Biology subjects

Jiang, D.

Publications and source records attributed to Jiang, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2024

A Computational Framework to Optimize the Mechanical Behavior of Synthetic Vascular Grafts

The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.

bioengineering↗

bioRxiv2024

STAMBPL1 activates the GRHL3/HIF1A/VEGFA axis through interaction with FOXO1 to promote angiogenesis in triple-negative breast cancer

In the clinic, anti-tumor angiogenesis is commonly employed for treating recurrent, metastatic, drug-resistant triple-negative and advanced breast cancer. Our previous research revealed that the deubiquitinase STAMBPL1 enhances the stability of MKP-1, thereby promoting cisplatin resistance in breast cancer. In this study, we discovered that STAMBPL1 could upregulate the expression of the hypoxia-inducible factor HIF1 in breast cancer cells. Therefore, we investigated whether STAMBPL1 promotes tumor angiogenesis. We demonstrated that STAMBPL1 increased HIF1A transcription in a non-enzymatic manner, thereby activating the HIF1/VEGFA signaling pathway to facilitate TNBC angiogenesis. Through RNA-seq analysis, we identified the transcription factor GRHL3 as a downstream target of STAMBPL1 that is responsible for mediating HIF1A transcription. Furthermore, we discovered that STAMBPL1 regulates GRHL3 transcription by interacting with the transcription factor FOXO1. These findings shed light on the role and mechanism of STAMBPL1 in the pathogenesis of breast cancer, offering novel targets and avenues for the treatment of triple-negative and advanced breast cancer.

cancer biology↗

bioRxiv2024

PepCleav: a classification method for evaluating the cleavability of peptide fragments presented by MHC class I

Neoantigens, due to their tumor specificity and lack of central tolerance, are promising targets for cancer immunotherapy. Evaluating the cleavability of peptide fragments generated by proteasomes and aminopeptidases is crucial for neoantigen identification, but tools for this purpose are scarce. To address this, we developed PepCleav, a method for evaluating peptide cleavability by classifying the amino acids at the proteasome and aminopeptidase recognition sites of the C- and N-termini. By integrating C- and N-terminal cleavability, PepCleav accurately predicted the overall cleavability of peptide fragments in test datasets, correctly identifying 84-89% of cleavable peptides and 63-92% of non-cleavable peptides. We also found that highly cleavable peptides have a higher likelihood of being effective neoantigens, highlighting PepCleavs potential to improve neoantigen identification. PepCleavs source code is publicly available at https://github.com/Dulab2020/PepCleav.

bioinformatics↗

bioRxiv2024

Genetic and selective constraints on the optimization of gene product diversity

RNA and protein expressed from the same gene can have diverse isoforms due to various post-transcriptional and post-translational modifications. For the vast majority of alternative isoforms, It is unknown whether they are adaptive or simply biological noise. As we cannot experimentally probe the function of each isoform, we can ask whether the distribution of isoforms across genes and across species is consistent with expectations from different evolutionary processes. However, there is currently no theoretical framework that can generate such predictions. To address this, we developed a mathematical model where isoform abundances are determined collectively by cis-acting loci, trans-acting factors, gene expression levels, and isoform decay rates to predict isoform abundance distributions across species and genes in the face of mutation, genetic drift, and selection. We found that factors beyond selection, such as effective population size and the number of cis-acting loci, significantly influence evolutionary outcomes. Notably, suboptimal phenotypes are more likely to evolve when the population is small and/or when the number of cis-loci is large. We also explored scenarios where modification processes have both beneficial and detrimental effects, revealing a non-monotonic relationship between effective population size and optimization, demonstrating how opposing selection pressures on cis- and trans-acting loci can constrain the optimization of gene product diversity. As a demonstration of the power of our theory, we compared the expected distribution of A-to-I RNA editing levels in coleoids and found this to be largely consistent with non-adaptive explanations.

evolutionary biology↗

bioRxiv2024

Improving positively tuned voltage indicators for brightness and kinetics

Existing positively tuned ASAP-family voltage indicators such as ASAP4e exhibit superior photostability compared to the negatively tuned ASAP3 and ASAP5, but signal-to-noise ratios for spike detection remained similar to ASAP3. To improve spike detection by positively tuned ASAP indicators, we performed multiple rounds of structure-guided saturation mutagenesis of an ASAP4e predecessor while screening directly for faster responses. One variant, ASAP6c, demonstrated [~]100% increases in fluorescence in response to single action potentials in both one-photon and two-photon imaging in vivo, achieving a 3-fold improvement in signal-to-noise ratios over ASAP4e.

