Biology subjects

Tu, T.

Publications and source records attributed to Tu, T..

15 recordsLinked to original sources

bioRxiv2026

From distyly to stigma-height dimorphism: phylogenetic insights into the evolutionary breakdown of distyly in Jasminum

Background and AimsDistylous polymorphisms (distyly) are adaptations for plants to improve efficiency of cross-pollination and reduce pollen wastage. Theoretical models suggest that distyly evolves from stylar monomorphism via an intermediate stage of stigma-height dimorphism (SHD), however, this evolutionary scenario is only observed in few distylous lineages. The genus Jasminum have many species exhibit either distyly or SHD, providing an ideal opportunity to test models of the evolution of distyly. Focusing on the evolution of distyly, we investigated floral morphs and evaluated the occurrence of distyly and SHD in Jasminum using phylogenetic reconstruction and morphological analysis. MethodsWe investigated floral morphs and evaluated the occurrence of distyly and stigma-height dimorphism through morphology observation. To perform phylogenetic analysis, we sequenced plastomes of forty species from Jasminum and Chrysojasminum using Illumina next generation sequencing, and then constructed phylogenetic tree using maximum likelihood method and Bayesian inference. Based on the phylogenetic tree, we inferred the ancestral floral type through ancestral reconstruction. Key ResultsOur results suggest that the distyly originated in the common ancestor of Jasminum and Chrysojasminum. SHD occurs in several Jasminum species scattered in different clades of the phylogenetic tree, suggesting multiple independent reversions from distyly back to SHD. However, this transition is not associated with the loss of ancillary polymorphisms, as all the species examined in this study well retain dimorphic traits for other floral organs such as pollens and stigmas. Moreover, most species maintain strict heteromorphic self-incompatibility, while J. officinale has lost or at least partially lost self-incompatibility, suggesting that distyly is not always linked to self-incompatibility. ConclusionsIn Jasminum, breakdown of distyly resulted in evolutionary transitions to stigma-height dimorphism for multiple times, suggesting that distyly is not a stable floral polymorphism under certain selective forces. These findings advance our understanding on the evolution of distyly and plant reproductive systems.

plant biology↗

bioRxiv2026

SynFit: Synergistic Contrastive Learning for Multi-Objective Protein Fitness Prediction and Optimization

Proteins function through a complex interplay of structural and biochemical properties, and mutations can reshape these properties to generate fitness landscapes spanning multiple functional objectives. A central challenge in protein engineering is the need to simultaneously optimize multiple properties. In biocatalysis, for example, practical enzyme development routinely requires the concurrent optimization of catalytic activity, selectivity, stability, and substrate generality. However, despite recent advances in computational protein design and fitness prediction, most existing approaches treat these properties independently and do not explicitly capture the dependencies and trade-offs that govern real-world protein performance. We present SynFit, a multi-objective learning framework that integrates pretrained protein language models with experimental fitness measurements for protein fitness prediction and engineering. SynFit learns both shared and property-specific protein sequence representations through a synergistic contrastive learning strategy, enabling the identification of variants that simultaneously optimize multiple functional properties. Across a large-scale multi-fitness deep mutational scanning benchmark, SynFit consistently outperforms state-of-the-art supervised models trained on individual objectives and more accurately identifies variants that balance competing functional constraints. We further applied SynFit to multi-objective enzyme design for a new-to-nature biocatalytic enantioselective borylation reaction, providing a diverse array of novel cytochrome c sextuple variants in a single round of design with simultaneously improved catalytic activity and enantioselectivity that rival the best variants obtained through directed evolution. Together, these results establish SynFit as a general framework for multidimensional protein fitness prediction and highlight its potential to enable efficient multi-objective optimization in protein engineering, particularly in biocatalysis.

bioinformatics↗

bioRxiv2026

Deconvolving mutation effects on protein stability and function with disentangled protein language models

