About

Shabnam Akhtari is a professor at the Department of Mathematics in the Eberly College of Science at Pennsylvania State University. Her research interests include Number Theory, Geometry of Numbers, and Diophantine Analysis. She is involved in advancing understanding in these mathematical fields, contributing to the academic community through her expertise and scholarly work.

Research topics

• Cell biology
• Chemistry
• Neuroscience
• Biology
• Biochemistry

Selected publications

• CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures

  JACS Au · 2026-03-27

  articleOpen accessSenior authorCorresponding

  Quantitative analysis of network-like biological molecular architectures, such as cytoskeletal networks, remains a fundamental challenge in super-resolution fluorescence imaging because single-molecule localization microscopy (SMLM) typically produces sparse and discontinuous localization patterns arising from stochastic labeling, incomplete probe occupancy, and structural deformation of biological networks. These factors obscure the underlying connectivity, periodicity, and symmetry, limiting the ability of existing analysis methods to resolve higher-order organization. Here, we report the Classifier of Super-resolution Structural Networks (CLaSSiNet), a conceptually novel computational framework that overcomes these sparsity and heterogeneity constraints. By integrating connectivity, 1D periodicity, and 2D regularity classifiers through newly developed algorithms, CLaSSiNet sensitively captures the organizational signatures of imaged networks to automatically segment and map networks with an unprecedented resolution (∼256 nm, reaching the diffraction limit of light). CLaSSiNet uniquely resolves four distinct organizational states (1D periodic, 2D polygonal, disordered, and non-network), providing a robust platform for analyzing SMLM data sets regardless of labeling chemistry. Using CLaSSiNet, we achieve the first spatially resolved, quantitative mapping of organizational heterogeneity in the actin-spectrin membrane-associated periodic skeleton (MPS), a conserved cytoskeletal network located underneath the plasma membrane of animal cells. This analysis reveals previously unrecognized organizational principles for these MPS networks, with ordered 1D and 2D networks enriched at cell edges and junctions, while non-network states dominate the cell body. Furthermore, we uncover a mechanical coupling principle wherein actin stress fibers bias the symmetry and orientation of nearby spectrin lattices, indicating bidirectional coordination between contractile actin bundles and periodic MPS networks. Comparative analysis across diverse cell types highlights the cell-specific “tuning” of these supramolecular design rules. Broadly, CLaSSiNet establishes a principled computational framework for dissecting the nanoscale design rules of complex molecular networks, offering a robust methodology applicable to the wider study of hierarchical biological and bioinspired architectures.

  PublisherDOI

• Coordination of cell organelles to promote metabolon formation

  Proceedings of the National Academy of Sciences · 2026-01-26

  articleOpen access

  The spatial coordination between cellular organelles and metabolic enzyme assemblies represents a fundamental mechanism for maintaining metabolic efficiency under stress. While previous work has shown that membrane-bound organelles regulate metabolic activities and that membrane-less condensates conduct metabolic reactions, the coordination between these two organizations remains unaddressed. By using a combination of proximity labeling, superresolution fluorescence microscopy, and metabolite analyses using isotopic tracing, we investigated the relationships between these metabolic hotspots. Here, we show that nutrient deficiency elongates mitochondria and transforms the ER from a tubular to sheet-like morphology, coinciding with increased mitochondrial respiration and inosine 5'-monophosphate levels. These structural changes promote the colocalization of purinosomes with these organelles, enhancing metabolic channeling. Disruption of ER sheet formation via MTM1 knockout destabilizes purinosomes, impairs substrate channeling, and reduces intracellular purine nucleotide pools without altering enzyme expression. Our findings reveal that organelle morphology and interorganelle contacts dynamically regulate the assembly and function of metabolic condensates, providing a structural basis for coordinated metabolic control in response to nutrient availability.

  PublisherDOI

• thezhoulab/Fei-et-al.-Science-Advances-2025

  Zenodo (CERN European Organization for Nuclear Research) · 2026-01-06

  otherOpen accessSenior author

  No description provided.

  PublisherDOI

• Code for "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-05 · 1 citations

  articleOpen accessSenior author

  Scripts for the indicated paper titled "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures".

  PublisherDOI

• Dataset for "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-10 · 1 citations

  datasetOpen accessSenior author

  Raw data for the indicated paper titled "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures".

  PublisherDOI

• Dataset 1 for "FLEXTAG: a small and self-renewable protein labeling system for anti-fading multi-color super-resolution imaging"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-01-07 · 1 citations

  datasetOpen accessSenior author

  Raw data for Main Figures 2-5, and NMR spectra. This deposited dataset is related to another dataset available at Zenodo (DOI: 10.5281/zenodo.18142785).

