Biology subjects

Rahmani, H.

Publications and source records attributed to Rahmani, H..

15 recordsLinked to original sources

bioRxiv2026

Imaging large fields-of-view at high resolution in cryo-ET with square beam montaging

Visualizing macromolecules within their native cellular context by cryo-electron tomography (cryo-ET) is fundamentally limited by the trade-off between field of view and resolution: Capturing high-resolution information about biomolecules requires high magnification, which restricts the field of view and obscures the cellular context in which those biomolecules function. Collecting montage data by tiling the electron beam over the region of interest offers one solution, although traditional round electron beams cause excessive radiation damage across overlapping regions. We previously made electron beams square in shape, enabling montage collection with minimal overlap and thereby reducing excessive exposure and loss of high-resolution information. Here, we create a pipeline for collecting and processing montage cryo-ET data with square electron beams. We show that square beam montages retain high-resolution information by reconstructing virus-like particles to 3.5 [A] resolution using sub-tomogram averaging, and apply the workflow to imaging a glial cell and malaria parasite lamellae over fields of view up to 65 m2. We also provide a comprehensive protocol to make square beams accessible to the community.

molecular biology↗

bioRxiv2026

ATAD3A structurally links mtDNA replication and mitochondrial fission

Mitochondrial function depends on the maintenance of its genome, and disruptions in copy number and distribution are hallmarks of mitochondrial disorders. Mitochondrial DNA (mtDNA) replication is spatially and temporally linked to mitochondrial division (i.e., fission). However, the signal that coordinates these two events, which are physically separated by the barrier of two mitochondrial membranes, remains unknown. To gain insight into this coordination, we employed correlative cryo-electron tomography (cryo-ET) to analyze the microenvironment surrounding replicating nucleoids. Mitochondrial regions containing replicating mtDNA exhibit a unique membrane architecture defined by the presence of clustered, membrane-spanning tethers that traverse the inner membrane space. Using a combination of superresolution microscopy and genetically encoded cryo-ET tagging technology, we identify these tethers as the AAA+ ATPase ATAD3A. We further show that ATAD3A knockdown reduces recruitment of the mitochondrial fission machinery, whereas overexpression promotes its recruitment and subsequent fission. Our work suggests that ATAD3A forms nanoscale linkages that coordinate these two distinct processes, revealing a new structural paradigm for organellar communication across distinct membrane-defined environments. HighlightsO_LIReplicating mitochondrial DNA (mtDNA) nucleoids are surrounded by a distinct membrane microenvironment. C_LIO_LIATAD3A forms membrane-spanning tethers enriched at replicating mtDNA sites. C_LIO_LIATAD3A enrichment is necessary and sufficient to recruit mitochondrial fission machinery and induce fission at mtDNA replication sites. C_LIO_LIATAD3A structurally couples mtDNA replication state to mitochondrial fission across distinct organellar subcompartments. C_LI

Cell Biology↗

bioRxiv2026

DM: a simple solution to suppress air-water interface interactions in cryo-EM

The air-water interface (AWI) remains the primary barrier to routine high-resolution cryo-EM structure determination, driving protein adsorption, structural denaturation, and restricted particle orientations during vitrification. Here, we describe a simple and broadly applicable strategy to mitigate these effects using the mild non-ionic detergent n-decyl-{beta}-D-maltopyranoside (DM). Addition of DM at low millimolar concentrations immediately prior to vitrification consistently suppresses AWI-driven artifacts, resulting in improved angular sampling, reduced structural damage, and enhanced reconstruction quality across diverse macromolecular systems. Using this approach, we obtained a high-resolution reconstruction of the 65 kDa Nucleophosmin 1 pentamer, a target previously limited by severe preferred orientation issues. We further show that DM promotes isotropic particle distributions for high-resolution reconstruction of hemagglutinin, transthyretin, as well as suppressing denaturation of aldolase while stabilizing its C-terminus. Our results indicate that DM effectively passivates deleterious air-water interface interactions without compromising particle integrity. These results establish DM as an effective additive for improving the robustness of single-particle cryo-EM sample preparation. O_FIG O_LINKSMALLFIG WIDTH=174 HEIGHT=200 SRC="FIGDIR/small/716008v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@108a6edorg.highwire.dtl.DTLVardef@10728b4org.highwire.dtl.DTLVardef@1014b2eorg.highwire.dtl.DTLVardef@1eed745_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2026