Understanding how evolutionary constraints shape protein sequences is fundamental to deciphering the molecular mechanisms underlying protein stability and function, which has broad implications in protein engineering and therapeutics development. Recent advances in protein language models (pLMs) have enabled accurate prediction of mutation effects through evolutionary information, effectively capturing the selective pressure that governs protein sequence variation. A critical challenge, however, remains in disentangling the intertwined mutation effects on protein stability and function, as evolutionary signals conflate both stability-driven and function-driven pressures, obscuring the mechanistic basis of mutation effects and limiting their utility for rational protein engineering. In this work, we introduce DETANGO, a novel deep learning framework that explicitly deconvolves the mutation effects on protein functions by removing components attributable to stability perturbations from the pLM-predicted mutation effects. Guided by computational or experimental stability measurements, DETANGO estimates a functional plausibility score for each single-point mutation that is the component of the mutation effect not accounted for by changes in stability. Single-point mutations with low functional plausibility are predicted to be stable-but-inactive (SBI) variants, whose compromised activities are caused by direct perturbations on functional mechanisms rather than structural stability. Residues enriched for such variants are inferred to be functionally critical, as indicated by the strong evolutionary pressures to maintain protein function. Through extensive benchmarking experiments, we show that DETANGO accurately identifies SBI variants and pinpoints functionally important residues across contexts, including ligand binding, catalysis, and allostery. Moreover, extending DETANGO from individual proteins to homologous protein families reveals shared and distinctive functional patterns across protein families. Collectively, these results establish DETANGO as a biologically grounded framework for disentangling evolutionary constraints on protein stability and function, advancing mechanistic understanding of protein function, and informing rational protein engineering.

bioinformatics↗

bioRxiv2025

Early-onset β-amyloidosis in human brains with hematological malignances and cardiovascular diseases: Revisiting injury/stress induced axonal pathology

{beta}-Amyloid (A{beta}) and tau pathologies are hallmarks of Alzheimers disease (AD) and they develop in human brain following differential spatiotemporal trajectories. As such, young/adult-onset tau-independent {beta}-amyloidosis is rare. We encountered four such cases among 397 banked brains, with the donors died of hematological malignances (blood cancers) or cardiovascular diseases. To explore the pathological implications, we examined 17 brains (10-87 year-old, y) from blood cancer patients and three (52-82 y) with cardiovascular diseases, focusing on vascular injury, axonal pathology and A{beta} formation. A{beta} plaques occurred in two adult brains (31 y, 63 y) with blood cancers and two (52 y, 65 y) with cardiovascular diseases in the absence of tau. In the blood cancer brains, 17/17 had vascular injuries seen in hematoxylin-eosin stained sections, 13/17 had iron leakage, and 13/17 had axonal pathology. Malignant cell infiltration was found in 5/14 brains with myeloid, lymphocytic and lymphoma malignances, with light chain infiltration in 3/3 brains with multiple myeloma. In the cardiovascular disease brains, A{beta} deposition primarily as diffuse plaques occurred in the cerebral cortex, with vascular and axonal pathologies in the white matter, striatum and internal capsule. Using a multi-labeling approach, the injury/stress induced axonal pathology was found to concur with {beta}-amyloid processor protein elevation and enhanced {beta}-secretase 1 processing but not intraneuronal A{beta} accumulation. The current findings suggest that hematological malignances and cardiovascular diseases are risk conditions for early-onset cerebral {beta}-amyloidosis, potentially attributable to vascular injury.

neuroscience↗

bioRxiv2025

Putative long-range mossy fiber sprouting and regional hypermetabolic capacity in the hippocampus of patients with mesial temporal lobe epilepsy

