Biology subjects

Wu, M.

Publications and source records attributed to Wu, M..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

KICDB: A Causality-Oriented Multi-Omics Database for Kinase Inhibitor-Induced Cardiotoxicity

BackgroundKinase inhibitors (KIs) are mainstays of targeted cancer therapy, but their clinical utility is frequently limited by cardiotoxicity. A systematic resource to explore the underlying causal mechanisms is urgently needed. MethodsWe present the KICDB (Kinase Inhibitor Cardiotoxicity Database), a comprehensive and interactive web server. KICDB is built upon a framework integrating large-scale transcriptomics meta-analysis with causal inference. ResultsThis database centralizes the findings from a comprehensive meta-analysis of 26 kinase inhibitors (KIs) across 7 studies (n=5291) identified 8,907 significant gene expression changes in human cardiomyocytes. To establish causality, we performed a two-pronged Mendelian randomization (MR) analysis testing hundreds of downstream genes and a panel of 43 key kinase proteins against 46 cardiovascular outcomes. This large-scale analysis revealed 26 significant causal associations, implicating novel molecular mediators in KI-induced cardiotoxicity. ConclusionsKICDB serves as a valuable and accessible platform for the cardio-oncology community. By integrating transcriptomic signatures with causal inference data, the database empowers researchers to formulate mechanistic hypotheses, accelerate biomarker validation, and guide the design of future cardioprotective strategies. URL: https://zhang-lab-database.shinyapps.io/KICDB/ Key PointsO_LIWe developed KICDB, a comprehensive and publicly accessible web server, to systematically investigate the causal mechanisms of KI-induced cardiotoxicity. C_LIO_LIKICDB integrates a large-scale meta-analysis of transcriptomic data from 26 KIs with a robust Mendelian randomization (MR) framework to move beyond correlation and infer causality. C_LIO_LIThe analysis identified 8,907 significant gene expression changes and 26 significant causal associations between KI-associated genes and 46 cardiovascular outcomes. C_LI

bioinformatics↗

bioRxiv2025

Network Modeling Predicts How DYRK1A Inhibition Promotes Cardiomyocyte Cycling after Ischemic/Reperfusion Injury

The adult mammalian heart has a limited ability to regenerate lost myocardium following myocardial infarction (MI), largely due to the poor proliferative capacity of cardiomyocytes (CMs). Dual-specificity tyrosine phosphorylation-regulated kinase 1A (DYRK1A) is a known regulator of cell quiescence, though the mechanisms underlying its function remain unclear. Previous studies have shown that pharmacological inhibition of DYRK1A using harmine induces CM cell cycle re-entry after ischemia/reperfusion (I/R) MI. Here, we developed a computational network model of DYRK1A-mediated regulation of the cell cycle, which predicts how DYRK1A inhibition promotes CM re-entry. To validate these predictions, we tested selective DYRK1A inhibitors and observed robust induction of cell cycle activity in neonatal rat cardiomyocytes (NRCMs). Integrating our network model with bulk RNA-sequencing data from DYRK1A inhibitor-treated NRCMs, we identified E2F1 as a key transcriptional driver of cell cycle gene expression. Finally, we demonstrate that both pharmacological and post-developmental inhibition of DYRK1A enhances heart function and increases CM cycling following I/R MI. Our findings suggest that functional recovery induced by small molecule inhibitor of DYRK1A is mediated by the induction of cycling CMs. One Sentence SummaryInhibition of DYRK1A through LCTB-92 induces cardiomyocyte cycling and improved heart function in a mouse model of ischemic/reperfusion injury.

pharmacology and toxicology↗

bioRxiv2025

Structural and mechanistic insights into bacterial hydrazine biosynthesis

Nitrogen-nitrogen (N-N) bond-containing motifs are prevalent in both clinical drugs and natural products. Bacterial hydrazine synthetases catalyze N-N bond formation by coupling an amino acid and a hydroxylamine via a distinctive O-aminoacyl-hydroxylamine intermediate. Despite its wide occurrence, the structural and mechanistic basis of this process has remained elusive. Here, we report the first crystal structures of the O-aminoacyl-hydroxylamine synthetase component of a bacterial hydrazine synthetase, captured in binary and ternary complexes with substrates and catalytic intermediates. These structures reveal the molecular determinants of substrate recognition and, together with biochemical and computational analyses, establish a detailed mechanistic framework for the hydrazine synthetase family. Leveraging these insights, we expanded hydrazine biosynthesis through the targeted discovery of novel hydrazine synthetases and implemented a chemoenzymatic synthesis strategy. This work provides fundamental insights into hydrazine synthetases and lays the groundwork for their rational engineering as versatile biocatalysts.

