Biology subjects

Gao, Y.

Publications and source records attributed to Gao, Y..

At least 469 records · Page 26Linked to original sources

bioRxiv2022

Spatially resolved single-cell deconvolution of bulk RNA-seq using Bulk2Space

Uncovering the tissue molecular architecture at single-cell resolution could help better understand organisms biological and pathological processes. However, bulk RNA-seq can only measure gene expression in cell mixtures, without revealing the transcriptional heterogeneity and spatial patterns of single cells. Herein, we introduce Bulk2Space (https://github.com/ZJUFanLab/bulk2space), a deep learning framework-based spatial deconvolution algorithm that can simultaneously disclose the spatial and cellular heterogeneity of bulk RNA-seq data using existing single-cell and spatial transcriptomics references. The use of bulk transcriptomics to validate Bulk2Space unveils, in particular, the spatial variance of immune cells in different tumor regions, the molecular and spatial heterogeneity of tissues during inflammation-induced tumorigenesis, and spatial patterns of novel genes in different cell types. Moreover, Bulk2Space is utilized to perform spatial deconvolution analysis on bulk transcriptome data from two different mouse brain regions derived from our in-house developed sequencing approach termed Spatial-seq. We have not only reconstructed the hierarchical structure of the mouse isocortex but also further annotated cell types that were not identified by original methods in the mouse hypothalamus.

bioinformatics↗

bioRxiv2022

A genome-wide screen identifies SCAI as a modulator of the UV-induced replicative stress response in human cells

Helix-destabilizing DNA lesions induced by environmental mutagens such as UV light cause genomic instability by strongly blocking the progression of DNA replication forks (RF). At blocked RF, single-stranded DNA (ssDNA) accumulates and is rapidly bound by Replication Protein A (RPA) complexes. Such stretches of RPA-ssDNA constitute platforms for recruitment/activation of critical factors that promote DNA synthesis restart. However, during periods of severe replicative stress, RPA availability may become limiting due to inordinate sequestration of this multifunctional complex on ssDNA, thereby negatively impacting multiple vital RPA-dependent processes. Here, we performed a genome-wide screen to identify factors which restrict the accumulation of RPA-ssDNA during UV-induced replicative stress. While this approach revealed some expected "hits" acting in pathways such as nucleotide excision repair, translesion DNA synthesis, and the intra-S phase checkpoint, it also identifed SCAI, whose role in the replicative stress response was previously unappreciated. Upon UV exposure, SCAI knock-down caused elevated accumulation of RPA-ssDNA during S phase, accompanied by reduced cell survival and compromised RF progression. These effects were independent of the previously reported role of SCAI in 53BP1-dependent DNA double-strand break repair. We also found that SCAI colocalized with stalled RF, and that its depletion promoted nascent DNA degradation. Finally, we (i) provide evidence that EXO1 is the major nuclease underlying ssDNA formation and consequent DNA replication defects in SCAI knockout cells and, consistent with this, (ii) demonstrate that SCAI inhibits EXO1 activity on a ssDNA gap in vitro. Taken together, our data establish SCAI as a novel regulator of the replicative stress response in human cells.

molecular biology↗

bioRxiv2022

Novel MBLs inhibitors screened from FDA-approved drug library restore the susceptibility of carbapenems to NDM-1-harbouring bacteria

