Biology subjects

Dong, K.

Publications and source records attributed to Dong, K..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

Relative importance of bacterivorous mixotrophs in an estuary-coast environment

Mixotrophic eukaryotes are important bacterivores in oligotrophic open oceans, but their significance as grazers in more nutrient-rich waters is less clear. Here we investigated the bacterivory partition between mixotrophs and heterotrophs in a productive, estuary-influenced coastal region in East China Sea. We found ubiquitous, actively feeding phytoplankton populations and taxa with mixotrophic potential, by identifying ingestion of fluorescent prey surrogate and analyzing community 18S rRNA gene amplicons. Potential and active mixotrophs accounted for 10-63% of total eukaryotic community and 17-69% of bacterivores observed, respectively, contributing 6-48% of estimated in situ bacterivory. The much higher mixotroph fitness outside of the turbid plume were potentially driven by increased light and decreased nutrients availability. Our results suggest that, although heterotrophs dominated overall in situ bacterivory, mixotrophs were abundant and important bacterivores in this low-latitude mesotrophic coastal region. Scientific Significance StatementMixotrophy, the combing of photosynthetic and phagotrophic nutrition, can dramatically increase primary production and alter material movements in aquatic food webs. Understanding the distribution and fitness of phagotrophic mixotrophs in a range of habitats are therefore critical to properly understand the biogeochemical cycles of the ocean. We developed a robust method to estimate active mixotrophs in situ and demonstrate rapid shifts of bacterivory partition between mixotrophs and heterotrophs across an estuary-coast environment in East China Sea. Our results help fill the knowledge gap of mixotroph niches in mesotrophic coastal environments that are impacted by riverine discharge, shedding light on relationships among mixotrophy, light and nutrient conditions.

microbiology↗

bioRxiv2023

Unified cross-modality integration and analysis of T-cell receptors and T-cell transcriptomes

Single-cell RNA sequencing and T-cell receptor sequencing (scRNA-seq and TCR-seq, respectively) technologies have emerged as powerful tools for investigating T-cell heterogeneity. However, the integrated analysis of gene expression profiles and TCR sequences remains a computational challenge. Herein, we present UniTCR, a unified framework designed for the cross-modality integration and analysis of TCRs and T-cell transcriptomes for a series of challenging tasks in computational immunology. By utilizing a dual-modality contrastive learning module and a single-modality preservation module to effectively embed each modality into a common latent space, UniTCR demonstrates versatility across various tasks, including single-modality analysis, modality gap analysis, epitope-TCR binding prediction and TCR profile cross-modality generation. Extensive evaluations conducted on multiple scRNA-seq/TCR-seq paired datasets showed the superior performance of UniTCR. Collectively, UniTCR is presented as a unified and extendable framework to tackle diverse T-cell-related downstream applications for exploring T-cell heterogeneity and enhancing the understanding of the diversity and complexity of the immune system.

bioinformatics↗

bioRxiv2023

Human Saliva Modifies Growth, Biofilm Architecture and Competitive Behaviors of Oral Streptococci

The bacteria within supragingival biofilms participate in complex exchanges with other microbes inhabiting the same niche. One example are the mutans group streptococci (Streptococcus mutans), implicated in the development of tooth decay, and other health-associated commensal streptococci species. Previously, our group transcriptomically characterized intermicrobial interactions between S. mutans and several species of oral bacteria. However, these experiments were carried out in a medium that was absent of human saliva. To better mimic their natural environment, we first evaluated how inclusion of saliva affected growth and biofilm formation of eight streptococci species individually, and found saliva to positively benefit growth rates while negatively influencing biomass accumulation and altering spatial arrangement. These results carried over during evaluation of 29 saliva-derived isolates of various species. Surprisingly, we also found that addition of saliva increased the competitive behaviors of S. mutans in coculture competitions against commensal streptococci that led to increases in biofilm microcolony volumes. Through transcriptomically characterizing mono- and cocultures of S. mutans and Streptococcus oralis with and without saliva, we determined that each species developed a nutritional niche under mixed-species growth, with S. mutans upregulating carbohydrate uptake and utilization pathways while S. oralis upregulated genome features related to peptide uptake and glycan foraging. S. mutans also upregulated genes involved in oxidative stress tolerance, particularly manganese uptake, which we could artificially manipulate by supplementing in manganese to give it an advantage over its opponent. Our report highlights observable changes in microbial behaviors via leveraging environmental- and host-supplied resources over their competitors.