Mesial temporal lobe epilepsy (MTLE) is pathologically characterized by neuronal loss in the dentate hilus, CA3 and CA1 regions, and mossy fiber (MF) sprouting into the inner molecular layer (iML). The latter forms aberrant excitatory circuities that are considered to facilitate recurrent seizures, with the subiculum also being related to epileptogenic activation. We recently identified a distinct expression of -smooth muscle actin (SMA) at the MF terminals in human hippocampus. This prompted us to explore MF sprouting in resected hippocampi (n=20) from patients with MTLE relative to postmortem control (n=20) using SMA along with reference markers for pathological cross-validation. Compared to control, neuronal loss assessed with neuron-specific nuclear antigen and sortilin immunolabeling reached CA1 in all resected hippocampi. SMA, zinc transporter 3 and {beta}-secretase 1 immunolabeling in the iML tended to be increased. The MF-related markers also revealed a preserved fibrous band extending across CA1 to subiculum. Cytochrome c oxidase immunolabeling also increased in iML and subiculum in the MTLE group. Taking together, the current findings point to the existence of long-range MF sprouting and a regional hypermetabolic compacity in the hippocampal formation of patients with drug resistant MTLE.

neuroscience↗

bioRxiv2025

Genetic association meta-analysis is susceptible to confounding by between-study cryptic relatedness

Meta-analysis of Genome-Wide Association Studies (GWAS) has important advantages, but it assumes that studies are independent, which does not hold when there is relatedness between studies. As a motivating example, recent work suggested applying sex-stratified meta-analysis to correct for participation bias, without considering that men and women from the same population will be highly related. Our theory demonstrates how cryptic relatedness results in correlated test statistics between studies, inflating meta-analysis. We characterize the effects of different between-study relatedness scenarios, particularly population structure and recent family relatedness, on meta-analysis type I error control and power. We simulated data with (1) no family relatedness between subpopulations, (2) family relatedness within subpopulations, (3) family relatedness across subpopulations, and (4) single population with family relatedness. We run joint and meta-analyses on simulations using both binary and quantitative traits. In scenarios with family relatedness, sex-stratified meta-analysis exhibits severe inflation and lower AUC compared to joint and subpopulation meta-analyses. Remarkably, genomic control succeeds in correcting inflation in these cases, but does not alter calibrated power. Analysis of real datasets confirms severe inflation for sex-stratified meta-analysis in family studies, but a negligible effect for population studies with up to 10,000 individuals. Our theoretical framework demonstrates that the inflation factor increases as the sample size increases. We recommend against meta-analyzing studies that share the same populations, which increases the risk of inflation due to cryptic relatedness between studies.

genetics↗

bioRxiv2025

AI-assisted Drug Re-purposing for Human Liver Fibrosis

Liver fibrosis is a severe disease with few treatment options due to the poor quality of the available animal and in vitro models. To address this, we investigated whether a hypothesis generating multi-agent AI system (AI co-scientist) could assist in re-purposing drugs for treatment of liver fibrosis and direct their experimental characterization. A multi-parameter image analysis workflow, which enabled anti-fibrotic efficacy and drug toxicity to be serially assessed in multi-lineage human hepatic organoids grown in microwells (i.e., microHOs), was used to assess the effects of 14 drugs. Remarkably, two of the three AI co-scientist-recommended drugs that targeted epigenomic modifiers exhibited significant anti-fibrotic activity. Analysis of the anti-fibrotic effects of five drugs indicated that two inhibited TGF{beta}-induced intracellular signaling and three drugs altered TGF{beta}-induced mesenchymal cell differentiation. Since all five of the anti-fibrotic drugs reduced TGF{beta}-induced chromatin structural changes, epigenomic changes play an important role in the pathogenesis of liver fibrosis. One AI co-scientist recommended drug is an FDA-approved anti-cancer treatment (Vorinostat) that reduced TGF{beta}-induced chromatin structural changes by 91% and promoted liver parenchymal cell regeneration in microHOs. Hence, the use of AI co-scientist and this microHO platform identified a potential new generation of liver fibrosis treatments that also promote liver regeneration.

bioinformatics↗

bioRxiv2025

Genetic architecture of the S-locus supergene revealed in a tetraploid distylous species

