Biology subjects

Yang, J.

Publications and source records attributed to Yang, J..

At least 721 records · Page 40Linked to original sources

bioRxiv2022

Identification of a novel deFADding activity in 5' to 3' exoribonucleases

Identification of metabolite caps including FAD on the 5 end of RNA has uncovered a previously unforeseen intersection between cellular metabolism and gene expression. To understand the function of FAD caps in cellular physiology, we characterised the proteins interacting with FAD caps in budding yeast. Here we demonstrate that highly conserved 5-3 exoribonucleases, Xrn1 and Rat1, physically interact with the RNA 5 FAD cap and both possess FAD cap decapping (deFADding) activity and subsequently degrade the resulting RNA. Xrn1 deFADding activity was also evident in human cells indicating its evolutionary conservation. Furthermore, we report that the recently identified bacterial 5-3 exoribonuclease RNase AM also possesses deFADding activity that can degrade FAD-capped RNAs in vitro and in E. coli cells. To gain a molecular understanding of the deFADding reaction, an RNase AM crystal structure with three manganese ions coordinated by a sulfate molecule and the active site amino acids was generated that provided details underlying hydrolysis of the FAD cap. Our findings reveal a general propensity for 5-3 exoribonucleases to hydrolyse and degrade RNAs with 5 end noncanonical caps in addition to their well characterized 5 monophosphate RNA substrates indicating an evolutionarily conserved intrinsic property of 5-3 exoribonucleases.

molecular biology↗

bioRxiv2022

Defining the HIV Capsid Binding Site of Nucleoporin 153

The interaction between the HIV-1 capsid (CA) and human nucleoporin 153 (NUP153) is vital for delivering the HIV-1 preintegration complex into the nucleus via the nuclear pore complex. The interaction with CA requires a phenylalanine/glycine-containing motif in the C-terminus of NUP153. This study used molecular modeling and biochemical assays to determine the amino acids of NUP153 that are essential for its interactions with CA. Molecular dynamics, FoldX, and PyRosetta simulations delineated the minimal CA binding motif of NUP153 based on the known structure of NUP153 bound to the HIV-1 CA hexamer. Computational predictions were experimentally validated by testing the interaction of NUP153 with CA using an in vitro binding assay and a cell-based TRIM-NUP153C restriction assay. This multidisciplinary approach identified eight amino acids from P1411 to G1418 that stably engage with CA, with significant correlations between molecular models and empirical experiments. Specifically, P1411, V1414, F1415, T1416, F1417, and G1418 were confirmed as critical amino acids required to interact NUP153 with CA. IMPORTANCEHuman immunodeficiency virus (HIV) can infect non-dividing cells by interacting with host nuclear pores. The host nuclear pore protein NUP153 directly interacts with the HIV capsid to promote viral nuclear entry. This study used a multidisciplinary approach combining computational and experimental techniques to map the essential amino acids of NUP153 required for HIV capsid interaction. This approach revealed that the HIV capsid interacts specifically with only six amino acids of NUP153, suggesting other FG-containing motifs could also interact with the capsid. Based on molecular modeling, naturally occurring polymorphisms in human and non-human primates would be predicted to prevent NUP153 interaction with capsid, potentially protecting from HIV infection.

molecular biology↗

bioRxiv2022

AI inspired discovery of new biomarkers for clinical prognosis of liver cancer

Tissue biomarkers are crucial for cancer diagnosis, prognosis assessment, and treatment planning. However, few of current biomarkers used in clinics are robust enough to show a true analytical and clinical value. Thus the search for additional tissue biomarkers, including the strategies to identify them, is imperative. Recently, the capabilities of deep learning (DL)-based computational pathology in cancer diagnosis and prognosis have been explored, but the limited interpretability and generalizability make the results difficult to be accepted in clinical practice. Here we present an interpretable human-centric DL-guided framework--PathFinder (Pathological-biomarker-finder)-- that can inspire pathologists to discover new tissue biomarkers from well-performing DL models, which bridges the gap between DL and clinical prognosis. By combining sparse multi-class tissue spatial distribution information of whole slide images (WSIs) with attribution methods, PathFinder can achieve localization, characterization, and verification of potential biomarkers, while guaranteeing state-of-the-art prognostic performance. With the inspiration of PathFinder, we discovered that tumor necrosis in liver cancer, a long-neglected factor, has a strong relationship with patient prognosis. Thus we proposed two clinically independent indicators, including necrosis area fraction and tumor necrosis distribution, for practical prognosis, and verified their potentials in clinical prognosis according to Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK)-derived criteria. Our work demonstrates a successful example of introducing artificial intelligence (AI) into clinical practice in a knowledge discovery way, which can be adopted in identifying biomarkers in various cancer types and modalities.