microbiology↗

bioRxiv2025

Light-Activated Nucleic Acid Amplification Systems Using Photo-caged DNA Polymerase or Primers

Precise control over nucleic acid amplification is essential for achieving reliable, quantitative, high-throughput, and multiplexed molecular diagnostics, particularly in point-of-care and field settings. However, conventional isothermal amplification methods, especially rapid assays at ambient temperature such as recombinase-aided amplification (RAA), suffer from spontaneous initiation and lack of synchronization across parallel reactions. Here, we report light-activatable RAA systems employing two distinct photocaging strategies to achieve spatiotemporal control. In the first, a photocaged DNA polymerase was engineered via site-specific incorporation of p-azido-L-phenylalanine and conjugation with a 2-nitrobenzyl-modified ssDNA blocker through click chemistry. This approach offers high stability, making it advantageous for long-term storage and lyophilized formats. In the second, 5'-nitrobenzyl-modified primers were synthesized to block hybridization or extension until UV activation, offering operational simplicity and rapid integration into existing workflows. Both strategies independently suppressed background activity in the dark and restored full amplification efficiency upon 365 nm UV exposure. The systems exhibited high sensitivity, low background, and compatibility with portable diagnostics. A custom-built device integrating UV activation and real-time fluorescence detection enabled seamless, on-demand operation. This modular platform provides flexible light-gated amplification solutions, allowing the selection of polymerase- or primer-based caging according to storage stability or workflow requirements, thereby advancing precise and field-ready molecular diagnostics.

molecular biology↗

bioRxiv2025

Sleep pressure is differentially regulated by molecularly distinct subtypes of Lhx6-positive and Lhx6-negative neurons of the zona incerta.

Sleep pressure, the accumulating drive towards sleep during wakefulness, is shaped by Lhx6-positive GABAergic neurons in the zona incerta (ZI). Here, we show that these neurons are broadly activated both by spontaneous and experimentally-elevated sleep pressure, and remain active for hours into recovery sleep. Activation is stronger in anterior ZI and varies across molecularly defined subgroups: Nkx2-2-positive neurons respond vigorously, whereas Calb2-positive neurons respond weakly. We also identify Lhx6-negative/Slc32a1-positive GABAergic ZI neurons with distinct sleep pressure responses. Selective genetic ablation of Nkx2-2 in Lhx6-positive neurons reduces the number of Lhx6-positive neurons, alters their distribution, blunts sleep pressure-induced activation of both Lhx6-positive and negative cells, and increases sleep duration. These findings show that developmentally specified, molecularly heterogeneous Lhx6-positive ZI neurons form a key hub for regulating sleep homeostasis, and offer new insight into the circuitry that controls sleep pressure.

neuroscience↗

bioRxiv2025

Human ribosome interactions reframe neomycin toxicity

Aminoglycosides such as neomycin are clinically limited by toxicity, commonly attributed to the inhibition of mitoribosomes. Here, we re-evaluate this mechanism by integrating Cryo-EM and functional assays to assess neomycins binding potential in vitro with its cellular engagement and functional consequences. Cryo-EM revealed extensive multi-site binding of neomycin on both human mitochondrial and cytosolic ribosomes in vitro, including conserved regions of the decoding center. In contrast, ribosomes isolated from neomycin-treated cells show markedly remodeled occupancy patterns, with no detectable neomycin bound to the mitoribosomes and reduced occupancy at a subset of cytosolic ribosome sites. However, neomycin remained functionally active in cells, inducing widespread stop-codon readthrough while having minimal effects on global mitochondrial and cytosolic protein synthesis. These findings reveal a disconnect between structural binding potential and cellular target engagement and identify disruption of translational fidelity, rather than global translational inhibition, as a major cellular consequence of neomycin exposure.

