Biology subjects

Cheng, S.

Publications and source records attributed to Cheng, S..

At least 127 records · Page 7Linked to original sources

bioRxiv2023

Genetic control of cell layer interactions in plants via tissue mechanics

Plant development depends on coordination of growth between different cell layers. Coordination may be mediated by molecular signalling or mechanical connectivity between cells, but evidence for genetic control via direct mechanics has been lacking. We show that a brassinosteroid-deficient dwarf mutant of the aquatic plant Utricularia gibba has twisted internal tissue, likely caused by a mechanical constraint from a slow-growing epidermis creating tissue stresses. This conclusion is supported by showing that inhibition of brassinosteroid action in an Arabidopsis mutant compromised for cell adhesion, enhances epidermal crack formation, an indicator of increased tissue tension. Thus, genes driving brassinosteroid synthesis can promote growth of internal tissue by reducing mechanical epidermal constraint, showing that tissue mechanics plays a key role in coordinating growth between cell layers. One-Sentence SummaryInternal twists in a mutant carnivorous plant reveal how genes control growth via tissue mechanics.

plant biology↗

bioRxiv2023

Learning to predict future locations with internally generated theta sequences

Representing past, present and future locations is key for spatial navigation. Indeed, within each cycle of the theta oscillation, the population of hippocampal place cells appears to represent trajectories starting behind the current position of the animal and sweeping ahead of it. In particular, we reported recently that the position represented by CA1 place cells at a given theta phase corresponds to the location where animals were or will be located at a fixed time interval into the past or future assuming the animal ran at its typical, not the current, speed through that part of the environment. This coding scheme leads to longer theta trajectories, larger place fields and shallower phase precession in areas where animals typically run faster. Here we present a mechanistic computational model that accounts for these experimental observations. The model consists of a continuous attractor network with short-term synaptic facilitation and depression that internally generates theta sequences that advance at a fixed pace. Spatial locations are then mapped onto the active units via modified Hebbian plasticity. As a result, neighboring units become associated with spatial locations further apart where animals run faster, reproducing our earlier experimental results. The model also accounts for the higher density of place fields generally observed where animals slow down, such as around rewards. Furthermore, our modeling results reveal that an artifact of the decoding analysis might be partly responsible for the observation that theta trajectories start behind the animals current position. Overall, our results shed light on how the hippocampal code might arise from the interplay between behavior, sensory input and predefined network dynamics.

neuroscience↗

bioRxiv2023

Navigation and the Efficiency of Spatial Coding: Insights from Closed-Loop Simulations

Spatial learning is critical for survival and its underlying neuronal mechanisms have been studied extensively. These studies have revealed a wealth of information about the neural representations of space, such as place cells and boundary cells. While many studies have focused on how these representations emerge in the brain, their functional role in driving spatial learning and navigation has received much less attention. We extended an existing computational modeling tool-chain to study the functional role of spatial representations using closed-loop simulations of spatial learning. At the heart of the model agent was a spiking neural network that formed a ring attractor. This network received inputs from place and boundary cells and the location of the activity bump in this network was the output. This output determined the movement directions of the agent. We found that the navigation performance depended on the parameters of the place cell input, such as their number, the place field sizes, and peak firing rate, as well as, unsurprisingly, the size of the goal zone. The dependence on the place cell parameters could be accounted for by just a single variable, the overlap index, but this dependence was nonmonotonic. By contrast, performance scaled monotonically with the Fisher information of the place cell population. Our results therefore demonstrate that efficiently encoding spatial information is critical for navigation performance.

neuroscience↗

bioRxiv2022

CoBeL-RL: A neuroscience-oriented simulation framework for complex behavior and learning