neuroscience↗

bioRxiv2024

A commensal-derived sugar protects against metabolic disease

Obesity is a worsening global epidemic that is regulated by the microbiota through unknown bacterial factors. We discovered a human commensal bacterium, Clostridium immunis, that treats obesity by secreting a phosphocholine-modified exopolysaccharide. Loss- and gain-of-function bacterial mutants involving the phosphocholine biosynthesis locus (licABC) revealed the phosphocholine moiety is critically required to protect against metabolic disease. This C. immunis exopolysaccharide decreases small-intestinal and visceral fat levels of IL-22, which increases metabolic activity specifically in visceral adipose tissue. Importantly, phosphocholine biosynthesis genes are less abundant in humans with obesity or hypertriglyceridemia, findings that suggest the role of bacterial phosphocholine is conserved across mice and humans. These results define a bacterial molecule--and its key structural motif--that provides immunometabolic control of obesity. More broadly, they highlight a clinically translatable strategy to reduce visceral fat.

microbiology↗

bioRxiv2024

Commensal bacteria inhibit viral infections via a tryptophan metabolite

Clinical outcomes following viral exposures exhibit substantial interindividual variability. Although developing evidence suggests commensal bacteria modulate viral infections, the specific bacteria and mechanisms remain underexplored. Here we define a pathway by which viral infections are inhibited by specific tryptophan-catabolizing bacteria. Using HIV as a model, we bioinformatically associated and experimentally validated several bacterial species that inhibited viral replication. This activity required the aromatic amino acid aminotransferase (ArAT) to metabolize tryptophan into 3-indolelactic acid, which agonizes the aryl hydrocarbon receptor (AhR). Given that AhR regulates multiple viral infections, we found that commensal bacteria also inhibit cytomegalovirus (CMV) in an ArAT-dependent manner. Finally, we confirmed that ArAT is associated with protection against disease outcomes in three distinct human cohorts at-risk for HIV, CMV, or symptomatic COVID-19. Taken together, our results provide mechanistic insight into how commensal bacteria impact viral infections, thereby adding to an emerging field focused on host-commensal-virus interactions.

microbiology↗

bioRxiv2024

PPFlow: Target-aware Peptide Design with Torsional Flow Matching

Therapeutic peptides have proven to have great pharmaceutical value and potential in recent decades. However, methods of AI-assisted peptide drug discovery are not fully explored. To fill the gap, we propose a target-aware peptide design method called PPFO_SCPLOWLOWC_SCPLOW, based on conditional flow matching on torus manifolds, to model the internal geometries of torsion angles for the peptide structure design. Besides, we establish a protein-peptide binding dataset named PPBench2024 to fill the void of massive data for the task of structure-based peptide drug design and to allow the training of deep learning methods. Extensive experiments show that PPFO_SCPLOWLOWC_SCPLOW reaches state-of-the-art performance in tasks of peptide drug generation and optimization in comparison with baseline models, and can be generalized to other tasks including docking and side-chain packing.

molecular biology↗

bioRxiv2023

Identification of functional genes underlining growth in large yellow croaker

Large yellow croaker (Larimichthys crocea) is the largest cultured marine fish in China, although its economic benefits are significant, its growth cycle is long and it takes 2 years to market. Identification of genomic variations and genes affecting the growth of L. crocea is of great significance for breeding fast-growing strains by molecular means. We utilized whole genome resequencing to identify a highly effective GWAS locus on chromosome 6 of the genome, and identified some candidate genes that affect growth. This study provides a theoretical basis for analyzing the genetic mechanism of growth traits of L. crocea and cultivating fast-growing varieties.

genetics↗

bioRxiv2023

The Velvet transcription factor PnVeA regulates necrotrophic effectors and secondary metabolism in the wheat pathogen Parastagonospora nodorum

