Biology subjects

Li, B.

Publications and source records attributed to Li, B..

At least 343 records · Page 19Linked to original sources

bioRxiv2023

Synchrony of Bird Migration with Avian Influenza Global Spread; Implications for Vulnerable Bird Orders

Highly pathogenic avian influenza virus (HPAIV) A H5 clade 2.3.4.4 has caused worldwide outbreaks in domestic poultry, occasional spillover to humans, and increasing deaths of diverse species of wild birds since 2014. Wild bird migration is currently acknowledged as an important ecological process contributing to the global dispersal of HPAIV H5. However, it is unclear how seasonal bird migration facilitates global virus dispersal, and which avian species are exposed to HPAI H5 clade 2.3.4.4 viruses and where. To shed light on ongoing global outbreaks, we sought to explore these questions through phylodynamic analyses based on empirical data of bird movement tracking and virus genome sequences. First, based on viral phylogeography and bird migration networks, we demonstrate that seasonal bird migration can explain salient features of the global dispersal of clade 2.3.4.4. Second, we detect synchrony between the seasonality of bird annual cycle phases and virus lineage movements. We reveal the differing vulnerable bird orders at geographical origins and destinations of HPAIV H5 lineage movements. Notably, we highlight the potential importance of relatively under-discussed Suliformes and Ciconiiformes, in addition to Anseriformes and Charadriiformes, in virus lineage movements. Our study provides a phylodynamic framework that links the bird movement ecology and genomic epidemiology of avian influenza; it highlights the importance of integrating bird behaviour and life history in avian influenza studies.

ecology↗

bioRxiv2023

A single-cell atlas of the single versus multiple parous Hu Sheep ovary

In the modern sheep production system, the reproductive performance of ewes determines the economic profitability of farming. The mechanism of difference in litter size is important for the selection and breeding of high-fecundity ewes. Hu sheep is a high-quality sheep breed with high fecundity in China and is ideal for investigating high reproductive traits. In the current study, the sheep with lambing number [≥]3 in three consecutive lambing records were assigned to the HLS group, and lambing number = 1 as the LLS group selected from the same farm with three consecutive lambing. Three randomly picked ewes were slaughtered within 12 h of estrus, and unilateral ovarian tissue was collected and analyzed by single-cell RNA sequencing in each group. A total of five types of somatic cells were identified, and corresponding expression profiles were mapped in the ovaries of the Hu sheep. Additionally, the results of the difference in ovary somatic cell expression profiles between HLS and LLS present that the differences between multiples vs. singleton Hu sheep were mainly clustered in the GCs. In addition, 4 granulosa cell subtypes were identified. GeneSwitches results revealed the opening of JPH1 expression and the closure of LOC101112291, which leads to different evolutionary directions of the granular cells. The expression levels of FTH1 and FTL in GCs of Hu sheep in the HLS group were significantly higher, which inhibited necroptosis and ferroptosis of mural- GCs from decreasing follicular atresia. This study constructed the cellular atlas of the ovary and revealed related biological characteristics at the cellular molecular level. It provides a theoretical basis for the mechanisms underlying the differences in ovulation numbers, which contributes to breeding high-fertility sheep and molecular genetics-based selection.

zoology↗

bioRxiv2023

Discovery of new deaminase functions by structure-based protein clustering

The elucidation of protein function and its exploitation in bioengineering have greatly contributed to the development of the life sciences. Existing protein mining efforts generally rely on amino acid sequences rather than protein structures due to technical difficulties in structural elucidation. We describe here for the use of AlphaFold2 to predict and subsequently cluster an entire protein family based on predicted structure similarities. We selected the deaminase family of proteins to analyze and through this approach identified many previously unknown deaminase properties. We applied these new deaminases to the development of new cytosine base editors with distinct features. Although we found many new double-stranded DNA deaminases from the DddA-like protein clade, we were surprised to find that most of the proteins in this family were not actually double-stranded DNA cytidine deaminases. From this protein clade, we engineered the smallest single-strand specific cytidine deaminase, which facilitates the first efficient cytosine base editor to be packaged into a single AAV vector. Importantly, we also profiled a deaminase from this clade that edits robustly in soybean plants, which previously suffered from poor editing by cytosine base editors. These newly discovered deaminases based on AI-assisted structural predictions greatly expand the utility of base editors for therapeutic and agricultural applications.