Reinforcement learning (RL) has become a popular paradigm for modeling animal behavior, analyzing neuronal representations, and studying their emergence during learning. This development has been fueled by advances in understanding the role of RL in both the brain and artificial intelligence. However, while in machine learning a set of tools and standardized benchmarks facilitate the development of new methods and their comparison to existing ones, in neuroscience, the software infrastructure is much more fragmented. Even if sharing theoretical principles, computational studies rarely share software frameworks, thereby impeding the integration or comparison of different results. Machine learning tools are also difficult to port to computational neuroscience since the experimental requirements are usually not well aligned. To address these challenges we introduce CoBeL-RL, a closed-loop simulator of complex behavior and learning based on RL and deep neural networks. It provides a neuroscience-oriented framework for efficiently setting up and running simulations. CoBeL-RL offers a set of virtual environments, e.g. T-maze and Morris water maze, which can be simulated at different levels of abstraction, e.g. a simple gridworld or a 3D environment with complex visual stimuli, and set up using intuitive GUI tools. A range of RL algorithms, e.g. Dyna-Q and deep Q-network algorithms, is provided and can be easily extended. CoBeL-RL provides tools for monitoring and analyzing behavior and unit activity, and allows for fine-grained control of the simulation via interfaces to relevant points in its closed-loop. In summary, CoBeL-RL fills an important gap in the software toolbox of computational neuroscience.

bioinformatics↗

bioRxiv2022

Age but not menopausal status is linked to lower resting energy expenditure

ContextIt remains uncertain whether aging before late adulthood and menopause are associated with fat-free mass and fat mass-adjusted resting energy expenditure (REEadj). ObjectivesWe investigated whether REEadj differs between middle-aged and younger women and between middle-aged women with different menopausal statuses. We repeated the age group comparison between middle-aged mothers and their daughters to partially control for genotype. We also explored whether serum estradiol and follicle-stimulating hormone concentrations explain REEadj in midlife. MethodsWe divided 120 women, including 16 mother-daughter pairs, into age groups; group I (n = 26) consisted of participants aged 17-21, group II (n = 35) of those aged 22-38 and group III (n = 59) of those aged 41-58 years. The women in group III were further categorized as pre- or perimenopausal (n = 19), postmenopausal (n = 30) or postmenopausal hormone therapy users (n = 10). REE was assessed using indirect calorimetry, body composition using dual-energy X-ray absorptiometry and hormones using immunoassays. ResultsThe REEadj of group I was 126 kcal/d (95% CI: 93-160) higher than that of group III, and the REEadj of group II was 88 kcal/d (95% CI: 49-127) higher. Furthermore, daughters had a 100 kcal/d (95% CI: 63-138 kcal/d) higher REEadj than their middle-aged mothers (all P < 0.001). In group III, REEadj was not lower in postmenopausal women and did not vary by sex hormone concentrations. ConclusionsWe demonstrated that REEadj declines with age in women before late adulthood, also when controlling partially for genetic background, and that menopause may not contribute to this decline.

physiology↗

bioRxiv2022

SGC-CLK-1 (CAF-170) a chemical probe for the Cdc2-Like kinases CLK1, CLK2, and CLK4

Small molecule modulators are important tools to study both basic biology and the complex signaling of protein kinases. The cdc2-like kinases (CLK) are a family of four kinases that have garnered recent interest for their involvement in a diverse set of diseases such as neurodegeneration, autoimmunity, and many cancers. Targeted medicinal chemistry around a CLK inhibitor hit identified through screening of a kinase inhibitor set against a large panel of kinases allowed us to identify a potent and selective inhibitor of CLK1, 2 and 4. Here, we present the synthesis, selectivity, and potential binding site of this compound - SGC-CLK-1. We further show CLK2 has the highest binding affinity, and high CLK2 expression correlates with a lower IC50 in a screen of multiple cancer cell lines. Finally, we show that SGC-CLK-1 not only reduces serine arginine rich (SR) protein phosphorylation, but also alters SR protein and CLK2 subcellular localization in a reversible way. Therefore, we anticipate that this compound will be a valuable tool for increasing our understanding of CLKs and their targets, SR proteins, at the level of phosphorylation and subcellular localization.

cancer biology↗

bioRxiv2022

Comparative transcriptome revealed potential genes related with drug resistance in Melanoma