biochemistry↗

bioRxiv2025

MTARC1 Regulates Lipid Droplet Degradation via Phospholipid Remodeling in Metabolic Fatty Liver Disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is a spectrum of liver disease, including simple fatty liver, hepatic steatosis, fibrosis, cirrhosis, and hepatocellular carcinoma, with limited treatment options. MTARC1 p.A165T variant is associated with reduced risk of MASLD. We previously showed that this variant promotes MTARC1 protein degradation, suggesting MTARC1 inactivation may represent a potential therapeutic strategy. Here, we report that global or liver specific Mtarc1 knockout markedly suppresses diet-induced hepatic TG accumulation, liver injury, inflammation, and fibrosis in a manner dependently on lipolysis and lipophagy. MTARC1 inactivation post-transcriptionally upregulates PEMT and CEPT1 expression, consequently elevating GPL levels, including PC, PE, and lyso-PE, three major GPLs of hepatic LDs. Furthermore, we observed that MTARC1-deficient hepatocytes exhibited smaller but more numerous LDs compared to controls, under comparable cellular TG levels during lipolysis/lipophagy inhibition. Importantly, inhibition of CEPT1 or PEMT could attenuated the hepatoprotective effect of MTARC1 deficiency. Mechanistically, subcellular GPL remodeling induced by MTARC1 deficiency reduce LD size while increase their surface-to-volume ratio, which in turn promote TG degradation through lipolysis and lipophagy. Collectively, our findings identify MTARC1-GPL biosynthesis-LD degradation axis as a key regulator of fatty liver disease and highlight MTARC1 inhibition as a promising therapeutic strategy for MASLD.

cell biology↗

bioRxiv2025

Antibody evasion and receptor binding of SARS-CoV-2 LP.8.1.1, NB.1.8.1, XFG, and related subvariants

SARS-CoV-2 continues to evolve, causing repeated waves of infections around the world. It is critical to understand the features of the virus that explain its growth advantages. Recently, the SARS-CoV-2 Omicron JN.1 subvariants KP.3.1.1 and XEC were outcompeted by later JN.1 progenies, most prominently LP.8.1 and LP.8.1.1. Other recent JN.1 subvariants, such as LF.7.2.1, which became prevalent in Asia, and MC.10.1, have also been under monitoring. Subsequently, NB.1.8.1 and XFG subvariants began increasing in prevalence, as well. We found that serum neutralizing antibody titers against LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, MC.10.1 were similar to XEC in a cohort of 20 KP.2-based monovalent mRNA vaccine (KP.2 MV) recipients and in a cohort 20 adults who did not receive KP.2 MV. NB.1.8.1 and XFG were more evasive of serum neutralization than LP.8.1.1. We then characterized subvariant susceptibility to monoclonal antibody (mAb) neutralization using a panel of 12 mAbs spanning several epitopes on the SARS-CoV-2 spike, and found that LP.8.1 and XFG, MC.10.1 and NB.1.8.1, and LF.7.2.1 evade different classes of mAbs relative to earlier JN.1 subvariants, even if the tested polyclonal serum neutralizing antibody titers were not different overall. Next, we found that the receptor-binding affinity of LP.8.1 to ACE2 was the highest among the tested viruses, while that of LF.7.2.1 was lowest. Therefore, unlike most prior SARS-CoV-2 sublineage evolutionary trajectories, receptor-binding affinity, possibly reflecting enhanced transmissibility-and not increased antibody evasion-better explained the rise of LP.8.1, while the expansion of NB.1.8.1 and XFG again appear correlated with their enhanced antibody evasion.

microbiology↗

bioRxiv2025

Community Socioeconomic Disadvantage relates to White Matter Hyperintensity Burden in Mid-to-Late Life Adults