The production of metallo-{beta}-lactamases (MBLs) is one of the major mechanisms adopted by bacterial pathogens to resist carbapenems. One promising strategy to overcome MBLs-mediated carbapenems resistance is to develop effective inhibitors. Repurposing approved drugs to restore the efficacy of carbapenems represents an efficient and cost-effective approach to fight infections caused by carbapenem resistant pathogens. Here, twelve FDA-approved compounds were screened to neutralize the ability of NDM-1. Among these compounds, dexrazoxane, embelin, candesartan cilexetil (CAN) and nordihydroguaiaretic acid (NDGA) were further demonstrated to inhibit all tested MBLs, and showed an in vitro synergistic bactericidal effect with meropenem against MBLs-producing bacteria. Mechanistic studies revealed that dexrazoxane, embelin and CAN are metal ion chelating agents, while the inhibition of NDM-1 by NDGA involves its direct binding with the active region of NDM-1. Furthermore, dexrazoxane, embelin and CAN and NDGA dramatically rescued the treatment efficacy of meropenem in three infection models. Our observations indicated that dexrazoxane, embelin, CAN and NDGA are promising carbapenem adjuvants against MBLs-positive carbapenem resistant bacterial pathogens.

microbiology↗

bioRxiv2022

Time-lapsed proteomics reveals a role for the novel protein, SNED1, in modulating ECM composition and protein folding

The extracellular matrix (ECM) is a complex and dynamic meshwork of proteins providing structural support to cells. It also provides biochemical signals governing cellular processes including proliferation and migration. Alterations of ECM structure and/or composition has been shown to lead to, or accompany, many pathological processes including cancer and fibrosis. To understand how the ECM contributes to diseases, we first need to obtain a comprehensive characterization of the ECM of tissues and of its changes during disease progression. Over the past decade, mass-spectrometry-based proteomics has become the state-of-the-art method to profile the protein composition of ECMs. However, existing methods do not fully capture the broad dynamic range of protein abundance in the ECM, nor do they permit to achieve the high coverage needed to gain finer biochemical information, including the presence of isoforms or post-translational modifications. In addition, broadly adopted proteomic methods relying on extended trypsin digestion do not provide structural information on ECM proteins, yet, gaining insights into ECM protein structure is critical to better understanding protein functions. Here, we present the optimization of a time-lapsed proteomic method using limited proteolysis of partially denatured samples and the sequential release of peptides to achieve superior sequence coverage as compared to standard ECM proteomic workflow. Exploiting the spatio-temporal resolution of this method, we further demonstrate how 3-dimensional time-lapsed peptide mapping can identify protein regions differentially susceptible to trypsin and can thus identify sites of post-translational modifications, including protein-protein interactions. We further illustrate how this approach can be leveraged to gain insight on the role of the novel ECM protein SNED1 in ECM homeostasis. We found that the expression of SNED1 by mouse embryonic fibroblasts results in the alteration of overall ECM composition and the sequence coverage of certain ECM proteins, raising the possibility that SNED1 could modify accessibility to trypsin by engaging in protein-protein interactions.

cell biology↗

bioRxiv2022

Sequence Coverage Visualizer: A web application for protein sequence coverage 3D visualization

Protein structure is connected with its function and interaction and plays an extremely important role in protein characterization. As one of the most important analytical methods for protein characterization, Proteomics is widely used to determine protein composition, quantitation, interaction, and even structures. However, due to the gap between identified proteins by proteomics and available 3D structures, it was very challenging, if not impossible, to visualize proteomics results in 3D and further explore the structural aspects of proteomics experiments. Recently, two groups of researchers from DeepMind and Baker lab have independently published protein structure prediction tools that can help us obtain predicted protein structures for the whole human proteome. Although there is still debate on the validity of some of the predicted structures, it is no doubt that these represent the most accurate predictions to date. More importantly, this enabled us to visualize the majority of human proteins for the first time. To help other researchers best utilize these protein structure predictions, we present the Sequence Coverage Visualizer (SCV), http://scv.lab.gy, a web application for protein sequence coverage 3D visualization. Here we showed a few possible usages of the SCV, including the labeling of post-translational modifications and isotope labeling experiments. These results highlight the usefulness of such 3D visualization for proteomics experiments and how SCV can turn a regular result list into structural insights. Furthermore, when used together with limited proteolysis, we demonstrated that SCV can help validate and compare different protein structures, including predicted ones and existing PDB entries. By performing limited proteolysis on native proteins at various time points, SCV can visualize the progress of the digestion. This time-series data further allowed us to compare the predicted structure and existing PDB entries. Although not deterministic, these comparisons could be used to refine current predictions further and represent an important step towards a complete and correct protein structure database. Overall, SCV is a convenient and powerful tool for visualizing proteomics results.