molecular biology↗

bioRxiv2023

Latitudinal scaling of aggregation with abundance and its consequences for coexistence in species rich forests

The search for simple principles underlying the complex spatial structure and dynamics of plant communities is a long-standing challenge in ecology1-6. In particular, the relationship between the spatial distribution of plants and species coexistence is challenging to resolve in species-rich communities7-9. Analysing the spatial patterns of tree species in 21 large forest plots, we find that rare species tend to be more spatially aggregated than common species, and a latitudinal gradient in the strength of this negative correlations that increases from tropical to temperate forests. Our analysis suggests that latitudinal gradients in animal seed dispersal10 and mycorrhizal associations11,12,13 may jointly generate this intriguing pattern. To assess the consequences of negative aggregation-abundance correlations for species coexistence, we present here a framework to incorporate the observed spatial patterns into population models8 along with an analytical solution for the local extinction risk14 of species invading from low abundances in dependence of spatial structure, demographic parameters, and immigration. For example, the stabilizing effect of the observed spatial patterns reduced the local extinction risk of species when rare almost by a factor of two. Our approach opens up new avenues for integrating observed spatial patterns into mathematical theory, and our findings demonstrate that spatial patterns, such as species aggregation and segregation, can contribute substantially to coexistence in species-rich communities. This underscores the need to understand the interactions between multiple ecological processes and spatial patterns in greater detail.

ecology↗

bioRxiv2023

Prognostic Gene Signature for lung adenocarcinoma with a Higher Risk for Treatment Failure and Accelerated cell cycle and cell proliferation Pathway Activity

Lung cancer is the most common of malignant cancers which represents poor prognosis and high invasive. However, the reliable prognosis genes signature and the differential between the genetic and epigenetic are remain unclear. Here, we confirmed 78 genes of signature A to construct a model to predicted the prognosis and the activity of tumorigenesis-related pathways. The score based on the 78 genes expression is high correlation with the cell cycle and cell proliferation activity. Based on the median of score, the lung adenocarcinoma patients were divided into two cohorts which presents different prognosis, tumorigenesis-related pathways activity. The high score group was enriched in the E2F target, mtorc1 signaling and MYC targets. The low score group can be identified as better prognosis subtype. Also, we used the GDSC data to predicted the PIM inhibitor (AZD1208) as the effective compounds for high score group patients, which is supported by a higher PIM1 and PIM2 expression in the score group. An integrative analysis of multi-omics data identified ECT2 as key nodes in a regulatory network related to the prognostic phenotype. In conclusion, our data identified a molecular classifier for the different score groups patients, and the high score group patients might benefit from treatment with PIM inhibitor.

cancer biology↗

bioRxiv2023

Analyzing bivariate cross-trait genetic architecture in GWAS summary statistics with the BIGA cloud computing platform

As large-scale biobanks provide increasing access to deep phenotyping and genomic data, genome-wide association studies (GWAS) are rapidly uncovering the genetic architecture behind various complex traits and diseases. GWAS publications typically make their summary-level data (GWAS summary statistics) publicly available, enabling further exploration of genetic overlaps between phenotypes gathered from different studies and cohorts. However, systematically analyzing high-dimensional GWAS summary statistics for thousands of phenotypes can be both logistically challenging and computationally demanding. In this paper, we introduce BIGA (https://bigagwas.org/), a website that aims to offer unified data analysis pipelines and processed data resources for cross-trait genetic architecture analyses using GWAS summary statistics. We have developed a framework to implement statistical genetics tools on a cloud computing platform, combined with extensive curated GWAS data resources. Through BIGA, users can upload data, submit jobs, and share results, providing the research community with a convenient tool for consolidating GWAS data and generating new insights.

