptomes from healthy endometrial samples obtained during the proliferative, secretory, early pregnancy, and late pregnancy stages. Our investigation revealed that proliferative natural killer (NK) cells, a potential source of endometrial NK cells, exhibit the most robust proliferative and differentiation potential during non-pregnant stages. During early pregnancy, NK cells display high oxidative phosphorylation metabolism activity, and together with macrophages and T cells, exhibit a strong type II interferon response. Based on our cell-cell interaction analyses, we identify a large majority of interaction pairs to occur in late pregnancy. Finally, we explored the correlation between stage-specific alterations in transcriptomics and the risk genes of common reproductive diseases, unveiling that MHC class I/II molecules, along with TGFBR1, exhibited the potential to serve as biomarkers. Our study provides insights into the dynamics of the endometrial immune microenvironment during different reproductive cycle stages, thus serving as a reference for detecting pathological changes during pregnancy.

bioinformatics↗

bioRxiv2023

Multi-modal microvascular cerebral blood flow velocity mapping with 14T single-vessel MRI and optical microscopy in the mouse brain

In this study, we imaged the same penetrating cortical vessels in a mouse using ultrahigh field single-vessel MRI at 14 T and high-resolution optical microscopy imaging. The optical imaging was performed through a chronic sealed cranial window, while the single-vessel MRI was facilitated by a custom-designed, chronically implanted radiofrequency coil surrounding the window. The MRI and optical imaging were performed sequentially focused on the same penetrating cortical arterioles and surfacing venules within the whisker barrel cortex. With MRI, we obtained high-resolution multi-gradient echo (MGE) images and single-vessel phase contrast (PC) velocity maps. With optical imaging, we acquired microvascular angiograms using 2-Photon Microscopy (2PM) and Optical Coherence Tomography (OCT) and measured the blood flow velocity using Dynamic Light Scattering OCT (DLS-OCT). The MGE images, PC-based MRI velocity maps, OCT angiograms, and DLS-OCT velocity maps were coregistered with the 2PM microvascular angiograms. Using these tools, we cross-validated blood flow velocity in the penetrating cortical arterioles and surfacing venules measured by single-vessel MRI and OCT at rest. Our novel method demonstrates the possibility of combining ultrahigh field single-vessel MRI and high-resolution optical methods (e.g., 2PM and OCT) for studying brain structure and function with single microvessel precision.

bioengineering↗

bioRxiv2023

A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis

The contribution of epistasis (interactions among genes or genetic variants) to human complex trait variation remains poorly understood. Methods that aim to explicitly identify pairs of genetic variants, usually single nucleotide polymorphisms (SNPs), associated with a trait suffer from low power due to the large number of hypotheses tested while also having to deal with the computational problem of searching over a potentially large number of candidate pairs. An alternate approach involves testing whether a single SNP modulates variation in a trait against a polygenic background. While overcoming the limitation of low power, such tests of polygenic or marginal epistasis (ME) are infeasible on Biobank-scale data where hundreds of thousands of individuals are genotyped over millions of SNPs. We present a method to test for ME of a SNP on a trait that is applicable to biobank-scale data. We performed extensive simulations to show that our method provides calibrated tests of ME. We applied our method to test for ME at SNPs that are associated with 53 quantitative traits across {approx} 300 K unrelated white British individuals in the UK Biobank (UKBB). Testing 15, 601 trait-loci associations that were significant in GWAS, we identified 16 trait-loci pairs across 12 traits that demonstrate strong evidence of ME signals (p-value [Formula]). We further partitioned the significant ME signals across the genome to identify 6 trait-loci pairs with evidence of local (within-chromosome) ME while 15 show evidence of distal (cross-chromosome) ME. Across the 16 trait-loci pairs, we document that the proportion of trait variance explained by ME is about 12x as large as that explained by the GWAS effects on average (range: 0.59 to 43.89). Our results show, for the first time, evidence of interaction effects between individual genetic variants and overall polygenic background modulating complex trait variation.

genetics↗

bioRxiv2023

How formate dehydrogenase-lacking acetogen Clostridium bovifaecis utilize formate as the sole carbon source for its acetogenic growth?