bioinformatics↗

bioRxiv2022

Repeated toxic injuries of murine liver are tolerated through microsteatosis and mild inflammation

The liver has a remarkable capacity to regenerate and thus compensates for repeated injuries through toxic chemicals, drugs, alcohol or malnutrition for decades. However, largely unknown is how and when alterations in the liver occur due to tolerable damaging insults. To that end, we induced repeated liver injuries over ten weeks in a mouse model injecting carbon tetrachloride (CCl4) twice a week. We lost 10% of the study animals within the first six weeks, which was accompanied by a steady deposition of extracellular matrix (ECM) regardless of metabolic activity of the liver. From week six onwards, all mice survived, and in these mice ECM deposition was rather reduced, suggesting ECM remodeling as a liver response contributing to better coping with repeated injuries. The data of time-resolved paired transcriptome and proteome profiling of 18 mice was subjected to multi-level network inference, using Knowledge guided Multi-Omics Network inference (KiMONo), identified multi-level key markers exclusively associated with the injury-tolerant liver response. Interestingly, pathways of cancer and inflammation were lighting up and were validated using independent data sets compiled of 1034 samples from publicly available human cohorts. A yet undescribed link to lipid metabolism in this damage-tolerant phase was identified. Immunostaining revealed an unexpected accumulation of small lipid droplets (microvesicular steatosis) in parallel to a recovery of catabolic processes of the liver to pre-injury levels. Further, mild inflammation was experimentally validated. Taken together, we identified week six as a critical time point to switch the liver response program from an acute response that fosters ECM accumulation to a tolerant "survival" phase with pronounced deposition of small lipid droplets in hepatocytes potentially protecting against the repetitive injury with toxic chemicals. Our data suggest that microsteatosis formation plus a mild inflammatory state represent biomarkers and probably functional liver requirements to resist chronic damage. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=163 HEIGHT=200 SRC="FIGDIR/small/476054v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@11ecc7aorg.highwire.dtl.DTLVardef@1027df5org.highwire.dtl.DTLVardef@9ba0f7org.highwire.dtl.DTLVardef@164f80a_HPS_FORMAT_FIGEXP M_FIG C_FIG The datasets generated via transcriptomics, proteomics as well as blood, histopathological and biochemical analysis were analyzed in an independent and integrative manner. The independent analysis was performed via state-of-the-art statistical approaches i.e. differential and consistently regulated genes and proteins. Combining the results identified three fibrosis phases. Using the KiMONo algorithm, a fibrosis specific multi-omic network was inferred. Within this network we identified several nodes connecting phase III specific features forming 13 distinct multi-omic modules suggesting a tolerance scheme. Some of these modules were experimentally validated and compared to 11 independent human studies of various liver diseases.