genetics↗

bioRxiv2023

High-throughput functional mapping of variants in an arrhythmia gene, KCNE1, reveals novel biology

BackgroundKCNE1 encodes a 129-residue cardiac potassium channel (IKs) subunit. KCNE1 variants are associated with long QT syndrome and atrial fibrillation. However, most variants have insufficient evidence of clinical consequences and thus limited clinical utility. ResultsHere, we demonstrate the power of variant effect mapping, which couples saturation mutagenesis with high-throughput sequencing, to ascertain the function of thousands of protein coding KCNE1 variants. We comprehensively assayed KCNE1 variant cell surface expression (2,554/2,709 possible single amino acid variants) and function (2,539 variants). We identified 470 loss-of-surface expression and 588 loss-of-function variants. Out of the 588 loss-of-function variants, only 155 had low cell surface expression. The latter half of the protein is dispensable for protein trafficking but essential for channel function. 22 of the 30 KCNE1 residues (73%) highly intolerant of variation were in predicted close contact with binding partners KCNQ1 or calmodulin. Our data were highly concordant with gold standard electrophysiological data ({rho} = -0.65), population and patient cohorts (32/38 concordant variants), and computational metrics ({rho} = -0.55). Our data provide moderate-strength evidence for the ACMG/AMP functional criteria for benign and pathogenic variants. ConclusionsComprehensive variant effect maps of KCNE1 can both provide insight into IKs channel biology and help reclassify variants of uncertain significance.

genomics↗

bioRxiv2023

Exact analysis of the subthreshold variability for conductance-based neuronal models with synchronous synaptic inputs

The spiking activity of neocortical neurons exhibits a striking level of variability, even when these networks are driven by identical stimuli. The approximately Poisson firing of neurons has led to the hypothesis that these neural networks operate in the asynchronous state. In the asynchronous state neurons fire independently from one another, so that the probability that a neuron experience synchronous synaptic inputs is exceedingly low. While the models of asynchronous neurons lead to observed spiking variability, it is not clear whether the asynchronous state can also account for the level of subthreshold membrane potential variability. We propose a new analytical framework to rigorously quantify the subthreshold variability of a single conductance-based neuron in response to synaptic inputs with prescribed degrees of synchrony. Technically we leverage the theory of exchangeability to model input synchrony via jump-process-based synaptic drives; we then perform a moment analysis of the stationary response of a neuronal model with all-or-none conductances that neglects post-spiking reset. As a result, we produce exact, interpretable closed forms for the first two stationary moments of the membrane voltage, with explicit dependence on the input synaptic numbers, strengths, and synchrony. For biophysically relevant parameters, we find that the asynchronous regime only yields realistic subthreshold variability (voltage variance [~=]4-9mV2) when driven by a restricted number of large synapses, compatible with strong thalamic drive. By contrast, we find that achieving realistic subthreshold variability with dense cortico-cortical inputs requires including weak but nonzero input synchrony, consistent with measured pairwise spiking correlations. We also show that without synchrony, the neural variability averages out to zero for all scaling limits with vanishing synaptic weights, independent of any balanced state hypothesis. This result challenges the theoretical basis for mean-field theories of the asynchronous state.

neuroscience↗

bioRxiv2023

Amoeboid cells undergo durotaxis with soft end polarized NMIIA

Cell migration towards stiff substrates has been coined as durotaxis and implicated in development, wound healing and cancer, where complex interplays between immune and non-immune cells are present. Compared to the emerging mechanisms underlying the strongly adhesive mesenchymal durotaxis, little is known about whether immune cells - migrating in amoeboid mode - could follow mechanical cues. Here we develop an imaging-based confined migration device with stiffness gradient. By tracking live cell trajectory and analyzing the directionality of T cells and neutrophils, we observe that amoeboid cells can durotax. We further delineate the underlying mechanism to involve non-muscle myosin IIA (NMIIA) polarization towards the soft-matrix-side but may not require differential actin flow up- or down-stiffness gradient. Using the protista Dictyostelium, we demonstrate the evolutionary conservation of amoeboid durotaxis. Finally, these experimental phenomena are theoretically captured by an active gel model capable of mechanosensing. Collectively, these results may shed new lights on immune surveillance and recently identified confined migration of cancer cells, within the mechanically inhomogeneous tumor microenvironment or the inflamed fibrotic tissues.