The fungus Parastagonospora nodorum causes septoria nodorum blotch on wheat. The role of the fungal Velvet-family transcription factor VeA in P. nodorum development and virulence was investigated here. Deletion of the P. nodorum VeA ortholog, PnVeA, resulted in growth abnormalities including pigmentation, abolished asexual sporulation and highly reduced virulence on wheat. Comparative RNA-Seq and RT-PCR analyses revealed that the deletion of PnVeA also decoupled the expression of major necrotrophic effector genes. In addition, the deletion of PnVeA resulted in an up-regulation of four predicted secondary metabolite (SM) gene clusters. Using liquid-chromatography mass-spectrometry, it was observed that one of the SM gene clusters led to an accumulation of the mycotoxin alternariol. PnVeA is essential for asexual sporulation, full virulence, secondary metabolism and necrotrophic effector regulation.

microbiology↗

bioRxiv2023

Absolute Quantification of Viral Proteins from Pseudotyped Vesicular Stomatitis Virus (VSV-GP) using Ultra High-Performance Liquid Chromatography- Multiple Reaction Monitoring (UPLC-MRM)

The rapidly developing field of oncolytic virus (OV) therapy necessitates development of new and improved analytical approaches for characterization of the virus during production and development. Accurate monitoring and absolute quantification of viral proteins is crucial for OV product characterization and can facilitate the understanding of infection, immunogenicity, and development stages of viral replication. Targeted mass spectrometry methods, like multiple reaction monitoring (MRM), offers a robust way to directly detect and quantify specific targeted proteins represented by surrogate peptides. We have leveraged the power of MRM by combining ultra-high performance liquid chromatography (UPLC) with a Sciex 6500 triple stage quadrupole mass spectrometer to develop an assay that accurately and absolutely quantifies the structural proteins of a pseudotyped vesicular stomatitis virus intended for use as a new biotherapeutic (designated hereafter as VSV-GP) to differentiate it from native VSV. The new UPLC-MRM method provides absolute quantification with the use of heavy labeled reference standard surrogate peptides. When added in known exact amounts to standards and samples, the reference standards normalize and account for any small perturbations during sample preparation and/or instrument performance, resulting in accurate and precise quantification. Because of the multiplexed nature of MRM all targeted proteins are quantified at the same time. The optimized assay has been enhanced to quantify the ratios of the processed GP1 and GP2 proteins while simultaneously measuring any remaining or unprocessed form of the envelope protein GPC (full-length GPC). IMPORTANCEDevelopment of oncolytic viral therapy has gained considerable momentum in the recent years. VSV-GP is a new biotherapeutic emerging in the oncolytic viral therapy platform. Novel analytical assays that can accurately and precisely quantify the viral proteins are a necessity for the successful development of viral vector as a biotherapeutic. We developed a UPLC-MRM based assay to quantify the absolute concentrations of the different structural proteins of VSV-GP. The complete processing of GPC is a pre-requisite for infectivity of the virus. The assay extends the potential for quantifying full-length GPC, which provides an understanding of the processing of GPC (along with the quantification of GP1 and GP2 separately). We used this assay in tracking GPC processing in HEK-293-F production cell lines infected with VSV-GP.

biochemistry↗

bioRxiv2023

Reduced SV2A and GABAA receptor levels in the brains of type 2 diabetic rats revealed by flumazenil PET

PurposeType 2 diabetes mellitus (T2DM) is associated with a greater risk of Alzheimers disease. Synaptic impairment and protein aggregates have been reported in the brains of T2DM models. Here, we assessed whether neurodegenerative changes in synaptic vesicle 2A (SV2A), {gamma};-aminobutyric acid type A (GABAA) receptor, amyloid-{beta}, tau and receptor for advanced glycosylation end product (RAGE) can be detected in vivo in T2DM rats. MethodsPositron emission tomography (PET) using [18F]SDM-8 (SV2A), [18F]flumazenil (GABAA receptor), [18F]florbetapir (amyloid-{beta}), [18F]PM-PBB3 (tau), and [18F]FPS-ZM1 (RAGE) was carried out in 12-month-old diabetic Zucker diabetic fatty (ZDF) and Sprague{square}Dawley (SD) rats. Proteomic profiling and pathway analysis of the hippocampus of ZDF and SD rats were performed. ResultsReduced cortical [18F]SDM-8 and cortical and hippocampal [18F]flumazenil uptake were observed in 12-month-old ZDF rats compared to SD rats. [18F]florbetapir and [18F]PM-PBB3 uptake were comparable in the brains of 12-month-old ZDF rats and SD rats. ConclusionThe findings provide in vivo evidence for regional reductions in SV2A and GABAA receptor levels in the brains of aged T2DM ZDF rats.

