Biology subjects

Lin, G.

Publications and source records attributed to Lin, G..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

A Multiscale Framework for Uncovering Surfactant Mediated Viral Capsid Disruption

Disinfection remains a critical strategy for controlling the transmission of infectious diseases. However, small non-enveloped viruses exhibit exceptional resistance to many disinfectants, often requiring harsh protein-disrupting chemicals for effective inactivation, thereby limiting their applicability in personal care products due to associated side effects. Sodium dodecyl sulphate (SDS) is a widely used anionic surfactant known for its virucidal efficacy; however, the molecular details of its action against robust non-enveloped viruses remain poorly understood, limiting efforts to design safer and more targeted antiviral formulations. In this study, a multiscale simulation approach combining a novel atomic-resolution icosahedral "scaffold framework" and coarse-grained modelling was developed to elucidate the mechanism of SDS-driven disruption of MS2 bacteriophage capsid, a surrogate for non-enveloped viruses. Experimental analyses including dynamic light scattering and transmission electron microscopy revealed that SDS inactivates MS2 in a strongly pH-dependent manner, triggering capsid disassembly at acidic pH while leaving particles largely intact at neutral pH. Molecular dynamics simulations demonstrated that SDS micelles preferentially associate with hexameric pores and inter-dimer clefts under acidic conditions, where protonation of acidic residues weakens the electrostatic network of the capsid surface. Together, these findings provide a detailed molecular framework for SDS virucidal action and highlight the importance of environmental pH in modulating surfactant-virus interactions. These insights offer a foundation for designing next-generation antiviral surfactants with improved efficacy and biocompatibility.

biophysics↗

bioRxiv2025

PML1-Mediated Feedforward Loop Through PI3K and MAPK Axes Drives Endocrine Resistance

Treatment of estrogen receptor-positive (ER+) breast cancer is significantly hindered by endocrine resistance. We identified PML1 as a key therapeutic entity that can be targeted to overcome resistance. Endocrine-resistant breast cancer cells share three key characteristics: elevated PML1 protein levels, enhanced activity of PI3K, MAPK, or both signaling pathways, and reduced ER activity. We developed a PML1 gene signature that predicts poor prognosis and correlates strongly with PI3K, MAPK, and endocrine resistance gene signatures, as evident by cellular studies, scRNA-seq analysis, and spatial transcriptomics of endocrine therapy-treated tumors. This signature is present in endocrine-resistant breast cancer cells harboring the Y537S ER mutation. We consistently demonstrate high PML1 protein levels across cells resistant to various treatments, including 4-hydroxytamoxifen, fulvestrant, elacestrant, and CDK4/6 inhibitors. Furthermore, treatments with these therapeutic agents or knockdown of ESR1 mRNA also increase PML1 protein levels. Mechanistically, we show that ER inhibition through fulvestrant treatment activates PI3K and MAPK signaling, which enhance PML1 protein stability and synthesis. PML1 then drives a feedforward loop by stimulating the expression of cytokine and growth factor mRNAs, including CCL5 and HBEGF, further amplifying PI3K and MAPK signaling. Consequently, in endocrine-resistant cells, endocrine therapies, while inactivating ER, paradoxically reinforce this loop through increased PI3K/MAPK activation and PML1 protein accumulation, ultimately compromising therapeutic efficacy. Finally, we demonstrated that arsenic trioxide, an FDA-approved, PML-reducing drug, effectively disrupts this feedforward loop, offering a promising strategy for treating resistant metastatic breast cancer. STATEMENT OF SIGNIFICANCEEndocrine resistance remains a major obstacle in treating estrogen receptor-positive metastatic breast cancer. Our study identifies PML1 as a central mediator of this resistance, revealing how it maintains a self-reinforcing signaling network through PI3K and MAPK pathways by enhancing the production of cytokines and growth factors. The clinical significance of our findings is threefold: we establish PML1 as a biomarker for therapy resistance, demonstrate its mechanistic role in treatment failure, and show that FDA-approved arsenic trioxide can disrupt PML1-driven resistance. These insights provide a direct path to clinical translation, as combining arsenic trioxide with existing therapies could benefit patients with limited treatment options.

