Biology subjects

Fang, P.

Publications and source records attributed to Fang, P..

At least 19 recordsLinked to original sources

bioRxiv2026

Resistance to the conjugation inhibitor AZT reveals mating partner incompatibility during plasmid transfer

Plasmid-mediated dissemination of antibiotic resistance genes (ARGs) is a major driver of antimicrobial resistance (AMR). The nucleoside analogue zidovudine (azidothymidine, AZT) has emerged as a promising conjugation inhibitor, yet the consequences of AZT resistance for subsequent plasmid transfer remain poorly understood. Here, we investigated how AZT resistance in donor and recipient bacteria influences conjugative plasmid transfer. Independent AZT-resistant mutants arose through nonsense mutations in two distinct thymidine metabolism genes, yjjG and tdk. Consistent with previous studies, AZT suppressed plasmid transfer 10-fold between susceptible mating partners, whereas resistance in both partners restored transfer despite continued AZT exposure. Unexpectedly, plasmid transfer was markedly reduced even in the absence of AZT when only one mating partner carried a resistance mutation, declining by up to 11.5-fold regardless of whether the resistant strain was the donor or the recipient. This mixed-resistance phenotype was rescued by supplementation with dTMP, a thymidine pathway metabolite downstream of both resistance-associated mutations, thereby increasing plasmid transfer by up to 5.88-fold and restoring transfer to levels comparable to those of susceptible-susceptible matings. In contrast, excess dTMP reduced conjugation between susceptible partners, supporting a broader role for balanced nucleotide metabolism in determining conjugation efficiency. Together, our findings identify nucleotide metabolism as a previously unrecognised determinant of conjugative plasmid transfer and suggest that the long-term efficacy of conjugation inhibitors such as AZT will depend not only on the evolution of resistance, but also on how resistance reshapes the physiological compatibility of bacterial mating partners. ImportanceAntibiotic resistance spreads rapidly because conjugative plasmids transfer resistance genes between bacteria. Drugs that inhibit plasmid transfer are therefore being explored as a new strategy to limit antimicrobial resistance, but little is known about how resistance against these compounds affects subsequent gene transfer. We show that resistance to the conjugation inhibitor zidovudine (AZT) does not simply restore plasmid transfer. Instead, transfer depends on the resistance status of both mating partners. While two susceptible or two resistant bacteria transferred plasmids efficiently, mixed susceptible-resistant pairings showed markedly reduced conjugation even in the absence of AZT. Restoring thymidine metabolism rescued this phenotype, identifying balanced nucleotide metabolism as a previously unrecognised determinant of conjugative plasmid transfer. These findings suggest that the long-term performance of conjugation inhibitors will depend not only on the evolution of resistance, but also on how resistance reshapes the physiological compatibility of bacterial mating partners, providing a new framework for understanding and designing anti-conjugation strategies.

microbiology↗

bioRxiv2026

Alignment-free phylogenetic inference via hyperbolic protein language models

Conventional phylogenetic methods rely on multiple sequence alignments which are computationally intensive and often fail for highly divergent lineages. Here, we introduce LucaPhylo, an alignment-free framework that infers evolutionary relationships directly from unaligned sequences. Through a cascaded learning strategy LucaPhylo integrates protein language models with hyperbolic geometry, a representation space naturally suited to hierarchical branching, to capture deep evolutionary constraints without explicit homology matching. Using highly divergent RNA virosphere as a test case, LucaPhylo places unaligned sequences into phylogenetic trees with an accuracy comparable to leading alignment-based tree construction tools, while retaining divergent sequences that conventional pipelines frequently discard. It further enables the integration of divergent viral lineages into phylogenetic trees, thereby expanding the evolutionary landscape of RNA viruses. Together, LucaPhylo establishes an AI-driven, alignment-free paradigm for phylogenetic inference and provides a robust computational foundation for resolving deep evolutionary relationships among RNA viruses and other biological systems.