cell biology↗

bioRxiv2023

Inference of single cell profiles from histology stains with the Single-Cell omics from Histology Analysis Framework (SCHAF)

Tissue biology involves an intricate balance between cell-intrinsic processes and interactions between cells organized in specific spatial patterns, which can be respectively captured by single cell profiling methods, such as single cell RNA-seq (scRNA-seq) and spatial transcriptomics, and histology imaging data, such as Hematoxylin-and-Eosin (H&E) stains. While single cell profiles provide rich molecular information, they can be challenging to collect routinely in the clinic and either lack spatial resolution or high gene throughput. Conversely, histological H&E assays have been a cornerstone of tissue pathology for decades, but do not directly report on molecular details, although the observed structure they capture arises from molecules and cells. Here, we leverage vision transformers and adversarial deep learning to develop the Single Cell omics from Histology Analysis Framework (SCHAF), which generates a tissue samples spatially-resolved whole transcriptome single cell omics dataset from its H&E histology image. We demonstrate SCHAF on a variety of tissues-- including lung cancer, metastatic breast cancer, placentae, and whole mouse pups--training with matched samples analyzed by sc/snRNA-seq, H&E staining, and, when available, spatial transcriptomics. SCHAF generated appropriate single cell profiles from histology images in test data, related them spatially, and compared well to ground-truth scRNA-Seq, expert pathologist annotations, or direct spatial transcriptomic measurements, with some limitations. SCHAF opens the way to next-generation H&E analyses and an integrated understanding of cell and tissue biology in health and disease.

bioinformatics↗

bioRxiv2023

Genetic dysregulation of an endothelial Ras signaling network in vein of Galen malformations

To elucidate the pathogenesis of vein of Galen malformations (VOGMs), the most common and severe congenital brain arteriovenous malformation, we performed an integrated analysis of 310 VOGM proband-family exomes and 336,326 human cerebrovasculature single-cell transcriptomes. We found the Ras suppressor p120 RasGAP (RASA1) harbored a genome-wide significant burden of loss-of-function de novo variants (p=4.79x10-7). Rare, damaging transmitted variants were enriched in Ephrin receptor-B4 (EPHB4) (p=1.22x10-5), which cooperates with p120 RasGAP to limit Ras activation. Other probands had pathogenic variants in ACVRL1, NOTCH1, ITGB1, and PTPN11. ACVRL1 variants were also identified in a multi-generational VOGM pedigree. Integrative genomics defined developing endothelial cells as a key spatio-temporal locus of VOGM pathophysiology. Mice expressing a VOGM-specific EPHB4 kinase-domain missense variant exhibited constitutive endothelial Ras/ERK/MAPK activation and impaired hierarchical development of angiogenesis-regulated arterial-capillary-venous networks, but only when carrying a "second-hit" allele. These results illuminate human arterio-venous development and VOGM pathobiology and have clinical implications.

