Biology subjects

Li, G.

Publications and source records attributed to Li, G..

At least 307 records · Page 17Linked to original sources

bioRxiv2023

The emergence and diversification of a zoonotic pathogen from within the microbiota of intensively farmed pigs

The expansion and intensification of livestock production is predicted to promote the emergence of pathogens. As pathogens sometimes jump between species this can affect the health of humans as well as livestock. Here we investigate how livestock microbiota can act as a source of these emerging pathogens through analysis of Streptococcus suis, a ubiquitous component of the respiratory microbiota of pigs that is also a major cause of disease on pig farms and an important zoonotic pathogen. Combining molecular dating, phylogeography and comparative genomic analyses of a large collection of isolates, we find that several pathogenic lineages of S. suis emerged in the 19th and 20th centuries, during an early period of growth in pig farming. These lineages have since spread between countries and continents, mirroring trade in live pigs. They are distinguished by the presence of three genomic islands with putative roles in metabolism and cell adhesion, and an ongoing reduction in genome size, which may reflect their recent shift to a more pathogenic ecology. Reconstructions of the evolutionary histories of these islands reveal constraints on pathogen emergence that could inform control strategies, with pathogenic lineages consistently emerging from one subpopulation of S. suis and acquiring genes through horizontal transfer from other pathogenic lineages. These results shed light on the capacity of the microbiota to rapidly evolve to exploit changes in their host population and suggest that the impact of changes in farming on the pathogenicity and zoonotic potential of S. suis is yet to be fully realised.

evolutionary biology↗

bioRxiv2023

Interpretable modeling of time-resolved single-cell gene-protein expression using CrossmodalNet

Cell-surface proteins play a critical role in cell function and are primary targets for therapeutics. CITE-seq is a single-cell technique that enables simultaneous measurement of gene and surface protein expression. It is powerful but costly and technically challenging. Computational methods have been developed to predict surface protein expression using gene expression information such as from single-cell RNA sequencing (scRNA-seq) data. Existing methods however are computationally demanding and lack the interpretability to reveal underlying biological processes. We propose CrossmodalNet, an interpretable machine learning model, to predict surface protein expression from scRNA-seq data. Our model with a customized adaptive loss accurately predicts surface protein abundances. When samples from multiple time points are given, our model encodes temporal information into an easy-to-interpret time embedding to make prediction in a time point-specific manner able to uncover noise-free causal gene-protein relationships. Using two publicly available time-resolved CITE-seq data sets, we validate the performance of our model by comparing it to benchmarking methods and evaluate its interpretability. Together, we show our method accurately and interpretably profiles surface protein expression using scRNA-seq data, thereby expanding the capacity of CITE-seq experiments for investigating molecular mechanisms involving surface proteins.

bioinformatics↗

bioRxiv2023

Novel discovery of a lymphatic bridge connecting Schlemm's canal to limbal and conjunctival lymphatic pathway

PurposeSchlemms canal (SC) is a critical structure regulating aqueous humor (AH) drainage and intraocular pressure (IOP). It is known that in the conventional outflow pathway, AH flows from SC to episcleral veins. We recently reported a high-resolution three-dimensional (3D) imaging technology for intact eyeballs, SC and ocular surface. Using this advanced technology, we herein report the discovery of a new structure, termed lymphatic bridge, that directly connects SC to the limbal and conjunctival lymphatic pathway. Further investigation on this novel outflow pathway may provide new mechanisms and therapeutic approaches for glaucoma. MethodsAs reported previously, intact eyeballs were harvested from Prox-1-GFP (green fluorescent protein) mice and processed by a tissue clearing technique with CLARITY. Samples were immunolabeled with specific antibodies for CD31 (pan-endothelial marker) and LYVE-1 (lymphatic vessel endothelial hyaluronan receptor-1) and imaged by light-sheet fluorescent microscopy. The limbal areas were examined to locate connecting channels between SC and limbal and conjunctival lymphatic vessels. Moreover, in vivo anterior chamber dye injection was performed with Texas Red dextran for functional analysis on AH outflow. ResultsA novel lymphatic bridge structure that expressed both Prox-1 and LYVE-1 was discovered between the SC and limbal lymphatic vessels connected with conjunctival lymphatic pathway. Results from the anterior chamber dye injection showed AH drainage into the conjunctival lymphatic outflow pathway. ConclusionsThis study provides the first evidence on the direct connection between SC and limbal and conjunctival lymphatic pathway. This new pathway is distinctive from the conventional episcleral vein pathway and merits further investigation.