Chemotherapy remains a relatively ineffective and unsatisfactory treatment because of drug resistance in melanoma (whether due to intrinsic resistance or the use of cytostatic drugs). In order to explore the genes and signaling pathways related to melanoma drug resistance, the study presented here obtained drug-resistant melanoma cell lines of A375 and M14 by gradually increasing the concentration of dacarbazine (DTIC), followed by comparative transcriptomics studies (RNA-seq) and real-time quantitative PCR (RT-qPCR) and Western Blotting validation. The results showed that after 8 months of continuous treatment, the IC50 values of A375 and M14 to DTIC were increased by more than 5 folds. Meanwhile, flow cytometry analysis found that drug-resistant melanoma cells have a significant ability to resist apoptosis induced by DTIC. Subsequently, RNA-seq revealed high expression of SENP1 and abnormal activation of the Hippo signaling pathway in drug-resistant cells. Finally, we found that compared with wild-type cells, the expressions of SENP1 and YAP were both up-regulated in drug-resistant cells via RT-qPCR and Western Blotting. Roles of SENP1 in drug resistance was finally verified via its overexpression in normal A375 cell lines. Therefore, this paper infers that there is a positive correlation between the ubiquitin-specific protease SENP1 and the drug resistance of melanoma. Meanwhile, the up-regulation of its expression may lead to changes in the Hippo signaling pathway and increase the resistance of melanoma to DTIC.

cancer biology↗

bioRxiv2022

Time-Aligned Hourglass Gastrulation Models in Rabbit and Mouse

The hourglass model describes the convergence of species within the same phylum to a similar body plan during development, yet the molecular mechanisms underlying this phenomenon in mammals remain poorly described. Here, we compare rabbit and mouse time-resolved differentiation trajectories to revisit this model at single cell resolution. We modeled gastrulation dynamics using hundreds of embryos sampled between gestation days 6.0-8.5, and compare the species using a new framework for time-resolved single-cell differentiation-flows analysis. We find convergence toward similar cell state compositions at E7.5, underlied by quantitatively conserved expression of 76 transcription factors, despite divergence in surrounding trophoblast and hypoblast signaling. However, we observed noticeable changes in specification timing of some lineages, and divergence of primordial germ cells programs, which in the rabbit do not activate mesoderm genes. Comparative analysis of temporal differentiation models provides a new basis for studying the evolution of gastrulation dynamics across mammals.

evolutionary biology↗

bioRxiv2022

Understanding water conservation vs. profligation traits in vegetable legumes through a physio-transcriptomic-functional approach

Vegetable soybean and cowpea are related warm-season legumes showing contrasting leaf water use behaviors under similar root drought stresses, whose mechanisms are not well understood. Here we conducted an integrative phenomic-transcriptomic study on the two crops grown in a feedback irrigation system that enabled precise control of soil water contents. Continuous transpiration rate monitoring demonstrated that cowpea used water more conservatively under earlier soil drought stages, but tended to maintain higher transpiration under prolonged drought. Interestingly, we observed a soybean-specific transpiration rate increase accompanied by phase shift under moderate soil drought. Time-series transcriptomic analysis suggested a dehydration avoidance mechanism of cowpea at early soil drought stage, in which the VuHAI3 and VuTIP2;3 genes were suggested to be involved. Multifactorial gene clustering analysis revealed different responsiveness of genes to drought, time of day and their interactions between the two crops, which involved species-dependent regulation of the core clock genes. Gene network analysis identified two co-expression modules each associated with transpiration rate in cowpea and soybean, including a pair of negatively-correlated modules between species. Module hub genes, including the ABA-degrading gene GmCYP707A4 and the trehalose-phosphatase/synthase gene VuTPS9 were identified. Inter-modular network analysis revealed putative co-players of the hub genes. Transgenic analyses verified the role of VuTPS9 in regulating transpiration rate under osmotic stresses. These findings propose that species-specific transcriptomic reprograming in leaves of the two crops suffering similar soil drought was not only a result of the different drought resistance level, but a cause of it.

plant biology↗

bioRxiv2022

Hematopoietic stem and progenitor cell heterogeneity is inherited from the embryonic hemogenic endothelium