Little is known about the growth of formate dehydrogenase-lacking acetogen on formate as sole carbon source. Here, we analyzed formate metabolism in Clostridium bovifaecis strain BXX using different concentrations of formate. The results show that C. bovifaecis converted formate (11.5-96 mM) into acetate with molar ratio of 2.0:1[~]2.6:1 by using L-cysteine in the anaerobic medium as electron source according to the stoichiometry of acetogenesis. Genome analysis of C. bovifaecis revealed genes encoding anaerobic ribonucleoside triphosphate reductase (nrdD and nrdG) catalyzing the oxidation of formate to CO2 while ATP is being reduced to the desoxy form. The existence of nrdD was verified by PCR, reverse transcription-PCR analysis and acetogenesis from formate. The process mode of acetogenesis from formate in C. bovifaecis provides insight into the unique metabolic feature of an FDH-lacking acetogen. IMPORTANCEWood-Ljungdahl pathway (WLP) lacking formate dehydrogenase (FDH) which catalyzes CO2 reduction to formate has been reported to occur acetogenesis only in the presence of formate and exogenous CO2, which seems to result from the formate-rich habitats adaptation of gastrointestinal acetogens. Here, we found FDH-lacking Clostridium bovifaecis strain BXX converted formate (11.5-96 mM) into acetate with molar ratio of 2.0:1[~]2.6:1 fitting the stoichiometry of acetogenesis when using formate as the sole carbon source. CO2 needed in the carbonyl branch of WLP was from the oxidation of formate to CO2 catalyzed by anaerobic ribonucleoside triphosphate reductase while ATP is being reduced to the desoxy form. L-cysteine in the anaerobic medium was the electron source of WLP. The process mode of acetogenesis from formate in C. bovifaecis provides insight into how an FDH-lacking acetogen can make a living from the simplest resources as carbon source, which has both ecological and biotechnological significance.

microbiology↗

bioRxiv2023

A Cellular Platform for Production of C4 Monomers

Living organisms carry out a wide range of remarkable functions, including the synthesis of thousands of simple and complex chemical structures for cellular growth and maintenance. The manipulation of this reaction network has allowed for the genetic engineering of cells for targeted chemical synthesis, but it remains challenging to alter the program underlying their fundamental chemical behavior. By taking advantage of the unique ability of living systems to use evolution to find solutions to complex problems, we have achieved ~95% theoretical yield of three C4 commodity chemicals, n-butanol, 1,3-butanediol, and 4-hydroxy-2-butanone. Genomic sequencing of the evolved strains identified pcnB and rpoBC as two gene loci that are able to alter carbon flow by remodeling the transcriptional landscape of the cell, highlighting the potential of synthetic pathways as a tool to identify metabolic control points.

synthetic biology↗

bioRxiv2023

Leveraging family data to design Mendelian Randomization that is provably robust to population stratification

Mendelian Randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases due to weak instruments as well as the confounding effects of population stratification and horizontal pleiotropy. Here, we show that family data can be leveraged to design MR tests that are provably robust to confounding from population stratification, assortative mating, and dynastic effects. We demonstrate in simulations that our approach, MR-Twin, is robust to confounding from population stratification and is not affected by weak instrument bias, while standard MR methods yield inflated false positive rates. We applied MR-Twin to 121 trait pairs in the UK Biobank dataset and found that MR-Twin identifies likely causal trait pairs and does not identify trait pairs that are unlikely to be causal. Our results suggest that confounding from population stratification can lead to false positives for existing MR methods, while MR-Twin is immune to this type of confounding.

