Biology subjects

Tian, A.

Publications and source records attributed to Tian, A..

13 recordsLinked to original sources

bioRxiv2026

Inverse FoldDir: Structure-conditioned Protein Sequence Design by Dirichlet Flow Matching

Protein engineering has important implications in the bioeconomy, enabling applications in materials, medicine, and energy. A key challenge is designing protein sequences that have a specific form and function. Protein inverse folding seeks to address this challenge by identifying amino acid sequences compatible with a desired protein backbone. This task is central to protein redesign and can provide a sequence design capability for de novo backbones produced by structure-generation methods. Ideally, inverse folding can provide diverse sequence alternatives, fixed residues or motifs, soft biochemical preferences at selected positions, and candidates that remain experimentally useful. We developed Inverse FoldDir, a controllable inverse-folding method that performs iterative denoising on the amino acid probability simplex. Given a backbone structure, the model updates all positions jointly through a learned Dirichlet flow, supporting full sequence generation, fixed-residue inpainting, and user-defined soft residue priors. On the held-out CATH 4.2 test set, Inverse FoldDir achieved a mean TM-score of 84.5 (on a 0-100 scale) and a mean C RMSD of 1.76[A], compared with 83.3 and 1.86[A], respectively, for ESM-IF1, the strongest evaluated baseline on both metrics. Denoising trajectory analyses showed that positions commit at different rates and that some residues change identity late in generation, illustrating whole-sequence refinement rather than one-shot prediction or irreversible sequential decoding. We experimentally tested Inverse FoldDir in an anti-GFP nanobody redesign task, where two of 35 redesigned sequences retained reproducible sfGFP-binding signal across independent assay runs with approximately 43% sequence divergence from the native nanobody. Inverse FoldDir is a structure-conditioned protein redesign method that combines structural recovery, user control, experimental validation, and a natural route toward future property-guided sampling.

bioinformatics↗

bioRxiv2026

Machine learning guided cell-free expression maps the biochemical landscape of carbonic anhydrase

Carbonic anhydrases are among the fastest known biocatalysts, reversibly facilitating the hydration of CO2 to HCO3- at rates up to 107 s-1, which warrants their investigation for industrial carbon capture technologies. However, engineering carbonic anhydrases to maintain stability under harsh industrial process conditions remains a key challenge, and sequence-to-function datasets compatible with machine learning to inform forward engineering are lacking. Here, we developed a high-throughput platform that couples cell-free gene expression with a gaseous CO2 colorimetric assay to map the fitness landscapes of carbonic anhydrases. From 96 diverse natural homologs, we identified a robust variant from the Aquificota phylum and conducted an exhaustive mutational scan and functional assessment of this enzyme at 70{degrees}C and 90{degrees}C, covering >99% of all single-amino acid substitutions (totaling 4,365 mutations assayed in 39,285 reactions). This biochemical landscape was used to benchmark 22 zero-shot protein fitness models and identify critical mutations that improved enzyme stability at 90{degrees}C by more than three-fold. We then used both zero-shot protein language models and supervised learning to filter 419 model-generated variants from a ProteinMPNN library of 100,000 sequences, leading to a best-in-class enzyme that retained activity after incubation at 95{degrees}C. This work demonstrates that integrating cell-free enzyme engineering with machine learning enables opportunities for high-throughput experimental measurements to benchmark and improve protein language models, accelerate design loops, and expand functional exploration within protein families where experimental information is limited.

synthetic biology↗

bioRxiv2026

Topological reprogramming transforms an integral membrane oligosaccharyltransferase into a water-soluble glycosylation catalyst