physiology↗

bioRxiv2023

Exercise improved P2Y12-regulated microglial dynamics during stroke via endocannabinoid signaling

Microglia are vigilant housekeepers in the adult brain, they continually extend and retract their processes to survey their microenvironment. In a dependent manner involving P2Y12 receptors, microglia undergo morphological and functional changes to form microglia-neuron contacts to protect neurons from damage. By using in vivo two-photon imaging, we found that physical exercise (PE) upregulated microglial P2Y12 expression, increased microglial dynamics, and promoted the microglia contacting with neurons in a mouse model of transit middle cerebral artery occlusion (tMCAO). As a result, microglial processes inhibited neuronal calcium overloads, protected against damage of the neuronal mitochondria and synaptic structure. Inhibition of P2Y12 by PSB0739 abolished the protection induced by PE. Mechanistically, we found PE increased the cannabinoid receptor 2 (CBR2) in microglia, and administration of AM630, a CBR2 antagonist, decreased P2Y12R expression and abolished PE-mediated effects. These findings identified endocannabinoid signaling may as the critical regulator of the PE-induced P2Y12-mediated effect whereby PE increased the endocannabinoid system to regulate purinergic signaling, further inducing microglial processes at microglia-neuron contacts to monitor and protect neuronal functioning.

neuroscience↗

bioRxiv2023

Plant recognition by Trichoderma harzianum elicits upregulation of a novel secondary metabolite cluster required for colonization

Trichoderma harzianum is a filamentous ascomycete frequently applied as biocontrol agent in agriculture. While mycoparasitism and antagonism of Trichoderma spp. against fungal pathogens are well known, early fungal responses to the presence of a plant await broader investigation. Analyzing early stages of plant-fungus communication we show that T. harzianum B97 chemotropically responds to a plant extract and that both plant and fungus alter secondary metabolite secretion upon recognition. We developed a strategy for omics-analysis simulating conditions of early plant recognition eliciting a chemotropic response in the fungus and found 102 genes to be differentially regulated, including nitrate and nitrite reductases. Additionally, the previously uncharacterized Plant Communication Associated (PCA) gene cluster was strongly induced upon recognition of the plant, comprises a palindromic DNA motif and was essential for plant colonization. The PCA-cluster is only present in the Harzianum clade of Trichoderma and closely related to a homologous cluster in Metarhizium spp. Horizontal gene transfer (HGT) was detected for PCA-cluster genes by plants, while the cluster in T. harzianum is likely under balancing or positive selection. Hence, the PCA-cluster mediates early fungus-plant chemical communication and may be responsible for the high potential of T. harzianum and closely related species for biocontrol applications. Plain language summaryInteractions of plants with fungi - beneficial or pathogenic - are crucial for the ecological function of both partners. Yet, the chemical "language" they use and how or when they use it is still insufficiently known. We describe discovery of a novel gene cluster, which is strongly induced upon plant recognition and essential for plant-fungal interkingdom interaction in the biocontrol-agent Trichoderma harzianum.

microbiology↗

bioRxiv2023

Doxorubicin inhibits phosphatidylserine decarboxylase and confers broad-spectrum antifungal activity