cancer biology↗

bioRxiv2025

Delayed forebrain excitatory and inhibitory neurogenesis inSTRADA-related megalencephaly via mTOR hyperactivity

Biallelic pathogenic variants in STRADA, an upstream regulator of the mechanistic target of rapamycin (mTOR) pathway, result in megalencephaly, drug-resistant epilepsy, and severe intellectual disability. This study explores how mTOR pathway hyperactivity alters cell fate specification in dorsal and ventral forebrain development using STRADA knock-out human stem cell derived brain organoids. In both dorsal and ventral forebrain STRADA knock-out organoids, neurogenesis is delayed, with a predilection for progenitor renewal and proliferation and an increase in outer radial glia. Ventrally, interneuron subtypes shift to an increase in neuropeptide-Y expressing cells. Inhibition of the mTOR pathway with rapamycin results in rescue for most phenotypes. When mTOR pathway variants are present in all cells of the developing brain, overproduction of interneurons and altered interneuron cell fate may underlie mechanisms of megalencephaly, epilepsy, and cognitive impairment. Our findings suggest mTOR inhibition during fetal brain development as a potential therapeutic strategy in STRADA deficiency.

neuroscience↗

bioRxiv2025

Quantitative phosphoproteomic analysis of testes from Iqcn-deficient mice highlights the significance of calmodulin signaling in spermiogenesis

Calmodulin (CaM) plays a crucial role in sperm function. Studies have reported that proteins containing IQ motif interact with CaM, subsequently engaging with downstream target proteins known as calmodulin-binding proteins (CaMBPs). It is reported that the loss of interaction between IQCN and CaM is mainly manifested as decreased motility, leading to fertilization failure and male infertility. However, no relevant reports have been published detailing which CaMBPs exist and the mechanisms by which they are regulated. In this study, we conducted a comprehensive quantitative proteomic and phosphoproteomic analysis of mouse testes from wild-type (WT) and Iqcn knockout (Iqcn-/-) mice. The results indicated that Iqcn deficiency substantially rewires the downstream phosphorylation signaling pathway, while not causing equivalent changes in protein levels. Among the total 577 differentially regulated phosphorylated sites in our results, most of them (494/577) belong to calmodulin-binding proteins (CaMBPs). Gene ontology analysis of these differentially phosphorylated CaMBPs showed enrichment in male gamete generation, actin cytoskeleton organization and microtubule cytoskeleton organization process, demonstrating IQCN regulates sperm function by interacting with CaM, which in turn affects the phosphorylation level of CaMBPs. Further kinase substrate network analysis revealed that most kinases with substrates phosphorylation sites up-regulated were tyrosine kinases, and the inhibition assay showed that FGFR4 and SYK tyrosine kinases are important for sperm motility and progressive motility. In summary, this study reveals the interaction between IQ motif-containing protein IQCN and CaM, which regulates the phosphorylation of downstream CaMBPs and is involved in the related processes of spermiogenesis and sperm function.

developmental biology↗

bioRxiv2025

Experimental evidence of stress-induced critical state in schooling fish

How do animal groups dynamically adjust their collective behavior in response to environmental changes is an open and challenging question. Here, we investigate the mechanisms that allow fish schools to tune their collective state under stress, testing the hypothesis that these systems operate near criticality, a state maximizing sensitivity, responsiveness, and adaptability. We combine experiments and data-driven computational modeling to study how group size and stress influence the collective behavior of rummy-nose tetras (Hemigrammus rhodostomus). We quantify the collective state of fish schools using polarization, milling, and cohesion metrics and use a burst-and-coast model to infer the social interaction parameters that drive these behaviors. Our results indicate that group size modulates stress levels, with smaller groups experiencing higher baseline stress, likely due to a reduced social buffering effect. Under stress, fish adjust the strength of their social interactions in a way that leads the group into a critical state, thus enhancing its sensitivity to perturbations and facilitating rapid adaptation. However, large groups require an external stressor to enter the critical regime, whereas small groups are already near this state. Unlike previous studies suggesting that fish adjust their interaction network structure under risk, our results suggest that the intensity of social interactions, rather than network structure, governs collective state transitions. This simpler mechanism reduces cognitive demands while enabling dynamic adaptation. By revealing how stress and group size drive self-organization toward criticality, our study provides fundamental insights into the adaptability of collective biological systems and the emergent properties in animal groups.