microbiology↗

bioRxiv2023

Bacterial pathogens deliver water/solute-permeable channels as a virulence strategy

Many animal and plant pathogenic bacteria utilize a type III secretion system to deliver effector proteins into the host cell1,2. Elucidation of how these effector proteins function in the host cell is critical for understanding infectious diseases in animals and plants3-5. The widely conserved AvrE/DspE-family effectors play a central role in the pathogenesis of diverse phytopathogenic bacteria6. These conserved effectors are involved in the induction of "water-soaking" and host cell death that are conducive to bacterial multiplication in infected tissues. However, the exact biochemical functions of AvrE/DspE-family effectors have been recalcitrant to mechanistic understanding for three decades. Here we show that AvrE/DspE-family effectors fold into a {beta}-barrel structure that resembles bacterial porins. Expression of AvrE and DspE in Xenopus oocytes results in (i) inward and outward currents, (ii) permeability to water and (iii) osmolarity-dependent oocyte swelling and bursting. Liposome reconstitution confirmed that the DspE channel alone is sufficient to allow the passage of small molecules such as fluorescein dye. Targeted screening of chemical blockers based on the predicted pore size (15-20 [A]) of the DspE channel identified polyamidoamine (PAMAM) dendrimers as inhibitors of the DspE/AvrE channels. Remarkably, PAMAMs broadly inhibit AvrE/DspE virulence activities in Xenopus oocytes and during Erwinia amylovora and Pseudomonas syringae infections. Thus, we have unraveled the enigmatic function of a centrally important family of bacterial effectors with significant conceptual and practical implications in the study of bacterial pathogenesis.

plant biology↗

bioRxiv2023

Large-scale map of RNA binding protein interactomes across the mRNA life-cycle

Messenger RNAs (mRNAs) interact with RNA-binding proteins (RBPs) in diverse ribonucleoprotein complexes (RNPs) during distinct life-cycle stages for their processing and maturation. While substantial attention has focused on understanding RNA regulation by assigning proteins, particularly RBPs, to specific RNA substrates, there has been considerably less exploration leveraging protein-protein interaction (PPI) methodologies to identify and study the role of proteins in mRNA life-cycle stages. To address this gap, we generated an RNA-aware RBP-centric PPI map across the mRNA life-cycle by immunopurification (IP-MS) of [~]100 endogenous RBPs across the life-cycle in the presence or absence of RNase, augmented by size exclusion chromatography (SEC-MS). Aside from confirming 8,700 known and discovering 20,359 novel interactions between 1125 proteins, we determined that 73% of our IP interactions are regulated by the presence of RNA. Our PPI data enables us to link proteins to life-cycle stage functions, highlighting that nearly half of the proteins participate in at least two distinct stages. We show that one of the most highly interconnected proteins, ERH, engages in multiple RNA processes, including via interactions with nuclear speckles and the mRNA export machinery. We also demonstrate that the spliceosomal protein SNRNP200 participates in distinct stress granule-associated RNPs and occupies different RNA target regions in the cytoplasm during stress. Our comprehensive RBP-focused PPI network is a novel resource for identifying multi-stage RBPs and exploring RBP complexes in RNA maturation. HIGHLIGHTSO_LIAn RBP-centric RNA-aware PPI network focuses on the mRNA life-cycle in human cells C_LIO_LIPrey-prey correlation analysis assigns prey proteins to life-cycle stages, of which 536 proteins (half of the network) interact with multiple steps C_LIO_LIERH is highly connected to multiple RNPs to affect nuclear speckle organization and mRNA export C_LIO_LISplicing factor SNRNP200 interacts with stress granule proteins and has distinct RNA occupancy in the cytoplasm C_LI

systems biology↗

bioRxiv2023

Reply to: The pitfalls of negative data bias for the T-cell epitope specificity challenge

