Biology subjects

Jiang, M.

Publications and source records attributed to Jiang, M..

At least 109 records · Page 6Linked to original sources

bioRxiv2023

Positive coping supports children's emotional wellness: Behavioral evidence and neuroendocrine mechanisms

A positive coping style is recognized as a stable disposition to foster emotional wellness and resilience, enabling an adaptive process of assessing and dealing with environmental challenges. Such an adaptive process is believed to rely on a nuanced interplay of the hippocampal system and the primary stress hormone cortisol activity. As a hallmark of diurnal cortisol rhythm, cortisol awakening response (CAR) is sensitive to upcoming stress and subserves the preparation of the hippocampal system for rapid behavioral adaption. Yet, little is known about how the hippocampal system and CAR contribute to the merit of positive coping on emotional wellness. By two studies, we investigate the effects of positive coping on childrens emotional wellness and CAR, as well as longitudinal changes in hippocampal-neocortical functional systems involved in emotional processing. Behaviorally, positive coping predicted better emotional regulation ability, but lower anxiety and lower response caution in emotional decision-making. At the endocrine and neurocognitive level, positive coping was associated with greater CAR, which further predicted higher connectivity of the hippocampus with ventrolateral prefrontal cortex (vlPFC) and stimulus-sensitive neocortex one year later. Furthermore, CAR mediated an indirect association between positive coping and longitudinal increases in hippocampal-neocortical connectivity. Positive coping and CAR together could account for the maturity of vlPFC through longitudinal changes in hippocampal-neocortical connectivity. Overall, our findings suggest a cognitive-neuroendocrinal framework in which positive coping shapes hippocampal-neocortical maturation via stress hormone response to support emotional wellness. SignificanceThe role of the hippocampal system in regulating stress response is well recognized, but its contribution to emotional well-being is not yet understood. Here we show that the protective effects of positive coping on emotional well-being are contingent on two factors: the cortisol awakening response (CAR), which is sensitive to upcoming stress, and hippocampal development. We found that positive coping practices promoted emotional wellness, enhanced emotional decision-making and increased CAR in young children. Longitudinal neuroimaging analysis revealed that positive coping-related CAR predicted greater hippocampal connectivity with stimulus-sensitive neocortex one year later. Importantly, CAR acted as a mediator of the promotive influence of positive coping on the longitudinal development of hippocampal-neocortical connectivity, which contributed to the maturity of prefrontal control systems. Our findings emphasize the importance of hippocampal-neocortical development in resilient coping and emotional wellness.

neuroscience↗

bioRxiv2023

Impact of Peripheral Auditory Structure on the Development of Auditory-Language Network in Children with Profound Sensorineural Hearing Loss

Profound congenital sensorineural hearing loss (SNHL) prevents children from developing spoken language. Cochlear implantation and auditory brainstem implantation can provide hearing sensation, but language development outcomes can vary, particularly for patients with inner ear malformations and/or cochlear nerve deficiency (IEM&CND). Currently, the peripheral auditory structure is evaluated through visual inspection of clinical imaging, but this method is insufficient for surgical planning and prognosis. The central auditory pathway is also challenging to examine in vivo due to its delicate subcortical structures. Previous attempts to locate subcortical auditory nuclei using fMRI responses to sounds are not applicable to deaf patients. In this study, we developed a new pipeline for mapping the auditory pathway using structural and diffusional MRI. We used a fixel-based approach to investigate the structural development of the auditory-language network for profound SNHL children with normal peripheral structure and those with IEM&CND under six years old. Our findings indicate that the language pathway is more sensitive to peripheral auditory condition than the central auditory pathway, highlighting the importance of early intervention for profound SNHL children to provide timely speech inputs. We also propose a comprehensive pre-surgical evaluation extending from the cochlea to the auditory-language network, which has promising clinical potential.

neuroscience↗

bioRxiv2022

Cell composition inference and identification of layer-specific spatial transcriptional profiles with POLARIS