Glycosyltransferases (GTs) catalyze the formation of new glycosidic bonds and thus are vital for synthesizing natures vast repertoire of glycans and glycoconjugates and for engineering glycan-related medicines and materials. However, obtaining detailed structural and functional insights for the >750,000 known GTs is limited by difficulties associated with their efficient recombinant expression. Members of the GT-C fold, in particular, pose the most significant expression challenges due to the integration and folding requirements of their multiple membrane-spanning regions. Here, we address this challenge by engineering water-soluble variants of an archetypal GT-C fold enzyme, namely the oligosaccharyltransferase PglB from Campylobacter jejuni (CjPglB), which possesses 13 hydrophobic transmembrane helices. To render CjPglB water-soluble, we leveraged two advanced protein engineering methods: one that is universal called SIMPLEx (solubilization of IMPs with high levels of expression) and the other that is custom tailored called WRAPs (water-soluble RFdiffused amphipathic proteins). Each approach was able to transform CjPglB into a water-soluble enzyme that could be readily expressed in the cytoplasm of Escherichia coli cells at yields in the 3-6 mg/L range. Importantly, solubilization was achieved without the need for detergents and with retention of catalytic function. Collectively, our findings demonstrate that both SIMPLEx and WRAPs are promising platforms for advancing the molecular characterization of even the most structurally complex GTs, while also enabling broader GT-mediated glycosylation capabilities within synthetic glycobiology applications.

synthetic biology↗

bioRxiv2025

Long-read proteogenomic atlas of human neuronal differentiation reveals isoform diversity informing neurodevelopmental risk mechanisms

RNA splicing shapes neuronal identity and disease risk, yet current maps lack the developmental resolution and depth to resolve this complexity. Here, we integrate deep long-read RNA sequencing and proteomics in iPSC-derived cortical neurons to generate a high-resolution proteogenomic atlas of human neuron development. We identify 182,371 mRNA isoforms (over half previously unknown) and provide direct peptide evidence for the translation of hundreds of novel protein-coding sequences. Population genetics demonstrates that variants affecting novel exons and splice sites are under negative selection, underscoring the potential significance of these isoforms. During neuronal maturation, we observe that ASD risk genes undergo dynamic isoform switching, including microexon inclusion and intron retention, that remodel key protein domains and regulatory regions. Furthermore, we uncover widespread, long-range coordination between splicing and polyadenylation. Finally, our atlas enables variant reinterpretation in ASD, highlighting the value of an isoform-centric view for interpreting pathogenic variation in neurodevelopment.

bioinformatics↗

bioRxiv2025

Expression screening and functional verification of recombinant hirudin from novel chassis cell Chlamydomonas reinhardtii

Hirudin is a potent anticoagulant peptide whose clinical application is limited by scarce natural supplies and the suboptimal activity of recombinant versions from conventional microbial hosts lacking key post-translational modifications. Here, for the first time, we establish the "Generally Regarded as Safe" (GRAS) microalga, Chlamydomonas reinhardtii, as a novel biological chassis for producing fully functional hirudin. Using high-density heterotrophic fermentation, we generated a bioactive lyophilized algal powder suitable for oral delivery. Crucially, the algal-derived hirudin underwent proper tyrosine sulfation--a key modification absent in prokaryotic hosts--conferring exceptionally high thrombin-inhibitory activity (up to 20,000 ATU/mg). When orally administered to a murine thrombosis model, this hirudin-loaded alga demonstrated potent antithrombotic efficacy. It also exhibited a superior safety profile, showing no signs of the thrombocytopenia or bleeding associated with traditional anticoagulants. This study establishes a green, scalable biomanufacturing and oral delivery platform for therapeutics, highlighting transformative potential at the nexus of agricultural bioengineering, functional foods, and biomedicine.

synthetic biology↗

bioRxiv2025

ARP2/3 complex mediates the neuropathology of PTEN-deficient human neural cells downstream of mTORC1 and mTORC2 hyperactivation