BackgroundResiding in communities characterized by socioeconomic disadvantage may confer risk for neurodegenerative brain changes and future neuropathology. Based on prior evidence, this study tested the hypotheses that (1) community-level disadvantage would relate independently of individual-level socioeconomic position to white matter hyperintensities (WMHs), which reflect subclinical brain pathology that may presage later dementia; and (2) this association would be partly explained by blood pressure, cardiometabolic risk, and/or systemic levels of inflammation. These hypotheses were examined among otherwise healthy middle- and older-aged adults without clinical dementia at testing. MethodsParticipants were 388 adults aged 40-72 years (53% female; 12% non-White) whose street addresses were entered into the Neighborhood Atlas to compute Area Deprivation Index scores by census block. Participants also underwent high resolution (7 Tesla) brain imaging to assess total WMH volume normalized for intracranial volume, and assessment of blood pressure, cardiometabolic (adiposity, lipids, glucose and insulin), and inflammatory (interleukin-6 and C-reactive protein) risk factors. ResultsLinear regression models showed that higher community deprivation on the ADI associated with greater WMH volume, independently of age, sex, years of education and smoking. This association was largely independent of blood pressure, cardiometabolic risk and systemic inflammation. ConclusionThe present novel findings add to growing evidence that community disadvantage relates to preclinical neurodegenerative changes, which may contribute to accelerated brain and cognitive aging. Future work is warranted to better understand pathways that link residential environments to brain health and to identify targets for community and public policy interventions.

neuroscience↗

bioRxiv2025

Light-orchestrated multi-step solid-phase picodroplet reactors

Picoliter droplet reactors, enabled by droplet microfluidics, are revolutionary tools for biochemical reactions with high efficiency, precision, and minimal reagent use. They excel in single-step reactions and reagent addition through droplet merging. Integrating reagent exchange and washing capabilities directly into these platforms may enable complex multi-step processes, such as de novo oligonucleotide synthesis and multiplex immunoassays. However, current picodroplet microfluidics, lacking such capabilities, remain critically deficient in executing multi-step processes. Here we introduce light-orchestrated solid-phase picodroplet reactors to overcome these limitations. Our platform employs optoelectronic tweezers to manipulate individual picodroplets and microbeads. Using this platform, we demonstrate an eight-step click chemistry-based DNA ligation synthesis cycle, with real-time in situ fluorescence detection of reaction products. This platform overcomes single-step limitations by achieving precise sequential encapsulation and decapsulation of beads with different reagent droplets, ensuring uniform reagent exposure and effective washing. Hence it mitigates reaction errors caused by nonuniform reagent exposure and trapped impurities in conventional bulk processing of microbeads. With minimal reagent consumption, real-time analysis, and programmable light- based control, the platform can potentially be scaled and fully automated into a universal and versatile picoliter-scale reagent handling robot for miniaturizing and streamlining workflows in synthetic biology, drug discovery, and beyond.

bioengineering↗

bioRxiv2025

Genome Mining and Characterization of a Heme-Dependent Enzyme Catalyzing Intermolecular Nitrogen-Nitrogen Bond Formation in Hydrazinosuccinic Acid Biosynthesis

Nitrogen-nitrogen (N-N) bond-forming enzymes are rare but play vital roles in both primary and secondary metabolism. Guided by a nitric oxide synthase (NOS)-based genome mining strategy, we report the discovery and characterization of a new heme-dependent enzyme system that catalyzes intermolecular N-N bond formation. Using both in vivo and in vitro reconstitution approaches, we demonstrated that a protein complex, comprising a heme enzyme and a 2[4Fe-4S] ferredoxin partner, mediates the coupling of the -amine group of L-aspartate with inorganic nitrogen oxide species, such as nitrite or nitric oxide, to generate hydrazinosuccinic acid, a key biosynthetic precursor in several natural product pathways. Structural modeling and site-directed mutagenesis suggest a plausible catalytic mechanism involving the formation of a reactive nitrogen intermediate, potentially a heme-bound nitrene species. These findings reveal a new family of N-N bond-forming biocatalysts that leverage inorganic nitrogen sources, offering valuable tools for genome mining and the synthetic biology.

biochemistry↗

bioRxiv2025

Rethinking Representation Complexity in Drug-Target Prediction via Supervised Vector Quantization

Accurate prediction of drug-target interactions (DTIs) is crucial for computational drug discovery. Although pretrained language models offer richer molecular and protein representations, their increasing complexity does not always lead to better predictive performance. In many cases, the inclusion of redundant or irrelevant features may obscure biologically relevant patterns. In this study, we systematically evaluate the contribution of complex features in DTI prediction and demonstrate that only a portion of these features is truly informative. Based on this insight, we propose a Vector Quantization (VQ)-based module that functions as a plug-and-play feature selection layer within deep learning architectures. When combined with a simple fully connected classifier, this supervised VQ (SVQ) framework not only surpasses recent state-of-the-art DTI methods in performance, but also enhances interpretability through the learning of discriminative codewords. This work highlights the importance of input feature selection in deep learning and offers a new perspective for constructing robust and interpretable DTI prediction models.