Multipotent hematopoietic stem/progenitor cells (HSPCs) generate all mature blood cells in the erythroid, lymphoid, and myeloid lineages. HSPCs are initially produced in the embryo, via transdifferentiation of hemogenic endothelial cells (hemECs) in the aorta-gonad mesonephros (AGM). HSPCs in the AGM are functionally heterogenous in differentiation and proliferative output, but how these intrinsic differences are acquired remains unanswered. This knowledge could inform approaches to overcome the dysregulation of HSPC heterogeneity associated with poor outcomes of autologous transplants. Here we discovered that loss of microRNA (miR)-128 (miR-128{Delta}/{Delta}) in zebrafish leads to an expansion of hemECs forming replicative HSPCs in the AGM, and a skew towards the erythroid and lymphoid lineages in larval and adult stages. Furthermore, we found that inhibiting miR-128 during the differentiation of human pluripotent stem cells into hemECs, but not during the endothelial-to-hematopoietic transition, recapitulated the lineage skewing. In vivo, expression of wild-type miR-128 in endothelium restored the blood lineage distribution in miR-128{Delta}/{Delta} zebrafish. We found that miR-128 represses the expression of the Wnt inhibitor csnk1a1 and the Notch ligand jag1b, and thus promotes Wnt and Notch signaling in hemECs. De-repression of cskn1a1 resulted in hemECs generating replicative and erythroid-biased HSPCs, whereas de-repression of jag1b resulted in hemECs forming lymphoid-biased HSPCs in the AGM and relative mature blood cells in adult. We propose that HSPC heterogeneity is established in hemogenic endothelium prior to transdifferentiation and is programmed in part by Wnt and Notch signaling modulation.

developmental biology↗

bioRxiv2022

A Model of Hippocampal Replay Driven by Experience and Environmental Structure Facilitates Spatial Learning

Replay of neuronal sequences in the hippocampus during resting states and sleep play an important role in learning and memory consolidation. Consistent with these functions, replay sequences have been shown to obey current spatial constraints. Nevertheless, replay does not necessarily reflect previous behavior and can construct never-experienced sequences. Here we propose a stochastic replay mechanism that prioritizes experiences based on three variables: 1. Experience strength, 2. experience similarity, and 3. inhibition of return. Using this prioritized replay mechanism to train reinforcement learning agents leads to far better performance than using random replay. Its performance is close to the state-of-the-art, but computationally intensive, algorithm by Mattar & Daw (2018). Importantly, our model reproduces diverse types of replay because of the stochasticity of the replay mechanism and experience-dependent differences between the three variables. In conclusion, a unified replay mechanism generates diverse replay statistics and is efficient in driving spatial learning.

neuroscience↗

bioRxiv2022

CTPC, a combined transcriptome dataset of prostate cancer cell lines

Cell lines are the most used model system in cancer research. The transcriptomic data of established prostate cancer (PCa) cell lines help researchers to explore the differential gene expression across the different PCa cell lines and develop hypothesis. Through large scale datamining, we established a curated Combined Transcriptome dataset of PCa Cell lines (CTPC) which contains the transcriptomic data of 1840 samples of seven commonly used PCa cell lines including LNCaP, C4-2, VCaP, 22Rv1, PC3, DU145, and NCI-H660. The CTPC dataset provides an opportunity for researchers to not only compare gene expression across different PCa cell lines but also retrieve the experiment information and associate the differential gene expression with meta data such as gene manipulation and drug treatment information. Additionally, based on the CTPC dataset, we built a platform for users to visualize the data (https://pcatools.shinyapps.io/CTPC_V2/). It is our hope that the combined CTPC dataset and the user-friendly platform are of great service to the PCa research community.

cancer biology↗

bioRxiv2022

Molecular basis for the pheromone-mediated feeding preference of early-instar Mythimna separata larvae