Mutations in the phosphatase and tensin homolog (PTEN) gene are linked to severe neurodevelopmental disorders. Loss of PTEN causes hyperactivation of both mechanistic target of rapamycin (mTOR) complexes, mTORC1 and mTORC2. Recent studies have shown that this dual hyperactivation is required for the neuropathology observed in PTEN-deficient human stem cell-derived neural cells. However, the molecular effectors that integrate these synergistic signals remain unknown. Here, we identify the actin-regulating ARP2/3 complex as a critical point of convergence downstream of mTORC1 and mTORC2. We show that concurrent hyperactivation of both complexes drives increased filamentous actin and elevated levels of the ARP2/3 complex subunits in PTEN-deficient human neural precursors and neurons. Pharmacological or genetic inhibition of ARP2/3 is sufficient to rescue multiple disease-relevant phenotypes, including neural precursor hyperproliferation, neuronal hypertrophy, and electrical hyperactivity, without affecting the upstream mTORC1 or mTORC2 hyperactivation. Together, these findings reveal the PTEN-mTOR-ARP2/3 signaling axis as a core mechanism of neuropathology and highlight ARP2/3 inhibition as a potential therapeutic strategy for PTEN-related neurodevelopmental disorders.

neuroscience↗

bioRxiv2025

From Wiring to Firing: Collapse of embryonic identities and emergence of functional diversity during motor neuron maturation

Neurons born in the embryo undergo a protracted process of maturation during which time they project axons to their specific targets, integrate into circuits, refine synapses, and acquire unique electrophysiological properties. The molecular strategies that individual neuron types deploy to complete this complex process remain poorly understood. In this work, we used single nucleus multiome sequencing (RNA-seq and ATAC-seq) to track the transition from specification to functional maturation in mouse skeletal motor neurons (SMNs). Our data show that individual SMNs undergo significant transcriptional changes as they mature, but more strikingly, we find that diversity within SMNs fluctuates dramatically as the functional needs of these cells change over time. At embryonic day E15.5, when motor axons are innervating their specific muscle targets, SMNs can be subdivided into dozens of transcriptional subclusters. These embryonic subclusters represent known motor columns and pools, which utilize column- and pool-specific genes to innervate unique muscle targets. About a week later, at postnatal day 3 (P3) many column- and pool-specific genes are downregulated or become broadly expressed and SMNs coalesce on the molecular level into a more homogenous state. These neurons then undergo a second round of diversification during the first two weeks of postnatal life (P3-P13), acquiring gene expression patterns that divide them into the functionally distinct alpha, gamma, and type3 subtypes found in adults. The fluctuations in SMN diversity go hand-in-hand with changes in accessible chromatin regions and transcription factor (TF) expression. Differential ATAC-seq peaks that define embryonic diversity are lost over time while new peaks that control expression in adult subtypes are gained. TFs that are known to regulate embryonic diversity are also downregulated over time, as a separate set of TFs that likely regulate adult subtype identities are upregulated. Our work uncovers a novel maturation trajectory for postmitotic neurons where extensive spatial diversity is first acquired in the embryo to ensure proper circuit wiring; this diversity is then lost as maturing neurons re-diversify into functional identities required for proper circuit firing in postnatal life. Therefore, all aspects of a neurons identity - its morphology, circuitry, and electrophysiologically - may not be fully described by its gene expression program at adulthood, but instead is a culmination of transcriptional events that occur throughout its specification and maturation trajectory as the functional needs of the cells evolve.

neuroscience↗

bioRxiv2024

{-}Numb provides a fail-safe mechanism for intestinal stem cell self-renewal in adult Drosophila midgut