bioinformatics↗

bioRxiv2025

Lysosomal control of proteostasis and reproductive capacity by conserved LMD-3 protein in C. elegans

The reproductive capacity declines markedly with female age in humans. Similarly, C. elegans exhibit a rapid age-dependent decline in fecundity shortly after reaching adulthood. Emerging evidence suggests a significant link between proteostasis disruption and reduced fertility in both worms and humans, but the regulatory mechanisms governing this connection are not fully understood. Here, we report that LMD-3, a LysM domain protein, regulates proteostasis and reproductive capacity in C. elegans. The deficiency of lmd-3 leads to striking defects in oxidation resistance and constitutively high cellular stress responses, such as ER stress response and cytosolic stress response. We demonstrate that lysosome-localized LMD-3 protein interacts with vitellogenin and V-type ATPase, which drives proton-transporting and lysosomal lumen acidification. LMD-3 regulation of lysosomal function is essential for maintaining yolk protein homeostasis and reproductive health. We also identify that vitamin B12 (meCbl) supplementation revert the fecundity decline of lmd-3 mutants by reducing oxidative stress and improving lysosomal function. Together, these findings emphasize the role of LMD-3 in sustaining protein homeostasis and oocyte quality control, and establish a model system to find potent therapeutic strategies to increase reproductive health.

cell biology↗

bioRxiv2025

Do Existing COVID-19 Vaccines Need to Be Updated in 2025?

COVID-19 vaccines have been updated each year since 2022 to improve protection against evolving SARS-CoV-2 variants. However, it is unclear whether a reformulation will be necessary for 2025. KP.2-based monovalent COVID-19 mRNA vaccines (KP.2 MV) were authorized for use in 2024, and they conferred substantial protection against hospitalizations caused by viral variants that emerged and dominated later, such as KP.3.1.1 and XEC. Today, LP.8.1 and its subvariant LP.8.1.1 have become dominant worldwide, particularly so in North America. Other variants, such as the LF.7 subvariant LF.7.2.1, have emerged with a growth advantage in Asia. To characterize the antigenicity of LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, and another variant under monitoring, MC.10.1, we tested serum samples from 20 individuals who recently received KP.2 MV in neutralization assays against JN.1, KP.2, KP.3, KP.3.1.1, XEC, LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, or MC.10.1 pseudoviruses. Serum neutralizing antibody titers against LP.8.1, LP.8.1.1, LF.7, LF.7.2.1, and MC.10.1 were comparable to those against KP.3.1.1 and XEC, indicating that LP.8.1.1 and other recently dominant subvariants are antigenically similar to their predecessors. Therefore, the currently authorized KP.2 MV may not need to be updated for 2025, if the vaccine manufacturers could demonstrate comparable immunogenicity for KP.2 MV and LP.8.1-based mRNA vaccines and, of course, in the absence of an antigenically divergent SARS-CoV-2 variant emerging.

microbiology↗

bioRxiv2025

Dimethyl fumarate reprograms cervical cancer cells to enhance antitumor immunity by activating mtDNA-cGAS-STING pathway

