Location is information: an engineering framework for subcellular biology
- 1Bioengineering
- 2University of California, Berkeley
- 3Chan Zuckerberg Biohub
Abstract
The cell is not a well-mixed bag of molecules; its functions are compartmentalized across the nucleus, cytoplasm, and organelles. Despite this, the single-cell and spatial revolution has largely resolved cells only as wholes, averaging away the subcellular detail that drives cellular behavior. Resolving where a molecule resides within a cell, and keeping that information linked to the originating cell, is a next frontier of single-cell measurement. Contemporary approaches span physical compartment fractionation, live-cell microsampling, coordinate-defined imaging, low-loss single-cell mass spectrometry, and barcoded multiomics. Physical compartment fractionation directly preserves subcellular origin of measured material, whereas coordinate-defined methods span cell-level spatial mapping to true subcellular measurement; low-loss single-cell mass spectrometry and barcoded multiomics generally collapse subcellular origin; however, these methods establish current benchmarks for molecular depth and multiplexing scale. Because these modalities optimize different readouts and report different performance metrics, direct comparison across technologies remains challenging. In this Critical Review, we compare these technologies by how they preserve the link between a readout, its subcellular source and the originating cell rather than by the molecule measured. We introduce a framework that maps 32 platforms according to two axes, the indexing mechanism (molecular barcode, spatial coordinate, physical address, or tracked cell) and the type of information preserved, from subcellular location to global molecular depth and scale. The framework defines four classes including coordinate-defined subcellular measurement, physical subcellular access, low-loss molecular profiling, and molecular indexing for global multiomics. The latter two serve as adjacent reference classes that inform the recovery and scale requirements for future subcellular platforms. Comparison of these technologies identifies deep, organelle-resolved measurement that remains indexed to the cell of origin at biologically relevant throughput as a central unmet capability. We conclude with engineering guidelines and minimum reporting metrics to guide the development of platforms that address this gap. 1. Introduction Population-level assays average over molecular differences among individual cells, obscuring heterogeneity in cell state, regulatory potential and spatial organization. Single-cell technologies were developed to recover this variation and now measure RNA, chromatin accessibility, proteins, metabolites and tissue location at single cell resolution (1-4). Yet many biological processes are organized below the scale of the whole cell. Nuclear-cytoplasmic partitioning, organelle remodeling, localized RNA translation, compartment-specific protein signaling and spatially restricted metabolism depend on where molecules reside within a cell, not only on whether they are present (5-9). Microscopy has long resolved molecular localization within individual cells, with highly multiplexed imaging methods such as MERFISH and seqFISH+ extending this capability to hundreds to thousands of molecular targets (10,11). The challenge is therefore not only to measure more molecular features per cell, but to preserve the relationship between a molecular readout, its subcellular source and the cell from which it came.
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BibTeX
@misc{islam2026location,
title = {{Location is information: an engineering framework for subcellular biology}},
author = {Md Nazibul Islam and Xin Wang and Amy E. Herr},
howpublished = {ChemRxiv},
year = {2026},
month = sep,
doi = {10.26434/chemrxiv.15008406/v1},
url = {https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008406/v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - Location is information: an engineering framework for subcellular biology
AU - Md Nazibul Islam
AU - Xin Wang
AU - Amy E. Herr
PY - 2026
DA - 2026/09/07
PB - ChemRxiv
DO - 10.26434/chemrxiv.15008406/v1
UR - https://chemrxiv.org/doi/full/10.26434/chemrxiv.15008406/v1
AB - The cell is not a well-mixed bag of molecules; its functions are compartmentalized across the nucleus, cytoplasm, and organelles. Despite this, the single-cell and spatial revolution has largely resolved cells only as wholes, averaging away the subcellular detail that drives cellular behavior. Resolving where a molecule resides within a cell, and keeping that information linked to the originating cell, is a next frontier of single-cell measurement. Contemporary approaches span physical compartment fractionation, live-cell microsampling, coordinate-defined imaging, low-loss single-cell mass spectrometry, and barcoded multiomics. Physical compartment fractionation directly preserves subcellular origin of measured material, whereas coordinate-defined methods span cell-level spatial mapping to true subcellular measurement; low-loss single-cell mass spectrometry and barcoded multiomics generally collapse subcellular origin; however, these methods establish current benchmarks for molecular depth and multiplexing scale. Because these modalities optimize different readouts and report different performance metrics, direct comparison across technologies remains challenging. In this Critical Review, we compare these technologies by how they preserve the link between a readout, its subcellular source and the originating cell rather than by the molecule measured. We introduce a framework that maps 32 platforms according to two axes, the indexing mechanism (molecular barcode, spatial coordinate, physical address, or tracked cell) and the type of information preserved, from subcellular location to global molecular depth and scale. The framework defines four classes including coordinate-defined subcellular measurement, physical subcellular access, low-loss molecular profiling, and molecular indexing for global multiomics. The latter two serve as adjacent reference classes that inform the recovery and scale requirements for future subcellular platforms. Comparison of these technologies identifies deep, organelle-resolved measurement that remains indexed to the cell of origin at biologically relevant throughput as a central unmet capability. We conclude with engineering guidelines and minimum reporting metrics to guide the development of platforms that address this gap. 1. Introduction Population-level assays average over molecular differences among individual cells, obscuring heterogeneity in cell state, regulatory potential and spatial organization. Single-cell technologies were developed to recover this variation and now measure RNA, chromatin accessibility, proteins, metabolites and tissue location at single cell resolution (1-4). Yet many biological processes are organized below the scale of the whole cell. Nuclear-cytoplasmic partitioning, organelle remodeling, localized RNA translation, compartment-specific protein signaling and spatially restricted metabolism depend on where molecules reside within a cell, not only on whether they are present (5-9). Microscopy has long resolved molecular localization within individual cells, with highly multiplexed imaging methods such as MERFISH and seqFISH+ extending this capability to hundreds to thousands of molecular targets (10,11). The challenge is therefore not only to measure more molecular features per cell, but to preserve the relationship between a molecular readout, its subcellular source and the cell from which it came.
ER -