Ricardo Henriques

• PhD Biophysics
• Group Leader at University College London

Deep learning has established itself as the state-of-the-art approach for segmentation in bioimage analysis. However, these powerful algorithms present an intriguing paradox regarding image resolution: contrary to intuition, lower-resolution images can yield superior performance for specific image analysis carried out by deep learning. This phenome...

Visual proteomics (VP) aims to allow researchers to visualise, measure and analyse proteins in the context of cell and tissue structure in health and disease. VP is becoming a reality through technological advances across several domains, including in situ structural biology and correlative light and electron microscopy (CLEM). However, widespread...

The expanding scale and complexity of microscopy image datasets require accelerated analytical workflows. NanoPyx meets this need through an adaptive framework enhanced for high-speed analysis. At the core of NanoPyx, the Liquid Engine dynamically generates optimized central processing unit and graphics processing unit code variations, learning and...

From molecules to organelles, cells exhibit recurring structural motifs across multiple scales. Understanding these structures provides insights into their functional roles. While super-resolution microscopy can visualise such patterns, manual detection in large datasets is challenging and biased. We present the Structural Repetition Detector (SReD...

Generative models, such as diffusion models, have made significant advancements in recent years, enabling the synthesis of high‐quality realistic data across various domains. Here, the adaptation and training of a diffusion model on super‐resolution microscopy images are explored. It is shown that the generated images resemble experimental images,...

From molecules to organelles, cells exhibit recurring structural motifs across multiple scales. Understanding these structures provides insights into their functional roles. While super-resolution microscopy can visualise such patterns, manual detection in large datasets is challenging and biased. We present the Structural Repetition Detector (SReD...

In life sciences, tracking objects from movies enables researchers to quantify the behavior of single particles, organelles, bacteria, cells, and even whole animals. While numerous tools now allow automated tracking from video, a significant challenge persists in compiling, analyzing, and exploring the large datasets generated by these approaches....

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes, yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT (Phototoxicity Fitness Time Trial), an integrated framework combining a standardised experimental protocol with advanced image analysis to quantify light-induced cellular st...

Phototoxicity in live-cell fluorescence microscopy can compromise experimental outcomes, yet quantitative methods to assess its impact remain limited. Here we present PhotoFiTT (Phototoxicity Fitness Time Trial), an integrated framework combining a standardised experimental protocol with advanced image analysis to quantify light-induced cellular st...

Bacterial cell division requires recruitment of peptidoglycan (PG) synthases to the division site by the tubulin homologue, FtsZ. Septal PG synthases promote septum growth. FtsZ treadmilling is proposed to drive the processive movement of septal PG synthases and septal constriction in some bacteria; however, the precise mechanisms spatio-temporally...

Optical microscopy is an indispensable tool in life sciences research, but conventional techniques require compromises between imaging parameters like speed, resolution, field of view and phototoxicity. To overcome these limitations, data‐driven microscopes incorporate feedback loops between data acquisition and analysis. This review overviews how...

Fluorescence microscopy is essential for studying living cells, tissues and organisms. However, the fluorescent light that switches on fluorescent molecules also harms the samples, jeopardizing the validity of results – particularly in techniques such as super-resolution microscopy, which demands extended illumination. Artificial intelligence (AI)-...

This special feature of Open Biology, titled ‘Advances in Quantitative Bioimaging’, proposes an overview of the latest advancements in quantitative bioimaging techniques and their wide-ranging applications. The articles cover various topics, including modern imaging methods that enable visualization on a nanoscale, such as super-resolution microsco...

Deep learning has revolutionised the analysis of extensive microscopy datasets, yet challenges persist in the widespread adoption of these techniques. Many lack access to training data, computing resources, and expertise to develop complex models. We introduce DL4MicEverywhere, advancing our previous ZeroCostDL4Mic platform, to make deep learning m...

Using 3D single-molecule localization microscopy and live-cell imaging, we show that the Escherichia coli nucleoid adopts a condensed, membrane-associated configuration during rapid growth. To study the influence of different biosynthetic processes on nucleoid morphology and positioning, we recorded multi-colour super-resolution images during drug...

The expanding scale and complexity of microscopy image datasets require accelerated analytical workflows. NanoPyx meets this need through an adaptive framework enhanced for high-speed bioimage analysis. At the core of NanoPyx, the Liquid Engine dynamically generates optimised CPU and GPU-based code variations, learning and predicting the fastest ba...