Predicting and identifying TCR-antigen pairings accurately presents a significant computational challenge within the field of immunology. The negative sampling issue is important T-cell specificity modeling and it is known clearly by the community that different negative data sampling strategy will influence the prediction results. Therefore, proper negative data sampling strategy should be carefully selected, and this is exactly what PanPep has noticed, emphasized and performed. Now we would like to clarify this point further by formulating this problem as a PU learning. Our findings suggest that the reshuffling strategy may generate potential false negative samples, which can adversely affect model training and result in biased model testing for PanPep. Furthermore, a proper comparison between different negative sampling strategies should be performed in a consistent way to make a proper conclusion. Finally, future updating to explore more possible and suitable negative sampling strategy is expected.

bioinformatics↗

bioRxiv2023

Coronary Artery Disease Risk Gene PRDM16 is Preferentially Expressed in Vascular Smooth Muscle Cells and a Potential Novel Regulator of Smooth Muscle Homeostasis

ObjectiveVascular smooth muscle cells (VSMCs) are the primary contractile component of blood vessels and can undergo phenotypic switching from a contractile to a synthetic phenotype in vascular diseases such as coronary artery disease (CAD). This process leads to decreased expression of SMC lineage genes and increased proliferative, migratory and secretory abilities that drive disease progression. Super-enhancers (SE) and occupied transcription factors are believed to drive expression of genes that maintain cell identify and homeostasis. The goal of this study is to identify novel regulator of VSMC homeostasis by screening for SE-regulated transcription factors in arterial tissues. Approach and ResultsWe characterized human artery SEs by analyzing the enhancer histone mark H3K27ac ChIP-seq data of multiple arterial tissues. We unexpectedly discovered the transcription factor PRDM16, a GWAS identified CAD risk gene with previously well-documented roles in brown adipocytes but with an unknown function in vascular disease progression, is enriched with artery-specific SEs. Further analysis of public bulk RNA-seq and scRNA-seq datasets, as well as qRT-PCR and Western blotting analysis, demonstrated that PRDM16 is preferentially expressed in arterial tissues and in contractile VSMCs but not in visceral SMCs, and down-regulated in phenotypically modulated VSMCs. To explore the function of Prdm16 in vivo, we generated Prdm16 SMC-specific knockout mice and performed histological and bulk RNA-Seq analysis of aortic tissues. SMC-deficiency of Prdm16 does not affect the aortic morphology but significantly alters expression of many CAD risk genes and genes involved in VSMC phenotypic modulation. Specifically, Prdm16 negatively regulates the expression of Tgfb2 that encodes for an upstream ligand of TGF-{beta} signaling pathway, potentially through binding to the promoter region of Tgfb2. These transcriptomic changes likely disrupt VSMC homeostasis and predispose VSMCs to a disease state. ConclusionsOur results suggest that the CAD risk gene PRDM16 is preferentially expressed in VSMCs and is a novel regulator of VSMC homeostasis. Future studies are warranted to investigate its role in VSMCs under pathological conditions such as atherosclerosis.

cell biology↗

bioRxiv2022

Integrating spatial transcriptomics data across different conditions, technologies, and developmental stages