evolutionary biology↗

bioRxiv2025

Pan-cancer tumor classification by a holistic tumor microenvironment atlas

The tumor microenvironment (TME) heterogeneity presents a major bottleneck to effective cancer immunotherapies. We address this by establishing a pan-cancer tumor classification system based on the holistic TME cellular components. First, using single-cell transcriptomes from 1,271 patients across 26 cancer types, we compile a TME cellular atlas, leading to the identification of recurrent cell states and multicellular modules across cancer types. Among these, we highlight a type I interferon (IFN-I)-related multicellular module, including IFIT1+ tumor-associated macrophages, as a critical contributor to immune-activation TMEs. From a holistic perspective, pan-cancer TMEs exhibit trichotomous patterns predominantly driven by T, myeloid, and stromal compartments. Leveraging fine-grained TME cellular composition, we further stratify all tumors into 10 stable groups. These groups display varying responses to immune checkpoint blockade (ICB), and each rationally selected therapeutic strategy specifically perturbs the corresponding expression signature. Our pan-cancer tumor classification scheme reveals the underlying patterns of TME heterogeneity and provides a framework for stratifying patients, guiding treatment selection, and developing novel therapeutic options.

cancer biology↗

bioRxiv2025

Construction of recombinant Bacillus subtilis spores surface-displaying PRRSV ORF1b, GP5, M, and N proteins in tandem and evaluation of their immunogenicity in mice

Porcine reproductive and respiratory syndrome virus (PRRSV), a single-stranded RNA virus, is a highly contagious pathogen that causes severe reproductive and respiratory disorders in pigs, leading to significant economic losses in the swine industry worldwide. However, current commercial vaccines provide only limited protection against circulating PRRSV strains, highlighting the urgent need for novel vaccine strategies. B. Bacillus subtilis, a well-characterized probiotic, has emerged as a promising platform for mucosal vaccine delivery due to its safety profile and ability to induce robust immune responses. In this study, we screened B cell and T cell linear epitopes from PRRSV-ORF1b, GP5, M, and N proteins to construct a recombinant tandem antigen (ER), which was displayed on the surface of B. subtilis 168 spores. The resulting recombinant strain, designated B. subtilis BE, was evaluated for immunogenicity in mice via oral administration. The results showed that Oral immunization with B. subtilis BE significantly elevated antigen-specific secretory IgA levels in intestinal contents and IgG levels in serum, indicating potent mucosal and systemic humoral responses. Moreover, B. subtilis BE induced measurable neutralizing antibody titers and enhanced cellular immunity, as evidenced by increased frequencies of CD3+ and CD8+ T cells in mesenteric lymph nodes and upregulation of IFN-, TNF-, and IFN-{gamma} expression in intestinal tissues. Collectively, these findings demonstrate that B. subtilis BE elicits both humoral and cellular immune responses and may serve as a novel oral vaccine candidate against PRRSV, offering a promising alternative for controlling the ongoing epidemic.

immunology↗

bioRxiv2025

Using Artificial Intelligence to Assess Cross-Species Transmission Potential of Influenza A Virus

Influenza A viruses (IAVs) pose pandemic threats through cross-species transmission, yet predicting their adaptive evolution remains challenging. We introduced Influenza A virus Adaptability to host X (FluAdaX), a deep learning framework that integrates a moving average-equipped gated attention mechanism using full-genome sequences. FluAdaX demonstrated robust host classification performance across endemic IAV strains, and outperformed traditional models in detecting avian-to-human transmission. Spillover score and adaptability score were introduced to evaluate host shift risk, which prioritized variants with elevated human adaptation potential, such as H7N9, H9N2 avian IAVs, and H1N1 swine IAVs. Besides HA and NA genes, PB2 and NS genes were found critical for zoonosis. Potential molecular markers associated with avian/human tropism were identified across PB2 and NS genes using XGBoost. FluAdaX provided a dynamic framework to decode IAV host adaptation, enabling real-time risk assessment of cross-species transmission of emerging IAV variants.

bioinformatics↗

bioRxiv2025

Differential control of growth and identity by HNF4α isoforms in pancreatic ductal adenocarcinoma