systems biology↗

bioRxiv2022

Chronic Ca2+ imaging of cortical neurons with long-term expression of GCaMP-X

Dynamic Ca2+ signals reflect acute changes in membrane excitability (e.g. sensory response), and also mediate intracellular signaling cascades normally of longer time scales (e.g., Ca2+-dependent neuritogenesis). In both cases, chronic Ca2+ imaging has been often desired, but largely hindered by unexpected cytotoxicity intrinsic to GCaMP, a popular series of genetically-encoded Ca2+ indicators. Here, we demonstrate that the recently developed GCaMP-X outperforms GCaMP in long-term probe expression and/or chronic Ca2+ imaging. GCaMP-X shows much improved compatibility with neurons and thus more reliable than GCaMP as demonstrated in vivo by acute Ca2+ responses to whisker deflection or spontaneous Ca2+ fluctuations over an extended time frame. Chronic Ca2+ imaging data ([≥]1 month) are acquired from the same set of cultured cortical neurons, unveiling that spontaneous/local Ca2+ activities would progressively develop into autonomous/global Ca2+ oscillations. Besides the morphological indices of neurite length or soma size, the major metrics of oscillatory Ca2+, including rate, amplitude, synchrony among different neurons or organelles have also been examined along with the developmental stages. Both neuritogenesis and Ca2+ signals are dysregulated by GCaMP in virus-infected or transgenic neurons, in direct contrast to GCaMP-X without any noticeable side-effect. Such in vitro data altogether consolidate the unique importance of oscillatory Ca2+ to activity-dependent neuritogenesis, as one major factor responsible for the distinctions between GCaMP vs GCaMP-X in vivo. For the first time with GCaMP-X of long-term expression in neurons, spontaneous and sensory-evoked Ca2+ activities are imaged and evaluated both in vitro and in vivo, providing new opportunities to monitor neural development or other chronic processes concurrently with Ca2+ dynamics.

neuroscience↗

bioRxiv2022

Efficient inactivation of African swine fever virus by a highly complexed iodine combined with compound organic acids

African swine fever (ASF) is a highly contagious disease with high morbidity and mortality caused by African swine fever virus (ASFV). Cleaning and disinfection remain one of the most effective biosecurity measures to prevent and control the spread of ASFV. In this study, we evaluated the inactivation effects of highly complexed iodine (HPCI) combined with compound organic acids (COAs) against ASFV under different conditions. The results showed that the inactivation rates of the disinfectants on the reporter ASFV increased in dose- and time-dependent manners, the best inactivation effects were obtained when the compatibility ratio of HPCI and COAs was 5:1 at 25{degrees}C. Furthermore, there were no significant differences by comparing the efficacy of HPCI combined with COAs (HPCI+COAs) in inactivating wild-type ASFV and the reporter ASFV (P > 0.05). ASFV of 104.0 TCID50/mL was completely inactivated by 0.13% HPCI (0.0065% effective iodine), 0.06% COAs or 0.13% HPCI+COAs (approximately 0.0054% effective iodine), respectively, while 106.0 TCID50/mL ASFV was completely inactivated by 1.00% HPCI (0.05% effective iodine), 0.50% COAs or 1.00% HPCI+COAs (0.042% effective iodine), respectively. Therefore, HPCI+COAs had synergistic effects to inactivate ASFV. This study demonstrated that HPCI+COAs could rapidly and efficiently inactivate ASFV and represent an effective compound disinfectant for the control of ASF. IMPORTANCEAfrican swine fever (ASF) is a highly contagious disease with high morbidity and mortality caused by African swine fever virus (ASFV). Due to the lack of commercial vaccines and treatment available for ASF, effective disinfectants and the proper use of them are extremely essential to inactivate ASFV. The significance of this research is in searching for an ideal disinfectant that not only has the advantages of low toxicity and non-pollution but also can inactivate ASFV rapidly and efficiently. In this study, we proved that HPCI+COAs not only exhibited low cytotoxicity, but also could completely inactivate ASFV within 5 min at 4{degrees}C, 25{degrees}C and 37{degrees}C. In addition, HPCI+COAs had synergistic effects on inactivated ASFV. Thus, HPCI +COAs could be used as an effective disinfectant for the control of ASF.

microbiology↗

bioRxiv2022

Structural insights as to how iron-loaded siderophores are imported into Mycobacterium tuberculosis by IrtAB