cancer biology↗

bioRxiv2022

Antimicrobial susceptibility testing using MYCO test-system and MIC distribution of 8 drugs against clinical isolates from Shanghai of Nontuberculous Mycobacteria

Given the increased incidence and prevalence of nontuberculous mycobacteria (NTM) diseases and the natural resistance of NTM to multiple antibiotics, in vitro susceptibility testing of different NTM species against drugs from the MYCO test system and new applied drugs are required. 241 NTM clinically isolates were under analyzed, including 181 slowly growing mycobacterium (SGM) and 60 rapidly growing mycobacterium (RGM). The Sensititre SLOMYCO and RAPMYCO panels were used for the drug susceptibility testing to commonly used anti-NTM antibiotics. Furthermore, Minimum inhibitory concentration (MIC) distributions were determined against 8 potential anti-NTM drugs, including vancomycin (VA), bedaquiline (BDQ), delamanid (DLM), faropenem (FAR), meropenem (MPM), clofazimine (CFZ), avibactam (CAZ), and Cefoxitin (FOX) and epidemiological cut-off values (ECOFFs) were analyzed using ECOFFinder. The results showed that most of the SGM strains were susceptible to clarithromycin (CLA), rifampicin (RFB) from the SLOMYCO panels and BDQ, CFZ from the 8 applied drugs, while, RGM strains were susceptible to tigecycline (TGC) from the RAPMYCO panels and also BDQ, CFZ. The ECOFF values of CFZ were 0.25g/ml, 0.25g/ml, 0.5g/ml, and 1g/ml for M. kansasii, M. avium, M. intracellulare, and M. abscessus, respectively, and BDQ was 0.5g/ml for the same four prevalent NTM species. Due to the weak activity of the other 6 drugs, no ECOFF was determined. This study on the susceptibility of NTM includes 8 potential anti-NTM drugs and a large sample size of Shanghai clinical isolates. and demonstrated that BDQ and CFZ had efficient activities against different NTM species in vitro, which can be applied for the treatment of NTM diseases.

microbiology↗

bioRxiv2022

Covalent Docking and Molecular Dynamics Simulations Reveal the Specificity-Shifting Mutations Ala237Arg and Ala237Lys in TEM Beta-Lactamase

The rate of modern drug discovery using experimental screening methods still lags behind the rate at which pathogens mutate, underscoring the need for fast and accurate predictive simulations of protein evolution. Multidrug-resistant bacteria evade our defenses by expressing a series of proteins, the most famous of which is the 29-kilodalton enzyme, TEM {beta}-lactamase. Considering these challenges, we applied a covalent docking heuristic to measure the effects of all possible alanine 237 substitutions in TEM due to this codons importance for catalysis and effects on the binding affinities of commercially-available {beta}-lactam compounds. In addition to the usual mutations that reduce substrate binding due to steric hindrance, we identified two distinctive specificity-shifting TEM mutations, Ala237Arg and Ala237Lys, and their respective modes of action. Notably, we discovered and verified through minimum inhibitory concentration assays that, while these mutations and their bulkier side chains lead to steric clashes that curtail ampicillin binding, these same groups foster salt bridges with the negatively-charged side-chain of the cephalosporin cefixime, widely used in the clinic to treat multi-resistant bacterial infections. To measure the stability of these unexpected interactions, we used molecular dynamics simulations and found the binding modes to be stable despite the application of biasing forces. Finally, we found that both TEM mutants also bind strongly to other drugs containing negatively-charged R-groups, such as carumonam and ceftibuten. As with cefixime, this increased binding affinity stems from a salt bridge between the compounds negative moieties and the positively-charged side chain of the arginine or lysine, suggesting a shared mechanism. In addition to reaffirming the power of using simulations as molecular microscopes, our results can guide the rational design of next-generation {beta}-lactam antibiotics and bring the community closer to retaking the lead against the recurrent threat of multidrugresistant pathogens. Author SummaryResistance to antibiotics is a major public health threat. Microorganisms are able to resist commonly used drugs by evolving and expressing enzymes capable of neutralizing antibiotics. Understanding the relationships between structural elements in these enzymes and their drug-clearing functions can lead to crucial insights for the discovery of next-generation antibiotics. In this study, we have used cutting-edge computational modeling methods to predict the effects of all naturally-occurring variations of an important region of the binding site of TEM {beta}-lactamase, one of the major resistance-granting enzymes in bacteria. In an effort to identify patterns that could be useful for drug discovery, our simulations sought to understand how chemical changes in the tested region can affect resistance against a collection of over 90 widely used antibiotics. Crucially, through our simulations, we have identified a pathway for bacterial resistance against {beta}-lactam antibiotics containing a negatively-charged moiety. We have also elucidated the mechanism behind the gain of resistance, which involves strong interactions between the drugs negative moieties and the positively-charged chemical shifts resulting from the mutation. Finally, we validated our predictions against fitness experiments for two commonly used antibiotics, which qualitatively corroborated our most important findings.

