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bioRxiv2023

Nuclear Lipid Droplets Exit to the Cytoplasm: A Novel Mechanism of non-nuclear pore-dependent material exchange

In cellular biology, the extrusion of large molecular complexes from the nucleus has consistently represented a considerable challenge. In this investigation, we reveal a hitherto unexplored mechanism facilitating the efflux of nuclear lipid droplets (nLDs) from the nucleus directly into the cytoplasm, a process integral to comprehending cellular processes and nuclear dynamics. Through high-throughput sequencing, immunoprecipitation, and immunofluorescence experimentation, we demonstrated that the type I nucleoplasmic reticulum engages with nLDs, enabling the dynamic protein Rab8as transfer to the nLDs and fostering their translocation to the nuclear membrane. Phosphorylation of LMNA/C at the S392 site, adjacent to the nLD-nuclear membrane contact site, induces local depolymerization of lamins, creating an aperture that enables gradual nuclear exit of nLDs. Following this, nLDs, carrying DNA fragments, are released into the cytoplasm through budding and subsequently undergo autophagy-mediated degradation. Furthermore, we demonstrate that RhoA-PKC signaling enhances nLD movement and LMNA/C phosphorylation, while its inhibition impedes nuclear nLD efflux. Our groundbreaking investigation illuminates non-nuclear pore-dependent mechanisms of material exchange and offers fresh perspectives on nuclear metabolic pathways. In Brief O_FIG O_LINKSMALLFIG WIDTH=197 HEIGHT=200 SRC="FIGDIR/small/556761v1_ufig1.gif" ALT="Figure 1"> View larger version (107K): org.highwire.dtl.DTLVardef@38a213org.highwire.dtl.DTLVardef@1898caorg.highwire.dtl.DTLVardef@d7270forg.highwire.dtl.DTLVardef@14582a2_HPS_FORMAT_FIGEXP M_FIG C_FIG In this study, Jin et al. elucidate a novel mechanism for the expulsion of nuclear lipid droplets (nLDs) from the nucleus. They demonstrate that the activation of RhoA within the nucleus recruits Rab8a to the surface of nLDs. Concurrently, PKC phosphorylation triggers the phosphorylation of LMNA/C at the S392 site, leading to a localized depolymerization of lamins. This creates an aperture that allows for the gradual exit of nLDs from the nucleus. The efflux process of nLDs involves three sequential steps: rupture of the nuclear fibril layer, fusion of nLDs with the inner nuclear membrane (INM), and subsequent fusion with the outer nuclear membrane (ONM). This enables nLDs to enter the cytoplasm, shedding light on a previously unknown process of large molecular entity expulsion from the nucleus.

molecular biology↗

bioRxiv2023

Integrated spatial protein and RNA analysis on the same section using MICS technology

Spatial Biology has evolved from the molecular characterization of microdissected cells to high throughput spatial RNA and protein expression analysis at scale. The main limitation of spatial technologies so far is the inability to resolve protein and RNA information in the same histological section. Here, we report for the first time the integration of highly multiplexed RNA and protein detection on the same tissue section. We developed a new, automated, spatial RNA detection method (RNAsky), which is based on targeted rolling circle amplification and iterative staining. We combine RNAsky with MACSima Imaging Cyclic Staining (MICS) based protein analysis and show compatibility with subsequent standard hematoxylin and eosin (H&E) staining. Using both, open-source tools and our recently developed software suite MACS(R) iQ View, we demonstrate our multiomics MICS workflow by characterizing key immune-oncology markers at subcellular resolution across normal and diseased tissues.

molecular biology↗

bioRxiv2019

Identification of suitable reference genes for qPCR expression analysis on the gonads of the invasive mussel Limnoperna fortunei