The ATP-binding cassette (ABC) transporter, IrtAB, plays a vital role in the replication and viability of Mycobacterium tuberculosis (Mtb), where its function is to import iron-loaded siderophores. Unusually, it adopts the typical fold of canonical ABC exporters. Here, we report the structure of unliganded Mtb IrtAB and its structure in complex with ATP, ADP, and an ATP analogue (AMP-PNP) at resolutions from 2.9 to 3.5 [A]. In the ATP-bound state, the two nucleotide-binding domains (NBDs) form a "head-to-tail" dimer, but IrtAB has an unexpectedly occluded conformation, with the inner core forming a large hydrophilic cavity of about 4600 [A]3. Comparison of the structure of the transporter in inward-facing and occluded conformations reveals that the NBD and the intracellular helical region of transmembrane domain (TMD) have an asymmetric allosteric mechanism when ATP binding/hydrolysis such that the one exhibits rigid-body rotation and the other moves in a concerted response as a rigid body. This study provides a molecular basis for the ATP-driven conformational changes that occur in IrtAB and an explanation as to how iron-loaded siderophores are imported into Mtb by IrtAB.

molecular biology↗

bioRxiv2021

A systems approach discovers the role and characteristics of seven LysR type transcription factors in Escherichia coli

Although Escherichia coli K-12 strains represent perhaps the best known model bacteria, we do not know the identity or functions of all of their transcription factors (TFs). It is now possible to systematically discover the physiological function of TFs in E. coli BW25113 using a set of synergistic methods; including ChIP-exo, growth phenotyping, conserved gene clustering, and transcriptome analysis. Among 47 LysR-type TFs (LTFs) found on the E. coli K-12 genome, many regulate nitrogen source utilization or amino acid metabolism. However, 19 LTFs remain unknown. In this study, we elucidated the regulation of seven of these 19 LTFs: YbdO, YbeF, YgfI, YiaU, YneJ, YcaN, YbhD. We show that: 1) YbdO regulation has an effect on bacterial growth at low pH with citrate supplementation. YbdO is a repressor of the ybdNM operon and is implicated in the regulation of citrate lyase genes (citCDEFG); 2) YgfI activates the dhaKLM operon that encodes the phosphotransferase system involved in glycerol and dihydroxyacetone utilization; 3) YiaU regulates the yiaT gene encoding an outer membrane protein, and waaPSBOJYZU operon is also important in determining cell density at the stationary phase; 4) YneJ, re-named here as PtrR, directly regulates the expression of the succinate-semialdehyde dehydrogenase, Sad (also known as YneI), and is a predicted regulator of fnrS (a small RNA molecule). PtrR is important for bacterial growth in the presence of L-glutamate and putrescine as nitrogen sources; and 5) YbhD and YcaN regulate adjacent y-genes on the genome and YbeF is involved in flagella gene regulation. We have thus established the functions for four LTFs and identified the target genes for three LTFs. IMPORTANCEThe reconstruction of the transcriptional regulatory network (TRN) is important for gram-negative bacteria such as E. coli. LysR-type TFs are abundant in Enterobacteria, but many LTF functions still remain unknown. Here we report putative functions of uncharacterized TFs based on multi-omics data related to L-threonine, L-glutamate, and putrescine utilization. Amino acids (AAs) and polyamines are important sources of nitrogen for many microorganisms, but the increase in one amino acid or putrescine concentration in a minimal medium also induces stress. Although polyamine metabolism has been studied, the TRN that controls the putrescine (Ptr) and AA utilization at minimal medium conditions are still poorly understood. The function of previously uncharacterized transcriptional regulators YbdO, YgfI, and YneJ (PtrR) were identified in Escherichia coli. PtrR is important for Ptr and L-glutamate utilization, while YgfI transcriptional regulation was found to be important for growth on L-threonine and glycerol as a carbon source.

systems biology↗

bioRxiv2021

Response of Surface Water Quality Characteristics to Socio-economic Factors in Eastern-Central China