BackgroundCervical cancer (CC) remains a significant global health challenge for women, especially in advanced stages where effective treatments are limited. Current immunotherapies, including PD-1/PD-L1 blockades and adoptive T cell therapies, show limited response rates and durability. Dimethyl fumarate (DMF), an FDA-approved drug for autoimmune diseases, has demonstrated that it might exhibit direct antitumor activity in several cancers. However, its influence on anti-tumor immunity and its function in CC remain poorly understood. This study aims to investigate the therapeutic potential of DMF in CC models and elucidate its underlying mechanisms of action. MethodsCC cell lines and mouse models were treated with DMF. Transcriptional level changes in cervical cancer cells following DMF treatment were analyzed by RNA-seq. Mitochondrial DNA (mtDNA) release, and cGAS-STING activation were assessed via qPCR, immunofluorescence, immunoblotting and ELISA. CD8+ T cell recruitment was analyzed by flow cytometry. Combinatorial therapies (DMF + anti-PD-1/TILs) were tested in syngeneic or patient-derived xenografts (PDX) models. ResultsDMF treatment induces mitochondrial dysfunction in tumor cells, resulting in the release of mtDNA into the cytosol. The cytosolic mtDNA activates the cGAS-STING-TBK1 pathway and type I interferon response, leading to the secretion of CCL5 and CXCL10, thereby enhancing CD8 T cell infiltration. Additionally, DMF exhibits synergistic effect with PD-1 blockade in murine CC model, and can enhance the therapeutic efficacy of adoptively transferred T cells toward CC patient-derived xenografts model. ConclusionThis work elucidated that DMF reprograms CC cells to activate the mtDNA-cGAS-STING pathway, fostering a chemokine-rich microenvironment that recruits CD8+ T cells. Its synergy with PD-1 blockade or TIL therapy underscores its potential as an immunomodulatory adjuvant. These findings suggest that DMF holds promise as a novel immunotherapeutic strategy for improving clinical outcomes in CC.

immunology↗

bioRxiv2025

Periventricular Diffusivity Reflects APOE4-modulated Amyloid Accumulation and Cognitive Impairment in Alzheimers Continuum

BackgroundAltered glymphatic-related fluid dynamics are increasingly recognized as a key feature of Alzheimers disease (AD). We generalized an established diffusion imaging technique to estimate periventricular diffusivity (PVeD), hypothesizing that fast diffusion signals in the periventricular region can reflect amyloid-beta (A{beta}) deposition across the Alzheimers continuum. MethodsParticipants from two multi-site cohorts (n = 440 and 414), comprising cognitively unimpaired individuals, those with mild cognitive impairment, and patients with AD, were included. We tested and validated the association of PVeD with A{beta} burden and core AD characteristics. ResultsLower PVeD was extensively associated with greater A{beta} burden, neurodegeneration, cognitive impairment, and clinical severity. Importantly, the relationship between PVeD and A{beta} burden was significantly modulated by APOE4 status, with APOE4 carriers showing a stronger negative association. Baseline PVeD also predicted longitudinal cognitive decline. DiscussionThese findings suggest that periventricular fast diffusion signals can reflect APOE4-modulated A{beta} burden and cognitive decline in AD. Research-in-ContextO_ST_ABSSystematic reviewC_ST_ABSA comprehensive PubMed literature search indicates that fluid movement related to glymphatic activity assessed by diffusion tensor image analysis along the perivascular space (DTI-ALPS) is associated with amyloid-beta deposition in Alzheimers disease (AD). However, recent evidence underscores certain limitations of DTI-ALPS, suggesting that it may not fully capture the diffusion processes involved in amyloid clearance. Moreover, no previous studies have investigated the role of APOE4 in modulating the relationship between glymphatic-related fast diffusion signals and amyloid-beta deposition. InterpretationThe transverse diffusion process along the perivenous space in the periventricular region appears to reflect glymphatic-related dysfunction manifested by amyloid-beta deposition. Reduced periventricular diffusivity is associated with greater amyloid burden across the AD continuum. This association is notably enhanced in APOE4 carriers, who exhibit higher amyloid accumulation for a given reduction in the periventricular diffusivity. Besides, periventricular diffusivity is related to other pathological markers of AD, including clinical symptom severity and neurodegeneration, and may also predict subsequent cognitive decline. Future directionsAlthough diffusion-based neuroimaging metrics hold promise as surrogate imaging biomarkers for glymphatic-related activity, they do not comprehensively capture the complex fluid dynamics such as convective bulk flow within the glymphatic system. By leveraging multimodal neuroimaging techniques and advanced analytic approaches, future research can refine these metrics into more sensitive, non-invasive tools capable of evaluating fluid dynamics related to glymphatic dysfunction in AD.

neuroscience↗

bioRxiv2025

Ancient DNA Reveals Hominoid Evolution: Intermediate DNA Sequences and Advances in Molecular Paleontology