animal behavior and cognition↗

bioRxiv2025

Single-cell RNA-seq reveals altered plasma cell subsets and decreased cytotoxicity of NK cells in patients with Kawasaki diseas

AimThe pathogenesis and therapeutic strategies of Kawasaki disease (KD) are worth further exploring. Using single-cell RNA sequencing (scRNA-seq), our study aimed to explore the landscape of peripheral blood mononuclear cells (PBMCs) in patients with KD. MethodsWe analyzed the scRNA-seq data of three patients with KD and three healthy controls from the GSE168732 dataset. Additionally, we explored the immune profiles and immune cell subtypes of patients with KD. ResultsSignificantly increased B cells and decreased NK cells were observed in the KD group compared with that in the control group. Furthermore, six B cell subsets were identified in the PBMCs of patients with KD. Particularly, plasma cells (CD9+ and S100A9+ B cell clusters) distinctly increased in the KD group. CD9+ B cell cluster was characterized by vascular endothelial growth factor (VEGF) signaling-associated marker genes and DEGs. Meanwhile the S100A9+ B cell cluster was characterized by platelet aggregation marker genes. As for NK cells, CD16+CD56dim NK cells were enriched in the KD group. Cytotoxicity-related activating receptors (KLRD1,KLRC3) and cytotoxicity-associated genes (PRF1, NKG7, GZMA, GZMH, GNLY) were downregulated in the KD group. ConclusionCD9+ and S100A9+ plasma cells may contribute to CALs in KD by upregulating VEGF and activating platelet. In addition, decreased cytotoxicity of NK cells mediated by KLRD1/KLRC3 receptor may play a vital role in the development of KD. Our results suggested that plasma cells and NK cells could be promising targets for the treatment of KD.

immunology↗

bioRxiv2025

ESMAdam: a plug-and-play all-purpose protein ensemble generator

Proteins often adopt multiple ensemble conformations to perform essential functions such as catalysis, transport, and signal transduction. Traditional physics-based methods for generating these conformations, including molecular dynamics and Monte Carlo simulations, are computationally expensive and time-consuming, limiting their practicality for high-throughput applications like screening. Recent advances in machine learning, particularly deep generative models, offer a promising alternative for protein conformation ensemble generation. However, these models are often task-specific or rely on strong assumptions to generalize. Here, we introduce ESMAdam, a versatile and efficient framework for protein conformation ensemble generation. Using the ESMFold protein language model ESMFold and ADAM stochastic optimization in the continuous protein embedding space, ESMAdam addresses a wide range of ensemble generation tasks. In this work, we demonstrate several basic applications of ESMAdam, including conditional ensemble generation and CG-to-all-atom backmapping. In addition, we showcase advanced applications, such as screening alternative binding modes of protein multimers and reconstructing 3D structures from cryo-EM images. Compared to traditional physics-based methods, ESMAdam significantly reduces computational time. Unlike deep-generative-model-based approaches, it requires no retraining and easily adapts to diverse ensemble restraint conditions, making it exceptionally suited for various structure prediction and screening tasks. This plug-and-play framework represents a step toward efficient and flexible protein ensemble generation for applications in structural biology and drug discovery.

