Biology subjects

Fan, J.

Publications and source records attributed to Fan, J..

At least 127 records · Page 7Linked to original sources

bioRxiv2023

Reactive nitrogen species inhibit branched chain alpha-ketoacid dehydrogenasecomplex and impact muscle cell metabolism

Branched chain -ketoacid dehydrogenase complex (BCKDC) is the rate limiting enzyme in branched chain amino acid (BCAA) catabolism, a metabolic pathway with great importance for human health. BCKDC belongs to the mitochondrial -ketoacid dehydrogenase complex family, which also includes pyruvate dehydrogenase complex (PDHC) and oxoglutarate dehydrogenase complex (OGDC). Here we revealed that BCKDC can be substantially inhibited by reactive nitrogen species (RNS) via a mechanism similar to what we recently discovered with PDHC and OGDC -- modifying the lipoic arm on its E2 subunit. In addition, we showed that such reaction between RNS and the lipoic arm of the E2 subunit can further promote inhibition of the E3 subunits of -ketoacid dehydrogenase complexes. We examined the impacts of this RNS-mediated BCKDC inhibition in muscle cells, an important site of BCAA metabolism, and demonstrated that the nitric oxide production induced by cytokine stimulation leads to a strong inhibition of BCKDC activity and BCAA oxidation in myotubes and myoblasts. More broadly, nitric oxide production reduced the level of functional lipoic arms across the multiple -ketoacid dehydrogenases and led to intracellular accumulation of their substrates (-ketoacids), reduction of their products (acyl-CoAs), and a lower cellular energy charge. This work revealed a new mechanism for BCKDC regulation, demonstrated its biological significance, and elucidated the mechanistic connection between RNS-driven inhibitory modifications on the E2 and E3 subunits of -ketoacid dehydrogenases. Together with previous work, we revealed a general mechanism for RNS to inhibit all -ketoacid dehydrogenases, which has numerous physiological implications across multiple cell types.

biochemistry↗

bioRxiv2023

Meta-colored compacted de Bruijn graphs: overview and challenges

MotivationThe colored compacted de Bruijn graph (c-dBG) has become a fundamental tool used across several areas of genomics and pangenomics. For example, it has been widely adopted by methods that perform read mapping or alignment, abundance estimation, and subsequent downstream analyses. These applications essentially regard the c-dBG as a map from k-mers to the set of references in which they appear. The c-dBG data structure should retrieve this set -- the color of the k-mer -- efficiently for any given k-mer, while using little memory. To aid retrieval, the colors are stored explicitly in the data structure and take considerable space for large reference collections, even when compressed. Reducing the space of the colors is therefore of utmost importance for large-scale sequence indexing. ResultsWe describe the meta-colored compacted de Bruijn graph (Mac-dBG) -- a new colored de Bruijn graph data structure where colors are represented holistically, i.e., taking into account their redundancy across the whole collection being indexed, rather than individually as atomic integer lists. This allows the factorization and compression of common sub-patterns across colors. While optimizing the space of our data structure is NP-hard, we propose a simple heuristic algorithm that yields practically good solutions. Results show that the Mac-dBG data structure improves substantially over the best previous space/time trade-off, by providing remarkably better compression effectiveness for the same (or better) query efficiency. This improved space/time trade-off is robust across different datasets and query workloads. Code availabilityA C++17 implementation of the Mac-dBG is publicly available on GitHub at: https://github.com/jermp/fulgor.