Following the implementation of the strictest water resource management system in China, it has become increasingly important to understand and improve the surface water quality and the rate at which water function zones reach the water quality standard. Based on the monthly monitoring data from 450 monitoring sites at the provincial borders of 27 provinces in China in 2019, the overall surface water quality at provincial boundaries in China was as follows: 61.7% of the water was classified under Class I-III; and 5%, 8.6%, and 12.2% of the water was classified under Class IV, V, and inferior V, respectively. The main standard items are DO, CODMn, COD, BOD5, NH3-N, and TP. The Canadian Council of Ministers of the Environment-water quality index (CCME-WQI) showed that the provincial boundary water quality exceeded the fair level, and F1 was the most influential factor. Then, 27 factors that directly or indirectly affect the water quality of surface water at the provincial boundaries of 27 provinces were identified, and the indirect influencing factors were integrated into the ecological environmental quality index and human activities quantitative index. Finally, the 27 factors were integrated into six factors, and the relationship between these indicators and CCME-WQI as well as the concentration of influencing elements with respect to regulatory standard limits were analyzed. The proportion of building land was the most significant factor affecting the quality of the aquatic environment in provincial boundaries. In addition, the economic development level, proportion of farmland, and degree of social development were identified as significant influencing factors. The six factors have different degrees of impact on the concentrations of major elements with respect to standard limits. This study basically explores water resource management and offers significant reference and guidelines for the improvement of the quality of surface water at provincial boundaries in China.

biochemistry↗

bioRxiv2021

The dual role of N6-methyladenosine on mouse maternal RNAs and 2-cell specific RNAs revealed by ULI-MeRIP sequencing

N6-methyladenosine (m6A) and its regulatory components play critical roles in various developmental processes in mammals(1-5). However, the landscape and function of m6A in the maternal-to-zygotic transition (MZT) remain unclear due to limited materials. Here, by developing an ultralow-input MeRIP-seq method, we revealed the dynamics of the m6A RNA methylome during the MZT process in mice. We found that more than 1/3 maternal decay and 2/3 zygotic mRNAs were modified by m6A. Moreover, m6As are highly enriched in the RNA of transposable elements MTA and MERVL, which are highly expressed in oocytes and 2-cell embryos, respectively. Notably, maternal depletion of Kiaa1429, a component of the m6A methyltransferase complex, leads to a reduced abundance of m6A-marked maternal RNAs, including both genes and MTA, in GV oocytes, indicating m6A-dependent regulation of RNA stability in oocytes. Interestingly, when the writers were depleted, some m6A-marked 2-cell specific RNAs, including Zscan4 and MERVL, appeared normal at the 2-cell stage but failed to be decayed at later stages, suggesting that m6A regulates the clearance of these transcripts. Together, our study uncovered that m6As function in context-specific manners during MZT, which ensures the transcriptome stability of oocytes and regulates the stage specificity of zygotic transcripts after fertilization. One Sentence Summarym6A RNA methylation stabilizes the maternal RNAs in mouse oocytes and degrades the 2-cell specific RNAs in the cleavage-stage embryos.

developmental biology↗

bioRxiv2021

Automated identification of chicken distress vocalisations using deep learning models

The annual global production of chickens exceeds 25 billion birds, and they are often housed in very large groups, numbering thousands. Distress calling triggered by various sources of stress has been suggested as an "iceberg indicator" of chicken welfare. However, to date, the identification of distress calls largely relies on manual annotations, which is very labour-intensive and time-consuming. Thus, a novel light-VGG11 was developed to automatically identify chicken distress calls using recordings (3,363 distress calls and 1,973 natural barn sounds) collected on intensive chicken farms. The light-VGG11 was modified from VGG11 with a significantly smaller size in parameters (9.3 million vs 128 million) and 55.88% faster detection speed while displaying comparable performance, i.e., precision (94.58%), recall (94.89%), F1-score (94.73%), and accuracy (95.07%), therefore more useful for model deployment in practice. To further improve the light-VGG11s performance, we investigated the impacts of different data augmentation techniques (i.e., time masking, frequency masking, mixed spectrograms of the same class, and Gaussian noise) and found that they could improve distress calls detection by up to 1.52%. In terms of precision livestock farming, our research opens new opportunities for developing technologies used to monitor the output of distress calls in large, commercial chicken flocks.