biochemistry↗

bioRxiv2024

Enzyme-independent functions of HDAC3 in the adult heart

The cardioprotective effects of histone deacetylase (HDAC) inhibitors (HDIs) are at odds with the deleterious effects of HDAC depletion. Here, we use HDAC3 as a prototype HDAC to address this contradiction. We show that adult-onset cardiac-specific depletion of HDAC3 in mice causes cardiac hypertrophy and contractile dysfunction on a high-fat diet (HFD), excluding developmental disruption as a major reason for the contradiction. Genetically abolishing HDAC3 enzymatic activity without affecting its protein level does not cause cardiac dysfunction on HFD. HDAC3 depletion causes robust downregulation of lipid oxidation/bioenergetic genes and upregulation of antioxidant/anti-apoptotic genes. In contrast, HDAC3 enzyme activity abolishment causes much milder changes in far fewer genes. The abnormal gene expression is cardiomyocyte-autonomous and can be rescued by an enzyme-dead HDAC3 mutant but not by an HDAC3 mutant ({Delta}33-70) that lacks interaction with the nuclear-envelope protein lamina-associated polypeptide 2{beta} (LAP2{beta}). Tethering LAP2{beta} to the HDAC3 {Delta}33-70 mutant restored its ability to rescue gene expression. Finally, HDAC3 depletion, not loss of HDAC3 enzymatic activity, exacerbates cardiac contractile functions upon aortic constriction. These results suggest that the cardiac function of HDAC3 in adults is not attributable to its enzyme activity, which has implications for understanding the cardioprotective effects of HDIs.

physiology↗

bioRxiv2024

Highly dynamic supernumerary mini-chromosomes in a Magnaporthe oryzae strain

Magnaporthe oryzae (syn. Pyricularia oryzae), the causative agent of devastating crop diseases, exhibits remarkable genomic plasticity that contributes to its adaptability and pathogenicity. Individual M. oryzae strains may contain supernumerary mini-chromosomes, which are dispensable and highly repetitive. Here, we explored the stability of two mini-chromosomes of a Lolium strain isolated in the US, TF05-1, in which one mini-chromosome contains sequences nearly identical to the mini-chromosome of the wheat isolate B71 from Bolivia. The discordance of their phylogenetic relationships based on genomic polymorphisms in core chromosomes and polymorphisms in mini-chromosomes indicated horizontal transfer of the mini-chromosome. Karyotyping analysis and genome sequencing analysis found variation in numbers and sizes of mini-chromosomes among asexual monoconidial progeny of TF05-1. Rearrangement within mini-chromosomes occurred frequently in the TF05-1 progeny. We characterized an intrachromosomal rearrangement presumably mediated by a palindrome repeat. The rearrangement resulted in a 300-kb deletion and a 900-kb duplication. The susceptibility to structural variation in mini-chromosomes may be associated with repetitive features and the high activity of transposable elements in mini-chromosomes, in which many intact retrotransposons were recently inserted, largely unmethylated, and likely have yet to be silenced by fungal genome defense mechanisms such as repeat-induced point mutation.

genomics↗

bioRxiv2024

Pre-trained protein language model for codon optimization

Messenger ribonucleic acid (mRNA) vaccines represent a major advancement in synthetic biology, yet their efficacy remains limited by how efficiently the encoded protein is translated within the host. Since multiple codons can code for the same amino acid, the search space of possible coding sequences (CDS) within mRNA grows exponentially with protein length, making the problem highly underdetermined. Finding CDSs that yield efficient translation hinges on codon optimization--the process of choosing among synonymous codons, while encoding the same protein but differ in their effects on translation speed, tRNA availability, and mRNA secondary structure. Recent deep learning approaches have framed codon optimization as a sequence learning problem, where the goal is to model context-dependent codon usage patterns across the amino acid in protein sequence. However, these methods rely on large sequence models that learn amino-acid embeddings from scratch, leading to computationally intensive training. We propose ppLM-CO, a lightweight codon optimization framework that integrates pretrained protein language models (ppLMs) to directly provide contextual amino-acid embeddings, thereby eliminating the need for embedding learning. This design reduces trainable parameters by over 92% - 99% compared with prior deep models while maintaining complete biological fidelity. In-silico evaluations across three species and two vaccine targets--SARS-CoV-2 spike and Varicella-Zoster Virus (VZV) gE viral proteins--demonstrate that ppLM-CO consistently achieves higher expression and competitive stability, establishing a scalable and biologically consistent approach for codon optimization.