Limnoperna fortunei -- popularly known as the Golden mussel -- is an aggressive invasive species that has been causing environmental damage and adversely affecting economic sectors dependent on freshwater ecosystems in South America. As a non-model species, knowledge about its biology is very limited, especially molecular mechanisms that contribute to its invasiveness, such as its high reproduction rate. Quantitative PCR (qPCR) is considered the gold standard technique to determine gene expression levels and its accuracy relies on the use of stably expressed reference genes for data normalization and to minimize technical variability. Our goal was to identify reliable reference genes to perform gene expression analysis on the gonads of L. fortunei. The stability of five candidate genes (RPS3, EF1a, HS6ST3B, NAPA and UBE2F) in the gonads of male and female mussels was evaluated by using two algorithms, Bestkeeper and Genorm. Results show that NAPA, UBE2F and RPS3 genes are stable enough to compose a reliable normalization factor for gene expression analyses comparing both sexes. HS6ST3B and NAPA were found to be more stable in female gonads; thus, their application as a normalization factor is preferable for studies limited to female processes only.

molecular biology↗

bioRxiv2017

Deciphering the regulation mechanism in biochemical networks by a systems-biology approach

To decipher molecular mechanisms in biological systems from system-level input-output data is challenging especially for complex processes that involve interactions among multiple components. Here, we study regulation of the multi-domain (P1-5) histidine kinase CheA by the MCP chemoreceptors. We develop a network model to describe dynamics of the system treating the receptor complex with CheW and P3P4P5 domains of CheA as a regulated enzyme with two substrates, P1 and ATP. The model enables us to search the hypothesis space systematically for the simplest possible regulation mechanism consistent with the available data. Our analysis reveals a novel dual regulation mechanism wherein besides regulating ATP binding the receptor activity has to regulate one other key reaction, either P1 binding or phosphotransfer between P1 and ATP. Furthermore, our study shows that the receptors only control kinetic rates of the enzyme without changing its equilibrium properties. Predictions are made for future experiments to distinguish the remaining two dual-regulation mechanisms. This systems-biology approach of combining modeling and a large input-output data-set should be applicable for studying other complex biological processes.

systems biology↗

bioRxiv2026

Learning from human and chemical languages to predict biological function

Understanding how molecular structure encodes biological function remains a grand challenge in drug discovery. Here, we present PubCheF-1, a deep learning model that predicts literature-derived biological function directly from chemical structure. PubCheF-1 was trained on a dataset linking molecules to labels derived from the scientific articles in which they appear, a strategy that connects disparate compounds through the language used to describe their functionalities. When tasked with identifying inhibitors of {beta}-lactamases, including enzymes considered largely refractory to inhibition, PubCheF-1 predicted structurally distinct compounds that collectively have activity against all {beta}-lactamase classes. Furthermore, hit compounds directly bind the enzyme active site, restore antibiotic efficacy in multidrug-resistant high-priority pathogens, and demonstrate potent activity in animal infection models. Together, these findings establish that machine learning-based prediction of biological function derived from the language of scientific literature allows the identification of bioactive molecules at high hit rates, thereby accelerating therapeutic discovery.

bioinformatics↗

bioRxiv2024

Facilitating Gene Editing in Human Lymphoma Cells Using Murine Ecotropic γ-Retroviruses

Genetic modifications using CRISPR-Cas9 have revolutionized cancer research and other pre-clinical studies. Exceptionally, these efficient tools are inadequate in a few disease models and cell lines due to the aberrant differentiation states and the accumulation of excessive somatic mutations that compromise the robustness of viral gene delivery and stable transduction. A couple of B lymphoma cell lines fall into this category where lentiviral transfection becomes inefficient and exhibits variable efficiency. Additionally, lentiviral delivery requires high biosafety levels. To address this challenge, we have developed a two-step strategy that supports CRISPR-Cas9 through lentivirus and murine ecotropic {gamma}-retrovirus. By engineering B lymphoma cell lines to express Cas9 and mCat-1, a specific receptor for ecotropic retroviruses, we enable efficient and safe gene editing through ecotropic {gamma}-retrovirus. We demonstrate the efficacy of this method by generating IgM-deficient B lymphoma cell lines. This innovative approach simplifies protocols, enhances accessibility, and paves the way for standardized gene manipulation of B cell lymphoma models for molecular cell biology research.