SummaryO_LIHeterostyly is a polymorphic floral adaptation controlled by supergenes and maintained in populations by disassortative mating. The molecular basis of distyly has been investigated in several unrelated families. Previous studies have been limited to diploid species and have not included Rubiaceae, which has the highest number of heterostylous species. C_LIO_LIHere, we investigate the genetic architecture of tetraploid Schizomussaenda henryi (Rubiaceae) to identify candidate style-length genes, evidence for hemizygosity and the potential role of gene duplication in the evolution of the S-locus. Chromosome-level genome assemblies and transcriptomic approaches identified the S-locus region comprised of four hemizygous genes. C_LIO_LIThe candidate gene SchzAUX22 may regulate style length and filament growth by acting in the auxin signaling pathway. Comparative studies of the two sub-genomes of S. henryi indicated strong similarities and no significant sub-genome dominance, as expected from autotetraploidy. Evidence from haplotype-resolved assemblies of a short-styled plant indicated that it possessed the ssSS genotype, consistent with autotetraploidy, which was estimated to have originated [~]3.6 Mya. Analysis of Ks values between S-locus genes and their paralogs indicated that the S-locus likely originated through stepwise duplication. C_LIO_LIOur study provides comprehensive genomic analysis of distyly in a polyploid and demonstrates that despite whole genome doubling the S-locus supergene remains intact and functional as an outbreeding mechanism. Our results contrast with many other heterostylous lineages where polyploidy is associated with breakdown of the polymorphism and transitions to self-fertilization. C_LI

plant biology↗

bioRxiv2025

AI mirrors experimental science to uncover a novel mechanism of gene transfer crucial to bacterial evolution

AI models have been proposed for hypothesis generation, but testing their ability to drive high-impact research is challenging, since an AI-generated hypothesis can take decades to validate. Here, we challenge the ability of a recently developed LLM-based platform, AI co-scientist, to generate high-level hypotheses by posing a question that took years to resolve experimentally but remained unpublished: How could capsid-forming phage-inducible chromosomal islands (cf-PICIs) spread across bacterial species? Remarkably, AI co-scientists top-ranked hypothesis matched our experimentally confirmed mechanism: cf-PICIs hijack diverse phage tails to expand their host range. We critically assess its five highest-ranked hypotheses, showing that some opened new research avenues in our laboratories. We benchmark its performance against other LLMs and outline best practices for integrating AI into scientific discovery. Our findings suggest that AI can act not just as a tool but as a creative engine, accelerating discovery and reshaping how we generate and test scientific hypotheses.

microbiology↗

bioRxiv2024

Sortilin C-terminal fragment deposition depicts tangle-related nonamyloid neuritic plaque growth in Alzheimers disease

Sortilin C-terminal fragments (sorfra) can co-deposit in {beta}-amyloid (A{beta}) plaques in human brain. However, sorfra plaques develop in the cerebrum with a spatiotemporal trajectory as of tauopathy. Here we examined sorfra pathogenesis relative to neuritic plaque evolution in the human brains with amyloid and tau pathologies converged in the neocortex and hippocampus. Sorfra plaques occurred in correlation with pTau/tangle, but not A{beta}, pathologies across cerebral regions, neighboring cortical/hippocampal areas, and along the sulcal valley to gyral hilltop transition. Sorfra plaques and neuritic plaques were matchable in location, shape and size between consecutive sections, and were colocalized in double-labeling preparations. Microscopical study and tissue clearance three-dimensional imaging revealed sorfra/A{beta} colocalized as well as independent plaques. Among the former, sorfra labeling correlated negatively to A{beta}/amyloid labeling and {beta}-secretase-1 labeling in dystrophic neurites. Sorfra plaques were depleted of microtubule-associated protein 2 (MAP2) labeled neuronal somata and dendrites, whereas normal looking MAP2/sortilin co-labeled profiles occurred nearby. Sorfra deposits were seen in astrocytes but not microglia around the plaques. Taken together, sorfra plaques are anatomically matchable to silver stained neuritic plaques. They develop with tangle-related somatodendritic degeneration, presenting as nonamyloid growth of the A{beta} plaques and formation of A{beta}-independent neuritic plaques during Alzheimers disease pathogenesis.