bioinformatics↗

bioRxiv2023

Identification and Description of Emotions by Current Large Language Models

The assertion that artificial intelligence (AI) cannot grasp the complexities of human emotions has been a long-standing debate. However, recent advancements in large language models (LLMs) challenge this notion by demonstrating an increased capacity for understanding and generating human-like text. In this study, we evaluated the empathy levels and the identification and description of emotions by three current language models: Bard, GPT 3.5, and GPT 4. We used the Toronto Alexithymia Scale (TAS-20) and the 60-question Empathy Quotient (EQ-60) questions to prompt these models and score the responses. The models performance was contrasted with human benchmarks of neurotypical controls and clinical populations. We found that the less sophisticated models (Bard and GPT 3.5) performed inferiorly on TAS-20, aligning close to alexithymia, a condition with significant difficulties in recognizing, expressing, and describing ones or others experienced emotions. However, GPT 4 achieved performance close to the human level. These results demonstrated that LLMs are comparable in their ability to identify and describe emotions and may be able to surpass humans in their capacity for emotional intelligence. Our novel insights provide alignment research benchmarks and a methodology for aligning AI with human values, leading toward an empathetic AI that mitigates risk.

neuroscience↗

bioRxiv2023

Coenyzme Q4 is a functional substitute for coenyzme Q10 and can be targeted to the mitochondria

Coenzyme Q10 (CoQ10) is an important cofactor and antioxidant for numerous cellular processes, and its deficiency has been linked to human disorders including mitochondrial disease, heart failure, Parkinsons disease, and hypertension. Unfortunately, treatment with exogenous oral CoQ10 is often ineffective, likely due to the extreme hydrophobicity and high molecular weight of CoQ10. Here, we show that less hydrophobic CoQ species with shorter isoprenoid tails can serve as viable substitutes for CoQ10 in human cells. We demonstrate that CoQ4 can perform multiple functions of CoQ10 in CoQ-deficient cells at markedly lower treatment concentrations, motivating further investigation of CoQ4 as a supplement for CoQ10 deficiencies. In addition, we describe the synthesis and evaluation of an initial set of compounds designed to target CoQ4 selectively to mitochondria using triphenylphosphonium (TPP). Our results indicate that select versions of these compounds can successfully be delivered to mitochondria in a cell model and be cleaved to produce CoQ4, laying the groundwork for further development.

biochemistry↗

bioRxiv2023

Single-molecule digital sizing of proteins in solution

Proteins constitute the molecular machinery of life and exert their biological function by interacting with other proteins, as well as by assembling into biomolecular complexes and higher order structures. Characterizing the sizes, interactions, and assembly states of proteins is thus key for understanding the normal functional behavior of proteins and for elucidating aberrant processes and interactions that can lead to dysfunction and disease. However, the physical characterization of proteins has remained a challenging problem due to the inherent compositional heterogeneity of protein mixtures as well as the polydisperse nature of protein complexes. Here, we address this challenge by demonstrating measurements of molecular diffusivity of single proteins and protein assemblies in microchannels using single-molecule fluorescence detection. The approach, termed single-molecule microfluidic diffusional sizing (smMDS), allows individual molecules to be counted directly, that is, in a digital manner, to enable calibration-free single-molecule diffusional-sizing-based monitoring of protein hydrodynamic radii even within heterogenous multicomponent mixtures. Applying smMDS to a variety of protein systems, we show that the high sensitivity provided by smMDS enables ultrasensitive sizing of proteins down to the femtomolar concentration range. We further demonstrate the applicability of the approach towards affinity profiling of protein interactions at the single-molecule level and illustrate the potential of smMDS in resolving different assembly states of high- and low-molecular weight protein oligomers. Furthermore, we highlight the digital nature of the detection process by sizing multiple protein species within complex aggregation mixtures. Finally, we apply the approach to characterize nanoscale clusters of a phase separating protein system. Taken together, smMDS constitutes a versatile approach for digital, in-solution characterization of the sizes, interactions, and assembly states of proteins. We anticipate that smMDS will facilitate the discovery of new biomolecular mechanisms of proteins and will find broad applicability in the analysis of protein complexes in the biological, biophysical, and biomedical sciences, and beyond.

biophysics↗

bioRxiv2023

Real-time targeted illumination in widefield microscopy achieves confocal quality neuronal images