molecular biology↗

bioRxiv2015

Molecular Mechanisms for the Biological Storage of Renewable Energy

Recent and ongoing discoveries in the field of extracellular electron transport offer the potential to electrically power highly flexible, carbon-fixing microbial metabolisms and generate a rich variety of chemicals and fuels. This process, electrosynthesis, creates the opportunity to use biology for the low cost storage of renewable electricity and the synthesis of fuels that produce no net carbon dioxide. This article highlights recent discoveries on the molecular machinery underpinning electrosynthesis and reviews recent work on the energy conversion efficiency of photosynthesis to begin to establish a framework to quantify the overall energy storage and conversion efficiency of electrosynthesis.

Systems Biology↗

bioRxiv2020

In-cell architecture of an actively transcribing-translating expressome

Structural biology performed inside cells can capture molecular machines in action within their native context. Here we develop an integrative in-cell structural approach using the genome-reduced human pathogen Mycoplasma pneumoniae. We combine whole-cell crosslinking mass spectrometry, cellular cryo-electron tomography, and integrative modeling to determine an in-cell architecture of a transcribing and translating expressome at sub-nanometer resolution. The expressome comprises RNA polymerase (RNAP), the ribosome, and the transcription elongation factors NusG and NusA. We pinpoint NusA at the interface between a NusG-bound elongating RNAP and the ribosome, and propose it could mediate transcription-translation coupling. Translation inhibition dissociates the expressome, whereas transcription inhibition stalls and rearranges it, demonstrating that the active expressome architecture requires both translation and transcription elongation within the cell.

molecular biology↗

bioRxiv2020

An insight into transcriptome of LlaNAC Gene Over- expressing Tobacco Plants

Here, we report a whole transcriptome analysis of LlaNAC gene (from Lepidium latifolium) containing transgenic tobacco line (NC10) and wild type (WT), to attain deeper knowledge into the downstream genes activated by the over-expressing transgene. Transcriptome sequencing of NC10 and WT samples generated huge data using Illumina platform. The maximum number of unigenes GO annotated were of Biological process (8988, 3209) followed by molecular function (5155, 2577) and cellular components (3826, 1583) for WT and NC10 samples respectively. KEGG Pathway analysis revealed the unigenes were enriched in different functional pathway categories. The unigenes whose products involved in carbohydrate metabolism, glycan metabolism, and secondary metabolites synthesis were more for NC10 library in comparison to WT. Greater variety of transcription factors were involved in transgenic than wild-type plants. Genes like, Copia-like retrotransposable element, Peroxidase 64-like, Peptidyl-prolyl cis-trans isomerise, Cytochrome P450, Lipoyl synthase, CBL-interacting serine/threonine-protein kinase 5-like etc. were found differentially expressed in both the samples. Promoter analysis of these differentially expressed genes have elements for defence and stress response, abscisic acid response, shoot specific expression and light response, etc. In summary this study reports the involvement of the overexpressed genes in the dual action of cold tolerance and biomass accumulation, as sugars participate in both of these activities of the cell.