O_LIAs phospholipids of cell membranes, phosphatidylethanolamine (PE) and phosphatidylserine (PS) play crucial roles in glycerophospholipid metabolism. Broadly, some phospholipid biosynthesis enzymes serve as potential fungicide targets. Therefore, revealing the functions and mechanism of PE biosynthesis in plant pathogens would provide potential targets for crop disease control. C_LIO_LIWe performed analyses including phenotypic characterizations, lipidomics, enzyme activity, site-directed mutagenesis, and chemical inhibition assays to study the function of PS decarboxylase-encoding gene MoPSD2 in rice blast fungus Magnaporthe oryzae. C_LIO_LIThe Mopsd2 mutant was defective in development, lipid metabolism and plant infection. The PS level increased while PE decreased in Mopsd2, consistent with the enzyme activity. Furthermore, chemical doxorubicin inhibited the enzyme activity of MoPsd2 and showed antifungal activity against ten phytopathogenic fungi including M. oryzae and reduced disease severity of two crop diseases in the field. Three predicted doxorubicin-interacting residues are important for MoPsd2 functions. C_LIO_LIOur study demonstrates that MoPsd2 is involved in de novo PE biosynthesis and contributes to the development and plant infection of M. oryzae and that doxorubicin shows broad-spectrum antifungal activity as a fungicide candidate. The study also implicates that bacterium Streptomyces peucetius, which biosynthesizes doxorubicin, could be potentially used as an eco-friendly biocontrol agent. C_LI

pathology↗

bioRxiv2023

Inhibition of serotonin biosynthesis in neuroendocrine neoplasm suppressestumor growth in vivo

Small bowel neuroendocrine tumors (SBNETs) originate from enterochromaffin cells in the intestine which synthesize and secrete serotonin. SBNETs express high levels of tryptophan hydroxylase 1 (Tph1), a key enzyme in serotonin biosynthesis. Patients with high serotonin level may develop carcinoid syndrome, which can be treated with somatostatin analogues and the Tph1 inhibitor telotristat ethyl in severe cases. Although the active drug telotristat can efficiently reduce serotonin levels, its effect on tumor growth is unclear. This study determined the effect of serotonin inhibition on tumor cell growth in vitro and in vivo. The levels of Tph1 in various neuroendocrine neoplasms (NENs) were determined and the biological effects of Tph1 inhibition in vitro and in vivo using genetic and pharmacologic approaches was tested. Gene and protein expression analyses were performed on patient tumors and cancer cell lines. shRNAs targeting TPH1 were used to create stable knockdown in BON cells. Control and knockdown lines were assessed for their growth rates in vitro and in vivo, angiogenesis potential, serotonin levels, endothelial cell tube formation, tumor weight, and tumor vascularity. TPH1 is highly expressed in SBNETs and many cancer types. TPH1 knockdown cells and telotristat treated cells showed similar growth rates as control cells in vitro. However, TPH1 knockdown cells formed smaller tumors in vivo and tumors were less vascularized. Although Tph1 inhibition with telotristat showed no effect on tumor cell growth in vitro, Tph1 inhibition reduced tumor formation in vivo. Serotonin inhibition in combination with other therapies is a promising new avenue for targeting metabolic vulnerabilities in NENs.

cancer biology↗

bioRxiv2023

Loss of myeloid cannabinoid CB1 receptor confers atheroprotection by reducing macrophage proliferation and immunometabolic reprogramming

Although the cannabinoid CB1 receptor has been implicated in atherosclerosis, its cell-specific effects in this disease are not well understood. Here, we report that male mice with myeloid-specific Cnr1 deficiency on atherogenic background developed smaller lesions and necrotic cores than controls, while only minor genotype differences were observed in females. Male Cnr1 deficient mice showed reduced arterial monocyte recruitment and macrophage proliferation with less inflammatory phenotype. The sex-specific differences were reproducible in bone marrow derived macrophages and blunted by estradiol. Kinase activity profiling revealed a CB1-dependent regulation of p53 and cyclin-dependent kinases. Transcriptomic profiling further unveiled chromatin modifications, mRNA processing and mitochondrial respiration among the key processes affected by CB1 signaling, which was supported by metabolic flux assays. Chronic administration of the peripherally-restricted CB1 antagonist JD5037 inhibited plaque progression and macrophage proliferation, but only in male mice. Finally, CNR1 expression was detectable in human carotid endarterectomy plaques and inversely correlated with proliferation, oxidative metabolism and inflammatory markers, hinting to a possible implication of CB1-dependent regulation in human pathophysiology. In conclusion, impaired CB1 signaling in macrophages is atheroprotective by limiting their arterial recruitment, proliferation and inflammatory reprogramming. The importance of macrophage CB1 signaling seems to be more pronounced in male mice. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=105 SRC="FIGDIR/small/535832v2_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@1d0b2f4org.highwire.dtl.DTLVardef@94f1b4org.highwire.dtl.DTLVardef@8868edorg.highwire.dtl.DTLVardef@1a0b151_HPS_FORMAT_FIGEXP M_FIG C_FIG Graphical summary (created with BioRender.com)