Spatial transcriptomics (ST) technology, providing spatially resolved transcriptional profiles, facilitates advanced understanding of key biological processes related to health and disease. Sequencing-based ST technologies provide whole-transcriptome profiles, but are limited by the non-single cell level resolution. Lack of knowledge in the number of cells or cell type composition at each spot can lead to invalid downstream analysis, which is a critical issue recognized in ST data analysis. Methods developed, however, tend to under-utilize histological images, which conceptually provide important and complementary information including anatomical structure and distribution of cells. To fill in the gaps, we present POLARIS, a versatile ST analysis method that can perform cell type deconvolution, identify anatomical or functional layer-wise differentially expressed (LDE) genes and enable cell composition inference from histology images. Applied to four tissues, POLARIS demonstrates high deconvolution accuracy, accurately predicts cell composition solely from images, and identifies LDE genes that are biologically relevant and meaningful.

genetics↗

bioRxiv2022

Latitude influences stability via stabilizing mechanisms in naturally-assembled forest ecosystems at different spatial grains

Ecosystem stability reveals how ecosystems respond to global change over time. Yet, the focus of past research on small spatial grains and extents overlooks scale dependence and how broad-scale environmental gradients shape stability. Here, we use forest inventory data covering a broad latitudinal gradient from the temperate to the tropical zone to examine cross-scale variation in stability of aboveground biomass and underlying stabilizing mechanisms. While stability did not shift systematically with latitude at either spatial grain, we found evidence that species asynchrony increased towards the tropics at the small spatial grain while species stability decreased at both spatial grains. Moreover, latitude stabilized forest communities via its effects on both stabilizing mechanisms, which compensated for the weak and destabilizing effects of species richness. Yet, the trade-off in the relative importance of species stability and species asynchrony for stability was not mediated by latitude, suggesting that context-dependent factors - to a greater extent than macroecological ones - underlie large-scale patterns of stability. Our results highlight the crucial role of species asynchrony and species stability in determining ecosystem stability across broad-scale environmental gradients, suggesting that conserving biodiversity alone may not be sufficient for stabilizing naturally-assembled forest ecosystems.

ecology↗

bioRxiv2022

Divergent microbial structure still results in convergent microbial function during arrested anaerobic digestion of food waste at different hydraulic retention times

In this study, two arrested anaerobic digestion bioreactors fed with food waste operated under different hydraulic retention times (HRTs) exhibited long-term stable volatile fatty acid (VFA) production performance including similar total yields (p = .085) with propionic acid (PA) being the most abundant VFA. Meta-omics analysis revealed distinct microbial structures (p = .02) at the two HRTs while there were no differences in potential and extant functionality as indicated by the whole-genome and whole-transcriptome sequencing, respectively. The highest potential (relative abundance of DNA sequence reads) and extant (relative abundance of mRNA sequence reads) functionality corresponded with PA production compared to other acids. The most abundant genus Prevotella produced PA mainly through the acryloyl-CoA pathway. Based on our results, the mechanistic basis for the similar VFA production performance observed under the HRTs tested lies in the community-level redundancy in convergent acidification functions and pathways, rather than trends in community structure.

microbiology↗

bioRxiv2022

Rapid and Signal Crowdedness-Robust In-Situ Sequencing through Hybrid Block Coding

Spatial transcriptomics technology has revolutionized our understanding of cell types and tissue organization, opening new possibilities for researchers to explore transcript distributions at subcellular levels. However, existing methods have limitations in resolution, sensitivity, or speed. To overcome these challenges, we introduce SPRINTseq (Spatially Resolved and signal-diluted Next-generation Targeted sequencing), an innovative in situ sequencing strategy that combines hybrid block coding and molecular dilution strategies. Our method enables fast and sensitive high-resolution data acquisition, as demonstrated by recovering over 142 million transcripts using a 108 gene panel from 453,843 cells from four mouse brain coronal slices in less than two days. Using this advanced technology, we uncover the cellular and subcellular molecular architecture of Alzheimers disease, providing additional information into abnormal cellular behaviors and their subcellular mRNA distribution. This improved spatial transcriptomics technology holds great promise for exploring complex biological processes and disease mechanisms.

genomics↗

bioRxiv2022

The metabolite alpha-ketobutyrate increases health and life spans by activating AMPK