molecular biology↗

bioRxiv2023

From initial RNA encoding to the Standard Genetic Code

Multiple experiments have shown that RNA binds chemically varied amino acids within specific oligoibonucleotide sequences. The smallest, simplest, and potentially most primitive RNA binding sites frequently contain conserved triplets corresponding to the Standard Genetic Code (SGC). Here, implications of such cognate coding triplets are calculated, combining them with an optimized kinetic model for SGC evolution. RNA-amino acid interactions at observed frequencies choose an SGC-like code, and, using the same mechanism, effectively resist alternative triplet assignments. Resistance to other kinds of coding is evident across varied code initiation scenarios. RNA-mediated assignments at experimental frequencies are sufficient to guide the ribonucleopeotide transition (RNPT) to a modern code. This can account for extreme selection of the SGC among its astronomical code possibilities; very SGC-like codes are ca. 1/50 to 1/5 of codes within such a population. Nevertheless, full accounting depends on RNA affinities yet unmeasured. Such a code begins as mostly stereochemical, excludes mismatched assignments, and critically relies on properties characteristic of fusible microbes. After its RNPT in a partially assigned code, evolution accelerates definitively. Other assignment methods (adaptation, co-evolution, revised stereochemistry, LGT) likely complete the modern SGC because stable cellular intermediates with > 1 code exist, allowing compartmental code exchanges. Though initiated using chemical affinities, the 83 order-of-magnitude focus required to find a near-complete SGC among all possible codes was made by sequential evolutionary anthologies, in successive biological settings.

molecular biology↗

bioRxiv2024

VISION -- an open-source software for automated multi-dimensional image analysis of cellular biophysics

Environment-sensitive probes are frequently used in spectral/multi-channel microscopy to study alterations in cell homeostasis. However, the few open-source packages available for processing of spectral images are limited in scope. Here, we present VISION, a stand-alone software based on Phyton for spectral analysis with improved applicability. In addition to classical intensity-based analysis, our software can batch-process multidimensional images with an advanced single-cell segmentation capability and apply user-defined mathematical operations on spectra to calculate biophysical and metabolic parameters of single cells. VISION allows for 3D and temporal mapping of properties such as membrane fluidity and mitochondrial potential. We demonstrate the broad applicability of VISION by applying it to study the effect of various drugs on cellular biophysical properties; the correlation between membrane fluidity and mitochondrial potential; protein distribution in cell-cell contacts; and properties of nanodomains in cell-derived vesicles. Together with the code, we provide a graphical user interface for facile adoption. We anticipate that VISION will find a broad range of applications in different fields of biology, spanning from molecular and tissue biology to immunology and biophysics. Summary statementVISION, an open-source software, enables high throughput and correlative analysis of cellular biophysical properties.

biophysics↗

bioRxiv2018

Orthogonal regulation of ferritin translation by human eIF3 and the iron response proteins

A central problem in human biology remains the discovery of causal molecular links between mutations identified in genome-wide association studies (GWAS) and their corresponding disease traits. This challenge is magnified for variants residing in non-coding regions of the genome. Single-nucleotide polymorphisms (SNPs) in the 5 untranslated region (5-UTR) of the ferritin light chain (FTL) gene that cause hyperferritinemia are thought to disrupt translation repression by altering iron regulatory protein (IRP) interactions with the FTL mRNA 5-UTR. Here, we show that human eukaryotic translation initiation factor 3 (eIF3) acts as a distinct repressor of FTL mRNA translation, and eIF3-mediated FTL repression is disrupted by a subset of SNPs in FTL that cause hyperferritinemia. These results identify a direct role for eIF3-mediated translational control in a specific human disease.

molecular biology↗

bioRxiv2019

SINEUP long non-coding RNA acts via PTBP1 and HNRNPK to promote translational initiation assemblies

SINEUPs are long non-coding RNAs (lncRNAs) that contain a SINE element, which up-regulate the translation of target mRNA and have been studied in a wide range of applications for biological and therapeutic tools, although the molecular mechanism is unclear. Here, we focused on the kinetic distribution of target mRNAs and SINEUP RNAs by performing co-transfection of expression vectors for these transcripts into human embryonic normal kidney cells (HEK293T/17) to investigate the network of translational regulation. The results showed that co-localization of target mRNAs and SINEUP RNAs in the cytoplasm was one of the key phenomena. We identified PTBP1 and HNRNPK as essential RNA binding proteins. These proteins contributed to SINEUP RNA sub-cellular distribution and to assembly of translational initiation complexes, leading to enhanced target mRNA translation. These findings will promote a better understanding of the mechanisms on the fate of regulatory RNAs implicated in efficient protein translation.