A Surfactant Cocktail Overcomes Air-Water Interface Artifacts in Single-Particle CryoEM

Single-particle cryogenic electron microscopy (cryoEM) is a widely used technique for structure determination of biomacromolecules to near-atomic resolution. Random distributions of these molecules in vitrified ice are necessary to accumulate enough two-dimensional views to generate a complete three-dimensional (3-D) reconstruction. However, interactions between the sample and the air-water interface (AWI) that occur during vitrification often bias the views of the sample, a phenomenon termed preferred orientation, limiting our ability to obtain 3-D reconstructions. Surfactants are often used as sample additives to prevent AWI-induced deterioration, but no general strategy exists for surfactant choice, requiring laborious screening for each sample. To circumvent these issues, we developed SurfACT, a cocktail of diverse surfactants with distinct physicochemical properties that limits AWI-dependent sample denaturation and orientation bias, while mitigating individual surfactant-specific drawbacks. Here we demonstrate SurfACTs effectiveness with four proteins plagued by AWI-induced issues, including two species of hemagglutinin (HA), molybdenum-iron protein (MoFeP) from the nitrogenase enzyme, and aldolase. All four samples show drastically improved viewing distribution and map completeness when SurfACT is applied. Cryogenic electron tomography demonstrates that SurfACT redistributes particles from the AWI into the bulk ice, driving signal recovery and inhibiting denaturation. This versatile sample additive minimizes sample-specific screening and expands the capabilities and range of suitable samples for cryoEM.

biophysics↗

bioRxiv2026

A biosecurity baseline for transboundary management of marine biological invasions in the ROPME Sea Area

Marine and brackish-water ecosystems are increasingly degraded by cumulative human pressures, with biological invasions representing a major driver of biodiversity loss, ecosystem disruption, and socio-economic impacts. Effective management requires regionally harmonized and scientifically robust baselines capable of supporting coordinated transboundary decision-making. Here we present the first consolidated marine biosecurity baseline for the Regional Organization for the Protection of the Marine Environment (ROPME) Sea Area, a transboundary region characterized by extreme environmental conditions and increasing biosecurity pressure. A total of 192 species (123 extant and 69 horizon), including birds, fishes, tunicates, invertebrates, plants, and chromists, were systematically reviewed, taxonomically validated, and cross-checked against major databases and Member State inputs. Re-evaluation of a previous regional screening revealed substantial inconsistencies, with 24 species ({approx}18%) requiring status correction or exclusion. The resulting consolidated inventory comprised 130 validated retained species supplemented by 62 additional taxa. Extant species were classified according to biogeographic origin and impact status, whereas horizon species were evaluated based on introduction pathways, environmental suitability, and projected climate trends. Risk screening under current and projected climate conditions identified 39 extant species as very high risk, providing an operational basis for progression to full risk assessment and coordinated regional biosecurity management.

ecology↗

bioRxiv2025

Prohibitin complexes associate with unique membrane microdomains in cells

Prohibitins are multi-subunit protein complexes implicated in a variety of roles in mitochondria, including maintaining cristae architecture, regulating lipid metabolism, and mediating protein quality control. Prohibitins form large, ring-like structures within the mitochondrial inner membrane, and it has been proposed that this unique architecture enables them to organize distinct membrane environments that support their diverse functions. However, the molecular mechanisms driving these structure-function relationships within the native cellular context remain poorly defined. In this work, we combine cellular cryo-electron tomography, subtomogram averaging, and Surface Morphometrics analysis to systematically characterize the structure and local membrane environment of prohibitin complexes in mouse embryonic fibroblast (MEF) cells. We show that prohibitins are enriched in the inner boundary membrane subdomain of the inner mitochondrial membrane. Moreover, we find that a subset of prohibitin complexes exhibits a unique association with a matrix-facing density that resembles an m-AAA protease. Further, we show that prohibitins consistently localize to regions of reduced lipid bilayer thickness across all inner mitochondrial membrane subdomains, suggesting that they locally remodel the membrane to support their function. Together, these findings provide direct structural evidence that prohibitin complexes are associated with unique membrane microdomains in cells and establish a framework for uncovering how the local cellular context enables prohibitin function.