Aging is a complex process that is directly related to human health and disease. The extraordinary finding that aging is malleable, as shown in model organisms whose life and health spans are extended by specific gene mutations or dietary or pharmacological perturbations 1-3, has offered enormous hope for our understanding and treatment of aging and related diseases. Although many molecules have been identified that can extend the lifespan of model organisms, few have been shown to alleviate age-related symptoms or illness in mammals 4. Here we show that supplementation with the endogenous metabolite -ketobutyrate (-KB) increases the lifespan of adult C. elegans. Using Gelfree DARTS-PROTOMAP, we identified microtubule-actin cross-linking factor (MACF1) that was protected against proteolysis in the presence of -KB. MACF1 belongs to the spectraplakin family of giant, evolutionarily conserved proteins with versatile functions 5, but their link to longevity regulation has not been explored. -KBs longevity effect in C. elegans is abrogated by loss-of-function mutation in vab-10, encoding the worm ortholog of mammalian MACF1 6. Like -KB treatment, vab-10 knockdown activates AMP-activated protein kinase (AMPK), and AMPK is required for -KB effects on longevity. The findings suggest a model in which -KB increases longevity by activating AMPK via VAB-10/MACF1 modulation. -KB also delays aging in mammals, increasing the lifespan of aged male mice and the healthspan of both male and female animals. Targeting of broadly expressed scaffolding proteins in connection to cellular energy homeostasis seems to be a clever way that nature has devised for metabolite signals to impinge upon multiple organ and tissue systems, which may have utility for controlling aging and related diseases.

physiology↗

bioRxiv2022

Diversity and biogeography of plant leaf bacteria along a latitudinal gradient

Plant-associated microbes are essential for promoting plant well-being, maintaining biodiversity, and supporting ecosystem function. However, little is known about the geographic distribution of plant-microbe symbioses and how they are formed and change along latitudinal gradients. Here we identified leaf bacteria for 328 plant species sampled from 10 forests along a tropical to temperate gradient in China. We analyzed the diversity and composition of plant leaf-associated bacteria and quantified the contributions of hosts, habitats, and neighborhood plants to the plant-bacterial symbiosis. We found a strong latitudinal gradient in leaf bacterial diversity and composition. Bacterial assemblages on leaves were most strongly selected by host plants, and the selection pressure increased with latitude. In contrast, at low latitudes and at large geographical scales multiple factors were found to jointly regulate bacterial community composition. Our result also showed that plant-bacteria symbiotic networks were structured by network hub bacteria taxa with high co-occurrence network centrality, and the abundance of temperate hub taxa was more influenced by host plants than that in tropical forests. For the first time, we documented a previously unrecognized latitudinal gradient in plant-bacterial symbioses that was regulated by a joint effect of multiple factors at low latitudes but mostly by host selection at high latitudes, implying that leaf microbiomes are likely to respond differently to global change along the latitudinal gradient.

ecology↗

bioRxiv2022

HybAVPnet: a novel hybrid network architecture for antiviral peptides identification

MotivationThe virus poses a great threat to human production and life, thus the research and development of antiviral drugs is urgently needed. Antiviral peptides play an important role in drug design and development. Compared with the time-consuming and laborious wet chemical experiment methods, accurate and rapid identification of antiviral peptides using computational methods is critical. However, it is still challenging to extract effective feature representations from the sequences for the accurate identification of antiviral peptides. ResultsThis study introduces a novel two-step approach, named HybAVPnet, with a hybrid network architecture to identify antiviral peptides based on neural networks and traditional machine learning methods. Firstly, eighteen kinds of features are extracted to predict labels and probabilities by the neural network classifier and LightGBM classifier, respectively. Secondly, the support vector machine classifier is carried out using the predicted probability of the first step to make the final prediction. The experimental result shows HybAVPnet can achieve better and more robust performance compared with the state-of-the-art methods, especially on independent datasets, which makes it useful for the research and development of antiviral drugs. Meanwhile, it can also be extended to other peptide recognition problems because of its generalization ability. Availability and implementationThe predicted model could be downloaded from: https://github.com/greyspring/HybAVPnet Contactgespring@hdu.edu.cn; yp.cai@siat.ac.cn Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Structural and biochemical mechanism for increased infectivity and immune evasion of Omicron BA.1 and BA.2 variants and their mouse origins