To overcome the challenges posed by large and complex microscopy datasets, we have developed NanoPyx, an adaptive bioimage analysis framework designed for high-speed processing. At the core of NanoPyx is the Liquid Engine, an agent-based machine-learning system that predicts acceleration strategies for image analysis tasks. Unlike traditional singl...

Fluorescence microscopy, widely used in the study of living cells, tissues, and organisms, often faces the challenge of photodamage. This is primarily caused by the interaction between light and biochemical components during the imaging process, leading to compromised accuracy and reliability of biological results. Methods necessitating extended hi...

Bacterial cell division is mediated by the tubulin-homolog FtsZ, which recruits peptidoglycan (PG) synthesis enzymes to the division site. Septal PG synthases promote inward growth of the division septum, but the mechanisms governing the spatiotemporal regulation of these enzymes are poorly understood. Recent studies on various organisms have propo...

Correlative light and volume electron microscopy (vCLEM) is a powerful imaging technique that enables visualisation of fluorescently labelled proteins within their ultrastructural context on a subcellular level. Currently, expert microscopists find the alignment between acquisitions by manually placing landmarks on structures that can be recognised...

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a p...

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a p...

Unwanted sample drift is a common issue that plagues microscopy experiments, preventing accurate temporal visualization and quantification of biological processes. While multiple methods and tools exist to correct images post-acquisition, performing drift correction of 3D videos using open-source solutions remains challenging and time-consuming. He...

We propose symmetrical cationic trimethine cyanine dyes with β-substituents in the polymethine chain based on modified benzothiazole and benzoxazole heterocycles as probes for the detection and visualization of live and fixed cells by fluorescence microscopy. The spectral-luminescent properties of trimethine cyanines have been characterized for fre...

Unwanted sample drift is a common issue that plagues microscopy experiments, preventing accurate temporal quantification of biological processes. While multiple methods and tools exist to correct images post-acquisition, performing drift correction of large 3D videos using open-source solutions remains challenging and time-consuming. Here we presen...

Understanding the structure of supramolecular complexes provides insight into their functional capabilities and how they can be modulated in the context of disease. Super-resolution microscopy (SRM) excels in performing this task by resolving ultrastructural details at the nanoscale with molecular specificity. However, technical limitations, such a...

This work demonstrates and guides how to use a range of state-of-the-art artificial neural-networks to analyse bacterial microscopy images using the recently developed ZeroCostDL4Mic platform. We generated a database of image datasets used to train networks for various image analysis tasks and present strategies for data acquisition and curation, a...

Deep learning-based approaches are revolutionizing imaging-driven scientific research. However, the accessibility and reproducibility of deep learning-based workflows for imaging scientists remain far from sufficient. Several tools have recently risen to the challenge of democratizing deep learning by providing user-friendly interfaces to analyze n...

Natural killer (NK) cell responses depend on the balance of signals from inhibitory and activating receptors. However, how the integration of antagonistic signals occurs upon NK cell–target cell interaction is not fully understood. Here we provide evidence that NK cell inhibition via the inhibitory receptor Ly49A is dependent on its relative coloca...

The unicellular eukaryote Saccharomyces cerevisiae is an invaluable resource for the study of basic eukaryotic cellular and molecular processes. However, its small size compared to other eukaryotic organisms the study of subcellular structures is challenging. Expansion microscopy (ExM) holds great potential to study the intracellular architecture o...

In recent years, the development of analytical approaches to super-resolution microscopy has highlighted the possibility of recovering super-resolution information from short sequences of wide-field images. Our recently developed method, SRRF (Super-Resolution Radial Fluctuations), enables long-term live-cell imaging beyond the resolution limit wit...

In recent years, the development of analytical approaches to super-resolution microscopy has highlighted the possibility of recovering super-resolution information from short sequences of wide-field images. Our recently developed method, SRRF (Super-Resolution Radial Fluctuations), enables long-term live-cell imaging beyond the resolution limit wit...

The unicellular eukaryote S. cerevisiae is an invaluable resource for the study of basic eukaryotic cellular and molecular processes. However, due to its small size compared to other eukaryotic organisms the study of subcellular structures is challenging. Expansion microscopy (ExM) holds great potential to study the intracellular architecture of ye...