immunology↗

bioRxiv2023

Revisiting the role of Acinetobacter sp. in EBPR systems

Side-stream Enhanced biological phosphorus removal (S2EBPR) has been incorporated with B-stage process to enable simultaneous phosphorus and nitrogen removal. However, the dominating phosphorus accumulating organisms (PAOs) in this novel configuration has not been evaluated. The dominance of Acinetobacter was confirmed by 16S sequencing. In addition, single cell Raman spectrum (SCRS) analysis in couple with in situ fluorescence in situ hybridization (FISH) was applied to obtain the feature spectrum and verify the phosphorus release/uptake activity of Acinetobacter spp. The phenotypic profiling further suggested the dominance of Acinetobacter-like organisms among all poly-phosphorus containing organisms and only certain phenotypic Acinetobacter (oligotype 1) contribution to P-removal in a unique HRAS-P(D)N-S2EBPR system. The findings suggest that Acinetobacter may outcompete other heterotrophic organisms in EBPR systems due to their sensitivity to operational conditions. However, stable P-removal was only observed during a specific section of the operation period, coinciding with an increase in the VFA/P ratio. Further research is needed to identify the phenotypes of Acinetobacter responsible for P-removal in EBPR systems. The study contributes to a better understanding of the microbial ecology and engineering aspects of EBPR systems and wastewater treatment in general.

bioengineering↗

bioRxiv2023

Comammox and Unknown Candidate AOBs Contribute to Nitrite Accumulation in An Integrated A-B stage process that Incorporates Side-stream EBPR (S2EBPR)

A novel integrated pilot-scale A-stage high rate activated sludge, B-stage short-cut biological nitrogen removal and side-stream enhanced biological phosphorus removal (A/B-shortcut N- S2EBPR) process for treating municipal wastewater was demonstrated with the aim to achieve simultaneous and carbon- and energy-efficient N and P removal. In this studied period, an average of 7.62 {+/-} 2.17 mg-N/L nitrite accumulation was achieved through atypical partial nitrification without canonical known NOB out-selection. Network analysis confirms the central hub of microbial community as Nitrospira, which was one to two orders of magnitude higher than canonical aerobic oxidizing bacteria (AOB) in a B-stage nitrification tank. The contribution of comammox Nitrospira as AOB was evidenced by the increased amoB/nxr ratio and higher ammonia oxidation activity. Furthermore, oligotyping analysis of Nitrospira revealed two dominant sub-clusters (microdiveristy) within the Nitrospira. The relative abundance of oligotype II, which is phylogenetically close to Nitrospira_midas_s_31566, exhibited a positive correlation with nitrite accumulation in the same operational period, suggesting its role as comammox Nitrospira. Additionally, the phylogenetic investigation suggested that heterotrophic organisms from the family Comamonadacea and the order Rhodocyclaceae embedding ammonia monooxygenase and hydroxylamine oxidase may function as heterotrophic nitrifiers. This is the first study that elucidated the impact of integrating the S2EBPR on nitrifying populations with implications on short-cut N removal. The unique conditions in the side-stream reactor, such as low ORP, favorable VFA concentrations and composition, seemed to exert different selective forces on nitrifying populations from those in conventional biological nutrient removal processes. The results provide new insights for integrating EBPR with short-cut N removal process for mainstream wastewater treatment.

bioengineering↗

bioRxiv2023

Molecular Evidence of Internal Carbon-Driven Partial Denitrification Annamox (PdNA) in a mainstream Pilot A-B System Coupled with Side-stream EBPR treating municipal wastewater