The Omicron BA.2 variant has become a dominant infective strain worldwide. Receptor binding studies reveal that the Omicron BA.2 spike trimer have 11-fold and 2-fold higher potency to human ACE2 than the spike trimer from the wildtype (WT) and Omicron BA.1 strains. The structure of the BA.2 spike trimer complexed with human ACE2 reveals that all three receptor-binding domains (RBDs) in the spike trimer are in open conformation, ready for ACE2 binding, thus providing a basis for the increased infectivity of the BA.2 strain. JMB2002, a therapeutic antibody that was shown to have efficient inhibition of Omicron BA.1, also shows potent neutralization activities against Omicron BA.2. In addition, both BA.1 and BA.2 spike trimers are able to bind to mouse ACE2 with high potency. In contrast, the WT spike trimer binds well to cat ACE2 but not to mouse ACE2. The structures of both BA.1 and BA.2 spike trimer bound to mouse ACE2 reveal the basis for their high affinity interactions. Together, these results suggest a possible evolution pathway for Omicron BA.1 and BA.2 variants from human-cat-mouse-human circle, which could have important implications in establishing an effective strategy in combating viral infection.

biophysics↗

bioRxiv2022

Alveolar regeneration following viral infection is independent of tuft cells

Severe injuries following viral infection cause lung epithelial destruction with the presence of ectopic basal progenitor cells (EBCs), although the exact function of EBCs remains controversial. We and others previously showed the presence of ectopic tuft cells in the disrupted alveolar region following severe influenza infection. Here, we further revealed that the ectopic tuft cells are derived from EBCs. This process is amplified by Wnt signaling inhibition but suppressed by Notch inhibition. Further analysis revealed that p63-CreER labeled population de novo arising during regeneration includes alveolar epithelial cells when Tamoxifen was administrated after viral infection. The generation of the p63-CreER labeled alveolar cells is independent of tuft cells, demonstrating segregated differentiation paths of EBCs in lung repair. EBCs and ectopic tuft cells can also be found in the lung parenchyma post SARS-CoV-2 infection, suggesting a similar response to severe injuries in humans.

cell biology↗

bioRxiv2022

Extensive neutralization against SARS-CoV-2 variants elicited by Omicron-specific subunit vaccine booster

The currently dominant variant of SARS-CoV-2 Omicron, carrying a great number of mutations, has been verified its strong capacity of immune escape in COVID-19 convalescents and vaccinated individuals. An increased risk of SARS-CoV-2 reinfection or breakthrough infection should be concerned. Here we reported higher humoral immune response elicited by Delta and Omicron variants after breaking through previous infection and cross-neutralization against VOCs, compared to the ancestral wild-type (WT) virus infection. To overcome the immune escape of Omicron, Omicron-specific vaccine was considered as a novel and potential strategy. Mouse models were used to verify whether Omicron-specific RBD subunit boost immune response by immunizing Omicron-RBD recombinant proteins. Three doses of Omicron-RBD immunization elicit comparable neutralizing antibody (NAb) titers with three doses of WT-RBD immunization, but the neutralizing activity was not cross-active. By contrast, two doses of WT-RBD with an Omicron-RBD booster increased the NAb geometric mean titers against Omicron by 9 folds. Moreover, an additional boost vaccination with Omicron-RBD protein could increase humoral immune response against both WT and current VOCs. These results suggest that the Omicron-specific subunit booster shows its advantages in the immune protection from both WT and current VOCs, and that SARS-CoV-2 vaccines administration using two or more virus lineages as antigens might improve the NAb response.

microbiology↗

bioRxiv2022

A comprehensive comparison on cell type composition inference for spatial transcriptomics data

Spatial transcriptomic (ST) technologies allow researchers to examine high-quality RNA-sequencing data along with maintained two-dimensional positional information as well as a co-registered histology image. A popular use of ST omics data is to provide insights about tissue structure and spatially unique features. However, due to the technical nature unique to most ST data, the resolution varies from a diameter of 2-10m to 50-100m instead of single-cell resolution, which brings uncertainty into cell number and cell mixture within each ST spot. Motivated by the important role for spatial arrangement of cell types within a tissue in physiology and disease pathogenesis, several ST deconvolution methods have been developed and are being used to explore gene expression variation and identification of spatial domains. The aim of this work is to review state-of-the-art methods for ST deconvolution, while comparing their strengths and weaknesses. Specifically, we use four real datasets to examine the performance of eight methods across different tissues and technological platforms. Key PointsO_LICell mixture inference is a critical step in the analysis of spatial transcriptomics (ST) data to prevent downstream analysis suffering from confounding factors at the spot level. C_LIO_LIExisting ST deconvolution methods can be classified into three groups: probabilistic-based, non-negative matrix factorization and non-negative least squares based, and other deep learning framework-based methods. C_LIO_LIWe compared eight ST deconvolution methods by using two single cell level resolution datasets and two spot level resolution ST datasets. We provided practical guidelines for the choice of method under different scenarios as well as the optimal subsets of genes to use for each method. C_LI