With the rapid generation of spatial transcriptomics (ST) data, integrative analysis of multiple ST datasets from different conditions, technologies, and developmental stages is becoming increasingly important. However, identifying shared and specific spatial domains across ST datasets of multiple slices remains challenging. To this end, we develop a graph attention neural network STAligner for integrating and aligning ST datasets, enabling spatially-aware data integration, simultaneous spatial domain identification, and downstream comparative analysis. We apply STAligner to the integrative analysis of ST datasets of the human cortex slices from different samples, the mouse olfactory bulb slices generated by two profiling technologies, the mouse hippocampus tissue slices under normal and Alzheimers disease conditions, and the spatiotemporal atlases of mouse organogenesis. STAligner efficiently captures the shared tissue structures across different slices, the disease-related substructures, and the dynamical changes during mouse embryonic development. Additionally, the shared spatial domain and nearest neighbor pairs identified by STAligner can be further considered as corresponding pairs to guide the three-dimensional reconstruction of consecutive slices, achieving more accurate local structure-guided registration results than the existing method.

bioinformatics↗

bioRxiv2022

STAMarker: Determining spatial domain-specific variable genes with saliency maps in deep learning

Spatial transcriptomics characterizes gene expression profiles while retaining the information of the spatial context, providing an unprecedented opportunity to understand cellular systems. One of the essential tasks in such data analysis is to determine spatially variable genes (SVGs), which demonstrate spatial expression patterns. Existing methods only consider genes individually and fail to model the inter-dependence of genes. To this end, we present an analytic tool STAMarker for robustly determining spatial domain-specific SVGs with saliency maps in deep learning. STAMarker is a three-stage ensemble framework consisting of graphattention autoencoders, multilayer perceptron (MLP) classifiers, and saliency map computation by the backpropagated gradient. We illustrate the effectiveness of STAMarker and compare it with three competing methods on four spatial transcriptomic data generated by various platforms. STAMarker considers all genes at once and is more robust when the dataset is very sparse. STAMarker could identify spatial domain-specific SVGs for characterizing spatial domains and enable in-depth analysis of the region of interest in the tissue section.

bioinformatics↗

bioRxiv2022

SmartGate is a spatial metabolomics tool for resolving tissue structures

Imaging mass spectrometry (IMS) is one of the powerful tools in spatial metabolomics for obtaining metabolite data and probing the internal microenvironment of organisms. It has dramatically advanced the understanding of the structure of biological tissues and the drug treatment of diseases. However, the complexity of IMS data hinders the further acquisition of biomarkers and the study of certain specific activities of organisms. To this end, we introduce an artificial intelligence tool SmartGate to enable automatic peak picking and spatial structure identification in an iterative manner. SmartGate selects discriminative m/z features from the previous iteration by differential analysis and employs a graph attention auto-encoder model to perform spatial clustering for tissue segmentation using the selected features. We applied SmartGate to diverse IMS data at multicellular or subcellular spatial resolutions and compared it with four competing methods to demonstrate its effectiveness. SmartGate can significantly improve the accuracy of spatial segmentation and identify biomarker metabolites based on tissue structure-guided differential analysis. For multiple consecutive IMS data, SmartGate can effectively identify structures with spatial heterogeneity by introducing three-dimensional spatial neighbor information.

bioinformatics↗

bioRxiv2022

Novel Viroid-like RNAs Naturally Infect a Filamentous Fungus

Viroids have been found to naturally infect only plants, resulting in big losses for some crops, but whether viroids or viroid-like RNAs naturally infect non-plant hosts remains unknown. Here we report the existence of a set of exogenous, single-stranded circular RNAs, ranging in size between 157-450 nucleotides (nt), isolated from the fungus Botryosphaeria dothidea and nominated Botryosphaeria dothidea circular RNAs (BdcRNAs). BdcRNA(s) replicate autonomously in the nucleus via a rolling-circle replication mechanism following symmetric pathways with distribution patterns depending on strand polarity and species. BdcRNAs can modulate to different degrees specific biological traits (e.g., alter morphology, decrease growth rate, attenuate virulence, and increase or decrease tolerance to osmotic stress and oxidative stress) of the host fungus by regulating related metabolic pathways. Overall, BdcRNA(s) have genome characteristics similar to those of viroids and exhibit pathogenic effects on the fungal hosts. These novel viroid-like RNAs infecting fungi are proposed to be termed as mycoviroids. BdcRNA(s) may be regarded as additional inhabitants at the frontier of life in terms of genomic complexity, and represent a new class of acellular entities endowed with regulatory functions, and novel epigenomic carriers of biological information. Significance statementSeveral viroids have been transfected into unicellular and filamentous fungi to assess whether they can replicate, but no natural infections of fungi with viroid or viroid-like RNAs have been reported before. Here we describe a set of exogenous circular RNAs (cRNAs) in a phytopathogenic fungus. These cRNAs display molecular and biological features which might represent a new class of viroid-like cRNAs endowed with regulatory functions, and novel epigenomic carriers of biological information. This is the first report of infectious viroid-like RNAs (or exogenous small cRNAs) in a life kingdom (fungi) other than plants. We also present a subcellular analysis of cRNAs in a fungus for the first time and provide useful understanding in how cRNAs replicate, move, and are distributed in fungal cells.