Widefield fluorescence imaging has significant challenges in visualizing neuronal fibers near cell bodies. Specifically, out-of-focus and scattered light from the bright cellbody often obscures nearby dim fibers and degrades their signal-to-background ratio. Scanning techniques can solve this problem but are limited by reduced imaging speed and increased cost. We greatly reduce stray light by modulating the illumination intensity to different structures. We use a digital micromirror device in the illumination channel of a common widefield microscope and use real-time image processing to pattern the illumination. With the setup, we illuminate bright cell bodies with minimal light intensity, and illuminate in focus fiber-like structures with high light intensity to reveal weak signals. Thus, we minimize the background and enhance the visibility of fibers in the final image. This targeted illumination significantly improves fiber contrast while maintaining a fast-imaging speed and low cost. Using a targeted illumination setup in a widefield microscope, we demonstrate confocal quality imaging of complex neurons in live C. elegans and zebrafish larva, as well as in in vitro mice brain slice.

neuroscience↗

bioRxiv2023

African swine fever virus I196L is a virulence determinant and its deletant induces robust protection in Domestic pig

The worldwide pandemic of African swine fever virus (ASFV) has a profound impact on the global pig industry. ASFV is a complex multilayered structure and the functions of unknown genes are being revealed. Here we deleted I196L from virulent ASFV SY18 with different length and obtained two recombinant viruses. The replication efficiency of the two recombinant viruses were similar but significantly lower than parental SY18. The pigs all survived the two recombinant viruses with 106.0TCID50 except one pig occurred sudden death and the suvived pigs all resisted the challenge without fever after intramuscularly injecting a lethal dose (102.0TCID50) of ASFV SY18. The recombinant viruses induced a strong anti-p54 humoral immune response. Meanwhile, the pigs also inevitably appeared moderate to high viremia throughout the observation period and presented a gradually downward trend. The results show that deleting I196L gene is a potential and effective vaccine that protects pigs from ASFV. IMPORTANCEThe worldwide outbreak of African swine fever (ASF) cannot be effectively prevented due to no availably commercial vaccine. Many different types of vaccine candidates are researched and reported, which is a hopeful trend to develop safety and efficacy vaccine. Here we report on an unknown functional gene, I196L, which affects the virulence and replication of ASFV. When I196L was deleted from ASFV SY18, the recombinant virus decreased virulence and resisted the challenge of parental strain. This is a novel, effective, potential live attenuated vaccine (LAVs) for ASF.

immunology↗

bioRxiv2023

Spatial redundancy transformer for self-supervised fluorescence image denoising

Fluorescence imaging with high signal-to-noise ratios has become the foundation of accurate visualization and analysis of biological phenomena. However, the inevitable photon shot noise poses a formidable challenge on imaging sensitivity. In this paper, we provide a spatial redundancy denoising transformer (SRDTrans) to remove noise from fluorescence images in a self-supervised manner. First, a sampling strategy based on spatial redundancy is proposed to extract adjacent orthogonal training pairs, which eliminates the dependence on high imaging speed. Secondly, to break the performance bottleneck of convolutional neural networks (CNNs), we designed a lightweight spatiotemporal transformer architecture to capture long-range dependencies and high-resolution features at a low computational cost. SRDTrans can overcome the inherent spectral bias of CNNs and restore high-frequency information without producing over-smoothed structures and distorted fluorescence traces. Finally, we demonstrate the state-of-the-art denoising performance of SRDTrans on single-molecule localization microscopy and two-photon volumetric calcium imaging. SRDTrans does not contain any assumptions about the imaging process and the sample, thus can be easily extended to a wide range of imaging modalities and biological applications.

biophysics↗

bioRxiv2023

Fulgor: A fast and compact k-mer index for large-scale matching and color queries