genetics↗

bioRxiv2022

A Self-attention Graph Convolutional Network for Precision Multi-tumour Early Diagnostics with DNA Methylation Data

DNA methylation data-based precision tumor early diagnostics is emerging as state of the art technology, which could capture the signals of cancer occurrence 3[~]5 years in advance and clinically more homogenous groups. At present, the sensitivity of early detection for many tumors is about 30%, which needs to be significantly improved. Nevertheless, based on the genome wide DNA methylation information, one could comprehensively characterize the entire molecular genetic landscape of the tumors and subtle differences among various tumors. With the accumulation of DNA methylation data, we need to develop high-performance methods that can model and consider more unbiased information. According to the above analysis, we have designed a self-attention graph convolutional network to automatically learn key methylation sites in a data-driven way for precision multi-tumor early diagnostics. Based on the selected methylation sites, we further trained a multi-class classification support vector machine. Large amount experiments have been conducted to investigate the performance of the computational pipeline. Experimental results demonstrated the effectiveness of the selected key methylation sites which are highly relevant for blood diagnosis.

bioinformatics↗

bioRxiv2021

5-aminolevulinic acid-photodynamic therapy ameliorates cutaneous granuloma by killing drug-resistant Mycobacterium marinum

BackgroundAlthough 5-aminolevulinic acid photodynamic therapy (ALA-PDT) has been extensively used to treat to various skin disease, the application of ALA-PDT on cutaneous infection caused by Mycobacterium marinum (M. marinum), especially by drug-resistant M. marinum is still not clear. ObjectivesWe evaluated the therapeutic efficacy of ALA-PDT on M. marinum in a mouse infection model and tested its killing effect on M. marinum in vitro. Finally, we investigated the clinical effect of ALA-PDT in treating cutaneous granuloma caused by drug-resistant M. marinum. Materials and methodsWe isolated total 9 strains of M. marinum from patients and confirmed by morphological and molecular approaches. The strains were identified by anti-mycobacterial susceptibility. Then we evaluated the killing effect of ALA-PDT on M. marinum in vitro and in a mouse model to observe the antimycobacterial effect of ALA-PDT. Therapeutic efficacy was further assessed in patients with cutaneous granuloma caused by drug-resistant M. marinum. ResultsWe demonstrated that the ALA-PDT directly killed M. marinum in vitro. The paws cutaneous lesions of mice caused by M. marinum were fully recovered 2 weeks after ALA-PDT treatment. However, there was no significant difference for immune cells in peripheral blood before and after ALA-PDT therapy. Finally, ALA-PDT proved to be effective in treat two patients with cutaneous infection caused by drug-resistant M. marinum. ConclusionsThe results suggest that ALA-PDT is effective in treating M. marinum cutaneous infections by killing M. marinum directly, independent of systemic immune responses. The data highlight the ALA-PDT as a promising therapeutic choice for M. marinum infection, especially for drug-resistant strains.

microbiology↗

bioRxiv2021

solPredict: Antibody apparent solubility prediction from sequence by transfer learning