Understanding the structure of supramolecular complexes provides insight into their functional capabilities and how they can be modulated in the context of disease. Super-resolution microscopy (SRM) excels in performing this task by resolving ultrastructural details at the nanoscale with molecular specificity. However, technical limitations, such a...

Significance Cell division is an essential requirement for life. Division requires mechanical forces, often exerted by protein assemblies from the cell interior, that split a single cell into two. Using coarse-grained computer simulations and live cell imaging we define a distinct cell division mechanism—based on the forces generated by the superco...

Deep Learning (DL) is rapidly changing the field of microscopy, allowing for efficient analysis of complex data while often outperforming classical algorithms. This revolution has led to a significant effort to create user-friendly tools allowing biomedical researchers with little background in computer sciences to use this technology effectively....

The maker movement has reached the optics labs, empowering researchers to create and modify microscope designs and imaging accessories. 3D printing has a disruptive impact on the field, improving accessibility to fabrication technologies in additive manufacturing. This approach is particularly useful for rapid, low‐cost prototyping, allowing unprec...

Deep learning algorithms are powerful tools for analyzing, restoring and transforming bioimaging data. One promise of deep learning is parameter-free one-click image analysis with expert-level performance in a fraction of the time previously required. However, as with most emerging technologies, the potential for inappropriate use is raising concer...

Despite the central role of division in bacterial physiology, how division proteins work together as a nanoscale machine to divide the cell remains poorly understood. Cell division by cell wall synthesis proteins is guided by the cytoskeleton protein FtsZ, which assembles at mid-cell as a dense Z-ring formed of treadmilling filaments. However, alth...

Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources to train DL networks leads to an accessibility barrier that novice users often find difficult to ove...

Living systems propagate by undergoing rounds of cell growth and division. Cell division is at heart a physical process that requires mechanical forces, usually exerted by protein assemblies. Here we developed the first physical model for the division of archaeal cells, which despite their structural simplicity share machinery and evolutionary orig...

With an estimated three to five million human cases annually and the potential to infect domestic and wild animal populations, influenza viruses are one of the greatest health and economic burdens to our society, and pose an ongoing threat of large-scale pandemics. Despite our knowledge of many important aspects of influenza virus biology, there is...

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between...

The first step of cellular entry for the human immunodeficiency virus type-1 (HIV-1) occurs through the binding of its envelope protein (Env) with the plasma membrane receptor CD4 and co-receptor CCR5 or CXCR4 on susceptible cells, primarily CD4+ T cells and macrophages. Although there is considerable knowledge of the molecular interactions between...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

At the end of mitosis, eukaryotic cells must segregate the two copies of their replicated genome into two new nuclear compartments1. They do this either by first dismantling and later reassembling the nuclear envelope in an ‘open mitosis’ or by reshaping an intact nucleus and then dividing it into two in a ‘closed mitosis’2,3. Mitosis has been stud...

Proteasomal control of division in Archaea In eukaryotes, proteasome-mediated degradation of cell cycle factors triggers mitotic exit, DNA segregation, and cytokinesis, a process that culminates in abscission dependent on the protein ESCRT-III. By studying cell division in an archaeal relative of eukaryotes, Tarrason Risa et al. identified a role f...

Live-cell imaging has revolutionized our understanding of dynamic cellular processes in bacteria and eukaryotes. Although similar techniques have been applied to the study of halophilic archaea [1, 2, 3, 4, 5], our ability to explore the cell biology of thermophilic archaea has been limited by the technical challenges of imaging at high temperature...

Fluorescence microscopy has become a ubiquitous method to observe the location of specific molecular components within cells. However, the resolution of light microscopy is limited by the laws of diffraction to a few hundred nanometers, blurring most cellular details. Over the last two decades, several techniques - grouped under the 'super-resoluti...

Deep Learning (DL) methods are increasingly recognised as powerful analytical tools for microscopy. Their potential to outperform conventional image processing pipelines is now well established. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources, install multiple computational tools...

Localization based super‐resolution microscopy relies on the detection of individual molecules cycling between fluorescent and non‐fluorescent states. These transitions are commonly regulated by high‐intensity illumination, imposing constrains to imaging hardware and producing sample photodamage. Here, we propose single‐molecule self‐quenching as a...