The problem of sequence identification or matching -- determining the subset of references from a given collection that are likely to contain a query nucleotide sequence -- is relevant for many important tasks in Computational Biology, such as metagenomics and pan-genome analysis. Due to the complex nature of such analyses and the large scale of the reference collections a resource-efficient solution to this problem is of utmost importance. The reference collection should therefore be pre-processed into an index for fast queries. This poses the threefold challenge of designing an index that is efficient to query, has light memory usage, and scales well to large collections. To solve this problem, we describe how recent advancements in associative, order-preserving, k-mer dictionaries can be combined with a compressed inverted index to implement a fast and compact colored de Bruijn graph data structure. This index takes full advantage of the fact that unitigs in the colored de Bruijn graph are monochromatic (all k-mers in a unitig have the same set of references of origin, or "color"), leveraging the order-preserving property of its dictionary. In fact, k-mers are kept in unitig order by the dictionary, thereby allowing for the encoding of the map from k-mers to their inverted lists in as little as 1 + o(1) bits per unitig. Hence, one inverted list per unitig is stored in the index with almost no space/time overhead. By combining this property with simple but effective compression methods for inverted lists, the index achieves very small space. We implement these methods in a tool called Fulgor. Compared to Themisto, the prior state of the art, Fulgor indexes a heterogeneous collection of 30,691 bacterial genomes in 3.8x less space, a collection of 150,000 Salmonella enterica genomes in approximately 2 x less space, is at least twice as fast for color queries, and is 2 - 6x faster to construct. 2012 ACM Subject ClassificationApplied computing [->] Bioinformatics

bioinformatics↗

bioRxiv2023

Population genomics reveals extensive inbreeding and purging of mutational load in wild Amur tigers

The inbreeding is a big threat for the persistence of genetic diversity in small and isolated populations of endangered species. The homozygous genome could exacerbate inbreeding depression by introducing homozygous deleterious alleles in the population. However, purging of inbreeding loads as they become homozygotes in small populations could alleviate the depression. The Amur tiger (Panthera tigris altaica) is typically exists in small population living in forests in Northeast Asia and is among the most endangered animals on the planet with great symbolic significance of conservation. By comparing with captive individuals, we revealed substantially higher and more extensive inbreeding in the wild Amur tiger population (FROH=0.51) than in captive Amur tigers (FROH=0.26). We further found much less mutational loads in wild populations when compared with captive Amur tigers. However, the frequency of loss of function and deleterious nonsynonymous mutations inside ROH regions are much lower than that in non-ROH regions in both wild and captive Amur tigers, indicating the purging may had occurred in both populations but much effective in the wild population. In addition, we found the average frequency of deleterious alleles was much lower than that of neutral alleles in the wild population, indicating that the purifying selection contributed to the purging of mutational loads in the wild Amur tigers. These findings provide valuable genome-wide evidence to support the making of future conservation plans of wild Amur tigers.

genomics↗

bioRxiv2023

Leveraging the power of 3D brain-wide imaging and mapping tools for brain injury research in murine models

Despite the fundamental importance of understanding impaired brain activity exhibited in post-traumatic epilepsy and other neurological impairments associated with traumatic brain injury (TBI), knowledge of how brain injury affects neuronal activity remains remarkably incomplete. We describe a whole-brain imaging and analysis approach to identify alterations in neuronal activity after TBI as a complementary method to conventional two-dimensional (2D) histological approaches. Here we report an easy-to-follow experimental pipeline to quantify changes in the whole mouse brain using tissue clearing, light sheet microscopy (LSM) and an optimised open-access atlas registration workflow. We validated the outcome of the pipeline using high throughput image analysis software and a secondary atlas registration method. Using the CHIMERA (Closed-Head Impact Model of Engineered Rotational Acceleration) TBI model, TRAP2 mice were subjected to repeated mild TBI or sham treatment followed by tamoxifen injection to lock c-Fos activity after TBI. Brains were SHIELD fixed and passively cleared for imaging of c-Fos+ cells throughout the rostro-caudal axis of the brain using a light sheet microscope equipped with a specialized whole-brain imaging chamber. Volumetric images were stitched and 3D rendered using Arivis Vision4D image analysis software. For quantitative analysis, 2D image stacks were exported to segment c-Fos+ cells and register them to the Allen Mouse Brain Atlas using the BrainQuant3D python package. As a result, c-Fos+ cell counts were estimated throughout the brain and heatmaps were generated. We identified a brain-wide reduction in c-Fos cell density in the TBI group compared to sham controls, indicative of TBI-induced changes in whole brain neuronal activity. Further studies using multi-dimensional imaging coupled with analysis tools will deepen our understanding of post-TBI brain-wide dynamics.