bioinformatics↗

bioRxiv2022

Circular mRNA encoded PROTAC (RiboPROTAC) as a new platform for the degradation of intracellular therapeutic targets

Although proteolysis targeting chimera (PROTAC) technology that hijacking the ubiquitin-proteasome system (UPS) to artificially degrade protein is an emerging promising technology for many undruggable targets, it still faces several challenges, such as the difficulty to select high specificity molecule to protein of interest (POI), and only few of the E3-ligase are suitable for PROTAC mediated protein degradation. Protein-based PROTAC, termed BioPROTAC, owns the advantage of specificity but lacks membrane permeability. Here, we develop a new targeted protein degrading platform, which we termed RiboPROTAC, by encoding BioPROTAC protein degraders with circular mRNA (cmRNA) and delivering intracellularly. In this way, intracellular protein GFP and nuclear protein PCNA were successfully degraded. For PCNA targeting, not only the level of target protein is strongly decreased, but also the cell function related is strongly interfered, such as cell proliferation, apoptosis, as well as the cell cycle. What is more, for the first time, we observed that degrading PCNA with RiboPROTAC causes immunogenic cell death (ICD), although not strong, but was verified in vivo. Importantly, our in vivo results demonstrated that cmRNA encoded PCNA degrader exhibited significant tumor suppression effect, thus we provide the first proof of concept for the application of RiboPROTAC as potential mRNA therapeutic. We consider that RiboPROTAC is a new and superior PROTAC technology for targeting the undruggable targets.

molecular biology↗

bioRxiv2022

Identification of two bZIP transcription factors that regulate development of pavement and trichome cells in Arabidopsis thaliana by single-cell RNA-sequencing

