Biology subjects

Liu, M.-J.

Publications and source records attributed to Liu, M.-J..

7 recordsLinked to original sources

bioRxiv2025

Visualization and Prediction of in vivo Phosphate Dynamics via Auto-Glowing Plant Sensors

Monitoring endogenous nutrient levels is crucial for maximizing crop yields and optimizing fertilizer use. Here, focusing on phosphorus, an essential nutrient for plant growth, we developed a low-cost and non-invasive biosensor to visualize and predict early stress signaling in plants. By combining plant phosphate (Pi)-deficiency-induced promoter systems with fungal self-sustained bioluminescence systems genetically engineered into tobacco plants, we created sensor plants that emitted more light when experiencing Pi deficiency. This light emission correlated with the expressions of known phosphate-responsive genes and the total phosphorus content in plants, and decreased during Pi recovery conditions, demonstrating the responsiveness and robustness of the sensor plants in reflecting endogenous phosphorus deficiency. The sensor plants responded primarily to Pi deficiency rather than nitrogen or potassium deficiencies and were sensitive to different ranges of external Pi concentrations. Additionally, when grafted onto tomato and chili pepper plants, the sensor plants responded to external phosphorus deficiency, showing promise for monitoring stress signals in different crop species. Using deep-learning-based image analysis techniques, auto-luminescent signals of sensor plants could be detected and used to predict phosphorus deficiency. This study outlines a strategy of creating a self-luminous biosensor to visualize phosphate dynamics in planta and predict nutrient deficiency for sustainable agriculture.

plant biology↗

bioRxiv2025

TISCalling: Leveraging Machine Learning to Identify Translational Initiation Sites in Plants and Viruses

The recognition of translational initiation sites (TISs) offers complementary insights into identifying genes encoding novel proteins or small peptides. Conventional computational methods primarily identify Ribo-seq-supported TISs and lack the capacity of systematical and global identification of TIS, especially for non-AUG sites in plants. Additionally, these methods are often unsuitable for evaluating the importance of mRNA sequence features for TIS determination. In this study, we present TISCalling, a robust framework that combines machine learning (ML) models and statistical analysis to identify and rank novel TISs across eukaryotes. TISCalling generalized and ranks important features common to multiple plant and mammalian species while identifying kingdom-specific features such as mRNA secondary structures and G-contents. Furthermore, TISCalling achieved high predictive power for identifying novel viral TISs. Importantly, TISCalling provides prediction scores for putative TIS along plant transcripts, enabling prioritization of those of interest for further validation. We offer TISCalling as a command-line-based package [https://github.com/yenmr/TIScalling], capable of generating prediction models and identifying key sequence features. Additionally, we provide web tools [https://predict.southerngenomics.org/TIScalling] for visualizing pre-computed potential TISs, making it accessible to users without programming experience. The TISCalling framework offers a sequence-aware and interpretable approach for decoding genome sequences and exploring functional proteins in plants and viruses.

bioinformatics↗

bioRxiv2024

PREDICT: Advancing Accurate Gene Expression Prediction and Motif Identification in Plant Stress Responses

Cells respond to environmental stimuli through transcriptional responses, orchestrated by transcription factors (TFs) that interpret the gene cis-regulatory DNA sequences, determining gene expression dynamics timing and locations. Diversification in TFs and cis-regulatory element (CRE) interactions result in unique gene regulatory networks (GRNs) that underpin plant adaptation. A primary challenge is identifying Transcription Factor Binding Motifs (TFBMs) for temporal and condition-specific gene expressions in plants. While the Multiple EM for Motif Elicitation (MEME) suite identifies stress-responsive CREs in Arabidopsis, its predictive power for gene expression remains uncertain. Alternatively, the k-mer approach identifies CRE sites and consensus TF motifs, thereby improving gene expression prediction models. In this study, we harnessed the power of a k-mer pipeline to address sequence-to-expression prediction problems across diverse abiotic stresses, in both bryophytic and vascular plants, including monocots and dicots. Moreover, we characterized both un-gapped and gapped CREs and, coupled with GRN analyses, pinpointed key TFs within transcriptional cascades. Lastly, we developed the Predictive Regulatory Element Database for Identifying Cis-regulatory elements and Transcription factors (PREDICT), a web tool for efficient k-mer identification. This advancement will enrich our understanding of the cis-regulatory code landscape that shapes gene regulation in plant adaptation. PREDICT web tool is available at [http://predict.southerngenomics.org/kmers/kmers.php].

bioinformatics↗

bioRxiv2024

Distinct Effects of Aducanumab and Lecanemab on Intraneuronal Endogenous Aβ42 and Phosphorylated Tau in Alzheimer's Disease Treatment