cell biology↗

bioRxiv2025

RobPicker: A Meta Learning Framework for Robust Identification of Macromolecules in Cryo-Electron Tomograms

Accurate particle picking of macromolecules of all kinds, shapes, and sizes in cryogenic electron tomograms (cryo-ET) is critical for understanding the molecular architecture of biological systems in their native state. Current deep learning methods have shown potential in identifying macromolecules from tomograms, but they are vulnerable to issues of noise in the training dataset obtained through human or automatic labeling and imbalanced distribution of macromolecule species. To address these limitations, we developed RobPicker, a meta-learning framework that effectively mitigates these issues by automatically learning deep neural networks to correct label errors and give greater emphasis to underrepresented macromolecule species. In evaluations across diverse cryo-ET datasets with noisy labels and imbalanced species distributions, RobPicker substantially outperforms state-of-the-art methods, particularly in identifying small and rare macromolecules. The efficiency and robustness of RobPicker can also be used for rapid fine-tuning of the tilt-series alignment, leading to improved tomogram reconstruction and enabling high-resolution cellular structural biology analysis.

bioinformatics↗

bioRxiv2025

Surface morphometrics reveals local membrane thickness variation in organellar subcompartments

Lipid bilayers form the basis of organellar architecture, structure, and compartmentalization in the cell. Decades of biophysical, biochemical, and imaging studies on purified or in vitro reconstituted liposomes have shown that variations in lipid composition influence the physical properties of membranes, such as thickness and curvature. However, similar studies characterizing these membrane properties within the native cellular context have remained technically challenging. Recent advancements in cellular cryo-electron tomography (cryo-ET) imaging enable high-resolution, three-dimensional views of native organellar membrane architecture preserved in near-native conditions. We previously developed a Surface Morphometrics pipeline that generates surface mesh reconstructions to model and quantify cellular membrane ultrastructure from cryo-ET data. Here, we expand this pipeline to measure the distance between the phospholipid head groups (PHG) of the membrane bilayer as a readout of membrane thickness. Using this approach, we demonstrate thickness variations both within and between distinct organellar membranes. We also demonstrate that membrane thickness positively correlates with other features, such as membrane curvedness. Further, we show that subcompartments of the mitochondrial inner membrane exhibit varying membrane thicknesses that are independent of network morphology (i.e., fragmented versus elongated networks). Finally, we demonstrate that large membrane-associated macromolecular complexes exhibit distinct density profiles that correlate with local variations in membrane thickness. Overall, our updated Surface Morphometrics pipeline provides a framework for investigating how changes in membrane composition in various cellular and disease contexts affect organelle ultrastructure and function.

biochemistry↗

bioRxiv2024

scLong: A Billion-Parameter Foundation Model for Capturing Long-Range Gene Context in Single-Cell Transcriptomics

Single-cell RNA sequencing (scRNA-seq) has revolutionized the study of cellular heterogeneity by providing gene expression data at single-cell resolution, uncovering insights into rare cell populations, cell-cell interactions, and gene regulation. Foundation models pretrained on large-scale scRNA-seq datasets have shown great promise in analyzing such data, but existing approaches are often limited to modeling a small subset of highly expressed genes and lack the integration of external genespecific knowledge. To address these limitations, we present sc-Long, a billion-parameter foundation model pretrained on 48 million cells. sc-Long performs self-attention across the entire set of 28,000 genes in the human genome. This enables the model to capture long-range dependencies between all genes, including lowly expressed ones, which often play critical roles in cellular processes but are typically excluded by existing foundation models. Additionally, sc-Long integrates gene knowledge from the Gene Ontology using a graph convolutional network, enriching its contextual understanding of gene functions and relationships. In extensive evaluations, sc-Long surpasses both stateof-the-art scRNA-seq foundation models and task-specific models across diverse tasks, including predicting transcriptional responses to genetic and chemical perturbations, forecasting cancer drug responses, and inferring gene regulatory networks.

