EVOS, HCS & Spatial Platform Literature Roundup 2026

This roundup summaries recent peer-reviewed literature on three connected areas: EVOS fluorescence microscopy, high-content screening (HCS) and spatial biology platforms. Each paper is linked to its publisher or open repository. Plankton & Zoom does not host paywalled content.

1. EVOS and fluorescence microscopy

Fluorescence microscopes such as the Thermo Fisher EVOS M3000, M5000 and S1000 lines remain common in UK cell-biology labs because they combine brightfield, phase and fluorescence in compact, all-in-one enclosures. Two recent papers show how researchers are pushing these systems beyond simple imaging.

Accessible cytometry of adherent cells using fluorescence microscopes

Foyt & Kuang, Scientific Reports, May 2025.

The authors demonstrate that a standard fluorescence microscope — and by extension a benchtop system such as the EVOS M5000 — can be turned into a cytometry-like tool for adherent cells. By capturing fields across a plate and using open-source segmentation, they extract single-cell fluorescence intensity distributions without a dedicated flow cytometer. The workflow is particularly useful for labs that want population-level data from small sample numbers or fragile adherent cultures. It also highlights the value of systems with uniform illumination and reproducible stage positioning — features EVOS users often cite as reasons for choosing the platform over open-bench alternatives.

Read the paper: Scientific Reports (exa.ai listing).

A high-throughput imaging and quantification pipeline for the EVOS platform

Klimaj et al., PLOS One, 2020.

Although not from 2025, this paper remains the clearest published blueprint for scaling EVOS imaging across multi-well plates. The authors describe an automated acquisition and analysis pipeline that sits on top of the EVOS FL Auto system, including segmentation, feature extraction and quality control. For UK labs buying a cell-culture microscope with an eye toward later automation, the paper is a practical sanity check: it shows which acquisition parameters matter for reproducibility and how much downstream analysis work is still required.

Read the paper: PLOS One.

Spectral multiplex fluorescence imaging with the EVOS S1000

Thermo Fisher technology spotlight, November 2025.

The EVOS S1000 is the spectral-multiplex member of the EVOS line, designed to unmix up to four fluorescent channels without filter-cube swaps. The manufacturer's technology note explains how spectral unmixing reduces bleed-through in multi-marker assays, a common problem when moving from two-colour to four-colour experiments. While this is vendor material rather than independent research, it is useful background when comparing the S1000 against alternative spectral systems such as the Revvity Opera Phenix or Nikon ECLIPSE Ji.

Read the note: Life Science Xchange.

2. High-content screening (HCS)

HCS bridges microscopy and assay biology by imaging thousands of wells and extracting quantitative features per cell. Recent papers focus on 3D models, artificial-intelligence analysis, and the practical problem of moving from 2D monolayers to spheroids and organoids.

HCS-3DX: AI-driven automated 3D-oid high-content screening

Diosdi, Toth, Horvath & colleagues, Nature Communications, October 2025.

HCS-3DX is presented as a next-generation high-content screening platform for screening 3D-oids — spheroids, organoids, tumouroids and assembloids — at scale. The paper argues that only about 1% of high-content publications currently use 3D-oids, largely because of handling, imaging and analysis bottlenecks. HCS-3DX integrates automated 3D-oid transfer, confocal imaging and deep-learning segmentation to make 3D phenotypic screening practical. For UK labs working in cancer immunotherapy, regenerative medicine or drug discovery, the paper is a useful marker of where the field is heading: fixed-endpoint 2D assays are being replaced by 3D, time-resolved, AI-analysed screens.

Read the paper: Nature Communications.

An automated HCS platform for spheroids at subcellular resolution

PLOS One, 2024.

This study describes a complete high-content screening (HCS) assay platform — from spheroid culture through confocal imaging to feature extraction — with the goal of resolving subcellular structures inside 3D aggregates. The work matters for anyone choosing an organoid microscope because it spells out the minimum optical and stage requirements: water-immersion or long-working-distance objectives, controlled CO₂ and temperature, and software that can segment nuclei inside dense 3D volumes.