neuroscience↗

bioRxiv2023

XBB.1.5 Spike Protein COVID-19 Vaccine Induces Broadly Neutralizing and Cellular Immune Responses Against EG.5.1 and Emerging XBB Variants

Monovalent SARS-CoV-2 Prototype (Wuhan-Hu-1) and bivalent (Prototype + BA.4/5) COVID-19 vaccines have demonstrated a waning of vaccine-mediated immunity highlighted by lower neutralizing antibody responses against SARS-CoV-2 Omicron XBB sub-variants. The reduction of humoral immunity due to the rapid evolution of SARS-CoV-2 has signaled the need for an update to vaccine composition. A strain change for all authorized/approved vaccines to a monovalent composition with Omicron subvariant XBB.1.5 has been supported by the WHO, EMA, and FDA. Here, we demonstrate that immunization with a monovalent recombinant spike protein COVID-19 vaccine (Novavax, Inc.) based on the subvariant XBB.1.5 induces cross-neutralizing antibodies against XBB.1.5, XBB.1.16, XBB.2.3, EG.5.1, and XBB.1.16.6 subvariants, promotes higher pseudovirus neutralizing antibody titers than bivalent (Prototype + XBB.1.5) vaccine, induces SARS-CoV-2 spike-specific Th1-biased CD4+ T-cell responses against XBB subvariants, and robustly boosts antibody responses in mice and nonhuman primates primed with a variety of monovalent and bivalent vaccines. Together, these data support updating the Novavax vaccine to a monovalent XBB.1.5 formulation for the 2023-2024 COVID-19 vaccination campaign.

immunology↗

bioRxiv2023

Ascertainment bias in the genomic test of positive selection on regulatory sequences

Evolution of gene expression mediated by cis-regulatory changes is thought to be an important contributor to organismal adaptation, but identifying adaptive cis-regulatory changes is challenging due to the difficulty in knowing the expectation under no positive selection. A new approach for detecting positive selection on transcription factor binding sites (TFBSs) was recently developed, thanks to the application of machine learning in predicting transcription factor (TF) binding affinities of DNA sequences. Given a TFBS sequence from a focal species and the corresponding inferred ancestral sequence that differs from the former at n sites, one can predict the TF binding affinities of many n-step mutational neighbors of the ancestral sequence and obtain a null distribution of the derived binding affinity, which allows testing whether the binding affinity of the real derived sequence deviates significantly from the null distribution. Applying this test genomically to all experimentally identified binding sites of three TFs in humans, a recent study reported positive selection for elevated binding affinities of TFBSs. Here we show that this genomic test suffers from an ascertainment bias because, even in the absence of positive selection for strengthened binding, the binding affinities of known human TFBSs are more likely to have increased than decreased in evolution. We demonstrate by computer simulation that this bias inflates the false positive rate of the selection test. We propose several methods to mitigate the ascertainment bias and show that almost all previously reported positive selection signals disappear when these methods are applied.

evolutionary biology↗

bioRxiv2023

Alternative mutational architectures can produce identical M-matrices but lead to different macroevolutionary dynamics

Explaining macroevolutionary divergence in light of population genetics requires understanding the extent to which the patterns of mutational input contribute to long-term trends. In the context of quantitative traits, mutational input is typically described by the mutational variance-covariance matrix, or the M-matrix, which summarizes phenotypic variances and covariances introduced by new mutations per generation. However, as a summary statistic, the M-matrix does not fully capture all the relevant information from the underlying mutational architecture, and there exist infinitely many possible underlying mutational architectures that give rise to the same M-matrix. Using individual-based simulations, we demonstrate mutational architectures that produce the same M-matrix can lead to different levels of constraint on evolution and result in difference in within-population genetic variance, between-population divergence, and rate of adaptation. In particular, the rate of adaptation and that of neutral evolution are both reduced when a greater proportion of loci are pleiotropic. Our results reveal that aspects of mutational input not reflected by the M-matrix can have a profound impact on long-term evolution, and suggest it is important to take them into account in order to connect patterns of long-term phenotypic evolution to underlying microevolutionary mechanisms.