Achieving mainstream short-cut nitrogen removal via nitrite has been a carbon and energy-efficient goal which wastewater engineers are dedicated to explore. This study applied a novel pilot-scale A-B-S2EBPR system process integrated with sidestream enhanced biological phosphorus removal) to achieve the nitrite accumulation and downstream anammox for treating municipal wastewater. Nitrite accumulated to 5.5 {+/-} 0.3 mg N/L in the intermittently aerated tanks of B-stage with the nitrite accumulation ratio (NAR) of 79.1 {+/-} 6.5%. The final effluent concentration and removal efficiency of total inorganic nitrogen (TIN) were 4.6 {+/-} 1.8 mg N/L and 84.9 {+/-} 5.6%, respectively. Batch nitrification/denitrification activity tests and functional gene abundance of ammonium oxidizing bacteria (AOB) and nitrite oxidizing bacteria (NOB) suggested that the nitrite accumulation was mostly caused by partial denitrification without NOB- selection. The unique features of S2EBPR (longer anaerobic HRT/SRT, lower ORPs, high and more complex VFAs etc.) seemed to impact the nitrogen microbial communities: the conventional AOB kept at a very low level of 0.13 {+/-} 0.13% during the operation period, and the dominant candidate internal carbon-accumulating heterotrophic genera of Acinetobacter (17.8 {+/-} 15.5)% and Comamonadaceae (6.7 {+/-} 3.4%) were highly enriched. Furthermore, the single-cell Raman spectroscopy-based intracellular polymer analysis revealed the dominate microorganisms that could utilize polyhydroxyalkanoates (PHA) as the potential internal carbon source to drive partial denitrification. This study provides insights and a new direction for implementing the mainstream PdNA short-cut nitrogen removal via incorporating S2EBPR into sustainable A-B process.

bioengineering↗

bioRxiv2023

Clustering scRNA-seq data via qualitative and quantitative analysis

Single-cell RNA sequencing (scRNA-seq) technologies have been driving the development of algorithms of clustering heterogeneous cells. We introduce a novel clustering algorithm scQA, which can effectively and efficiently recognize different cell types via qualitative and quantitative analysis. It iteratively extracts quasi-trend-preserved genes to conform a consensus by representing expression patterns with dropouts qualitatively and quantitatively, and, then automatically clusters cells using a new label propagation strategy without specifying the number of cell types in advance. Validated on 20 public scRNA-seq datasets, scQA consistently outperformed 9 salient tools in both accuracy and efficiency across 16 out of 20 datasets tested, and ranked top 2 or 3 across the other 4 datasets. Furthermore, we demonstrate scQA can extract informative genes in both perspectives of biology and data wise by performing consensus, allowing genes used for landmark construction multiple characteristics, which is essential for clustering cells accurately. Overall, scQA could be a useful tool for discovery of cell types that can be integrated into general scRNA-seq analyses.

bioinformatics↗

bioRxiv2023

Duckweed evolution: from land back to water

Terrestialization is supposedly an important evolutionary process plant experience. However, directions of land back to water acquired little attention. Here we integrate multiproxy evidence to elucidate the evolution of duckweed. Three genera of duckweed show chronologically gradient degeneration in roots structure and stomatal function and decrease in lignocellulose content, accompanied by gradual contraction in relevant gene numbers and/or decline in transcription. The gene numbers in the main phytohormonal pathway are also gradually decreased. The co-action of auxin and rhizoid development gene causes a gradual decrease in adventitious roots. The significant expansion of the flavonoid pathway is also related to the adaptation of duckweed to floating growth. This study reconstructs the evolution history of duckweeds from land back to water, reverse to that of early land plants. SummaryWith terrestrialization being the popularly acknowledged plant evolutionary process, little is known about the evolution of higher plant from land back to water. Here we integrate multiproxy evidence to elucidate the gradual reverse evolution of duckweed. Three genera of duckweed show chronologically gradient degeneration in the structure of roots, the function of stomata, and decrease in lignocellulose content, accompanied by gradient contraction in relevant gene numbers and/or decline in transcript expression. The gene numbers in the main phytohormonal pathway are also gradually decreased. The co-action of auxin and rhizoid development gene causes a gradual decrease in adventitious roots. The significant expansion of the flavonoid pathway is also highly related to the adaptation of duckweed to floating growth. Our study combined with the fossil evidence reconstruct the evolution history of duckweeds from land back to water, reverse to that of early land plants. This study reconstructed the process of how a land plant returns to water, a reverse evolutionary approach which is different from what we studied in textbook about plant terrestrialization. This finding could be helpful for us to deeply and widely understand the adaptation of plant to the environment, and to expand and deepen the knowledge of evolution theory.