molecular biology↗

bioRxiv2026

Structural insights into the recognition and catalysis of tRNA by human NSUN2

The human RNA m5C methyltransferase NSUN2 catalyzes site-specific cytosine methylation across diverse RNA substrates and thereby regulates a wide range of biological and physiological processes. However, the molecular basis by which NSUN2 achieves broad substrate recognition while maintaining catalytic specificity has remained unclear. Here we determine structures of human NSUN2 in both substrate-free and substrate-bound states using X-ray crystallography and cryo-electron microscopy. Structures of NSUN2 in complex with multiple tRNA substrates reveal a structure-first, sequence-tolerant strategy in which NSUN2 actively remodels tRNA architecture, exposing the buried target cytosine and positioning it within the catalytic pocket for methyl transfer. This recognition strategy enables NSUN2 to accommodate diverse tRNA substrates through a largely conserved interaction interface. Guided by these structural insights, we identify a small-molecule inhibitor that suppresses NSUN2 activity and cancer cell proliferation. Together, our findings define the molecular principles underlying NSUN2-mediated RNA m5C modification and provide a structural foundation for targeting NSUN2 in cancers.

molecular biology↗

bioRxiv2026

SELECTIVE TRANSCRIPTOMIC VULNERABILITY OF MEMBRANE-INTEGRATED ARCHITECTURES DURING NEURAL TISSUE VITRIFICATION

Cryopreservation is essential for long-term storage of biological tissues. Yet, surprisingly, the precise molecular impact of cryopreservation on tissue transcriptomes remains poorly defined. This study provides the first resource of whole-genome transcriptomic changes following cryopreservation. This study used bulk RNA sequencing to examine how preservation method (snap freezing or vitrification) affects transcriptomes in mouse cerebral cortex and hippocampus. This allowed us to separate cryoprotectant-specific changes from cold induced-changes via snap freezing. In a subset of genes, tissues processed under vitrification conditions showed selective under-representation of a small but structurally coherent group of transcripts, with the hippocampus exhibiting greater vulnerability than the cortex. UniProt annotation revealed that affected transcripts were strongly enriched for proteins with membrane-associated, secretory-pathway, and multi-pass topologies, indicating that structurally complex membrane-integrated architectures are disproportionately sensitive to vitrification. Pathway-level analysis using iPANDA further showed that negative preservation scores in vitrified tissue clustered primarily within signal transduction and metabolic pathways, suggesting coordinated pathway-level disruption rather than global transcript loss. Together, these results demonstrate that vitrification conditions induce selective and structured molecular perturbations in neural tissue, defined by the under-recovery of transcripts associated with membrane and secretory pathway organization. This work highlights molecular vulnerability during vitrification and emphasizes the need for transcript-level evaluation when optimizing cryopreservation approaches for neural systems.

molecular biology↗

bioRxiv2026

Target RNA abundance controls the collateral activity of RfxCas13d in human cells and zebrafish embryos

Collateral RNA cleavage by CRISPR-Cas13 effectors presents a critical obstacle to their application in biological research and therapeutics, yet the molecular determinants of this activity remain poorly understood. Here, we systematically investigate the collateral activity of various Cas13 variants in human cells in vitro and zebrafish embryos in vivo. Among these nucleases, RfxCas13d displays robust collateral activity that is highly dependent on target abundance. Targeting moderately expressed RNAs activates only a limited subset of RfxCas13d molecules, resulting in selective degradation of ectopically expressed transcripts, while endogenous RNAs remain largely protected. This selectivity indicates higher accessibility to exogenous RNAs through spatial proximity and temporal colocalization with activated RfxCas13d nuclease domains. In contrast, the recognition of highly abundant RNA targets drives simultaneous activation of a large fraction of cellular RfxCas13d, leading to widespread collateral cleavage of cellular RNAs, disruption of proteome homeostasis, and consequent cell toxicity and developmental defects in zebrafish embryos. Notably, transgenic zebrafish with target RNA expression restricted to endothelial or neuronal cell lineages exhibit localized collateral activity, leading to tissue-specific developmental abnormalities and motility deficits. These findings reveal that RfxCas13ds collateral activity is threshold-dependent, with abundant target RNA acting as a molecular switch for widespread collateral RNA degradation. This work underscores the need for careful consideration of target abundance when deploying RfxCas13d, and highlights PspCas13b as an alternative for RNA silencing free of collateral activity.