  PublisherDOI

• Code for "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-03-05

  articleOpen accessSenior author

  Scripts for the indicated paper titled "CLaSSiNet: A Computational Framework for High-Resolution Classification and Spatial Mapping of Heterogeneous Biological Network Architectures".

  PublisherDOI

• FLEXTAG: a small and self-renewable protein labeling system for anti-fading multi-color super-resolution imaging

  Nature Communications · 2026-03-09

  articleOpen accessSenior authorCorresponding

  Super-resolution fluorescence imaging enables visualization of subcellular structures and molecular interactions at the nanoscale, but its broader application has been hindered by long-standing limitations in current protein tagging systems, including rapid photobleaching, tag-induced artifacts, poor post-fixation labeling efficiency, and restricted multiplexing capability. Here, we present FLEXTAG (Fluorescent Labeling for Exchangeable, X-resilient Tagging in Advanced Generic Nanoscopy), a comprehensive protein labeling system comprising three orthogonal, ultrasmall (12-18 kDa), and self-renewable protein tags that collectively overcome these major limitations of existing tagging systems, enabling optimized multi-color super-resolution imaging. Through continuous exchange of organic fluorophores, FLEXTAG supports extended durations of high-resolution imaging in both live and fixed cells with minimal photobleaching. It is compatible with major super-resolution modalities, such as SIM, STED, STORM, and PAINT, and is applicable to a wide range of subcellular targets. To further address fixation-induced labeling inefficiency and background fluorescence, we developed an innovative protection-based fixation method and chemical blocking strategies that significantly preserve tag accessibility and enhance signal-to-noise ratio, improvements that are broadly applicable to other protein tagging systems. Altogether, FLEXTAG enables long-term tracking of dynamic behaviors and interactions of subcellular targets, as well as mapping of nanoscale protein organizations and cellular architecture, advancing both basic research and translational applications in cell biology.

  PublisherDOI

• Dataset 2 for "FLEXTAG: a small and self-renewable protein labeling system for anti-fading multi-color super-resolution imaging"

  Zenodo (CERN European Organization for Nuclear Research) · 2026-01-07

  datasetOpen accessSenior author

  Raw data for Main Figures 6,7, and Supplementary Figures 1-21. This deposited dataset is related to another dataset available at Zenodo (DOI: 10.5281/zenodo.18141385).

  PublisherDOI

• Actin depolymerization promotes axon regeneration by restoring axonal mitochondrial transport in mouse models of optic neuropathy

  Science Translational Medicine · 2026-02-25

  article

  Adult mammalian central nervous system (CNS) axons do not spontaneously regenerate after injury. We recently identified multiple genes that promote optic nerve regeneration, protect retinal ganglion cell (RGC) somata and axons, and preserve visual function in mouse glaucoma models. Here, we investigated the downstream molecular mechanisms driving the regenerative and neuroprotective effects of the actin depolymerization molecule gelsolin ( Gsn , one of the top up-regulated genes in regenerating RGCs) and the actin regulatory molecules (annexin A2, destrin, cofilin, profilin, latrunculin, and cytochalasin). Adeno-associated virus (AAV)–mediated specific expression of these genes in RGCs or topical delivery of small molecules promoted optic nerve regeneration and RGC protection in an optic nerve crush model and an ocular hypertension glaucoma mouse model. These regenerative effects were associated with a decrease in F-actin in axon shafts. Ex vivo mechanistic studies, furthermore, demonstrated that actin depolymerization enhances axonal mitochondrial transport in RGC axons, suggesting a mechanistic nodal point on which these pro-regeneration molecules converge. We showed that the natural compound latrunculin B targets this unified mechanism in both mouse and human RGCs to promote axon outgrowth. In addition, we detected up-regulated F-actin in aqueous humors of patients with severe glaucoma, emphasizing the translational potential of our findings.

  PublisherDOI

Frequent coauthors

• Taekjip Ha

  Howard Hughes Medical Institute

  55 shared

• Xiaowei Zhuang

  Harvard University Press

  38 shared

• Boran Han

  Amazon (United States)

  28 shared

• David M.J. Lilley

  University of Dundee

  18 shared

• Klaus Schulten

  16 shared

• Sungchul Hohng

  Seoul National University

  16 shared

• Jin Yu

  University of California, Irvine

  16 shared

• Michelle Nahas

  16 shared

Labs

• Zhou GroupPI

Education

• BS, Physics

  University of Science and Technology of China

• PhD, Physics

  University of Illinois Urbana-Champaign

• Postdoc, Chemistry and Chemical Biology

  Harvard University

Awards & honors

• Scialog Fellow for Advancing Bioimaging (2023)
• NIH Maximizing Investigators' Research Award (MIRA) (2021)
• Life Sciences Research Foundation (LSRF) Postdoctoral Fellow…
• NSF Center for the Physics of Living Cells (CPLC) Fellowship…
• Chinese Government Award for Outstanding Self-Financed Stude…