evolutionary biology↗

bioRxiv2023

PGAR-Zernike: an ultra-fast, accurate and fully open-sourcestructure retrieval toolkit for convenient structural database construction

With the release of AlphaFold2, protein model databases are growing at an unprecedented rate. Efficient structure retrieval schemes are becoming more and more important to quickly analyze structure models. The core problem in structural retrieval is how to measure the similarity between structures. Some structure alignment algorithms can solve this problem but at a substantial time cost. At present, the state-of-the-art method is to convert protein structures into 3D Zernike descriptors and evaluate the similarity between structures by Euclidean distance. However, methods for computing 3D Zernike descriptors of protein structures are almost always based on structural surfaces and most are web servers, which is not conducive for users to analyze customized datasets. To overcome this limitation, we propose PGAR-Zernike, a convenient toolkit for computing different types of Zernike descriptors of structures: the user simply needs to enter one line of command to calculate the Zernike descriptors of all structures in a customized datasets. Compared with the state-of-the-art method based on 3D Zernike descriptors and an efficient structural comparison tool, PGAR-Zernike achieves higher retrieval accuracy and binary classification accuracy on benchmark datasets with different attributes. In addition, we show how PGA-Zernike completes the construction of the descriptor database and the protocol used for the PDB dataset so as to facilitate the local deployment of this tool for interested readers. We construct a demonstration containing 590685 structures; at this scale, our retrieval system takes only 4 ~ 9 seconds to complete a retrieval, and experiments show that it reaches the state-of-the-art level in terms of accuracy. PGAR-Zernike is an open-source toolkit, whose source code and related data are accessible at https://github.com/junhaiqi/PGAR-Zernike/.

bioinformatics↗

bioRxiv2023

Resting-state functional brain network alternations related to non-suicidal and suicidal self-injurious behaviors in adolescents with depression

Nonsuicidal self-injury (NSSI) and suicidal attempt (SA) frequently occur during depressed adolescents, but the underlying neurobiological mechanisms are poorly understood. The maturation of network connectivity is a central feature of brain development during adolescence. However, few researchers have used resting-state functional magnetic resonance imaging (fMRI) to investigate the similarities and differences in the intrinsic brain networks between NSSI with NSSI+SA in depressed adolescent populations. In this study, we collected self-reported questionnaires and resting-state (fMRI data from a sample of depressed adolescents (N = 114), categorized into three groups: clinical control (non-self-harm), NSSI-only, and NSSI+SA based on their self-harm history. The alternations of FC patterns were identified through support vector machine-based classification, as machine learning approaches can help to overcome the multiple-comparison problems of their multivariate nature. Referring to the convergent alternations between adolescent NSSI with or without a history of SA, the alternations of intra-/inter-network FCs among the Control, SalVAtten, Limbic, and Default networks. Besides, divergent alternations were also observed for depressed adolescents with a history of SA, involving the Limbic, DorsAttn, Visual, and Subcortical networks. Besides, the severity of depressive symptoms only showed a significant correlation with altered FCs in Limbic-DorAttn and Limbic-Visual networks, strengthening the fact that these observed alternations of FC could not all be explained by increased depression severity. The emphasis of this study on the network basis could extend the existing evidence at a circuit level and the observed convergent alternations may explain an underlying neurobiological mechanism pertaining to the continuum of self-destructiveness in adolescents. In addition, our discovery of divergent alternations could help to identify biomarkers that will aid in differentiating those at risk for SA among those engaging in NSSI and contribute to the development of neurobiologically informed interventions.

neuroscience↗

bioRxiv2023

Quantifying tumor specificity using Bayesian probabilistic modeling for drug target discovery and prioritization