animal behavior and cognition↗

bioRxiv2021

Modeling of microRNA-derived disease network repurposes methotrexate for the prevention and therapy of abdominal aortic aneurysm in mice

Abdominal aortic aneurysm (AAA) is a highly lethal vascular disease characterized by permanent dilatation of the abdominal aorta. The main purpose of the current study is to search for noninvasive medical therapies for abdominal aortic aneurysm (AAA), for which there is currently no effective drug therapy. Network medicine represents a cutting-edge technology, as analysis and modeling of disease networks can provide critical clues regarding the etiology of specific diseases and which therapeutics may be effective. Here, we proposed a novel algorithm to quantify disease relations based on a large accumulated microRNA-disease association dataset and then built a disease network that covered 15 disease classes and included 304 diseases. Analysis revealed a number of patterns for these diseases; for example, diseases tended to be clustered and coherent in the network. Surprisingly, we found that AAA showed the strongest similarity with rheumatoid arthritis and systemic lupus erythematosus, both of which are autoimmune diseases, suggesting that AAA could be one type of autoimmune disease in etiology. Based on this observation, we further hypothesized that drugs for autoimmune disease could be repurposed for the prevention and therapy of AAA. Finally, animal experiments confirmed that methotrexate, a drug for autoimmune disease, was able to prevent the formation and inhibit the development of AAA.

bioinformatics↗

bioRxiv2021

Develop an efficient and specific AAV-based labeling system for Muller glia in mice

Cell degeneration in the retina leads to several ocular diseases and vision loss. Considerable research efforts focus on reprogramming Muller glia (MG) into functional cells to rescue vision as a promising therapeutic strategy, although whether MG can convert into functional bipolar cells, retinal ganglia cells (RGCs), rods or cones in mammals remains controversial. The broad applicability of tracking MG differentiation thus presents a need for improved labeling efficiency and specificity. Here, we compared AAV-based labeling strategies with conventional lineage-tracking by crossing transgenic mouse lines. We found that reporter expression was weak and not MG-specific in mGFAP-Cre transgenic mice. Different AAV serotypes showed a range of efficiency and specificity in labeling MG, leading us to optimize a human GFAP-Cre reporter system packaged in the AAV9 serotype with the WPRE (WPRE, woodchuck hepatitis virus post-transcriptional regulatory element) removed. The hGFAP-Cre- {Delta}WPRE reporter could label 20-73.8% MGs, with non-specific RGC labeling rates ranging from 0-0.08% at doses of 1 x 108 to 1010 vector genomes (vg) per eye, an approximate 40-fold reduction compared with the AAV9-hGFAP-Cre-WPRE labeling system. Furthermore, we validated the availability of the label system to trace MG reprogramming and also detected false-positive results reported previously. The AAV9-hGFAP-Cre-{Delta}WPRE system thus represents a highly efficient and specific labeling system for MG, providing a valuable tool for tracking cell fate in vivo.

neuroscience↗

bioRxiv2021

Regional Topological Aberrances of White Matter- and Gray Matter-based Functional Networks for Attention Processing may Foster Traumatic Brain Injury-Related Attention Deficits in Adults