Epidermal cells are the main avenue for signal and material exchange between plants and the environment. Leaf epidermal cells primarily include pavement cells (PCs), guard cells, and trichomes cells (TCs), which differentiate from protodermal cells or meristemoids. The development and distribution of different epidermal cells are tightly regulated by a complex transcriptional regulatory network mediated by phytohormones, including jasmonic acid (JA), and transcription factors. Understanding how the fate of leaf epidermal cells is determined, however, is still largely unknown due to the diversity of cell types and the complexity of its regulation. Here, we characterized the transcriptional profiles of epidermal cells in 3-day-old true leaves of Arabidopsis thaliana using single-cell RNA-sequencing. We identified two genes encoding BASIC LEUCINE-ZIPPER (bZIP) transcription factors, namely the bZIP25 and bZIP53, which are highly expressed in PCs and early-stage meristemoid cells. Densities of PCs and TCs were found to increase and decrease, respectively, in bzip25 and bzip53 mutants, compared with wild-type plants. This trend was more pronounced in the presence of JA, suggesting that these transcription factors regulate the development of TCs and PCs in response to JA. IN A NUTSHELLO_ST_ABSBackgroundC_ST_ABSLeaf epidermal cells, comprised of trichome cells (TCs), guard cells (GCs), and pavement cells (PCs), are responsible for exchanging materials and information between plants and the surrounding aerial environment. Many genes have been identified in Arabidopsis thaliana and confirmed to be involved in the initiation and differentiation of TCs and PCs. The fate determination of TCs and PCs is tightly regulated by positive and negative regulators at the cellular level. The precise underlying molecular mechanisms responsible for the fate determination of TCs and PCs, however, are still unclear at this time. QuestionWhat are the transcriptomic profiles of different leaf epidermal cell types? Can we dissect the genes that are specifically expressed in certain epidermal cell types? What kinds of transcription factors are involved in regulating the fate determination of TCs and PCs? FindingsWe performed single cell RNA-seq to investigate the transcriptomic profiles of different leaf epidermal cell types and identified differentially expressed genes in each cell type. We found that genes that are involved in jasmonic acid signaling are highly expressed in early-stage meristemoid (EM) cells which can act as the precursor of PCs and perhaps of TCs. To investigate the regulatory mechanisms underlying EM development, we identified the transcription factors (TFs) in EM cells and found that two bZIP TF genes, bZIP25 and bZIP53, are highly expressed in EMs. Further analyses of these two genes using both loss-of-function and gain-of-function approaches indicated that bZIP25 and bZIP53 are functionally involved in promoting trichome formation but inhibit pavement cell development in response to jasmonic acid. Next stepsBesides of bZIP25 and bZIP53, we also identified other key genes, for example FES1B, in leaf epidermal cells. Our next step will be to explore the regulation of other key genes involved in the fate determination of different cell types in leaf epidermis.

plant biology↗

bioRxiv2022

Estimation of Left Ventricular Mechanical Activation Times from Motion-Corrected Cardiac 4DCT Images

BackgroundMechanical activation times of the left ventricle (LV) are strongly correlated with patient response to cardiac resynchronization therapy (CRT); however, there remains an unmet clinical need for a simple, robust imaging modality that yields accurate and reproducible estimates of LV mechanical activation times. Modern four-dimensional computed tomography (4DCT) imaging systems with effective motion correction could fulfill this need. PurposeTo demonstrate the clinical utility of a newly developed cardiac motion correction algorithm called ResyncCT and to investigate its effect on estimating mechanical activation times of the LV. MethodsTwenty-four subjects with full cardiac volume, full cardiac cycle 4DCT images were retrospectively analyzed in this study. The reconstructed 4DCT images exhibited typical motion artifact characteristics that were dependent on the direction of LV wall motion with respect to the gantry position at each cardiac phase; these artifacts rotated synchronously with the gantry. The motion corrupted images, referred to as the uncorrected images, were processed with a novel cardiac motion correction algorithm called ResyncCT to yield motion corrected images (referred to as the ResyncCT images). Regional shortening (RSCT) of the LV was calculated over a 72-segment model for both the uncorrected and the ResyncCT images; each segment contained RSCT vs time data. From these RSCT vs time curves, LV mechanical activation was estimated as the time point at which the RSCT vs time curve shortened by 10% of its full dynamic range during systolic contraction; we refer to this time point as the time to onset of shortening (TOS). A shift in TOS > |35| ms has a significant effect on reclassifying patients based on their probabilities of responding to CRT; we investigated the effect of ResyncCT on the measured values of TOS over the LV. ResultsResyncCT had a pronounced effect on the TOS estimates; ResyncCT could potentially reclassify 23/24 (96%) subjects as either responders or non-responders to CRT. In 16/24 (67%) subjects, the differences in TOS that were sufficient to bring about a reclassification of CRT response were at least as large in surface area of the LV as one entire American Heart Association segment. ConclusionsWe demonstrated the clinical utility of ResyncCT in estimating LV mechanical activation times as times to onset of shortening in 24 human subjects. ResyncCT has a pronounced effect on the estimation of LV mechanical activation times; the differences in activation times between the ResyncCT and uncorrected images are heterogenous and subject specific. The effect of ResyncCT could potentially reclassify 96% of the subjects used in this study based on their probabilities of responding to CRT. The results reported in this study highlight the potential utility of ResyncCT in estimating timing of mechanical events of interest of the LV for CRT planning.