AbstractFossils and ancient crude pottery vessels function as physical "DNA containers," preserving oriDNA (original, in situ DNA) and accumulating eDNA (environmental DNA) over time. Ancient DNA (aDNA) serves as molecular fossils, chronicling evolutionaryhistory. Using "nano-affinitybead technology", we extracted and sequenced DNAfrom Lycoptera fossils in the Jehol region and a "round-bellied jar (Jar)" from the Erlitou period in Guangwu Town, yielding 236,545 primate sequences from the fossils and 86,908 from the pottery. We observed that the AFF value of DNA sequences negatively corre lates with species divergence time1, offering a quantitative measure of DNA preservation and host divergence. Some fragments distinct from modern genomic sequences, termed "intermediate DNAsequences" (IDS), have been identified. Many IDS exhibit an upper age limit, preserving characteristics of the last common ancestor (LCA) of the Hominidae and offering molecular insights into "Darwins puzzle". Among IDS, the SRRA subtype (Sequence Reversal and Rearrangement), identified in mRNA-coding exonic sequences, arises from the incorporation of a complementary antisense strand upstream of the sense strand, either adjacent to it or separated bya sequence interval. This introduces a novel post-transcriptional regulatory mechanism at the mRNA level, driven by SRRA, which presets hairpin structures and Indels in the UTR or CDS of exonic sequences, modulating gene variation. We propose: "SRRAs played a critical trial-and-error role in early Hominidae evolution, facilitating adaptive genomic changes, with some SRRA sequences later excised from exons", positioning SRRAas an evolutionary "genetic switch". Additionally, seven species -specific fragments (SSFs) of non-human primates (NHPs) linked to Asian Homo erectus were identified in the fossils, and pottery DNA reveale d sequences from tropical species (e.g., zebrass, oil palms), providing evidence of climate-driven local extinction and supporting paleo-ecological and paleo-environmental reconstruction. This method of analyzing aDNA from non-skeletal materials opens new avenues in paleontology, archaeology, and geology, guiding the tracing of ancient migration patterns and fossil searches. DNAfragments preserved within "DNA containers " exhibit an "old-few, new-many" turnover pattern, with many aDNA fragments displaying non-deamination. This evidence challenges prevailing perspectives, the authenticity criteria for aDNA, and the capabilities and scope of the traditional research method, necessitating a thorough reevaluation of the relevant knowledge framework. Furthermore, this study opens new opportunities for frontier research.

paleontology↗

bioRxiv2025

MiT4SL: multi-omics triplet representation learning for cancer cell line-adapted prediction of synthetic lethality

Synthetic lethality (SL) offers a promising approach for targeted cancer therapies. Current SL prediction models heavily rely on extensive labeled data for specific cell lines to accurately identify SL pairs. However, a major limitation is the scarcity of SL labels across most cell lines, which makes it challenging to predict SL pairs for target cell lines with limited or even no available labels in real-world scenarios. Furthermore, gene interactions could be opposite between training and test cell lines, i.e. SL vs. non-SL, which further aggravates the challenge of generalization among cell lines. A promising strategy is to transfer knowledge learned from cell lines with relatively abundant SL labels to those with limited SL labels for the discovery of novel SL pairs, i.e., cell line-adapted SL prediction. Here, we propose MiT4SL, a multi-omics triplet representation learning model for cell line-adapted SL prediction. The core idea of MiT4SL is to model cell lineage information as embeddings, which are generated by combining a protein-protein interaction network representation tailored to each cell line with the corresponding protein sequence embeddings. We then combine these cell line embeddings with gene pair representations derived from a biomedical knowledge graph and protein sequences. This triplet representation learning strategy enables MiT4SL to capture both shared biological mechanisms across cell lines and those unique to each cell line, effectively mitigating distribution shift and improving generalization to target cell lines. Additionally, explicit cell line embeddings provide the necessary signals for MiT4SL to effectively differentiate between cell line contexts, enabling it to adjust predictions and mitigate possible label conflicts for the same gene pair across different cell lines. Experimental results across various cell line-adapted scenarios show that MiT4SL outperforms six state-of-the-art models. To the best of our knowledge, MiT4SL is the first deep learning model designed specifically for cancer cell line-adapted SL prediction. AvailabilityThe code of our work is available at https://github.com/JieZheng-ShanghaiTech/MiT4SL.

bioinformatics↗