genomics↗

bioRxiv2023

On-grid purification of electron microscopy samples via a 3D-printed flow-cell

While recent advances in cryo-EM, coupled with single particle analysis, have the potential to allow structure determination in a near-native state from vanishingly few individual particles, this vision has yet to be realised in practise. Requirements for particle numbers that currently far exceed the theoretical lower limits, challenges with the practicalities of achieving high concentrations for difficult-to-produce samples, and inadequate sample-dependent imaging conditions, all result in significant bottlenecks preventing routine structure determination using cryo-EM. Therefore, considerable efforts are being made to circumvent these bottlenecks by developing affinity purification of samples on-grid; at once obviating the need to produce large amounts of protein, as well as more directly controlling the variable, and sample-dependent, process of grid preparation. In this proof-of-concept study, we demonstrate a further practical step towards this paradigm, developing a 3D-printable flow-cell device to allow on-grid affinity purification from raw inputs such as whole cell lysates, using graphene oxide-based affinity grids. Our flow-cell device can be interfaced directly with routinely-used laboratory equipment such as liquid chromatographs, or peristaltic pumps, fitted with standard chromatographic (1/16") connectors, and can be used to allow binding of samples to affinity grids in a controlled environment prior to the extensive washing required to remove impurities. Furthermore, by designing a device which can be 3D printed and coupled to routinely used laboratory equipment, we hope to increase the accessibility of the techniques presented herein to researchers working towards single-particle macromolecular structures.

biophysics↗

bioRxiv2023

BioConvert: a comprehensive format converter for life sciences

AO_SCPLOWBSTRACTC_SCPLOWBioinformatics is a field known for the numerous standards and formats that have been developed over the years. This plethora of formats, sometimes complementary, and often redundant, poses many challenges to bioinformatics data analysts. They constantly need to find the best tool to convert their data into the suitable format, which is often a complex, technical and time consuming task. Moreover, these small yet important tasks are often difficult to make reproducible. To over-come these difficulties, we initiated BioConvert, a collaborative project to facilitate the conversion of life science data from one format to another. BioConvert aggregates existing software within a single framework and complemented them with original code when needed. It provides a common interface to make the user experience more streamlined instead of having to learn tens of them. Currently, BioConvert supports about 50 formats and 100 direct conversions in areas such as alignment, sequencing, phylogeny, and variant calling. In addition to being useful for end-users, BioConvert can also be utilized by developers as a universal benchmarking framework for evaluating and comparing numerous conversion tools. Additionally, we provide a web server implementing an online user-friendly interface to BioConvert, hence allowing direct use for the community.

bioinformatics↗

bioRxiv2023

Integrated multi-omics data reveals the molecular subtypes and the contruction of novel signature to aid Immunotherapy

Malignant cancer exhibits a severe imbalance between the active of immune response and tolerance. And the different and connection between the establishment and deficiency of the tumor immune response is still unknown entirely. Here, we used ten clustering algorithms based on five immune cells infiltration matrix to identified two specific molecular subtypes and determine its potential clinical outcomes and immune response effect. The cluster A subtype can be called the cold inflammatory subtype, which revealed the worst prognosis. And the cluster B can be identified as hot inflammatory subtype with high activated immune-related pathways. Then we used the WGCNA algorithms and limma to confirm the driven genes between the cluster A and B. 67 genes were identified the cluster A signature genes, and based on that we used the ssgsea algorithm to quantize the two subtypes. We confirmed the high score group had high activated level of immune activity pathways and better survival rate. The tumorigenesis-associated pathways were analysed in low score group, indicating active cell proliferation may be associated with poor prognosis. An in-silico drug screen predicted the erlotinib can be an effective compound in low score group based on the lung cancer cell line. Our research confirmed that the score can worked as an effective immunotherapy index, which provide a promising therapeutic strategies on immune therapeutics for lung adenocarcinoma.

cancer biology↗

bioRxiv2023

Empowering Beginners in Bioinformatics with ChatGPT

The impressive conversational and programming abilities of ChatGPT make it an attractive tool for facilitating the education of bioinformatics data analysis for beginners. In this study, we proposed an iterative model to fine-tune instructions for guiding a ChatGPT in generating code for bioinformatics data analysis tasks. We demonstrated the feasibility of the model by applying it to various bioinformatics topics. Additionally, we discussed practical considerations and limitations regarding the use of the model in chatbot-aided bioinformatics education.

bioinformatics↗

bioRxiv2023

Antigen-presenting type-I conventional dendritic cells facilitate curative checkpoint blockade immunotherapy in pancreatic cancer