bioengineering↗

bioRxiv2022

OTTERS: A powerful TWAS framework leveraging summary-level reference data

Most existing TWAS tools require individual-level eQTL reference data and thus are not applicable to summary-level reference eQTL datasets. The development of TWAS methods that can harness summary-level reference data is valuable to enable TWAS in broader settings and enhance power due to increased reference sample size. Thus, we develop a TWAS framework called OTTERS (Omnibus Transcriptome Test using Expression Reference Summary data) that adapts multiple polygenic risk score (PRS) methods to estimate eQTL weights from summary-level eQTL reference data and conducts an omnibus TWAS. We show that OTTERS is a practical and powerful TWAS tool by both simulations and application studies.

genetics↗

bioRxiv2022

Exosomally targeting microRNA23a ameliorates microvascular endothelial barrier dysfunction following rickettsial infection

Spotted fever group rickettsioses caused by Rickettsia (R) are devastating human infections, which mainly target microvascular endothelial cells (EC) and can induce lethal EC barrier dysfunction in the brain and lungs. Our previous evidence reveals that exosomes (Exos) derived from rickettsial-infected ECs, namely R-ECExos, can induce disruption of the tight junctional (TJ) protein ZO-1 and barrier dysfunction of human normal recipient brain microvascular endothelial cells (BMECs). However, the underlying mechanism remains elusive. Given that we have observed that microRNA23a (miR23a), a negative regulator of endothelial ZO-1 mRNA, is selectively sorted into R-ECExos, the aim of the present study was to characterize the potential functional role of exosomal miR23a delivered by R-ECExos in normal recipient BMECs. We demonstrated that EC-derived Exos (ECExos) have the capacity to deliver oligonucleotide RNAs to normal recipient BMECs in an RNase-abundant environment. miR23a in ECExos impairs normal recipient BMEC barrier function, directly targeting TJ protein ZO-1 mRNAs. In separate studies using a traditional in vitro model and a novel single living-cell biomechanical assay, our group demonstrated that miR23a anti-sense oligonucleotide-enriched ECExos ameliorate R-ECExo-provoked recipient BMEC dysfunction in association with stabilization of ZO-1 in a dose-dependent manner. These results suggest that Exo-based therapy could potentially prove to be a promising strategy to improve vascular barrier function during bacterial infection and concomitant inflammation.

cell biology↗

bioRxiv2022

Behavioral and dopaminergic signatures of resilience

Chronic stress can have lasting adverse consequences in some individuals, yet others are resilient to the same stressor1,2. While previous work found differences in the intrinsic properties of mesolimbic dopamine (DA) neurons in susceptible and resilient individuals after stress was over;3-10 the causal links between DA activity during stress, dynamic stress-evoked behavior, and individual differences in susceptibility and resilience are not known. Here, we record behavior and neural activity in DA projections to the nucleus accumbens (NAc, signals reward11-14) and to the tail striatum (TS, signals threat15-18) during a multiday chronic social defeat paradigm and discover behavioral and neural signatures of resilience. Using supervised and unsupervised behavioral quantification, we find that resilient and susceptible individuals employ different behavioral strategies during stress. In addition, NAc-DA (but not TS-DA) activity is higher in the proximity of the aggressor in resilient mice, consistent with a greater subjective value of the aggressor. Moreover, NAc-DA tends to be elevated at the onset of fighting back in resilient mice and at the offset of attacks in susceptible mice. To test whether DA activation during defeat can generate resilience, and if its timing with respect to behavior is critical, we performed optogenetic stimulation of NAc-DA in open-loop (randomly timed) during defeat or timed to specific behaviors using real-time pose-tracking and behavioral classification. We find that both open-loop DA activation and fighting-back-timed activation promote resilience, in both cases reorganizing behavior during defeat toward resilience-associated patterns. Attack offset-timed activation promotes avoidance during defeat but does not promote susceptibility afterwards. Together, these data suggest a model whereby, during stress, DA in the NAc can increase resilience primarily by elevating the subjective value of the stressor rather than by reinforcing particular stress-responsive behaviors.