neuroscience↗

bioRxiv2023

Climate, host and geography shape insect and fungal communities of trees

Non-native pests, climate change, and their interactions are likely to alter relationships between trees and tree-associated organisms with consequences for forest health. To understand and predict such changes, factors structuring tree-associated communities need to be determined. Here, we analysed the data consisting of records of insects and fungi collected from dormant twigs from 155 tree species at 51 botanical gardens or arboreta in 32 countries. Generalized dissimilarity models revealed similar relative importance of studied climatic, host-related and geographic factors on differences in tree-associated communities. Mean annual temperature, phylogenetic distance between hosts and geographic distance between locations were the major drivers of dissimilarities. The increasing importance of high temperatures on differences in studied communities indicate that climate change could affect tree-associated organisms directly and indirectly through host range shifts. Insect and fungal communities were more similar between closely related vs. distant hosts suggesting that host range shifts may facilitate the emergence of new pests. Moreover, dissimilarities among tree-associated communities increased with geographic distance suggesting that human-mediated transport may facilitate the introductions of new pests. The results of this study highlight the need to limit the establishment of tree pests and increase the resilience of forest ecosystems to changes in climate.

ecology↗

bioRxiv2023

Alignment of spatial transcriptomics data using diffeomorphic metric mapping

Spatial transcriptomics (ST) technologies enable high throughput gene expression characterization within thin tissue sections. However, comparing spatial observations across sections, samples, and technologies remains challenging. To address this challenge, we developed STalign to align ST datasets in a manner that accounts for partially matched tissue sections and other local non-linear distortions using diffeomorphic metric mapping. We apply STalign to align ST datasets within and across technologies as well as to align ST datasets to a 3D common coordinate framework. We show that STalign achieves high gene expression and cell-type correspondence across matched spatial locations that is significantly improved over landmark-based affine alignments. Applying STalign to align ST datasets of the mouse brain to the 3D common coordinate framework from the Allen Brain Atlas, we highlight how STalign can be used to lift over brain region annotations and enable the interrogation of compositional heterogeneity across anatomical structures. STalign is available as an open-source Python toolkit at https://github.com/JEFworks-Lab/STalign and as supplementary software with additional documentation and tutorials available at https://jef.works/STalign.

bioinformatics↗

bioRxiv2023

Senescence-specific translation dysregulation desensitizes cells to stress by inhibiting activation of the integrated stress response

Senescence is a state of indefinite cell cycle arrest associated with aging, cancer, and age-related diseases. Here, using label-based mass spectrometry, ribosome profiling and nanopore direct RNA sequencing, we explore the coordinated interaction of translational and transcriptional programs of human cellular senescence. We find that translational deregulation and a corresponding maladaptive integrated stress response (ISR) is a hallmark of senescence that desensitizes senescent cells to stress. We present evidence that senescent cells maintain high levels of eIF2 phosphorylation, typical of ISR activation, but translationally repress production of the stress response transcription factor 4 (ATF4) by ineffective bypass of the inhibitory upstream open reading frames. Surprisingly, ATF4 translation remains inhibited even after acute proteotoxic and amino acid starvation stressors, resulting in a highly diminished stress response. Furthermore, absent a response, stress augments the senescence secretory phenotype, thus intensifying a proinflammatory state that exacerbates disease. Our results reveal a novel mechanism that senescent cells exploit to evade an adaptive stress response and remain viable.

