Cryoelectron Microscopy as a Functional Instrument for Systems Biology, Structural Analysis & Experimental Manipulations with Living Cells. A comprehensive review of the current works

The aim of this paper is to give an introductory review of the cryoelectron microscopy as a complex data source for the most of the system biology branches, including the most perspective non-local approaches known as “localomics” and “dynamomics”. A brief summary of various cryoelectron mi-croscopy methods and corresponding system biological ap-proaches is given in the text. The above classification can be considered as a useful framework for the primary comprehen-sions about cryoelectron microscopy aims and instrumental tools. We do not discuss any of these concepts in details, but merely point out that their methodological complexity follows only from the structure-functional complexity of biological systems which are investigated in this manner. We also postu-late that one can employ some of the cryoelectron microscopic techniques not only for observation, but also for modification and structural refunctionalization of some biological and similar soft matter objects and microscopic samples. In other worlds, we start with the cryoelectron microscopy as a tool for the sys-tem biology and progress to its applying as an instrument for system biology and functional biomimetics; i.e. “system cryobi-ology” goes over into “synthetic cryobiology” or “cryogenic biomimetics”. All these conclusions can be deduced from the most recent works of the latest years, including just submitted foreign papers. This article provides an up-to-date description of the conceptual basis for the novel view on the computational cryoelectron microscopy (in silico) approaches and the data mining principles which lie at the very foundation of modern structural analysis and reconstruction.

💡 Research Summary

The manuscript presents a forward‑looking review that positions cryo‑electron microscopy (cryo‑EM) as a central, multifunctional data source for contemporary systems biology. Beginning with a concise history of cryo‑EM, the authors outline recent technological breakthroughs—direct electron detectors, phase plates, automated data acquisition, and advanced sample preparation methods such as cryo‑FIB—that have expanded the technique from high‑resolution single‑particle analysis to cryo‑electron tomography (cryo‑ET), micro‑crystallography, and time‑resolved studies.

The core argument is that these diverse cryo‑EM modalities can be integrated with non‑local “omics” streams—genomics, transcriptomics, proteomics, metabolomics—to create a unified framework the authors label “localomics” (spatially distributed omics) and “dynamomics” (temporally distributed omics). In this framework, three‑dimensional density maps generated by cryo‑EM are coupled with large‑scale metadata describing cellular context, experimental conditions, and molecular interaction networks. The authors propose a stepwise pipeline: (1) deep‑learning‑driven particle picking and classification, (2) Bayesian or maximum‑likelihood 3D reconstruction, (3) in silico cryo‑EM simulations for hypothesis testing, (4) a standardized metadata schema that links EMDB/PDB entries with public omics repositories, and (5) downstream data‑mining, network analysis, and functional annotation.

A distinctive and speculative portion of the review suggests that cryo‑EM can move beyond passive imaging to actively remodel biological specimens. The authors cite emerging approaches such as electron‑beam‑induced structural rearrangement, low‑temperature laser heating to trigger controlled protein assembly, and focused ion‑beam milling to sculpt nanoscale architectures within vitrified samples. If realized, these capabilities would transform cryo‑EM from a “system biology observation tool” into a “synthetic cryobiology platform,” enabling what the authors term “cryogenic biomimetics.”

The manuscript acknowledges substantial technical hurdles. Maintaining vitreous ice while delivering sufficient energy for manipulation risks radiation damage and devitrification; thus, new sample‑preparation protocols, beam‑modulation algorithms, and low‑temperature chemistry models are required. Moreover, the sheer volume of data—hundreds of gigabytes per tomogram, terabytes of combined omics datasets—demands high‑performance computing, cloud‑based storage, and robust, open‑source pipelines (e.g., RELION, CryoSPARC, Scipion) that can interoperate with bioinformatics tools. The authors highlight ongoing community efforts to standardize metadata, develop cross‑database APIs, and create shared repositories that bridge structural and functional data.

In the concluding section, the authors synthesize recent literature (primarily from the last five years) to argue that cryo‑EM is poised to become the linchpin for integrative, multiscale models of cellular function. They envision a future where artificial‑intelligence‑driven automation, cloud‑based collaborative platforms, and convergence with synthetic biology will give rise to “cryogenic biomimetics”—engineered, cryo‑preserved systems that mimic or surpass natural biological functions. To achieve this vision, the paper stresses the necessity of methodological standardization, interdisciplinary collaboration, and sustained investment in computational infrastructure. Overall, the review offers a broad, concept‑driven roadmap that situates cryo‑EM at the intersection of structural biology, systems biology, and emerging synthetic cryobiology, while also candidly exposing the experimental and computational challenges that must be overcome.