neuroscience↗

bioRxiv2024

The subcommissural organ regulates brain development via secreted peptides

The subcommissural organ (SCO) is a gland located at the entrance of the aqueduct of Sylvius in the brain. It exists in species as distantly related as amphioxus and humans, but its function is largely unknown. To explore its function, we compared transcriptomes of SCO and non-SCO brain regions and found three genes, Sspo, Car3, and Spdef, that are highly expressed in the SCO. Mouse strains expressing Cre recombinase from endogenous promoter/enhancer elements of these genes were used to genetically ablate SCO cells during embryonic development, resulting in severe hydrocephalus and defects in neuronal migration and development of neuronal axons and dendrites. Unbiased peptidomic analysis revealed enrichment of three SCO-derived peptides, namely thymosin beta 4, thymosin beta 10, and NP24, and their reintroduction into SCO-ablated brain ventricles substantially rescued developmental defects. Together, these data identify a critical role for the SCO in brain development.

neuroscience↗

bioRxiv2023

Genetic Discovery Enabled by A Large Language Model

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.

genetics↗

bioRxiv2019

Developing a dengue forecast model using Long Short Term Memory neural networks method

BackgroundDengue Fever (DF) is a tropical mosquito-borne disease that threatens public health and causes enormous economic burdens worldwide. In China, DF expanded from coastal region to inner land, and the incidence sharply increased in the last few years. In this study, we conduct the analysis of dengue using the Long Short Term Memory (LSTM) recurrent neural networks. This is an artificial intelligence technology, to develop a precise dengue forecast model.\n\nMethodology/Principal FindingsThe model is developed from monthly dengue cases and local meteorological data of 2005-2018 among top 20 Chinese cities with a record of the highest dengue incidence. The first 13 year data were used to construct the LSTM and to predict the dengue outbreaks in 2018. The results are compared with the estimated dengue cases of other previously published models. Model performance and prediction accuracy were assessed using Root Mean Square Error (RMSE). With the LSTM method, the prediction measurements of average RMSE drop by 54.79% and 34.76% as compared with the Susceptible Infected Recovered (SIR) model and Zero Inflated Generalized Additive Model (ZIGAM). Our results showed that if only local data were used to develop forecast models, the LSTM neural networks would fail to capture the transmission characteristics of dengue virus in areas with fewer dengue cases. Contrarily, transfer learning (TL) can improve the accuracy of prediction of the LSTM neural network model in areas with fewer dengue incidences.\n\nConclusion and significanceThe LSTM model is beneficial in predicting dengue incidence as compared with other previously published forecasting models. The findings provide a more precise forecast dengue model, which can help the local government and health-related departments respond early to dengue epidemics.\n\nAuthor summaryIn China, DF is a public health concern that poses a great economic burden on local governments. However, the incidence has sharply increased in recent years with growth in the sub-regions. With this issue, it will be challenging to develop an accurate and timely dengue forecast model. LSTM recurrent neural networks, deep learning methods and virus propagation rules by learning from observational data offer more advantages in predicting the prevalence of infectious disease dynamics than the traditional statistical model. The 2005-2017 data of the top 20 Chinese cities with the highest dengue incidence were used to construct the LSTM model, advantageous in predicting dengue in most cities. Moreover, the model helped to predict the dengue outbreaks in 2018 and used to compare the estimated dengue cases with the RMSE results of other previously published models. A thorough search of the literature shows that this is the first established dengue forecast model using the LSTM method, which is effective in predicting the trend of dengue dynamics.

bioinformatics↗

bioRxiv2019

A novel thermostable aspartic protease from Talaromyces leycettanus and its specific autocatalytic activation through an intermediate transition state