bioinformatics↗

bioRxiv2024

ProteinAligner: A Multi-modal Pretraining Framework for Protein Foundation Models

Protein foundation models, particularly protein language models, have demonstrated strong success in learning meaningful representations of proteins using transformer architectures pretrained on large-scale protein datasets with self-supervised learning. These representations have been highly effective for downstream tasks such as predicting protein functions and properties. However, most current protein foundation models focus on pretraining with amino acid sequences, often neglecting additional modalities like protein structures and related literature, both of which provide valuable insights. To address this gap, we propose a multi-modal pretraining approach that integrates three key modalities - protein sequences, structures, and literature text. In our framework, the protein sequence modality serves as the anchor, with the other two modalities aligned to it, enhancing the models capacity to capture more comprehensive protein information. ProteinAligner out-performed state-of-the-art protein foundation models in predicting protein functions and properties across diverse down-stream tasks.

bioinformatics↗

bioRxiv2024

Multi-Modal Large Language Model Enables All-Purpose Prediction of Drug Mechanisms and Properties

Accurately predicting the mechanisms and properties of potential drug molecules is essential for advancing drug discovery. However, traditional methods often require the development of specialized models for each specific prediction task, resulting in inefficiencies in both model training and integration into work-flows. Moreover, these approaches are typically limited to predicting pharmaceutical attributes represented as discrete categories, and struggle with predicting complex attributes that are best described in free-form texts. To address these challenges, we introduce DrugChat, a multi-modal large language model (LLM) designed to provide comprehensive predictions of molecule mechanisms and properties within a unified framework. DrugChat analyzes the structure of an input molecule along with users queries to generate comprehensive, free-form predictions on drug indications, pharmacodynamics, and mechanisms of action. Moreover, DrugChat supports multi-turn dialogues with users, facilitating interactive and in-depth exploration of the same molecule. Our extensive evaluation, including assessments by human experts, demonstrates that DrugChat significantly outperforms GPT-4 and other leading LLMs in generating accurate free-form predictions, and exceeds state-of-the-art specialized prediction models.

pharmacology and toxicology↗

bioRxiv2024

Multi-Modal Large Language Model Enables Protein Function Prediction

Predicting the functions of proteins can greatly accelerate biological discovery and applications, where deep learning methods have recently shown great potential. However, these methods predominantly predict protein functions as discrete categories, which fails to capture the nuanced and complex nature of protein functions. Furthermore, existing methods require the development of separate models for each prediction task, a process that can be both resource-heavy and time-consuming. Here, we present ProteinChat, a versatile, multi-modal large language model that takes a proteins amino acid sequence as input and generates comprehensive narratives describing its function. ProteinChat is trained using over 1,500,000 (protein, prompt, answer) triplets curated from the Swiss-Prot dataset, covering diverse functions. This novel model can universally predict a wide range of protein functions, all within a single, unified framework. Furthermore, ProteinChat supports interactive dialogues with human users, allowing for iterative refinement of predictions and deeper exploration of protein functions. Our experimental results, evaluated through both human expert assessment and automated metrics, demonstrate that ProteinChat outperforms general-purpose LLMs like GPT-4, one of the flagship LLMs, by over ten-fold. In addition, ProteinChat exceeds or matches the performance of task-specific prediction models.

bioinformatics↗

bioRxiv2024

Cytoplasmic ribosomes on mitochondria alter the local membrane environment for protein import