evolutionary biology↗

bioRxiv2023

Neural stimulation hardware for the selective intrafascicular modulation of the vagus nerve

The neural stimulation of the vagus nerve is able to modulate various functions of the parasympathetic response in different organs. The stimulation of the vagus nerve is a promising approach to treating inflammatory diseases, obesity, diabetes, heart failure, and hypertension. The complexity of the vagus nerve requires highly selective stimulation, allowing the modulation of target-specific organs without side effects. Here, we address this issue by adapting a neural stimulator and developing an intraneural electrode for the particular modulation of the vagus nerve. The neurostimulator parameters such as amplitude, pulse width, and pulse shape were modulated. Single-, and multi-channel stimulation was performed at different amplitudes. For the first time, I polyimide thin-film neural electrode was designed for the specific stimulation of the vagus nerve. In vivo experiments were performed in the adult minipig to validate to elicit electrically evoked action potentials and to modulate physiological functions selectively, validating the selectivity of intraneural stimulation. Electrochemical tests of the electrode and the neurostimulator showed that the stimulation hardware was working correctly. Stimulating the porcine vagus nerve resulted in selective modulation of the vagus nerve. Alpha, beta, and theta waves could be distinguished during single- and multi-channel stimulation. We have shown that the here presented system is able to activate the vagus nerve selectively and can therefore modulate the heart rate, diastolic pressure, and systolic pressure. The here presented system may be used to restore the cardiac loop after denervation by implementing biomimetic stimulation patterns. Presented methods may be used to develop intraneural electrodes adapted for various applications.

bioengineering↗

bioRxiv2023

Rapid and accurate multi-phenotype imputation for millions of individuals

Deep phenotyping can enhance the power of genetic analysis, including genome-wide association studies (GWAS), but the occurrence of missing phenotypes compromises the potential of such resources. Although many phenotypic imputation methods have been developed, the accurate imputation of millions of individuals remains extremely challenging. In the present study, we developed a novel multi-phenotype imputation method based on mixed fast random forest (PIXANT) by leveraging efficient machine learning (ML)-based algorithms. We demonstrate that PIXANT runtime is faster and computer memory usage is less than that of other state-of-the-art methods when applied to the UK Biobank (UKB) data, suggesting that PIXANT is scalable to cohorts with millions of individuals. Our simulations with hundreds of individuals showed that PIXANT accuracy was superior to or comparable to the accuracy of the most advanced methods available. PIXANT was used to impute 425 phenotypes for the UKB data of 277,301 unrelated White British citizens. When GWAS was subsequently performed on the imputed phenotypes, 18.4% more GWAS loci were identified than before imputation (8,710 vs 7,355). The increased statistical power of GWAS identified novel positional candidate genes affecting heart rate, such as RNF220, SCN10A, and RGS6, suggesting that the use of imputed phenotype data from a large cohort may lead to the discovery of novel genes for complex traits.

bioinformatics↗

bioRxiv2023

A transcriptional cell atlas identifies the decline in the AT2 niche in aged human lungs

Aging poses a global public health challenge, associated with molecular and physiological changes in the lungs. It increases susceptibility to acute and chronic lung diseases, yet the underlying molecular and cellular drivers in aged populations are not fully appreciated. To systematically profile the genetic changes associated with age, we present a single-cell transcriptional atlas comprising nearly half a million cells from the healthy lungs of human subjects spanning various ages, sexes, and smoking statuses. Most annotated cell lineages in aged lungs exhibit dysregulated genetic programs. Specifically, the aged alveolar epithelial cells, including both alveolar type II (AT2) and type I (AT1) cells, demonstrate loss of epithelial identities, heightened inflammaging characterized by increased expression of AP-1 transcription factor and chemokine genes, and significantly increased cellular senescence. Furthermore, the aged mesenchymal cells display a remarkable decrease in Collagen and Elastin transcription. The decline of the AT2 niche is further exacerbated by a weakened endothelial cell phenotype and a dysregulated genetic program in macrophages. These findings highlight the dysregulation observed in both AT2 stem cells and their supportive niche cells, potentially contributing to the increased susceptibility of aged populations to lung diseases.

cell biology↗