BackgroundAlthough transcriptomic studies have stratified pancreatic ductal adenocarcinoma (PDAC) into clinically relevant subtypes, classical or basal-like, further research is needed to identify the transcriptional regulators of each subtype. Previous studies identified HNF4 as a key regulator of the classical subtype, but the distinct contributions of its isoforms (P1 and P2), which display dichotomous functions in normal development and gastrointestinal malignancies, remain unexplored. ObjectiveThe objective of this study is to investigate the role of HNF4 P1 and P2 isoforms in regulating growth and differentiation. DesignWe performed functional, transcriptomic, and epigenetic analysis after exogenous expression in HNF4-negative models or CRISPRi-mediated knockdown of endogenous isoforms. ResultsWe characterized the variable expression of P1 isoforms in HNF4-positive tumors. We demonstrate that P1 isoforms are less compatible with growth than P2 isoforms. Despite sharing a common DNA binding domain, we show that P1 isoforms are stronger transcriptional regulators. ConclusionsOur study characterizes the functional roles of HNF4 P1 and P2 isoforms in PDAC and highlights the necessity of considering different isoforms when studying molecular regulators.

cancer biology↗

bioRxiv2025

Ultradeep N-glycoproteome Atlas of Mouse Reveals Spatiotemporal Signatures of Brain Aging and Neurodegenerative Diseases

The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieved an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multiple workflows. The largest N-glycoproteomic dataset to date was established on mice, which contained 91,972 precursor glycopeptides, 62,216 glycoforms, 8,939 glycosites and 4,563 glycoproteins. The database consisted of 6.8 million glyco-spectra (containing oxonium ions), among which 160,928 were high-quality spectra with confident N-glycopeptide identifications. The large-scale and high-quality dataset enhanced the performance of current artificial intelligence models for glycopeptide tandem spectrum prediction. Using this ultradeep dataset, we observed tissue specific microheterogeneity and functional implications of protein glycosylation in mice. Furthermore, the region-resolved brain N-glycoproteomes for Alzheimers Diseases, Parkinson Disease and aging mice revealed the spatiotemporal signatures and distinct pathological functions of the N-glycoproteins. A comprehensive database resource of experimental N-glycoproteomic data from this study and previous literatures were further established. This N-glycoproteome atlas serves as a promising tool for revealing the role of protein glycosylation in biological systems.

neuroscience↗

bioRxiv2024

Jellyfish blooms - an overlooked hotspot and potential vector for the transmission of antimicrobial resistance in marine environments

Jellyfish, and gelatinous zooplankton (GZ) in general, represent an important component of marine food webs. Certain GZ species are capable of generating massive blooms of severe environmental impact. These blooms are often followed by a sudden collapse of the entire population, introducing considerable amounts of organic matter (GZ-OM) in the oceans interior. GZ-OM represents an abundant substrate to promote bacterial growth and copious colonizable surface for microbial interactions. Hence we hypothesized that this GZ-OM serves as a yet overlooked hotspot for transmitting antimicrobial resistance genes (ARGs) in marine environments. For this we experimentally evolved and analyzed marine microbial communities in microcosms in presence and absence of OM from scyphozoan Aurelia aurita s.l. and ctenophore Mnemiopsis leidyi. Communities evolved under GZ-OM exposure displayed an up to 4-fold increase in relative ARG and an up to 10-fold increase in abundance of horizontally transferable mobile genetic elements (MGEs) per 16S rRNA gene copy compared to the controls. This trait was consistent across ARG and MGE classes and independent of the GZ species, suggesting that the underlying mechanism is indeed based on the general influx of nutrients and colonizable surfaces. Potential ARG carriers included known key GZ-OM degraders, but also genera containing potential pathogens hinting towards an increased risk of ARG transfer to pathogenic strains. Here, Vibrio were pinpointed as potential key species directly associated with several significantly elevated ARGs and MGEs. Subsequent whole-genome sequencing of a Vibrio isolate from the microcosm experiment revealed the genetic potential for the mobilization and transfer of ARGs in GZ-OM degrading microbial consortia. With this study, we established the first link between two emerging issues of marine coastal zones, jellyfish blooms and AMR spread, both likely increasing in projected future ocean scenarios.

microbiology↗

bioRxiv2024

LucaOne: Generalized Biological Foundation Model with Unified Nucleic Acid and Protein Language

AbstractThe language of biology, encoded in DNA, RNA, and proteins, forms the foundation of life but remains challenging to decode due to its complexity. Traditional computational methods often struggle to integrate information across these molecules, limiting a comprehensive understanding of biological systems. Advances in Natural Language Processing (NLP) with pre-trained models offer new possibilities for interpreting biological language. Here, we introduce LucaOne, a pre-trained foundation model trained on nucleic acid and protein sequences from 169,861 species. Through large-scale data integration and semisupervised learning, LucaOne demonstrates an understanding of key biological principles, such as DNA-Protein translation. Using few-shot learning, it effectively comprehends the central dogma of molecular biology and performs competitively on tasks involving DNA, RNA, or protein inputs. Our results highlight the potential of unified foundation models to address complex biological questions, providing an adaptable framework for bioinformatics research and enhancing the interpretation of lifes complexity.