There is growing interest in developing therapeutic mAbs for the route of subcutaneous administration for several reasons, including patient convenience and compliance. This requires identifying mAbs with superior solubility that are amenable for high-concentration formulation development. However, early selection of developable antibodies with optimal high-concentration attributes remains challenging. Since experimental screening is often material and labor intensive, there is significant interest in developing robust in silico tools capable of screening thousands of molecules based on sequence information alone. In this paper, we present a strategy applying protein language modeling, named solPredict, to predict the apparent solubility of mAbs in histidine (pH 6.0) buffer condition. solPredict inputs embeddings extracted from pretrained protein language model from single sequences into a shallow neutral network. A dataset of 220 diverse, in-house mAbs, with extrapolated protein solubility data obtained from PEG-induced precipitation method, were used for model training and hyperparameter tuning through five-fold cross validation. An independent test set of 40 mAbs were used for model evaluation. solPredict achieves high correlation with experimental data (Spearman correlation coefficient = 0.86, Pearson correlation coefficient = 0.84, R2 = 0.69, and RMSE = 4.40). The output from solPredict directly corresponds to experimental solubility measurements (PEG %) and enables quantitative interpretation of results. This approach eliminates the need of 3D structure modeling of mAbs, descriptor computation, and expert-crafted input features. The minimal computational expense of solPredict enables rapid, large-scale, and high-throughput screening of mAbs during early antibody discovery.

bioinformatics↗

bioRxiv2021

Climate shapes flowering periods across plant communities

AimClimate shapes the composition and function of plant communities globally, but it remains unclear how this influence extends to floral traits. Flowering phenology, or the time period in which a species flowers, has well-studied relationships with climatic signals at the species level but has rarely been explored at a cross-community and continental scale. Here, we characterise the distribution of flowering periods (months of flowering) across continental plant communities encompassing six biomes, and determine the influence of climate on community flowering period lengths. LocationAustralia TaxonFlowering plants MethodsWe combined plant composition and abundance data from 629 standardised floristic surveys (AusPlots) with data on flowering period from the AusTraits database and additional primary literature for 2,983 species. We assessed abundance-weighted community mean flowering periods across biomes and tested their relationship with climatic annual means and the predictability of climate conditions using regression models. ResultsCombined, temperature and precipitation (annual mean and predictability) explain 29% of variation in continental community flowering period. Plant communities with higher mean temperatures and lower mean precipitation have longer mean flowering periods. Moreover, plant communities in climates with predictable temperatures and, to a lesser extent, predictable precipitation have shorter mean flowering periods. Flowering period varies by biome, being longest in deserts and shortest in alpine and montane communities. For instance, desert communities experience low and unpredictable precipitation and high, unpredictable temperatures and have longer mean flowering periods, with desert species typically flowering at any time of year in response to rain. Main conclusionsOur findings demonstrate the role of current climate conditions in shaping flowering periods across biomes, with implications under climate change. Shifts in flowering periods across climatic gradients reflect changes in plant strategies, affecting patterns of plant growth and reproduction as well as the availability of floral resources across the landscape.

ecology↗

bioRxiv2021

A novel R3H protein, OsDIP1, confers ABA-mediated adaptation to drought and salinity stress in rice

Abscisic acid (ABA) is a key component of many signaling networks mediating plant adaptation to various stresses. In this context, ABA-induced antioxidant defence is considered to be a main mechanism to that enhances water stress tolerance in plants. The specific details of this activation remain, however, elusive. In this work, we show that DIP1, a protein from novel R3H family, played a central role in modulating water stress tolerance in rice. OsDIP1 transcripts were induced by hydrogen peroxide (H2O2), ABA, drought (polyethylene glycol treatment), and salt stress. Overexpression of OsDIP1 in rice enhanced drought and salinity tolerance while knocking out OsDIP1 by CRISPR-Cas9 editing resulted in drought and salt sensitive phenotype. The activity and gene expression of antioxidant defence enzymes, superoxide dismutase (SOD), catalase (CAT), increased in OsDIP1-overexpressed transgenic rice plants, while the content of malondialdehyde (MDA) decreased. In contrast, the content and gene expression of SOD and CAT, decreased, and the content of MDA increased in knockout of OsDIP1 rice plants, suggesting that overexpression of OsDIP1 enhances the antioxidant capacity of rice plants. The yeast two hybrid screening test revealed that OsDIP1 interacted with ZFP36, a key zinc finger transcription factor involved in ABA-induced antioxidant defence. Moreover, OsDIP1 could modulate some key ABA-responsive genes via interacting with ZFP36. Overall, our findings indicate an important role of OsDIP1 in ABA-induced antioxidant defence signaling and adaptation to salinity and drought in rice.

molecular biology↗