molecular biology↗

bioRxiv2023

A Universal Method for Crossing Molecular and Atlas Modalities using Simplex-Based Image Varifolds and Quadratic Programming

This paper explicates a solution to the problem of building correspondences between molecular-scale transcriptomics and tissue-scale atlases. The central model represents spatial transcriptomics as generalized functions encoding molecular position and high-dimensional transcriptomic-based (gene, cell type) identity. We map onto low-dimensional atlas ontologies by modeling each atlas compartment as a homogeneous random field with unknown transcriptomic feature distribution. The algorithm presented solves simultaneously for the minimizing geodesic diffeomorphism of coordinates and latent atlas transcriptomic feature fractions by alternating LDDMM optimization for coordinate transformations and quadratic programming for the latent transcriptomic variables. We demonstrate the universality of the algorithm in mapping tissue atlases to gene-based and cell-based MERFISH datasets as well as to other tissue scale atlases. The joint estimation of diffeomorphisms and latent feature distributions allows integration of diverse molecular and cellular datasets into a single coordinate system and creates an avenue of comparison amongst atlas ontologies for continued future development.

bioengineering↗

bioRxiv2023

A hyper-quiescent chromatin state formed during aging is reversed by regeneration

Epigenetic alterations are a key hallmark of aging but have been limitedly explored in tissues. Here, using naturally aged murine liver as a model and extending to other quiescent tissues, we find that aging is driven by temporal chromatin alterations that promote a refractory cellular state and compromise cellular identity. Using an integrated multi-omics approach, and the first direct visualization of aged chromatin we find that globally, old cells show H3K27me3-driven broad heterochromatinization and transcription suppression. At the local level, site-specific loss of H3K27me3 over promoters of genes encoding developmental transcription factors leads to expression of otherwise non-hepatocyte markers. Interestingly, liver regeneration reverses H3K27me3 patterns and rejuvenates multiple molecular and physiological aspects of the aged liver.

genomics↗

bioRxiv2023

SynEcoSys: a multifunctional platform of large-scale single-cell omics data analysis

Next generation sequencing technologies enable the analysis of the transcriptomes of individual cells, providing a higher resolution of gene expression and function at the single cell level. Various single-cell data are continuously generated every year, covering fields from scientific research to clinical development. The fast-growing public datasets are collected by distinctive platforms, which are designed to facilitate biological discoveries, disease diagnosis, and new treatments. However, these platforms are hard to meet the urgency of having a unified data integration pipeline to improve comparability between datasets. Here we present SynEcoSys, an online multifunctional platform for single-cell transcriptomic data analysis, visualization, and exploration. SynEcoSys by Singleron Biotechnologies currently provides a massive collection of publicly available single-cell sequencing dataset, involving 46,326,175 cells from 731 datasets across multiple platforms and species. All datasets are generated with a strict and uniform data analysis pipeline and cell marker-based manual annotation, thus facilitating more comprehensive and reliable data mining. SynEcoSys is available at: https://www.synecosys.com.

bioinformatics↗

bioRxiv2023

Gene body DNA hydroxymethylation restricts the magnitude of transcriptional changes during aging

DNA hydroxymethylation (5hmC), the most abundant oxidative derivative of DNA methylation, is typically enriched at enhancers and gene bodies of transcriptionally active and tissue-specific genes. Although aberrant genomic 5hmC has been implicated in age-related diseases, its functional role in aging remains unknown. Here, using mouse liver and cerebellum as model organs, we show that 5hmC accumulates in gene bodies associated with tissue-specific function and restricts the magnitude of gene expression changes with age. Mechanistically, 5hmC decreases the binding of splicing associated factors and correlates with age-related alternative splicing events. We found that various age-related contexts, such as prolonged quiescence and senescence, drive the accumulation of 5hmC with age. We provide evidence that this age-related transcriptionally restrictive function is conserved in mouse and human tissues. Our findings reveal that 5hmC regulates tissue-specific function and may play a role in longevity.

genomics↗