bioinformatics↗

bioRxiv2024

Molecular basis of interchain disulfide-bond formation in BMP-9 and BMP-10

BMP-9 and BMP-10 are TGF-{beta} family signaling ligands naturally secreted into blood. They act on endothelial cells and are required for proper development and maintenance of the vasculature. In hereditary hemorrhagic telangiectasia, regulation is disrupted due to mutations in the BMP-9/10 pathway, namely in the type I receptor ALK1 or the co-receptor endoglin. It has been demonstrated that BMP-9/10 heterodimers are the most abundant signaling species in the blood, but it is unclear how they form. Unlike other ligands of the TGF-{beta} family, BMP-9 and -10 are secreted as a mixture of monomers and disulfide-linked dimers. Here, we show that the monomers are secreted in a cysteinylated form that crystallizes as a noncovalent dimer. Despite this, monomers do not self-associate at micromolar or lower concentrations and have reduced signaling potency compared to dimers. We further show using protein crystallography that the interchain disulfide of the BMP-9 homodimer adopts a highly strained syn-periplanar conformation. Hence, geometric strain across the interchain disulfide is responsible for the reduced propensity to dimerize, not the cysteinylation. Additionally, we show that the dimerization propensity of BMP-9 is lower than BMP-10 and these propensities can be reversed by swapping residues near the interchain disulfide that form attractive interactions with the opposing monomer. Finally, we discuss the implications of these observations on BMP-9/10 heterodimer formation.

molecular biology↗

bioRxiv2024

EGDiff: An Experiment-Guided Diffusion model for protein conformational ensemble generation

Understanding protein conformation is key to understanding their function. Importantly, most proteins adopt multiple conformations with non-trivial ensemble distributions that change depending on their environment to perform functions like catalysis, signaling, and transport. Recently, machine learning techniques, especially deep generative models, have been employed to develop protein conformation generators. These models, known as unified protein ensemble samplers, are trained on the PDB dataset and can generate diverse protein conformation ensembles given a protein sequence. However, their reliance solely on structural data from the PDB, which primarily captures folded protein states, restricts the diversity of the generated ensembles and can result in physically unrealistic conformations. In this paper, we overcome these challenges by introducing ExEnDiff, an experiment-guided diffusion model for protein conformation generation. ExEnDiff integrates experimental measurements as a physical prior, enabling the generation of protein conformations with desired properties. Our experiments on a variety of fast-folding and intrinsically disordered proteins demonstrate that ExEnDiff significantly advances the capabilities of current unified protein ensemble samplers. With little computational cost, ExEnDiff can capture important proteins configuration properties and the underlying Boltzmann distribution, paving the way for a next-generation molecular dynamics engine. We further demonstrate the effectiveness of ExEnDiff to capture conformational changes in the presence of mutations and as an efficient tool for determining a reasonable CV space for protein ensembles. With these results, ExEnDiff is well-poised to push the study of protein ensembles into a data-rich regime currently available to few problems in biology.

biophysics↗

bioRxiv2024

TRPC3 suppression ameliorates synaptic dysfunctions and memory deficits in Alzheimer's disease

Transient receptor potential canonical (TRPC) channels are widely expressed in the brain; however, their precise roles in neurodegeneration, such as Alzheimers disease (AD) remain elusive. Bioinformatic analysis of the published single-cell RNA-seq data collected from AD patient cohorts indicates that the Trpc3 gene is uniquely upregulated in excitatory neurons. TRPC3 expression is also upregulated in post-mortem AD brains, and in both acute and chronic mouse models of AD. Functional screening of TRPC3 antagonists resulted in a lead inhibitor JW-65, which completely rescued A{beta}-induced neurotoxicity, impaired synaptic plasticity (e.g., LTP), and learning memory in acute and chronic experimental AD models. In cultured rat hippocampal neurons, we found that treatment with soluble {beta}-amyloid oligomers (A{beta}Os) induces rapid and sustained upregulation of the TRPC3 expression selectively in excitatory neurons. This aberrantly upregulated TRPC3 contributes to A{beta}Os-induced Ca2+ overload through the calcium entry and store-release mechanisms. The neuroprotective action of JW-65 is primarily mediated via restoring A{beta}Os-impaired Ca2+/calmodulin-mediated signaling pathways, including calmodulin kinases CaMKII/IV and calcineurin (CaN). The synaptic protective mechanism via TRPC3 inhibition was further supported by hippocampal RNA-seq data from the symptomatic 5xFAD mice after chronic treatment with JW-65. Overall, these findings not only validate TRPC3 as a novel therapeutic target for treating synaptic dysfunction of AD but most importantly, disclose a distinct role of upregulated TRPC3 in AD pathogenesis in mediating Ca2+ dyshomeostasis.