bioinformatics↗

bioRxiv2023

Cigarette smoking promotes the spread of antimicrobial resistance in the human lung and the environment

While immediate health risks of cigarette smoking are well-established, indirect health impacts of cigarette-derived pollutants through proliferation of antimicrobial resistance (AMR) among bacteria remain understudied. Here, exposure to cigarette smoke condensate at relevant concentrations resulted in >2-fold elevated transfer rates of a multi-drug-resistance encoding plasmid between Pseudomonas strains in artificial lung sputum medium. This effect was connected to elevated reactive oxygen species production as part of the bacterial stress response when exposed to cigarette-derived toxicants. Similar results were obtained under exposure to cigarette ash leachate in environmental medium. Further, used cigarette filters enriched in toxic residues were submerged in a wastewater stream, and colonized by altered microbial communities compared to unused filters. These communities were significantly enriched in pathogens and AMR. Hence, filters could facilitate hitchhiking of high-risk bacteria to novel environments. We demonstrate that cigarette-derived compounds can promote the spread of AMR within the human lung and natural environments.

microbiology↗

bioRxiv2023

AnnoPRO: an innovative strategy for protein function annotation based on image-like protein representation and multimodal deep learning

Protein function annotation has been one of the longstanding issues, which is key for discovering drug targets and understanding physiological or pathological process. A variety of computational methods have therefore been constructed to facilitate the research developments in this particular direction. However, the annotation of protein function based on computational methods has been suffering from the serious "long-tail problem", and it remains extremely challenging for existing methods to improve the prediction accuracies for protein families in tail label levels. In this study, an innovative strategy, entitled AnnoPRO, for protein function annotation was thus constructed. First, a novel method enabling image-like protein representations was proposed. This method is unique in capturing the intrinsic correlations among protein features, which can greatly favor the application of the state-of-the-art deep learning methods popular in image classification. Second, a multimodal framework integrating multichannel convolutional neural network and long short-term memory neural network was constructed to realize a deep learning-based protein functional annotation. Since this framework was inspired by a reputable method used in image classification for dealing with its long-tail problem, our AnnoPRO was expected to significantly improve the annotation performance of the protein families in tail label level. Multiple case studies based on benchmark were also conducted, which confirmed the superior performance of AnnoPRO among the existing methods. All source codes and models of AnnoPRO were freely available to all users at https://github.com/idrblab/AnnoPRO, and would be essential complement to existing methods.

bioinformatics↗

bioRxiv2023

Artificial intelligence redefines RNA virus discovery

Current metagenomic tools can fail to identify highly divergent RNA viruses. We developed a deep learning algorithm, termed LucaProt, to discover highly divergent RNA-dependent RNA polymerase (RdRP) sequences in 10,487 metatranscriptomes generated from diverse global ecosystems. LucaProt integrates both sequence and predicted structural information, enabling the accurate detection of RdRP sequences. Using this approach we identified 161,979 potential RNA virus species and 180 RNA virus supergroups, including many previously poorly studied groups, as well as RNA virus genomes of exceptional length (up to 47,250 nucleotides) and genomic complexity. A subset of these novel RNA viruses were confirmed by RT-PCR and RNA/DNA sequencing. Newly discovered RNA viruses were present in diverse environments, including air, hot springs and hydrothermal vents, and both virus diversity and abundance varied substantially among ecosystems. This study advances virus discovery, highlights the scale of the virosphere, and provides computational tools to better document the global RNA virome. In briefA deep learning algorithm (LucaProt) that integrates both sequence and predicted structural information was employed to identify highly divergent RNA viral "dark matter" in 10,487 metatranscriptomes from diverse global ecosystems. A total of 161,979 potential RNA virus species and 180 RNA virus supergroups was unveiled using this AI approach, including many understudied groups.

microbiology↗

bioRxiv2023

Microbiome diversity: A barrier to the environmental spread of antimicrobial resistance?