Insect sex pheromones are important chemical signals in sexual communication, they are traditionally thought to be inactive to larvae. However, it was found that some lepidopteran larvae can be significantly attracted by sex pheromones of the same species in a food context. Here we reported that the host-feeding choice of early-instar Mythimna separata larvae can be effectively regulated by the sex pheromone component (Z)-11-hexadecenal (Z11-16: Ald). Further exploration revealed that two olfactory proteins, M. separata general odorant binding protein 2 (MsGOBP2) and olfactory receptor 3 (MsOR3), were molecular basis of the host-feeding choice regulation mediated by Z11-16: Ald. Silencing either MsGOBP2 or MsOR3 led to a sharply reduced preference for Z11-16: Ald-spiked hosts. It is possible that the Z11-16: Ald-based preference of the M. separata larvae for host is governed by the interplay between MsGOBP2 and MsOR3. In the present research, the interactions between MsGOBP2 and Z11-16: Ald were also discussed using molecular dynamics-based approaches. Our research explored insight into the Z11-16: Ald-mediated host-feeding choice regulation of M. separata larvae, all the results would aid in developing olfaction-based methods for controlling pests in larval stage.

ecology↗

bioRxiv2022

Navigation task and action space drive the emergence of egocentric and allocentric spatial representations

In general, strategies for spatial navigation could employ one of two spatial reference frames: egocentric or allocentric. Notwithstanding intuitive explanations, it remains unclear however under what circumstances one strategy is chosen over another, and how neural representations should be related to the chosen strategy. Here, we first use a deep reinforcement learning model to investigate whether a particular type of navigation strategy arises spontaneously during spatial learning without imposing a bias onto the model. We then examine the spatial representations that emerge in the network to support navigation. To this end, we study two tasks that are ethologically valid for mammals - guidance, where the agent has to navigate to a goal location fixed in allocentric space, and aiming, where the agent navigates to a visible cue. We find that when both navigation strategies are available to the agent, the solutions it develops for guidance and aiming are heavily biased towards the allocentric or the egocentric strategy, respectively, as one might expect. Nevertheless, the agent can learn both tasks using either type of strategy. Furthermore, we find that place-cell-like allocentric representations emerge preferentially in guidance when using an allocentric strategy, whereas egocentric vector representations emerge when using an egocentric strategy in aiming. We thus find that alongside the type of navigational strategy, the nature of the task plays a pivotal role in the type of spatial representations that emerge.

neuroscience↗

bioRxiv2022

Within-host genotypic and phenotypic diversity of contemporaneous carbapenem-resistant Klebsiella pneumoniae from blood cultures of patients with bacteremia

Carbapenem-resistant Klebsiella pneumoniae (CRKP) are major pathogens globally. It is unknown whether bloodstream infections (BSIs) by CRKP and other bacteria are commonly caused by single organisms or mixed microbial populations. We hypothesized that contemporaneous CRKP from blood cultures of individual patients are genetically and phenotypically distinct. We determined short-read whole genome sequences of 10 strains from single colonies from CRKP-positive blood cultures in each of 6 patients (Illumina HiSeq). All strains were sequence type (ST)-258 K. pneumoniae that were unique by core genome single nucleotide polymorphism phylogeny, antibiotic resistance and virulence genes, capsular polysaccharide (CPS) gene mutations, and/or plasmid loss. Strains from each of 3 patients that differed in antibiotic resistance, virulence and/or CPS gene content underwent long-read sequencing for genome completion (Oxford Nanopore), and were tested for phenotypes in vitro and pathogenicity during mouse BSIs. Genetically distinct strains within individual patients exhibited significant differences in carbapenem, beta-lactam/beta-lactamase inhibitor and other antibiotic responses, CPS production, mucoviscosity, and susceptibility to serum killing. In 2 patients, strains differed significantly in their ability to infect organs and cause mortality in mice. In conclusion, we identified genotypic and phenotypic variant ST258 K. pneumoniae strains from blood cultures of individual patients, which were not detected by the clinical laboratory at time of BSI diagnosis. The data support a new paradigm of CRKP population diversity during BSIs. If validated for other BSIs, within-host bacterial diversity may have profound implications for medical, microbiology laboratory and infection prevention practices, and for understanding emergence of antibiotic resistance and pathogenesis. IMPORTANCEIn processing positive microbiologic cultures, standard clinical laboratory practice is to test a single bacterial strain from each morphologically distinct colony. We performed comprehensive whole genome sequence analyses on 10 carbapenem-resistant Klebsiella pneumoniae (CRKP) strains from positive blood cultures from each of 6 patients. Our findings that all strains were genetically unique and that genetic variants manifested differences in phenotypes like antibiotic responsiveness and virulence suggest that CRKP bloodstream infections may be commonly caused by mixed bacterial populations. Results raise questions about laboratory protocols and treatment decisions that are directed against a single strain. The observation that pan-genome analyses revealed inter-strain differences that were not evident by studying core genomes has important implications for investigating nosocomial outbreaks and transmission. Data also suggest a model of pathogenesis of CRKP infections, in which environmental pressures in vivo may select for outgrowth of variants that manifest antibiotic resistance, tolerance or specific virulence attributes.