Traumatic brain injury (TBI) is highly prevalent in adults. TBI-related functional brain alterations have been linked with common post-TBI neurobehavioral sequelae, with unknown neural sub-strates. This study examined the systems-level functional brain alterations in white matter (WM) and gray matter (GM) for visual sustained attention processing, their interactions, and contribution to post-TBI attention deficits. Task-based functional MRI data were collected from 42 adults with TBI and 43 group-matched normal controls (NCs), and analyzed using the graph theoretic tech-nique. Global and nodal topological properties were calculated and compared between the two groups. Correlation analyses were conducted between the neuroimaging measures that showed significant between-group differences and the behavioral symptom measures in attention domain in the groups of TBI and NCs, respectively. Significantly altered nodal efficiency and/or degree in several WM and GM nodes were reported in the TBI group, including the posterior corona radiata (PCR), posterior thalamic radiation (PTR), postcentral gyrus (PoG), and superior temporal sulcus (STS). Subjects with TBI also demonstrated abnormal systems-level functional synchronization between the PTR and STS in the right hemisphere, hypo-interaction between PCR and PoG in the left hemisphere; as well as the involvement of systems-level functional aberrances in PCR in TBI-related behavioral impairments in the attention domain. Findings of the current study suggest that TBI-related systems-level functional alterations associated with these two major association WM tracts and their anatomically connected GM regions may play critical role in TBI-related behavioral deficits in attention domain.

neuroscience↗

bioRxiv2021

Joint Learning of Full-structure Noise in Hierarchical Bayesian Regression Models

We consider the reconstruction of brain activity from electroencephalography (EEG). This inverse problem can be formulated as a linear regression with independent Gaussian scale mixture priors for both the source and noise components. Crucial factors influencing the accuracy of the source estimation are not only the noise level but also its correlation structure, but existing approaches have not addressed the estimation of noise covariance matrices with full structure. To address this shortcoming, we develop hierarchical Bayesian (type-II maximum likelihood) models for observations with latent variables for source and noise, which are estimated jointly from data. As an extension to classical sparse Bayesian learning (SBL), where across-sensor observations are assumed to be independent and identically distributed, we consider Gaussian noise with full covariance structure. Using the majorization-maximization framework and Riemannian geometry, we derive an efficient algorithm for updating the noise covariance along the manifold of positive definite matrices. We demonstrate that our algorithm has guaranteed and fast convergence and validate it in simulations and with real MEG data. Our results demonstrate that the novel framework significantly improves upon state-of-the-art techniques in the real-world scenario where the noise is indeed non-diagonal and full-structured. Our method has applications in many domains beyond biomagnetic inverse problems.

neuroscience↗

bioRxiv2021

Increased heterogeneity and task-related reconfiguration of functional connectivity within a lexicosemantic network in autism

Autism spectrum disorder (ASD) is highly heterogeneous in etiology and clinical presentation. Findings on intrinsic functional connectivity (FC) or task-induced FC in ASD have been inconsistent including both over- and underconnectivity and diverse regional patterns. As FC patterns change across different cognitive demands, a novel and more comprehensive approach to network architecture in ASD is to examine the change in FC patterns between rest and task states, referred to as reconfiguration. This approach is suitable for investigating inefficient network connectivity that may underlie impaired behavioral functioning in clinical disorders. We used functional magnetic resonance imaging (fMRI) to examine FC reconfiguration during lexical processing, which is often affected in ASD, with additional focus on interindividual variability. Thirty adolescents with ASD and a matched group of 23 typically developing (TD) participants completed a lexicosemantic decision task during fMRI, using multiecho-multiband pulse sequences with advanced BOLD signal sensitivity and artifact removal. Regions of interest (ROIs) were selected based on task-related activation across both groups, and FC and reconfiguration were compared between groups. The ASD group showed increased interindividual variability and overall greater reconfiguration than the TD group. An ASD subgroup with typical performance accuracy (at the level of TD participants) showed reduced similarity and typicality of FC during the task. In this ASD subgroup, greater FC reconfiguration was associated with increased language skills. Findings suggest that intrinsic functional networks in ASD may be inefficiently organized for lexicosemantic decisions and may require greater reconfiguration during task processing, with high performance levels in some individuals being achieved through idiosyncratic mechanisms. HighlightsFC reconfiguration is a comprehensive approach to examining network architecture Functional networks are inefficiently organized for lexicosemantic decisions in ASD ASD may require greater reconfiguration during task processing Some ASD individuals achieve high performance through idiosyncratic mechanisms

neuroscience↗