BackgroundIn the environment, microbial communities are constantly exposed to invasion by antimicrobial resistant bacteria (ARB) and their associated antimicrobial resistance genes (ARGs) that were enriched in the anthroposphere. A successful invader has to overcome the biotic resilience of the habitat, which is more difficult with increasing biodiversity. The capacity to exploit resources in a given habitat is enhanced when communities exhibit greater diversity, reducing opportunities for invaders, leading to a lower persistence. In the context of antimicrobial resistance (AMR) dissemination, exogenous ARB reaching a natural community may persist longer if the biodiversity of the autochthonous community is low, increasing the chance of ARGs to transfer to community members. Reciprocally, high microbial diversity could serve as a natural long-term barrier towards invasion by ARB and ARGs. ResultsTo test this hypothesis, a sampling campaign across seven European countries was carried out to obtain 172 environmental samples from sites with low anthropogenic impact. Samples were collected from contrasting environments: stationary structured forest soils, or dynamic river biofilms and sediments. Microbial diversity and relative abundance of 27 ARGs and 5 mobile genetic element marker genes were determined. In soils, higher diversity, evenness and richness were all significantly negatively correlated with the relative abundance of the majority (>85%) of ARGs. Furthermore, the number of detected ARGs per sample was inversely correlated with diversity. However, no such effects were found for the more dynamic, regularly mixed rivers. Conclusions: In conclusion, we demonstrate that diversity can serve as barrier towards AMR dissemination in the environment. This effect is mainly observed in stationary, structured environments, where long-term, diversity-based resilience against invasion can evolve. Such barrier effects can in the future be exploited to limit the environmental proliferation of AMR.

microbiology↗

bioRxiv2022

Sequencing-free Tissue-wide Spatial Profiling of Post-transcriptional Regulations

The importance of genetic or epi-genetic heterogeneity has been increasingly recognized, but it has been challenging to profile intracellular post-transcriptional targets with sufficient throughput and resolution at across large-scale tissue samples. This study describes a technique, Spectrum-FISH, for high-throughput, sequencing-free, and tissue-wide spatial profiling of various post-transcriptional targets in acute tissue sections with subcellular resolution. The platform uses a biochip with an array of vertically aligned nanoprobes to effectively extract intracellular molecules for downstream analysis in the coordinates of the large-scale of cells within a tissue slice. As a proof-of-concept, the Spectrum-FISH is used to profile the spatial dynamics of 24 miRNAs and 9 m6A-modified messenger RNAs (m6A-mRNA) in acute olfactory bulb (OB) slices of millimeter scale. The results showed potentially multiomics spatial heterogeneity for the examined post-transcriptional regulations in rodent OB, especially in the outer plexiform layer and granule layer, where highly correlated miRNAs and m6A-mRNAs groups were identified, indicating a potential cooperative involvement of different post-transcriptional regulations at these OB regions.

genomics↗

bioRxiv2022

Sex-dependent interactions between prodromal intestinal inflammation and LRRK2 G2019S in mice promote symptoms of Parkinson's disease

Gastrointestinal (GI) disruptions, such as inflammatory bowel disease (IBD), are common prodromal symptoms of Parkinsons disease (PD), but how they may impact risk for PD remains poorly understood. Herein, we provide evidence that prodromal intestinal inflammation expedites and exacerbates PD symptoms in rodent carriers of the human PD risk allele LRRK2 G2019S in a sex-dependent manner. Chronic intestinal damage in genetically predisposed male, but not female, mice promotes -synuclein aggregation in the substantia nigra, elevated -synuclein loads in microglia, loss of dopaminergic neurons, and motor impairment. This male bias in gene-environment interaction is preserved in gonadectomized males, and similarly conferred by sex chromosomal complement in gonadal females expressing human LRRK2 G2019S, revealing that XY chromosomes, not testicular hormones, mediate the male bias in the gut-brain-driven risk for endophenotypes of PD. The early onset and heightened severity of neuropathological and behavioral outcomes in male LRRK2 G2019S mice is preceded by the accumulation of -synuclein in the colon, increases in -synuclein-positive macrophages in the colonic lamina propria, and elevations in -synuclein loads within microglia in the substantia nigra. Taken together, these data reveal that prodromal intestinal inflammation promotes the pathogenesis of PD symptoms in male carriers of LRRK2 G2019S, through mechanisms that depend on genotypic sex and involve early accumulation of -synuclein in myeloid cells within the gut and brain.