Inflammation and tissue damage associated with pancreatitis can precede or occur concurrently with pancreatic ductal adenocarcinoma (PDAC). We demonstrate that in PDAC coupled with pancreatitis (ptPDAC), antigen-presenting type-I conventional dendritic cells (cDC1s) are specifically activated. Immune checkpoint blockade therapy (iCBT) leads to cytotoxic CD8+ T cell activation and eradication of ptPDAC with restoration of lifespan even upon PDAC re-challenge. Such eradication of ptPDAC was reversed following specific depletion of dendritic cells. Employing PDAC antigen-loaded cDC1s as a vaccine, immunotherapy-resistant PDAC was rendered sensitive to iCBT with a curative outcome. Analysis of the T-cell receptor (TCR) sequences in the tumor infiltrating CD8+ T cells following cDC1 vaccination coupled with iCBT identified unique CDR3 sequences with potential therapeutic significance. Our findings identify a fundamental difference in the immune microenvironment and adaptive immune response in PDAC concurrent with, or without pancreatitis, and provides a rationale for combining cDC1 vaccination with iCBT as a potential treatment option.

cancer biology↗

bioRxiv2023

Isolation of ACE2-dependent and -independent sarbecoviruses from Chinese horseshoe bats

While the spike proteins from SARS-CoV and SARS-CoV-2 bind to host ACE2 to infect cells, the majority of bat sarbecoviruses cannot use ACE2 from any species. Despite their discovery almost 20 years ago, ACE2-independent sarbecoviruses have never been isolated from field samples, leading to the assumption these viruses pose little risk to humans. We have previously shown how spike proteins from a small group of ACE2-independent bat sarbecoviruses may possess the ability to infect human cells in the presence of exogenous trypsin. Here, we adapted our earlier findings into a virus isolation protocol, and recovered two new ACE2-dependent viruses, RsYN2012 and RsYN2016, as well as an ACE2-independent virus, RsHuB2019. Although our stocks of RsHuB2019 rapidly acquired a tissue-culture adaption that rendered the spike protein resistant to trypsin, trypsin was still required for viral entry, suggesting limitations on the exogenous entry factors that support bat sarbecoviruses. Electron microscopy revealed ACE2-independent sarbecoviruses have a prominent spike corona and share similar morphology to other coronaviruses. Our findings demonstrate a broader zoonotic threat posed by sarbecoviruses and shed light onto the intricacies of coronavirus isolation and propagation in vitro. SIGNIFICANCESeveral coronaviruses have transmitted from animals to people and 20 years of virus discovery studies have uncovered thousands of new coronavirus sequences in nature. Most of the animal-derived sarbecoviruses have never been isolated in culture due to cell incompatibilities and a poor understanding of the in vitro requirements for their propagation. Here, we built on our growing body of work characterizing viral entry mechanisms of bat sarbecoviruses in human cells and have developed a virus isolation protocol that allows for exploration of these understudied viruses. Our protocol is robust and practical, leading to successful isolation of more sarbecoviruses than previous approaches and from field samples that had been collected over a 10-year longitudinal study.

microbiology↗

bioRxiv2023

Spatial transcriptomic atlas of shoot organogenesis in tomato callus

Callus is a reprogrammed transitional cell mass during plant regeneration. Pluripotent callus cells develop into fertile shoots through de novo shoot organogenesis. This study represents a pioneering effort in exploring the spatial transcriptome of tomato callus during shoot regeneration, using technologies including BGI Stereo-seq, BMKMANU S1000, and 10x Visium. The results indicate that the callus comprises highly heterogeneous cells, classified into various cell types based on spatial gene expression and histological observation, including epidermis, shoot primordium, vascular tissue, inner callus, and outgrowth shoots. The developmental trajectories from shoot primordium to outgrowth shoot are traced, and vascular tissue development is characterized. The single-cell resolution spatial approach reveals the origin of shoot primordia from the sub-epidermis. The spatial full length RNA sequencing shows high incompletely spliced (IS) ratios in the shoot primordium cells. These findings enhance our knowledge of plant organogenesis and highlight the significance of spatial biology in plant research.

cell biology↗