Most of the mitochondria proteome is nuclear-encoded, synthesized by cytoplasmic ribosomes, and targeted to mitochondria post-translationally. However, a subset of mitochondrial-targeted proteins is imported co-translationally, although the molecular mechanisms governing this process remain unclear. We employ cellular cryo-electron tomography to visualize interactions between cytoplasmic ribosomes and mitochondria in Saccharomyces cerevisiae. We use surface morphometrics tools to identify a subset of ribosomes optimally oriented on mitochondrial membranes for protein import. This allows us to establish the first subtomogram average structure of a cytoplasmic ribosome on the surface of the mitochondria in the native cellular context, which showed three distinct connections with the outer mitochondrial membrane surrounding the peptide exit tunnel. Further, this analysis demonstrated that cytoplasmic ribosomes primed for mitochondrial protein import cluster on the outer mitochondrial membrane at sites of local constrictions of the outer and inner mitochondrial membrane. Overall, our study reveals the architecture and the spatial organization of cytoplasmic ribosomes at the mitochondrial surface, providing a native cellular context to define the mechanisms that mediate efficient mitochondrial co-translational protein import. SUMMARYChang et al. present a membrane-guided approach for identifying a subset of cytoplasmic ribosomes oriented for protein import on the mitochondrial surface in Saccharomyces cerevisiae using cryo-electron tomography. They show that ribosomes cluster, make multiple contacts with, and induce local changes to the mitochondrial membrane ultrastructure at import sites.

cell biology↗

bioRxiv2023

Oral copper-methionine decreases matrix metalloproteinase-2 activity in the liver and brain of broiler chickens subjected to cold stress for ascites incidence

Copper plays an antioxidant role in biological reactions. This study examined the impact of copper-methionine supplementation on the matrix metalloproteinase-2 (MMP-2) activity and gene expression in the liver and brain of broiler chickens subjected to cold temperature. A total of 480 broiler chickens were assigned to 6 groups and reared under either low (15-19 {o}C) or normal temperature (25-28{o}C) and fed a basal diet enriched with different concentrations of copper-methionine (Cu-Met) supplementation (0, 100 or 200 mg.kg-1). Ascites was exclusively observed in broiler chickens kept in low temperature and fed with basal diet without Cu-Met during the seventh week, identified by the presence of abdominal fluid accumulation. Broilers livers and brains were separated for MMP-2 and tissue inhibitor of metalloproteinase-2 (TIMP-2) analysis. Results of gelatin zymography on these samples demonstrated that incidence of ascites was associated with increased MMP-2 levels in liver and brain. MMP-2 activity assay confirmed the results obtained by zymography. RT-qPCR experiments revealed an upregulation in the mRNA expression of MMP-2. In contrast, the treatments did not induce significant alterations in TIMP-2 levels. Results suggest that oral copper-methionine can decrease the ascites occurrence and might be useful for prevention of ascites in broiler chickens.

cell biology↗

bioRxiv2020

CryoEM Structure of Drosophila Flight Muscle Thick Filaments at 7A Resolution

Striated muscle thick filaments are composed of myosin II and several non-myosin proteins. Myosin IIs long -helical coiled-coil tail forms the dense protein backbone of filaments while its N-terminal globular head containing the catalytic and actin binding activities extends outward from the backbone. Here we report the structure of thick filaments of the flight muscle of the fruit fly Drosophila melanogaster at 7 [A] resolution. Its myosin tails are arranged in curved molecular crystalline layers identical to flight muscles of the giant waterbug Lethocerus indicus. Four non-myosin densities are observed, three of which correspond to ones found in Lethocerus; one new density, possibly stretchin-Mlck, is found on the backbone outer surface. Surprisingly, the myosin heads are disordered rather than ordered along the filament backbone. Our results show striking myosin tail similarity within flight muscle filaments of two insect orders separated by several hundred million years of evolution. Significance StatementMyosin thick filaments are one of striated muscles key structures, but also one of its least understood. A key question is how the myosin a-helical coiled-coil tail is arranged in the backbone. At 7[A] resolution, sufficient to resolve individual a-helices, the myosin tail arrangement in thick filaments from the flight muscle of the fruit fly Drosophila melanogaster is strikingly similar to the myosin tail arrangement in flight muscles of the giant waterbug Lethocerus indicus. Nearly every other thick filament feature is different. Drosophila and Lethocerus evolved separately >245 million years ago suggesting myosin tail packing into curved molecular crystalline layers forms a highly conserved thick filament building block and different properties are obtained by alterations in non-myosin proteins.

biophysics↗