neuroscience↗

bioRxiv2022

The impacts of transfer learning, phylogenetic distance, and sample size on big-data bioacoustics

Vocalizations in animals, particularly birds, are critically important behaviors that influence their reproductive fitness. While recordings of bioacoustic data have been captured and stored in collections for decades, the automated extraction of data from these recordings has only recently been facilitated by artificial intelligence methods. These have yet to be evaluated with respect to accuracy of different automation strategies and features. Here, we use a recently published machine learning framework to extract syllables from ten bird species ranging in their phylogenetic relatedness from 1 to 85 million years, to compare how phylogenetic relatedness influences accuracy. We also evaluate the utility of applying trained models to novel species. Our results indicate that model performance is best on conspecifics, with accuracy progressively decreasing as phylogenetic distance increases between taxa. However, we also find that the application of models trained on multiple distantly related species can improve the overall accuracy to levels near that of training and analyzing a model on the same species. When planning big-data bioacoustics studies, care must be taken in sample design to maximize sample size and minimize human labor without sacrificing accuracy.

evolutionary biology↗

bioRxiv2022

Introducing an argonaute-facilitated PCR platform

Argonaute proteins are characterized by highly efficient guide DNA/RNA-directed binding to target nucleic acids with high fidelity. Employing this feature, we designed an argonaute-facilitated PCR platform by making use of an argonaute derived from Mesorhizobium japonicum (MejAgo) which does not carry nuclease activity and exposes the 3 end of guide DNA when binding. Each reaction cycle of the MejAgo-PCR platform consists of a denaturing step and a polymerase-mediated extension step, omitting the annealing step required by the traditional PCR. More importantly, MejAgo-PCR could significantly improve the sensitivity of PCR in template detection due to the argonaute-facilitated pairing between guide DNA/primer and template. Thus, an argonaute-facilitated PCR has the potential to be developed as an advanced PCR platform with higher sensitivity and efficiency.

biochemistry↗

bioRxiv2022

Vascular mimicry by VE-cadherin enables trophoblast endovascular invasion and spiral artery remodeling during placental development

During formation of the mammalian placenta trophoblasts invade the maternal decidua and remodel spiral arteries to bring maternal blood into the placenta. This process, known as endovascular invasion, is thought to involve the adoption of functional characteristics of vascular endothelial cells (ECs) by trophoblasts through a process termed vascular mimicry. The genetic and molecular basis of vascular mimicry remains poorly defined, however, and whether trophoblasts utilize specialized endothelial proteins in an analogous manner to create vascular channels remains untested. Vascular endothelial (VE-)cadherin is a homotypic adhesion protein that is expressed selectively by ECs in which it enables formation of tight vessels and regulation of EC junctions. VE-cadherin is also expressed in invasive trophoblasts and is a prime candidate for a molecular mechanism of vascular mimicry by those cells. Here, we show that the VE-cadherin is required for trophoblast migration and endovascular invasion into the maternal decidua in the mouse. VE-cadherin deficiency results in loss of spiral artery remodeling that leads to decreased flow of maternal blood into the placenta, fetal growth restriction, and death. These studies identify a non-endothelial role for VE-cadherin in trophoblasts during placental development and suggest that endothelial proteins may play functionally unique roles in trophoblasts that do not simply mimic those in ECs.

developmental biology↗

bioRxiv2022

A historically balanced locus under recent directional selection in responding to changed nitrogen conditions during modern maize breeding

Understanding the patterns of selection during plant evolution and recent crop improvement processes is the central topic in plant breeding and genetics. As an essential macronutrient for plant growth and development, nitrogen (N) is a key factor in affecting plant adaptation and crop improvement. The widespread adoption of less expensive industrial N fixation has dramatically reshaped plant morphology by favoring compact maize plants to tolerant crowding stress. The associated genetic changes, however, have not been systematically studied. Here, we investigated maize inbred lines developed before and after the 1960s -- the time point when inorganic N fertilizer started to be widely used for maize production. We identified a strong selective sweep exhibiting pronounced genomic differentiation between Old-Era (pre-1960s) and New-Era (post-1960s) inbred lines. Further study revealed population genetics statistics in the sweep exhibited patterns consistent with historical balancing selection. This balanced genomic interval is associated with a number of morphological, physiological, and metabolite traits related to vegetative N responses. A cluster of three glutamate receptor-like (GLR) genes is located within the region targeted by selection. Functional characterizations suggested differences in transcriptional activity of the GLR genes between the haplotypes carried by Old-Era and New-Era inbred lines likely play an essential role in mediating distinct N responses. The identification of both targets of selection and changes in the regulation of N responsive genes between maize lines developed in different eras sheds light on the N sensing and regulation pathways and paves the way to developing N resilient crops.