physiology↗

bioRxiv2022

Coupled functional physiological phenotyping and simulation model to infer the transpiration sensitivity traits and its implications for transpiration ideotype design

As agricultural drought becomes more frequent worldwide, it is essential to improve crop productivity whilst reducing the water consumption to achieve a sustainable production. Plant transpiration rate and water use efficiency (WUE) collectively determine the yield performance, yet it is challenging to balance the two in breeding programs due to still insufficient mechanistic understanding of the traits. Here we demonstrate the feasibility and effectiveness of calculating dynamic and momentary WUE by coupling WUE model and the state-of-the-art functional physiological phenotyping (FPP). We also present the method of quantifying genotype-specific traits reflecting sensitivity of transpiration to radiation (STr-Rad) and vapor pressure deficit (STr-VPD), under evolving developmental stage and water availability. Using these methods, we revealed the genotypic difference of STr-Rad and STr-VPD in three watermelon accessions, the dramatic change in each of them across the drought treatment phases, and the quantitative impacts of them on dynamic WUE patterns. Based on our results and computational simulations, a general principle for transpiration ideotype design is proposed, which highlights the benefits of lowering STr-VPD to increase WUE and increasing STr-Rad to offset the decline of Tr. FPP-enabled phenomic selection will help screen for elite crops lines with desired transpiration sensitivities.

physiology↗

bioRxiv2022

Understanding water conservation vs. profligation traits in vegetable legumes through a physio-transcriptomic-functional approach

Vegetable soybean and cowpea are related warm-season legumes showing contrasting leaf water use behaviors under similar root drought stresses, whose mechanisms are not well understood. Here we conducted an integrative phenomic-transcriptomic study on the two crops grown in a feedback irrigation system that enabled precise control of soil water contents. Continuous transpiration rate monitoring demonstrated that cowpea used water more conservatively under earlier soil drought stages, but tended to maintain higher transpiration under prolonged drought. Interestingly, we observed a soybean-specific transpiration rate increase accompanied by phase shift under moderate soil drought. Time-series transcriptomic analysis suggested a dehydration avoidance mechanism of cowpea at early soil drought stage, in which the VuHAI3 and VuTIP2;3 genes were suggested to be involved. Multifactorial gene clustering analysis revealed different responsiveness of genes to drought, time of day and their interactions between the two crops, which involved species-dependent regulation of the core clock genes. Gene network analysis identified two co-expression modules each associated with transpiration rate in cowpea and soybean, including a pair of negatively-correlated modules between species. Module hub genes, including the ABA-degrading gene GmCYP707A4 and the trehalose-phosphatase/synthase gene VuTPS9 were identified. Inter-modular network analysis revealed putative co-players of the hub genes. Transgenic analyses verified the role of VuTPS9 in regulating transpiration rate under osmotic stresses. These findings propose that species-specific transcriptomic reprograming in leaves of the two crops suffering similar soil drought was not only a result of the different drought resistance level, but a cause of it.

plant biology↗

bioRxiv2022

Mapping the GALNT1 substrate landscape with versatile proteomics tools

O-GalNAc type glycosylation is a common post-translational modification (PTM) of proteins catalyzed by polypeptide GalNAc transferases, but the substrate specificity of these transferases is poorly understood. Here we develop a strategy based on integral thermal proteome solubility profiling to identify and prioritize the protein substrates of polypeptide N-acetylgalactosaminyltransferase 1 (GALNT1). Combined with glycoprotein enrichment followed by HCD and soft EThcD gas-phase fragmentation technique, we uncover hundreds of novel GALNT1 substrates in two model human cell lines. GALNT1-mediated O-glycosylation is more common on Thr than Ser residues, with a strong preference for Pro at positions +3 and +4 in respect to O-glycosylation. These results implicate GALNT1 in potentially regulating proteins in several diverse pathways, including some unexpected processes, such as TCA cycle and DNA transcription. This study depicts a roadmap for identification of functional substrates for glycosyltransferases, facilitating fundamental insight into the role of glycosylation in homeostasis and disease.

biochemistry↗