microbiology↗

bioRxiv2022

Perfect adaptation achieved by transport limitations governs the inorganic phosphate response in S. cerevisiae.

Cells cope with and adapt to ever-changing environmental conditions. Sophisticated regulatory networks allow cells to adjust to these fluctuating environments. One such archetypal system is the S. cerevisiae Pho regulon. When external inorganic phosphate (Pi) concentration is low, the Pho regulon activates, expressing genes that scavenge external and internal Pi. However, the precise mechanism controlling this regulon remains elusive. We conducted a systems analysis of the Pho regulon on the single cell level under well-controlled environmental conditions. This analysis identified a robust, perfectly adapted Pho regulon state in intermediate Pi conditions, and we discovered a hitherto unknown intermediate nuclear localization state of the transcriptional master regulator Pho4p. The existence of an intermediate nuclear Pho4p state unifies and resolves outstanding incongruities associated with the Pho regulon, explains the observed programmatic states of the Pho regulon, and improves our general understanding of how nature evolves and controls sophisticated gene regulatory networks. We further propose that robustness and perfect adaptation are not achieved through complex network-centric control, but by simple transport biophysics. The ubiquity of multi-transporter systems suggests that similar mechanisms could govern the function of other regulatory networks as well.

systems biology↗

bioRxiv2022

ATM modulates nuclear mechanics by regulating lamin A levels

Ataxia-telangiectasia mutated (ATM) is one of the three main apical kinases at the crux of DNA damage response and repair in mammalian cells. ATM activates a cascade of downstream effector proteins to regulate DNA repair and cell cycle checkpoints in response to DNA double-strand breaks. While ATM is predominantly known for its role in DNA damage response and repair, new roles of ATM have recently begun to emerge, such as in regulating oxidative stress or metabolic pathways. Here, we report the surprising discovery that ATM inhibition and deletion lead to reduced expression of the nuclear envelope protein lamin A. Lamins are nuclear intermediate filaments that modulate nuclear shape, structure, and stiffness. Accordingly, inhibition or deletion of ATM resulted in increased nuclear deformability and enhanced cell migration through confined spaces, which requires substantial nuclear deformation. These findings point to a novel connection between ATM and lamin A and may have broad implications for cells with ATM mutations--as found in patients suffering from Ataxia Telangiectasia and many human cancers--which could lead to enhanced cell migration and increased metastatic potential.

cell biology↗

bioRxiv2022

Wheat Panache - a pangenome graph database representing presence/absence variation across 16 bread wheat genomes

Bread wheat is one of humanitys most important staple crops, characterized by a large and complex genome with a high level of gene presence/absence variation between cultivars, hampering genomic approaches for crop improvement. With the growing global population and the increasing impact of climate change on crop yield, there is an urgent need to apply genomic approaches to accelerate wheat breeding. With recent advances in DNA sequencing technology, a growing number of high-quality reference genomes are becoming available, reflecting the genetic content of a diverse range of cultivars. However, information on the presence or absence of genomic regions has been hard to visualize and interrogate due to the size of these genomes and the lack of suitable bioinformatics tools. To address this limitation, we have produced a wheat pangenome graph maintained within an online database to facilitate interrogation and comparison of wheat cultivar genomes. The database allows users to visualize regions of the pangenome to assess presence/absence variation between bread wheat genomes. Database URL: http://www.appliedbioinformatics.com.au/wheat_panache

bioinformatics↗