microbiology↗

bioRxiv2022

The LncRNA Carmn is a Critical Regulator for Gastrointestinal Smooth Muscle Contractile Function and Motility

Background & aimsVisceral smooth muscle cells (SMCs) are an integral component of the gastrointestinal (GI) tract and are critical for regulating motility. SMC contraction is regulated by changes in post-translational signaling and the state of differentiation. Impaired SMC contraction is associated with significant morbidity and mortality but the mechanisms regulating the expression levels of SMC-specific contractile proteins, including the role of long non-coding RNAs (lncRNAs), remains largely unexplored. Herein, we have uncovered an important role of Carmn (Cardiac mesoderm enhancer-associated noncoding RNA), a SMC-specific lncRNA, in regulating the phenotype of visceral SMCs of the GI tract. MethodsAnalysis of GTEx and publicly available single-cell RNA sequencing (scRNA-seq) datasets from embryonic, adult human and mouse GI tissues were used to identify SMC-specific lncRNAs. The functional role of Carmn was investigated using a novel GFP knock-in (KI) reporter/knockout (KO) mouse model. Bulk RNA sequencing (RNA-seq) and single nuclei RNA sequencing (snRNA-seq) of colonic muscularis were used to investigate underlying mechanisms. ResultsUnbiased in silico analyses and GFP expression patterns in Carmn GFP KI mice revealed that Carmn is specifically expressed in SMCs in human and mouse GI tract. Premature lethality was observed in global Carmn KO (gKO) and inducible SMC-specific KO (iKO) mice due to colonic pseudo-obstruction, severe distension of the GI tract with blockages in cecum and colon segments. Histology, whole-gut GI transit time and muscle myography analysis revealed severe dilation, significantly delayed GI transit and impaired GI contractility in Carmn KO mice versus control mice. Bulk RNA-seq of colonic muscularis revealed that Carmn deficiency promotes SMC de-differentiation as evidenced by up-regulation of extracellular matrix genes and down-regulation of SMC contractile genes including Mylk, a key regulator of SMC contraction. SnRNA-seq further revealed SMC Carmn deficiency not only compromised myogenic motility by reducing expression of contractile genes but also impaired neurogenic motility by disrupting cell-cell connectivity in the colonic muscularis. These findings may have translational significance as silencing CARMN in human colonic SMCs significantly attenuated contractile gene expression including MYLK and decreased SMC contractility. Luciferase reporter assays showed that CARMN enhances the transactivation activity of the master regulator of SMC contractile phenotype, myocardin, thereby maintaining the GI SMC myogenic program. ConclusionOur data suggest that Carmn is indispensable for maintaining GI SMC contractile function in mice, and that loss of function of CARMN may contribute to human visceral myopathy. To our knowledge this is the first study showing an essential role of lncRNA in the regulation of visceral SMC phenotype.

cell biology↗

bioRxiv2021

The C-terminal tail of polycystin-1 suppresses cystic disease in a mitochondrial enzyme-dependent fashion