Stem cell self-renewal often relies on asymmetric fate determination governed by niche signals and/or cell-intrinsic factors but how these regulatory mechanisms cooperate to promote asymmetric fate decision remains poorly understood. In adult Drosophila midgut, asymmetric Notch (N) signaling inhibits intestinal stem cell (ISC) self-renewal by promoting ISC differentiation into enteroblast (EB). We have previously shown that epithelium-derived BMP promotes ISC self-renewal by antagonizing N pathway activity (Tian and Jiang, 2014). Here we show that loss of BMP signaling results in ectopic N pathway activity even when the N ligand Delta (Dl) is depleted, and that the N inhibitor Numb acts in parallel with BMP signaling to ensure a robust ISC self-renewal program. Although Numb is asymmetrically segregated in about 80% of dividing ISCs, its activity is largely dispensable for ISC fate determination under normal homeostasis. However, Numb becomes crucial for ISC self-renewal when BMP signaling is compromised. Whereas neither Mad RNAi nor its hypomorphic mutation led to ISC loss, inactivation of Numb in these backgrounds resulted in stem cell loss due to precocious ISC-to-EB differentiation. Furthermore, we find that numb mutations resulted in stem cell loss during midgut regeneration in response to epithelial damage that causes fluctuation in BMP pathway activity, suggesting that the asymmetrical segregation of Numb into the future ISC may provide a fail-save mechanism for ISC self-renewal by offsetting BMP pathway fluctuation, which is important for ISC maintenance in regenerative guts.

developmental biology↗

bioRxiv2024

Topoisomerase I is an Evolutionarily Conserved Key Regulator for Satellite DNA Transcription

Repetitive satellite DNAs, divergent in nucleic-acid sequence and size across eukaryotes, provide a physical site for centromere assembly to orchestrate chromosome segregation during the cell cycle. These non-coding DNAs are transcribed by RNA polymerase (RNAP) II and the transcription has been shown to play a role in chromosome segregation, but a little is known about the regulation of centromeric transcription, especially in higher organisms with tandemly-repeated-DNA-sequence centromeres. Using RNA interference knockdown, chemical inhibition and AID/IAA degradation, we show that Topoisomerase I (TopI), not TopII, promotes the transcription of -satellite DNAs, the main type of satellite on centromeres in human cells. Mechanistically, TopI localizes to centromeres, binds RNAP II and facilitates RNAP II elongation on centromeres. Interestingly, in response to DNA double-stranded breaks (DSBs) induced by chemotherapy drugs or CRSPR/Cas9, -satellite transcription is dramatically stimulated in a DNA damage checkpoint-independent but TopI-dependent manner. These DSB-induced -satellite RNAs were predominantly derived from the -satellite high-order repeats of human centromeres and forms into strong speckles in the nucleus. Remarkably, TopI-dependent satellite transcription also exists in mouse 3T3 and Drosophila S2 cells and in Drosophila larval imaginal wing discs and tumor tissues. Altogether, our findings herein reveal an evolutionally conserved mechanism with TopI as a key player for the regulation of satellite transcription at both cellular and animal levels.

cell biology↗

bioRxiv2024

To be or not to be - Decoding the Trabecular Meshwork Cell Identity

The trabecular meshwork within the conventional outflow apparatus is critical in maintaining intraocular pressure homeostasis. In vitro studies employing primary cell cultures of the human trabecular meshwork (hTM) have conventionally served as surrogates for investigating the pathobiology of TM dysfunction. Despite its abundant use, translation of outcomes from in vitro studies to ex vivo and/or in vivo studies remains a challenge. Given the cell heterogeneity, performing single-cell RNA sequencing comparing primary hTM cell cultures to hTM tissue may provide important insights on cellular identity and translatability, as such an approach has not been reported before. In this study, we assembled a total of 14 primary hTM in vitro samples across passages 1-4, including 4 samples from individuals diagnosed with glaucoma. This dataset offers a comprehensive transcriptomic resource of primary hTM in vitro scRNA-seq data to study global changes in gene expression in comparison to cells in tissue in situ. We have performed extensive preprocessing and quality control, allowing the research community to access and utilize this public resource.

genomics↗

bioRxiv2022

SHINE: Protein Language Model based Pathogenicity Prediction for Inframe Insertion and Deletion Variants