Read the paper: PLOS One.

Senescence-modulating drug development with quantitative HCA and HTS

Communications Biology, 2025.

Cellular senescence is a growing target in ageing and oncology research, and this paper is a practical example of how quantitative high-content analysis (HCA) can accelerate drug discovery. The authors combine quantitative high-content analysis (HCA) with high-throughput screening to identify compounds that modulate senescence markers. The paper is a good example of how HCS is being repurposed for ageing biology — a topic that also appears on our sister site Longevity Tortoise — and shows the importance of multi-parametric readouts such as SA-β-gal, p16 and proliferation indices.

Read the paper: Communications Biology.

Scalable fixed-feature extraction from large-scale HCS screens

Comolet et al., iScience, 2024.

Large high-content screening (HCS) screens generate image-derived features that are only useful if they can be extracted consistently. This paper introduces a pipeline for fixed-feature extraction that is both efficient and scalable across thousands of wells. The practical takeaway: the imaging hardware is only half the system; the other half is the data pipeline. Labs evaluating HCS platforms should ask vendors not just about objective magnification, but also about batch analysis, feature reproducibility and export formats.

Read the paper: iScience.

3. Spatial biology platforms

Spatial transcriptomics and multiplexed imaging are moving from proof-of-concept to routine tools. The 2025 literature is dominated by methods that improve resolution, integrate multi-slice data, or combine histology with molecular readouts.

Thor: cell-level investigation of spatial transcriptomics and histology

Zhang et al., Nature Communications, August 2025.

Thor is a computational spatial biology platform that links spatial transcriptomics data with matched histology images at single-cell resolution. Instead of treating RNA maps and H&E slides as separate data layers, Thor uses the histology image to refine cell boundaries and assign transcripts more accurately. The approach improves cell-type calls in dense tissues and is relevant for cancer research groups that already have access to H&E sections but want to add spatial RNA data without re-sectioning.

Read the paper: Nature Communications.

SpaCross: spatial structures and batch-effect correction in multi-slice SRT

Communications Biology, September 2025.

Spatial transcriptomics experiments often run across multiple tissue slices. SpaCross addresses the batch effects that arise between slices and provides tools to reconstruct spatial domains consistently. For UK labs building spatial atlases or comparing tumour cores across a patient cohort, the paper is directly relevant: it turns a preprocessing headache into a solved step.

Read the paper: Communications Biology.

Spotiphy: single-cell spatial whole transcriptomics across an entire section

Yang et al., Nature Methods, March 2025.

Spotiphy targets a persistent limitation of sequencing-based spatial transcriptomics platforms: spots often contain several cells, blurring single-cell resolution. The method uses a generative model to infer transcriptomes at single-cell density across the whole tissue section. The result is closer to the resolution of image-based methods such as MERFISH or Xenium while retaining the genome-wide coverage of Visium-style approaches. The paper is a useful read for anyone choosing between spatial biology platforms.

Read the paper: Nature Methods.

Spatially informed graph transformers for SRT

Communications Biology, 2025.

This method adds spatial neighbourhood information to graph-transformer models used in spatial transcriptomics analysis., improving the accuracy of spatial-domain identification and cell-type deconvolution. The broader message is that spatial biology is becoming an AI-driven field: raw transcript counts are no longer enough; models now use location, neighbourhood and tissue morphology to make better biological calls.

Read the paper: Communications Biology.

Multiplexed spatial mapping of chromatin, transcriptome and proteins

Guo et al., Nature Methods, January 2025.

Multi-omics spatial biology methods are beginning to map chromatin features, RNA and proteins on the same tissue section. The work points toward a future where a single slide can reveal epigenetic state, gene expression and protein localisation simultaneously. For microscope buyers, this underlines the importance of platforms that can be upgraded for additional rounds of imaging and staining.

Read the paper: Nature Methods.