genetics↗

bioRxiv2022

The origin of a new chromosome in gerbils

Chromosome-scale genome assemblies based on ultra-long read sequencing technologies are able to illuminate previously intractable aspects of genome biology such as fine-scale centromere structure and large-scale variation in genome features such as heterochromatin, GC content, recombination rate, and gene content. We present here a new chromosome-scale genome of the Mongolian gerbil (Meriones unguiculatus) which includes the complete sequence of all centromeres. Gerbil centromeres are composed of four different repeats of length 6pb, 37bp, 127bp, or 1747bp which occur in simple alternating arrays and span 1-6Mb. Gerbil genomes have both an extensive set of GC-rich genes and chromosomes strikingly enriched for constitutive heterochromatin. We sought to determine if there was a link between these two phenomena and found that the two heterochromatic chromosomes of the Mongolian gerbil have distinct underpinnings: Chromosome 5 has a large block of intra-arm heterochromatin as the result of a massive expansion of centromeric repeats, while chromosome 13 is comprised of extremely large (>150kb) repeated sequences. In addition to characterizing centromeres, our results demonstrate the importance of including karyotypic features such as chromosome number and the locations of centromeres in the interpretation of genome sequence data, and highlight novel patterns involved in the evolution of chromosomes.

genomics↗

bioRxiv2022

LLPSWise - fast and accurate prediction of LLPS constituents

The recent discovery of different types of biological liquid-liquid phase separation (LLPS) systems presents enormous opportunities to uncover underlying biological mechanisms from a single-molecule level to mesoscopic scales and beyond. While progress has been made on the front of computational prediction of LLPS propensity of proteins, the constituent identification of LLPS systems continues to be a pertinent issue that has yet to be addressed. Compiled evidence indicates that the biological mechanism of LLPS involves the employment of different biomolecules into their liquid-liquid separation phase. Since constituent identification relies on experimental approaches, the process is arduous and inefficient. Here, we propose a sequence based LLPS propensity prediction method and scan the human proteome and biochemical pathways to establish a systematic biological view of LLPS. Additionally, we present a fast, accurate method for identifying the constituents of LLPS systems. The source code for our method is available via https://github.com/promethiume/LLPSWise

bioinformatics↗

bioRxiv2022

Accurate simultaneous sequencing of genetic and epigenetic bases in DNA

DNA comprises molecular information stored via genetic bases (G, C, T, A) and also epigenetic bases, principally 5-methylcytosine (5mC) and 5-hydroxymethylcytosine (5hmC). Both genetic and epigenetic information are vital to our understanding of biology and disease states. Most DNA sequencing approaches address either genetics or epigenetics and thus capture incomplete information. Methods widely used to detect epigenetic DNA bases typically fail to capture common C-to-T mutations or distinguish 5mC from 5hmC. Here, we present a single-base-resolution sequencing methodology that will simultaneously sequence complete genetics and complete epigenetics in a single workflow. The approach is non-destructive to DNA and provides a digital readout of bases, which we exemplify by simultaneous sequencing of G, C, T, A, 5mC and 5hmC; 6-Letter sequencing. We demonstrate sequencing of human genomic DNA and also cell-free DNA taken from a blood sample of a cancer patient. The approach is accurate, requires low DNA input and has a simple workflow and analysis pipeline. We envisage it will be versatile across many applications in life sciences.

genomics↗

bioRxiv2022

Fast Kernel-based Association Testing of non-linear genetic effects for Biobank-scale data

Our knowledge of non-linear genetic effects on complex traits remains limited, in part, due to the modest power to detect such effects. While kernel-based tests offer a powerful approach to test for nonlinear relationships between sets of genetic variants and traits, current approaches cannot be applied to Biobank-scale datasets containing hundreds of thousands of individuals. We propose, FastKAST, a Kernel-based approach that can test for non-linear effects of a set of variants on a trait. FastKAST provides calibrated hypothesis tests while enabling analysis of Biobank-scale datasets with hundreds of thousands of individuals. We applied FastKAST to thirty quantitative traits measured across {approx} 300 K unrelated white British individuals in the UK Biobank to detect sets of variants with nonlinear effects at genome-wide significance.

genetics↗