neuroscience↗

bioRxiv2024

Positive feedback regulation between RpoS and BosR in the Lyme disease pathogen

In Borrelia burgdorferi, the Lyme disease pathogen, differential gene expression is primarily controlled by the alternative sigma factor RpoS ({sigma}S). Understanding how RpoS levels are regulated is crucial for elucidating how B. burgdorferi is maintained throughout its enzootic cycle. Our recent studies have shown that a homolog of Fur/PerR repressor/activator, BosR, functions as an RNA-binding protein that controls the rpoS mRNA stability. However, the mechanisms of regulation of BosR, particularly in response to host signals and environmental cues, remain largely unclear. In this study, we revealed a positive feedback loop between RpoS and BosR, where RpoS post-transcriptionally regulates BosR levels. Specifically, mutation or deletion of rpoS significantly reduced BosR levels, while artificial induction of rpoS resulted in a dose-dependent increase in BosR levels. Notably, RpoS does not affect bosR mRNA levels but instead modulates the turnover rate of the BosR protein. Furthermore, we demonstrated that environmental cues do not directly influence bosR expression but instead induce rpoS transcription and RpoS production, thereby enhancing BosR protein levels. This discovery adds a new layer of complexity to the RpoN-RpoS pathway and suggests the need to re-evaluate the factors and signals previously believed to regulate RpoS levels through BosR. IMPORTANCELyme disease is the most prevalent arthropod-borne infection in the United States. The etiological agent, Borreliella (or Borrelia) burgdorferi, is maintained in nature through an enzootic cycle involving a tick vector and a mammalian host. RpoS, the master regulator of differential gene expression, plays a crucial role in tick transmission and mammalian infection of B. burgdorferi. This study reveals a positive feedback loop between RpoS and a Fur/PerR homolog. Elucidating this regulatory network is essential for identifying potential therapeutic targets to disrupt B. burgdorferis enzootic cycle. The findings also have broader implications for understanding the regulation of RpoS and Fur/PerR family in other bacteria.

microbiology↗

bioRxiv2024

Structural and Biophysical Dynamics of Fungal Plasma Membrane Proteins and Implications for Echinocandin Action in Candida glabrata

Fungal plasma membrane proteins represent key therapeutic targets for antifungal agents, yet their structure and spatial distribution in the native context remain poorly characterized. Herein, we employ an integrative multimodal approach to elucidate the structural and functional organization of plasma membrane protein complexes in Candida glabrata, focusing on prominent and essential membrane proteins, the polysaccharide synthase {beta}-(1,3)-glucan synthase (GS) and the proton pump Pma1. Cryo-electron tomography (cryo-ET) and live cell imaging reveal that GS and Pma1 are heterogeneously distributed into distinct plasma membrane microdomains. Treatment with caspofungin, an echinocandin antifungal that targets GS, alters the plasma membrane and disrupts the native distribution of GS and Pma1. Based on these findings, we propose a model for echinocandin action that considers how drug interactions with the plasma membrane environment lead to inhibition of GS. Our work underscores the importance of interrogating the structural and dynamic characteristics of fungal plasma membrane proteins in situ to understand function and facilitate precisely targeted development of novel antifungal therapies.

cell biology↗

bioRxiv2024

Comparative genomics of three non-hematophagous leeches (Whitmania spp.): focusing on antithrombotic genes