molecular biology↗

bioRxiv2019

Computation of stationary distributions in stochastic models of cellular processes with molecular memory

AbstractModeling stochastic dynamics of intracellular processes has long rested on Markovian (i.e., memoryless) hypothesis. However, many of these processes are non-Markovian (i.e., memorial) due to, e.g., small reaction steps involved in synthesis or degradation of a macroscopic molecule. When interrogating aspects of a cellular network by experimental measurements (e.g., by singlemolecule and single-cell measurement technologies) of network components, a key need is to develop efficient approaches to simulate and compute joint distributions of these components. To cope with this computational challenge, we develop two efficient algorithms: stationary generalized Gillespie algorithm and stationary generalized finite state projection, both being established based on a stationary generalized chemical master equation. We show how these algorithms can be combined in a streamlined procedure for evaluation of non-Markovian effects in a general cellular network. Stationary distributions are evaluated in two models of constitutive and bursty gene expressions as well as a model of genetic toggle switch, each considering molecular memory. Our approach significantly expands the capability of stochastic simulation to investigate gene regulatory network dynamics, which has the potential to advance both understanding of molecular systems biology and design of synthetic circuits.\n\nAuthor summaryCellular systems are driven by interactions between subsystems via time-stamped discrete events, involving numerous components and reaction steps and spanning several time scales. Such biochemical reactions are subject to inherent noise due to the small numbers of molecules. Also, they could involve several small steps, creating a memory between individual events. Delineating these molecular stochasticity and memory of biomolecular networks are continuing challenges for molecular systems biology. We present a novel approach to compute the probability distribution in stochastic models of cellular processes with molecular memory based on stationary generalized chemical master equation. We map a stochastic system with memory onto a Markovian model with effective reaction propensity functions. This formulation enables us to efficiently develop algorithms under the Markovian framework, and thus systematically analyze how molecular memories regulate stochastic behaviors of biomolecular networks. Here we propose two representative algorithms: stationary generalized Gillespie algorithm and stationary generalized finite state projection algorithm. The former generate realizations with Monte Carlo simulation, but the later compute approximations of the probability distribution by solving a truncated version of stochastic process. Our approach is demonstrated by applying it to three different examples from systems biology: generalized birth-death process, a stochastic toggle switch model, and a 3-stage gene expression model.

systems biology↗

bioRxiv2020

Extraction of Protein Dynamics Information Hidden in Cryo-EM Map Using Deep Learning

Technical breakthroughs in cryogenic electron microscopy (cryo-EM)-based single-particle analysis have enabled the structures of numerous proteins to be solved at atomic or near-atomic resolutions, including extremely large macromolecules whose structures could not be solved by conventional techniques. Determining the dynamics properties of these macromolecules, based on their solved structures, can further improve our understanding of their functional mechanisms. However, such analysis is often hampered by the large molecular size and complex structural assembly, making both experimental and computational approaches to determine dynamics properties challenging. Here, we report a deep learning-based approach, DEFMap, to extract the dynamics information "hidden" in cryo-EM density maps. By relying only on cryo-EM maps, DEFMap successfully provided dynamics information equivalent to that determined from molecular dynamics (MD) simulations and experimental approaches at the atomic and residue levels. Additionally, DEFMap could detect dynamics changes associated with molecular recognition and the accompanying allosteric conformational stabilizations, which trigger various biological events such as signal transduction and enzyme catalysis. This approach will provide new insights into the functional mechanisms of biological molecules, accelerating modern molecular biology researches. Furthermore, this advanced strategy combining experimental data, deep learning approaches, and MD simulations would open a new multidisciplinary science area

molecular biology↗