In the treatment of Alzheimers Disease (AD), two FDA-approved monoclonal antibodies, Aducanumab (Adu) and Lecanemab (LCN), exhibit significant differences in clinical benefits. By utilizing human-induced basal forebrain cholinergic neurons (BFCNs) derived from AD patient skin fibroblasts, we successfully recapitulated the natural endogenous neuropathologies of A{beta}42 and Tau within just 21 days and revealed distinct intraneuronal effects of Adu and LCN. Both antibodies are internalized into BFCNs and localize with cytosolic A{beta}42. However, LCN, selectively targeting A{beta}42 oligomers and protofibrils, triggers TRIM21 pathway and significantly enhances autolysosome- and proteasome-mediated A{beta}42 clearance, thereby leading to a marked reduction in phosphorylated Tau181 (pTau181) pathology. In contrast, the fibrillized A{beta}42-selective Adu shows considerably weaker effects. This study not only reveals the unique intraneuronal actions of Adu and LCN but also provides a reliable and accessible human neuronal model for evaluating potential AD therapeutics, emphasizing the importance of intraneuronal pathology in the treatment of AD.

neuroscience↗

bioRxiv2023

Modeling alternative translation initiation sites in plants reveals evolutionarily conserved cis-regulatory codes in eukaryotes

mRNA translation relies on identifying translation initiation sites (TISs) in mRNAs. Alternative TISs are prevalent across plant transcriptomes, but the mechanisms for their recognition are unclear. Using ribosome profiling and machine learning, we developed models for predicting alternative TISs in Arabidopsis thaliana and tomato (Solanum lycopersicum). Distinct feature sets were predictive of AUG and non-AUG TISs in 5' untranslated regions and coding sequences, including a novel CU-rich sequence that promoted plant TIS activity, a translational enhancer found across dicots and monocots and also in humans and viruses. Our results elucidate the mechanistic and evolutionary basis of TIS recognition, whereby cis-regulatory RNA signatures affect start site selection. The TIS prediction model provides global estimates of TISs to discover neglected protein-coding genes across plant genomes. The prevalence of cis-regulatory signatures across eukaryotes and viruses suggests their broad, critical roles in reprogramming the translational landscape in the plant-virus arms race. TeaserNew insights into how plant ribosomes distinguish AUG and non-AUG triplets for protein synthesis via a conserved eukaryotic cis-regulatory strategy.

systems biology↗

bioRxiv2023

A simple, flexible and high-efficiency western blot analysis for age-related human induced neurons

High-throughput western blot (WB) analysis of small and precious samples, such as various age-related subtype-specific human induced neurons (hiNs), confers the ability to obtain more consistent, comparable, and informative data from materials with extremely limited availability. In this study, p-toluenesulphonic acid (PTSA), an odorless tissue fixative, was used to inactivate HRP for developing a high-throughput WB method. PTSA-treated blots showed fast and efficient inactivation of HRP without detectable protein loss and epitope damage. With a brief PTSA-treatment before every next probing, 10 proteins of dopaminergic hiNs could be sequentially, sensitively, and specifically detected in a blot. These WB data proved the age-associated and neuron-specific features of hiNs and further revealed a sharp reduction of two Parkinsons disease-associated proteins, UCHL1 and GAP43, in the normal aging dopaminergic neurons. Together, this study developed a unique and high-efficiency WB analysis and pinpointed its special value for capturing robust useful data from limited, precious samples. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/526150v2_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@18fcd9dorg.highwire.dtl.DTLVardef@42426org.highwire.dtl.DTLVardef@1e13accorg.highwire.dtl.DTLVardef@1db2f39_HPS_FORMAT_FIGEXP M_FIG C_FIG HIGHLIGHTS{checkmark} P-toluenesulphonic acid (PTSA) quickly and fully deactivated HRP on immunoblots. {checkmark}PTSA was an odorless, non-volatile, low cost, and user-friendly HRP inactivator. {checkmark}PTSA allowed high-efficiency WB analysis to save small precious samples and time. {checkmark}10 proteins were detected in a single blot of age-relevant human induced neurons. {checkmark}UCHL1 and GAP43 sharp decline occurred in aging human induced dopaminergic neurons.

biochemistry↗

bioRxiv2017

Regulatory Divergence In Wound-Responsive Gene Expression In Domesticated And Wild Tomato

BackgroundThe evolution of cis- and trans-regulatory components of transcription is central to how stress response and tolerance differ across species. However, it remains largely unknown how divergence in TF binding specificity and cis-regulatory sites contribute to the divergence of stress-responsive gene expression between wild and domesticated species.\n\nResultsUsing tomato as model, we analyzed the transcriptional profile of wound-responsive genes in wild Solanum pennellii and domesticated S. lycopersicum. We found that extensive expression divergence of wound-responsive genes is associated with speciation. To assess the degree of trans-regulatory divergence between these two species, 342 and 267 putative cis-regulatory elements (pCREs) in S. lycopersicum and S. pennellii, respectively, were identified that were predictive of wound-induced gene expression. We found that 35-66% of pCREs were conserved across species, suggesting that the remaining proportion (34-65%) of pCREs are species specific. This finding indicates a substantially higher degree of trans-regulatory divergence between these two plant species, which diverged [~]3-7 million years ago, compared to that observed in mouse and human, which diverged [~]100 million years ago. In addition, differences in pCRE sites were significantly associated with differences in wound-responsive gene expression between wild and domesticated tomato orthologs, suggesting the presence of substantial cis-regulatory divergence.\n\nConclusionsOur study provides new insights into the mechanistic basis of how the transcriptional response to wounding is regulated and, importantly, the contribution of cis- and trans-regulatory components to variation in wound-responsive gene expression during species domestication.

evolutionary biology↗