Autosomal dominant polycystic kidney disease (ADPKD) is the most prevalent potentially lethal monogenic disorder. Approximately 78% of cases are caused by mutations in the PKD1 gene, which encodes polycystin-1 (PC1). PC1 is a large 462-kDa protein that undergoes cleavage in its N and C-terminal domains. C-terminal cleavage produces fragments that translocate to mitochondria. We show that transgenic expression of a protein corresponding to the final 200 amino acid residues of PC1 in a Pkd1-KO orthologous murine model of ADPKD dramatically suppresses cystic phenotype and preserves renal function. This suppression depends upon an interaction between the C-terminal tail of PC1 and the mitochondrial enzyme Nicotinamide Nucleotide Transhydrogenase. This interaction modulates tubular/cyst cell proliferation, the metabolic profile, mitochondrial function and the redox state. Together, these results suggest that a short fragment of PC1 is sufficient to suppress cystic phenotype and open the door to the exploration of gene therapy strategies for ADPKD.

physiology↗

bioRxiv2021

Wild pigs mediate far-reaching agricultural impacts on tropical forest soil microbial communities

Edge effects, the altered abiotic and biotic conditions on the borders of natural areas, rarely extend more than a few hundred meters. Edge effects have rarely been linked to altered soil biota, which shape ecosystem processes including carbon storage, biogeochemical cycling, and plant performance. Here, we investigated if agriculturally-mediated increased wildlife populations affect soil biotic communities at a distance well over that of estimated edge effects when they move between agriculture and natural habitats using a 22-year fenced exclusion experiment in a primary rainforest in Peninsular Malaysia. We found that the presence of wildlife (mainly native pigs (Sus scrofa) that crop-raid in nearby oil palm plantations) was associated with higher bacterial diversity, and an altered community composition (mediated by changes in soil pH), and reduced abundances of symbiotic ectomycorrhizal fungi compared to soil in exclosures. There were only minor effects of pigs on soil chemistry or microclimate, so we suggest that changes in soil communities are driven by pigs leaf litter removal and alterations to plant composition. Our study highlights that indirect effects from agriculture can be transferred by wildlife >1 km into protected areas and this could have important repercussions for ecosystem processes and plant-soil feedbacks.

ecology↗

bioRxiv2021

Deciphering spatial domains from spatially resolved transcriptomics with adaptive graph attention auto-encoder

Recent advances in spatially resolved transcriptomics have enabled comprehensive measurements of gene expression patterns while retaining the spatial context of the tissue microenvironment. Deciphering the spatial context of spots in a tissue needs to use their spatial information carefully. To this end, we developed a graph attention auto-encoder framework STAGATE to accurately identify spatial domains by learning low-dimensional latent embeddings via integrating spatial information and gene expression profiles. To better characterize the spatial similarity at the boundary of spatial domains, STAGATE adopts an attention mechanism to adaptively learn the similarity of neighboring spots, and an optional cell type-aware module through integrating the pre-clustering of gene expressions. We validated STAGATE on diverse spatial transcriptomics datasets generated by different platforms with different spatial resolutions. STAGATE could substantially improve the identification accuracy of spatial domains, and denoise the data while preserving spatial expression patterns. Importantly, STAGATE could be extended to multiple consecutive sections to reduce batch effects between sections and extracting three-dimensional (3D) expression domains from the reconstructed 3D tissue effectively.