In diseases such as cancer, the design of new therapeutic strategies requires extensive, costly, and unfortunately sometimes deadly testing to reveal life threatening "off target" effects. A crucial first step in predicting toxicity are analyses of normal RNA and protein tissue expression, which are now possible using comprehensive molecular tissue atlases. However, no standardized approaches exist for target prioritization, which instead rely on ad-hoc thresholds and manual inspection. Such issues are compounded, given that genomic and proteomic data detection sensitivity and accuracy are often problematic. Thus, quantifiable probabilistic scores for tumor specificity that address these challenges could enable the creation of new predictive models for combinatorial drug design and correlative analyses. Here, we propose a Bayesian Tumor Specificity (BayesTS) score that can naturally account for multiple independent forms of molecular evidence derving from both RNA-Seq and protein expression while preserving the uncertainty of the inference. We applied BayesTS to 24,905 human protein-coding genes across 3,644 normal samples (GTEx and TCGA) spanning 63 tissues. These analyses demonstrate the ability of BayesTS to accurately incorporate protein, RNA and tissue distribution evidence, while effectively capturing the uncertainty of these inferences. This approach prioritized well-established drug targets, while deemphasizing those which were later found to induce toxicity. BayesTS allows for the adjustment of tissue importance weights for tissues of interest, such as reproductive and physiologically dispensable tissues (e.g., tonsil, appendix), enabling clinically translatable prioritizations. Our results show that BayesTS can facilitate novel drug target discovery and can be easily generalized to unconventional molecular targets, such as splicing neoantigens. We provide the code and inferred tumor specificity predictions as a database available online (https://github.com/frankligy/BayesTS). We envision that the widespread adoption of BayesTS will facilitate improved target prioritization for oncology drug development, ultimately leading to the discovery of more effective and safer drugs. Code and Data AvailabilityThe BayesTS code and inferred tumor specificities are available at (https://github.com/frankligy/BayesTS), along with the scripts for reproducing the results in the study and instructions on retraining the model. The training data is available at Synapse (https://www.synapse.org/#!Synapse:syn51170082/files/).

bioinformatics↗

bioRxiv2023

Local administration of a novel siRNA modality into the CNS extends survival and improves motor function in the SOD1G93A mouse model for ALS

Antisense oligonucleotides (ASOs) were the first modality to pioneer targeted gene knockdown in the treatment of ALS caused by mutant superoxide dismutase 1 (SOD1). RNA interference (RNAi) is another mechanism of gene silencing with historically superior potency in which short interfering RNAs (siRNAs) guide the RNA-induced silencing complex (RISC) to cleave complementary transcripts. However, delivery to extrahepatic tissues like the central nerve system (CNS) has been a bottleneck in the clinical development of RNAi. Herein, we identify potent siRNA duplexes for the knockdown of human SOD1 (hSOD1) in which medicinal chemistry and conjugation to an accessory oligonucleotide (ACO) enables durable and potent activity in CNS tissues. Local delivery via intracerebroventricular (ICV) or intrathecal (IT) injection into SOD1G93A mice delayed disease progression and extended animal survival with superior efficacy compared to an ASO compound resembling Tofersen in sequence and chemistry. Treatment also prevented disease-related declines in motor function including improvements in animal mobility, muscle strength, and coordination. The ACO itself does not target any specific complementary nucleic acid sequence; rather, it imparts benefits conducive to bioavailability and delivery through its chemistry. The complete conjugate (i.e., siRNA-ACO) represents a novel modality for delivery of RNAi to the CNS in which we aim to pursue ALS as an exemplary indication for clinical development.

cell biology↗

bioRxiv2023

Influence of Demographic, Socio-economic, and Brain Structural Factors on Adolescent Neurocognition: A Correlation Analysis in the ABCD Initiative

The Adolescent Brain Cognitive Development (ABCD) initiative is a longitudinal study aimed at characterizing brain development from childhood through adolescence and identifying key biological and environmental factors that influence this development. The study measures neurocognitive abilities across a multidimensional array of functions, with a focus on the critical period of adolescence during which physical and socio-emotional changes occur and the structure of the cortical and white matter changes. In this study, we perform a correlation analysis to examine the linear relation of adolescent neurocognition functions with the demographic, socio-economic, and magnetic resonance imaging-based brain structural factors. The overall goal is to obtain a comprehensive understanding of how natural and nurtural factors influence adolescent neurocognition. Our results on > 10,000 adolescents show many positive and negative statistical significance interrelations of different neurocognitive functions with the demographic, socioeconomic, and brain structural factors, and also open up questions inviting further future studies.

bioinformatics↗