Aspartic proteases exhibit optimum enzyme activity under acidic condition and have been extensively used in food, fermentation and leather industries. In this study, a novel aspartic protease precursor (proTlAPA1) from Talaromyces leycettanus was identified and successfully expressed in Pichia pastoris. Subsequently, the auto-activation processing of the zymogen proTlAPA1 was studied by SDS-PAGE and N-terminal sequencing, under different processing conditions. TlAPA1 shared the highest identity of 70.3 % with the aspartic endopeptidase from Byssochlamys spectabilis (GAD91729) and was classified into a new subgroup of the aspartic protease A1 family, based on evolutionary analysis. Mature TlAPA1 protein displayed an optimal activity at 60 {degrees}C and remained stable at temperatures of 55 {degrees}C and below, indicating the thermostable nature of TlAPA1 aspartic protease. During the auto-activation processing of proTlAPA1, a 45 kDa intermediate was identified that divided the processing mechanism into two steps: formation of intermediates, and activation of the mature protein (TlAPA1). The former step was completely induced by pH of the buffer, while the latter process depended on protease activity. The discovery of the novel aspartic protease TlAPA1 and study of its activation process will contribute to a better understanding of the mechanism of aspartic proteases auto-activation. IMPORTANCEThe novel aspartic protease TlAPA1 was identified from T. leycettanus and expressed as a zymogen (proTlAPA1) in P. pastoris. Enzymatic characteristics of the mature protein were studied and the specific pattern of zymogen conversion was described. The auto-activation processing of proTlAPA1 proceeded in two stages and an intermediate was identified in this process. These results describe a new subgroup of aspartic protease A1 family and provide insights into a novel mode of activation processing in aspartic proteases.

molecular biology↗

bioRxiv2018

Characterizing Activity and Thermostability of GH5 Cellulase Chimeras from Mesophilic and Thermophilic Parents

Cellulases from glycoside hydrolase (GH) family 5 are key enzymes in the degradation of diverse polysaccharide substrates and are used in industrial enzyme cocktails to break down biomass. The GH5 family shares a canonical ({beta})8-barrel structure, where each ({beta}) module is essential for the enzyme stability and activity. Despite their shared topology, the thermostability of GH5 enzymes can vary significantly, and highly thermostable variants are often sought for industrial applications. Based on a previously characterized thermophilic GH5 cellulase from Talaromyces emersonii (TeEgl5A, with an optimal temperature of 90{degrees}C), we created ten hybrid enzymes with the mesophilic cellulase from Prosthecium opalus (PoCel5) to determine which elements are responsible for enhanced thermostability. Five of the expressed hybrid enzymes exhibit enzyme activity. Two of these hybrids exhibited pronounced increases in the temperature optima (10 and 20{degrees}C), T50 (15 and 19{degrees}C), Tm (16.5 and 22.9{degrees}C), and extended half life, t1/2 (~240- and 650-fold at 55{degrees}C) relative to the mesophilic parent enzyme, and demonstrated improved catalytic efficiency on selected substrates. The successful hybridization strategies were validated experimentally in another GH5 cellulase from Aspergillus nidulans (AnCel5), which demonstrated a similar increase in thermostability. Based on molecular dynamics simulations (MD) of both PoCel5 and TeEgl5A parent enzymes as well as their hybrids, we hypothesize that improved hydrophobic packing of the interface between 2 and 3 is the primary mechanism by which the hybrid enzymes increase their thermostability relative to the mesophilic parent PoCel5.\n\nIMPORTANCEThermal stability is an essential property of enzymes in many industrial biotechnological applications, as high temperatures improve bioreactor throughput. Many protein engineering approaches, such as rational design and directed evolution, have been employed to improve the thermal properties of mesophilic enzymes. Structure-based recombination has also been used to fuse TIM-barrel fragments and even fragments from unrelated folds, to generate new structures. However, there are not many research on GH5 cellulases. In this study, two GH5 cellulases, which showed TIM-barrel structure, PoCel5 and TeEgl5A with different thermal properties were hybridized to study the roles of different ({beta}) motifs. This work illustrates the role that structure guided recombination can play in helping to identify sequence function relationships within GH5 enzymes by supplementing natural diversity with synthetic diversity.

bioengineering↗