What this means for UK labs

Three trends are clear from the 2025 literature:

• Fluorescence microscopes are becoming quantitative cytometers. EVOS and similar systems are no longer just for pretty pictures; they are being used for plate-level, single-cell analysis.
• HCS is going 3D. Spheroid and organoid screening is moving from niche to mainstream, driven by AI segmentation and automated handling.
• Spatial biology is resolving finer detail. Single-cell resolution, multi-slice integration and multi-omics mapping are the next frontiers.

For labs planning purchases, the practical implication is to buy systems that can grow: enough fluorescence channels for future multiplexing, software APIs for custom analysis, and upgrade paths for 3D or spatial workflows. Our fluorescence microscope buyer guide and spatial biology guide cover these decisions in more detail.

Frequently asked questions

What is EVOS microscopy?

EVOS microscopy refers to the Invitrogen EVOS line of all-in-one cell-imaging systems from Thermo Fisher Scientific. They combine brightfield, phase-contrast and fluorescence imaging in a compact, enclosed benchtop unit and are widely used in UK cell-biology labs for routine culture checks and quantitative fluorescence assays.

What is high-content screening (HCS)?

High-content screening (HCS) is an automated microscopy approach that captures images across many wells or samples and extracts quantitative, often single-cell, features. It is commonly used in drug discovery to measure morphology, fluorescence intensity, texture and spatial patterns at scale.

What is spatial transcriptomics?

Spatial transcriptomics maps gene expression back onto the physical location of cells within a tissue section. Unlike single-cell sequencing, it preserves the spatial code of how cells interact, making it valuable for cancer, developmental biology and tissue-mapping projects.

Why are 3D cell models important in HCS?

Three-dimensional models such as spheroids, organoids and tumouroids better mimic in vivo tissue architecture, including oxygen gradients, cell-cell signalling and drug penetration. Recent HCS platforms like HCS-3DX aim to make 3D phenotypic screening as routine as traditional 2D assays.

How do spatial biology platforms differ from each other?

Sequencing-based platforms such as 10x Visium, Stereo-seq and Slide-Seq offer genome-wide coverage across tissue spots. Image-based methods such as MERFISH, seqFISH, CosMx and Xenium provide higher spatial resolution and single-cell or subcellular detail, usually for a predefined panel of genes. The best choice depends on whether the project needs breadth, resolution or both.

Which EVOS model is best for fluorescence multiplexing?

The EVOS S1000 is the spectral-multiplex model in the line, designed to separate up to four fluorescent channels without swapping filter cubes. For labs running multi-marker fixed-cell or live-cell assays, it is the most flexible option in the EVOS family.

What is the difference between HCS and HCA?

High-content screening (HCS) usually implies a screening workflow across many compounds or conditions. High-content analysis (HCA) refers to the downstream quantification and interpretation of the image-derived features. In practice the terms are often used interchangeably.

References

1. Foyt DA, Kuang YP. Accessible and accurate cytometry analysis of adherent cells using fluorescence microscopes. Scientific Reports. 2025.
2. Klimaj S et al. A high-throughput imaging and quantification pipeline for the EVOS imaging platform. PLOS One. 2020.
3. Diosdi A et al. HCS-3DX, a next-generation AI-driven automated 3D-oid high-content screening system. Nature Communications. 2025.
4. An automated high-content screening and assay platform for the analysis of spheroids at subcellular resolution. PLOS One. 2024.
5. An effective system for senescence modulating drug development using quantitative high-content analysis and high-throughput screening. Communications Biology. 2025.
6. Comolet G et al. A highly efficient, scalable pipeline for fixed feature extraction from large-scale high-content imaging screens. iScience. 2024.
7. Zhang P et al. Thor: a platform for cell-level investigation of spatial transcriptomics and histology. Nature Communications. 2025.
8. SpaCross deciphers spatial structures and corrects batch effects in multi-slice spatially resolved transcriptomics. Communications Biology. 2025.
9. Yang J et al. Spotiphy enables single-cell spatial whole transcriptomics across an entire section. Nature Methods. 2025.
10. Spatially informed graph transformers for spatially resolved transcriptomics. Communications Biology. 2025.
11. Guo P et al. Multiplexed spatial mapping of chromatin features, transcriptome and proteins in tissues. Nature Methods. 2025.