genomics↗

bioRxiv2022

Designing a novel monitoring approach for the effects of space travel on astronauts' health

Space exploration and extraterrestrial civilization have fascinated humankind since the earliest days of human history. However, it was only until last century that humankind finally began taking significant steps towards these goals by sending astronauts into space, landing on the moon, and building the International Space Station. However, space voyage is very challenging and dangerous, and astronauts are under constant space radiation and microgravity. It has been shown that astronauts are at a high risk of developing a broad range of diseases/disorders. Thus, it is critical to develop a rapid and effective assay to monitor astronauts health in space. In this study, gene expression and correlation patterns were analyzed for 10 astronauts (8 male and 2 female) using the publicly available microarray dataset E-GEOD-74708. We identified 218 differentially expressed genes between In-flight and Pre-flight and noticed that space travel decreased genome regulation and gene correlations across the entire genome, as well as individual signaling pathways. Furthermore, we rationally designed a rapid assay of 32 genes which could be used to monitor astronauts health during space travel. Further studies, including microgravity experiments, are warranted to optimize and validate the proposed assay.

molecular biology↗

bioRxiv2022

Gut-liver-axis microphysiological system for studying cellular fluidic shear stress and inter-tissue interaction

Gut-liver-axis (GLA) is a fundamental interaction between the gut and liver for maintaining human health. To clarify the physiological and pathological roles of GLA in the human body, a GLA microphysiological system (GLA-MPS) holds great potential. However, in current GLA-MPS, the importance of a physiologically relevant flow for gut and liver cells cultivation is not fully addressed. In addition, the integration of individual organ perfusion, circulation flow, and organ tissue functions in a single device has not been achieved. Here, we introduce a GLA-MPS by integrating two cell culture chambers with individually applied perfusion flows and a circulation channel with an on-chip pneumatic micropump under cell culture chambers via a porous membrane for interconnecting them. We analyzed the fluid shear stress (FSS) with computational fluid dynamics simulations and confirmed that the physiologically relevant FSS (i.e., 8 x 10-3 and 1.2 x 10-7 dyne cm-2) could be applied for the gut (Caco-2) and liver (HepG2) cells, respectively. Under physiologically relevant flow, the Caco-2 and HepG2 cells in the GLA-MPS maintained a cell survival rate of 95% and 92%, respectively; further, they enhanced the expression of functional proteins such as zonula occludens 1 (ZO-1) and albumin (ALB), respectively. Thus, the presented GLA-MPS can be adapted as an advanced in vitro model in a wide range of applications for disease modeling associated with inter-tissue interactions, such as fatty liver diseases.

bioengineering↗

bioRxiv2022

Generative pretraining from large-scale transcriptomes: Implications for single-cell deciphering and clinical translation

Exponential accumulation of single-cell transcriptomes poses great challenge for efficient assimilation. Here, we present an approach entitled tGPT towards integration of 22.3 million single-cell transcriptomes by modeling gene expression rankings as generative pretraining task. tGPT is conceptually simple in that it autoregressively models the ranking of a gene in the context of its preceding neighbors. We demonstrated the high performance of tGPT on a range of fundamental single-cell analysis tasks and novel applications on bulk tissues. The single-cell clusters and cell lineage trajectories derived from tGPT are highly aligned with known cell labels and states. The feature patterns of tumor bulk tissues learned by tGPT are associated with a wide range of genomic alteration events, prognosis and treatment outcome of immunotherapy. tGPT represents a new analytical paradigm for integrating and deciphering massive amount of transcriptome data and it will facilitate the interpretation and clinical translation of single-cell transcriptomes.

bioinformatics↗