bioinformatics↗

bioRxiv2021

Network diffusion for scalable embedding of massive single-cell ATAC-seq data

With the rapid development of single-cell ATAC-seq technology, it has become possible to profile the chromatin accessibility of massive individual cells. However, it remains challenging to characterize their regulatory heterogeneity due to the high-dimensional, sparse and near-binary nature of data. Most existing data representation methods were designed based on correlation, which may be ill-defined for sparse data. Moreover, these methods do not well address the issue of excessive zeros. Thus, a simple, fast and scalable approach is needed to analyze single-cell ATAC-seq data with massive cells, address the "missingness" and accurately categorize cell types. To this end, we developed a network diffusion method for scalable embedding of massive single-cell ATAC-seq data (named as scAND). Specifically, we considered the near-binary single-cell ATAC-seq data as a bipartite network that reflects the accessible relationship between cells and accessible regions, and further adopted a simple and scalable network diffusion method to embed it. scAND can take information from similar cells to alleviate the sparsity and improve cell type identification. Extensive tests and comparison with existing methods using synthetic and real data as benchmarks demonstrated its distinct superiorities in terms of clustering accuracy, robustness, scalability and data integration. AvailabilityThe Python-based scAND tool is freely available at http://page.amss.ac.cn/shihua.zhang/software.html.

bioinformatics↗

bioRxiv2021

Elevation-related climate trends dominate fungal co-occurrence patterns on Mt. Norikura, Japan

Although many studies have explored patterns of fungal community diversity and composition along various environmental gradients, the trends of co-occurrence networks across similar gradients remain elusive. Here, we constructed co-occurrence networks for fungal community along a 2300 m elevation gradient on Mt Norikura, Japan, hypothesizing a progressive decline in network connectivity with elevation due to reduced niche differentiation caused by declining temperature and ecosystem productivity. Results agreed broadly with predictions, with an overall decline in network connectivity with elevation for all fungi and the high abundance phyla. However, trends were not uniform with elevation, most decline in connectivity occurred between 700 m and 1500 m elevation, remaining relatively stable above this. Temperature and precipitation dominated variation in network properties, with lower mean annual temperature (MAT) and higher mean annual precipitation (MAP) at higher elevations giving less network connectivity, largely through indirect effects on soil properties. Among keystone taxa that played crucial roles in network structure, the variation in abundance along the elevation gradient was also controlled by climate and also pH. Our findings point to a major role of climate gradients in mid-latitude mountain areas in controlling network connectivity. Given the importance of the orographic precipitation effect, microbial community trends seen along elevation gradients might not be mirrored by those seen along latitudinal temperature gradients. ImportanceAlthough many studies have explored patterns of fungal community diversity and composition along various environmental gradients, it is unclear how the topological structure of co-occurrence networks shifts across environmental gradients. In this study, we found that the connectivity of the fungal community decreased with increasing elevation, and that climate was the dominant factor regulating co-occurrence patterns, apparently acting indirectly through soil characteristics. Assemblages of keystone taxa playing crucial roles in network structure varied along the elevation gradient and were also largely controlled by climate. Our results provide insight into the shift of soil fungal community co-occurrence structure along elevational gradients, and possible driving mechanisms behind this. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/428196v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@12e555aorg.highwire.dtl.DTLVardef@e5c4d7org.highwire.dtl.DTLVardef@de00bdorg.highwire.dtl.DTLVardef@102967c_HPS_FORMAT_FIGEXP M_FIG C_FIG

microbiology↗

bioRxiv2021

Proteomic portraits reveal evolutionarily conserved and divergent responses to spinal cord injury

Despite the emergence of promising therapeutic approaches in preclinical studies, the failure of large-scale clinical trials leaves clinicians without effective treatments for acute spinal cord injury (SCI). These trials are hindered by their reliance on detailed neurological examinations to establish outcomes, which inflate the time and resources required for completion. Moreover, therapeutic development takes place in animal models whose relevance to human injury remains unclear. Here, we address these challenges through targeted proteomic analyses of CSF and serum samples from 111 acute SCI patients and, in parallel, a large animal (porcine) model of SCI. We develop protein biomarkers of injury severity and recovery, including a prognostic model of neurological improvement at six months with an AUC of 0.91, and validate these in an independent cohort. Through cross-species proteomic analyses, we dissect evolutionarily conserved and divergent aspects of the SCI response, and establish the CSF abundance of glial fibrillary acidic protein (GFAP) as a biochemical outcome measure in both humans and pigs. Our work opens up new avenues to catalyze translation by facilitating the evaluation of novel SCI therapies, while also providing a resource from which to direct future preclinical efforts.

neuroscience↗