Leeches are well known for their blood-feeding habits and are widely used for medicinal purposes as they secrete various antithrombotic substances. However, some leeches such as Whitmania spp. exhibit non-hematophagous feeding habits and their significance for medicinal use is debated. In this study, we provide chromosome-level genomes of two non-hematophagous leeches Whitmania acranulata and Whitmania laevis, and combined with our previous results of Whitmania pigra, we systematically analyzed the similarities and differences on the genomes and especially their antithrombotic genes among the three non-hematophagous Whitmania leeches. For W. acranulata, W. laevis, and W. pigra, the genome size (181.72 Mb, 173.87 Mb, and 173.56), the percentage of repeat sites (29.55%, 28.28%, and 27.02%), and the number of protein-coding genes (27,068, 23,805, and 24,156) were close to each other, respectively. In contrast, both the total number of the antithrombotic genes (100, 63, and 79), and the detailed constitutes of different antithrombotic gene families were obviously different among the three leeches. There were also massive genetic variations among the members within each antithrombotic gene/protein family. RNA-Seq-based gene expression estimation showed that the expression profiles of the antithrombotic gene families were apparently different among the three leeches. This is the most comprehensive comparison of the genomes and antithrombic biomacromolecules for the Whitmania leeches to date. Our results will greatly facilitate the evolutionary research and application of leech derivatives for medical and pharmaceutical purposes of thrombosis.

genomics↗

bioRxiv2024

Geometry theory of distribution shapes for autoregulatory gene circuits

In this study, we provide a complete mathematical characterization of the phase diagram of distribution shapes in an extension of the two-state telegraph model of stochastic gene expression in the presence of positive or negative autoregulation. Using the techniques of second-order difference equations and nonlinear discrete dynamical systems, we prove that the feedback loop can only produce three shapes of steady-state protein distributions (decaying, bell-shaped, and bimodal), corresponding to three distinct parameter regions in the phase diagram. The boundaries of the three regions are characterized by two continuous curves, which can be constructed geometrically by the contour lines of a series of ratio operators. Based on the geometric structure of the phase diagram, we then provide some simple and verifiable sufficient and/or necessary conditions for the existence of the bimodal parameter region, as well as the conditions for the steady-state distribution to be decaying, bell-shaped, or bimodal. Finally, we also investigate how the phase diagram is affected by the strength of positive or negative feedback.

biophysics↗

bioRxiv2024

msCNVS: medium throughput single cell copy number variation sequencing with barcoded library construction free of preamplification toward clinical implementation

Single cell copy number variation sequencing (scCNV-seq) is valuable for genomic analysis of a variety of health and disease systems, yet the available methods either depend on either preamplification of the whole genome of each cell, special devices or untracable, which hinder scCNV-seq practice in clinics. Here we provide scalable multiplex scCNV-seq (msCNVS) that allows direct medium-throughput library construction for single cells, which are barcoded individually with Tn5 transposome in a microplate and immediately pooled for downstream processes, elevating the efficiency by orders of magnitude. An algorithm is developed on the distribution of segmented normalized read count density to identify the major peaks associating with integer copy numbers, further improving the accuracy for objective CNV calling. Here msCNVS faithfully distinguishes the unique CNV patterns of 5 cell lines. The individual msCNVS profiles of 70 individual K562 cells highly correlate with the profile of K562 bulk cells (R=0.90-0.98), and the triplicates of HeLa3 bulk cells correlated nearly perfect (R=0.99). The msCNVS CNV profiles of primary cell cultures of amniotic fluid are confirmed by G-banding karyotype analysis and chromosomal microarray analysis. Additionally, the coverage uniformity of msCNVS is superior to that of MDA and MALBAC and approaches what eMDA and DOP-PCR achieves. Furthermore, msCNVS detects CNV deletions in 2 stunted, abnormal blastocysts, one with CNV mosaicism, and uncovered variants of CNVs in circulated tumor cells, cancerous pleural effusion cells, and patient-derived xenograft nuclei. Thus, msCNVS promises a robust, reliable and highly efficient approach to genomic testing of precious and rare cells like those typically obtained in reproductive and cancer clinics. One-Sentence SummaryBy early pooling of multiple single cells individually barcoded with Tn5 transposome, msCNVS enables efficient CNV profiling of rare clinic samples

genomics↗