Inframe insertion and deletion variants (indels) alter protein sequence and length. Accurate pathogenicity predictions are important in genetic studies of human diseases. Indel Interpretation is challenging due to limitations in the available number of known pathogenic variants for training. Existing methods largely use manually encoded features including conservation, protein structure and function, and allele frequency. Recent advances in deep learning modeling of protein sequences and structures provide an opportunity to improve the representation of salient features based on large numbers of protein sequences. We developed a new pathogenicity predictor for SHort Inframe iNsertion and dEletion (SHINE). SHINE uses pre-trained protein language models to construct a latent representation of an indel and its protein context from protein sequences and multiple protein sequence alignments, and feeds the latent representation into supervised machine learning models for pathogenicity prediction. We curated training data from ClinVar and gnomAD, and created two test datasets from different sources. SHINE achieved better prediction performance than existing methods for both deletion and insertion variants in these two test datasets. Our work suggests that unsupervised protein language models can provide valuable information about proteins, and new methods based on these models can improve variant interpretation in genetic analyses.

bioinformatics↗

bioRxiv2021

Re-entry into mitosis and regeneration of intestinal stem cells through enteroblast dedifferentiation in Drosophila midguts

Many adult tissues and organs including the intestine rely on resident stem cells to maintain homeostasis. In mammalian intestines, upon ablation of resident stem cells, the progenies of intestinal stem cells (ISCs) such as secretory cells and tuft cells can dedifferentiate to generate ISCs to drive epithelial regeneration, but whether and how the ISC progenies dedifferentiate to generate ISCs under physiological conditions remains unknown. Here we show that infection of pathogenic bacteria induces enteroblasts (EBs) as one type of ISC progenies to re-enter the mitotic cycle in the Drosophila intestine. The re-entry into mitosis is dependent on epithermal growth factor receptor (EGFR)-Ras signaling and ectopic activation of EGFR-Ras signaling in EBs is sufficient to drive EBs cell-autonomously to re-enter into mitosis. In addition, we examined whether EBs gain ISC identity as a prerequisite to divide, but the immunostaining with stem cell marker Delta shows that these dividing EBs do not gain ISC identity. After employing lineage tracing experiments, we further demonstrate that EBs dedifferentiate to generate functional ISCs after symmetric divisions of EBs. Together, our study in Drosophila intestines uncovers a new role of EGFR-Ras signaling in regulating re-entry into mitosis and dedifferentiation during regeneration and reveals a novel mechanism by which ISC progenies undergo dedifferentiation through a mitotic division, which has important implication to mammalian tissue homeostasis and tumorigenesis.

cell biology↗

bioRxiv2018

Spatiotemporal dynamics of river viruses, bacteria and microeukaryotes

Freshwater is an essential resource of increasing value, as clean water sources diminish. Microorganisms in rivers, a major source of renewable freshwater, are significant due to their role in drinking water safety, signalling environmental contamination1, and driving global nutrient cycles2,3. However, a foundational understanding of microbial communities in rivers is lacking4, especially temporally and for viruses5-7. No studies to date have examined the composition of the free-floating river virome over time, and explanations of the underlying causes of spatial and temporal changes in riverine microbial composition, especially for viruses, remain unexplored. Here, we report relationships among riverine microbial communities and their environment across time, space, and superkingdoms (viruses, bacteria, and microeukaryotes), using metagenomics and marker-based microbiome analysis methods. We found that many superkingdom pairs were synchronous and had consistent shifts with sudden environmental change. However, synchrony strength, and relationships with environmental conditions, varied across space and superkingdoms. Variable relationships were observed with seasonal indicators and chemical conditions previously found to be predictive of bacterial community composition4,8-10, emphasizing the complexity of riverine ecosystems and raising questions around the generalisability of single-site and bacteria-only studies. In this first study of riverine viromes over time, DNA viral communities were stably distinct between sites, suggesting the similarity in riverine bacteria across significant geographic distances10-12 does not extend to viruses, and synchrony was surprisingly observed between DNA and RNA viromes. This work provides foundational data for riverine microbial dynamics in the context of environmental and chemical conditions and illustrates how a bacteria-only or single-site approach would lead to an incorrect description of microbial dynamics. We show how more holistic microbial community analysis, including viruses, is necessary to gain a more accurate and deeper understanding of microbial community dynamics.

microbiology↗