Cellular mechanics play a crucial role in tissue homeostasis and are often misregulated in disease. Traction force microscopy is one of the key methods that has enabled researchers to study fundamental aspects of mechanobiology; however, traction force microscopy is limited by poor resolution. Here, we propose a simplified protocol and imaging stra...

Live-cell imaging has revolutionized our understanding of dynamic cellular processes in bacteria and eukaryotes. While similar techniques have recently been applied to the study of halophilic archaea, our ability to explore the cell biology of thermophilic archaea is limited, due to the technical challenges of imaging at high temperatures. Here, we...

Super-Resolution Microscopy enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for l...

Localization based super-resolution microscopy relies on the detection of individual molecules cycling between fluorescent and non-fluorescent states. These transitions are commonly regulated by high-intensity illumination, imposing constrains to imaging hardware and producing sample photodamage. Here, we propose single-molecule self-quenching as a...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

To achieve efficient binding and subsequent fusion, most enveloped viruses encode between one and five proteins. For many viruses, the clustering of fusion proteins—and their distribution on virus particles—is crucial for fusion activity. Poxviruses, the most complex mammalian viruses, dedicate 15 proteins to binding and membrane fusion4. However,...

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions. Here, we exploit the stereotypic arrangement of proteins in the nucl...

At the end of mitosis, eukaryotic cells must segregate both copies of their replicated genome into two new nuclear compartments (1). They do this either by first dismantling and later reassembling the nuclear envelope in a so called “open mitosis”, or by reshaping an intact nucleus and then dividing into two in a “closed mitosis” (2, 3). However, w...

Cellular mechanics play a crucial role in tissue morphogenesis and homeostasis and are often misregulated in disease. Traction force microscopy (TFM) is one of the key methods that has enabled researchers to study fundamental aspects of mechanobiology; however, the power of TFM is limited by poor resolution and low throughput. Here, we propose a si...

The archaeon Sulfolobus acidocaldarius is a relative of eukaryotes known to progress orderly through its cell division cycle despite lacking obvious CDK/cyclin homologues. Here, in exploring the mechanisms underpinning archaeal cell division cycle control, we show that the proteasome of S. acidocaldarius, like its eukaryotic counterpart, regulates...

Super-Resolution Microscopy enables non-invasive, molecule-specific imaging of the internal structure and dynamics of cells with sub-diffraction limit spatial resolution. One of its major limitations is the requirement for high-intensity illumination, generating considerable cellular phototoxicity. This factor considerably limits the capacity for l...

Artificial Intelligence based on Deep Learning (DL) is opening new horizons in biomedical research and promises to revolutionize the microscopy field. It is now transitioning from the hands of experts in computer sciences to biomedical researchers. Here, we introduce recent developments in DL applied to microscopy, in a manner accessible to non-exp...

To achieve efficient binding and subsequent fusion, most enveloped viruses encode between one and five proteins¹. For many viruses, the clustering of fusion proteins—and their distribution on virus particles—is crucial for fusion activity2,3. Poxviruses, the most complex mammalian viruses, dedicate 15 proteins to binding and membrane fusion⁴. Howev...

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.

In the version of this paper originally published, Figure 4a contained errors that were introduced during typesetting. The bottom 11° ThunderSTORM image is an xz view but was incorrectly labeled as xy, and the low x-axis value in the four line profiles was incorrectly set as –60 instead of –50. These errors have been corrected in the PDF and HTML v...

With the widespread uptake of two-dimensional (2D) and three-dimensional (3D) single-molecule localization microscopy (SMLM), a large set of different data analysis packages have been developed to generate super-resolution images. In a large community effort, we designed a competition to extensively characterize and rank the performance of 2D and 3...

Single-molecule localization microscopy (SMLM) techniques allow near molecular scale resolution (~ 20 nm) as well as precise and robust analysis of protein organization at different scales. SMLM hardware, analytics and probes have been the focus of a variety of studies and are now commonly used in laboratories across the world. Protocol reliability...

Single-molecule localization microscopy (SMLM) techniques allow near molecular scale resolution (~ 20 nm) as well as precise and robust analysis of protein organization at different scales. SMLM hardware, analytics and probes have been the focus of a variety of studies and are now commonly used in laboratories across the world. Protocol reliability...

Quantitative fluorescence and superresolution microscopy are often limited by insufficient data quality or artifacts. In this context, it is essential to have biologically relevant control samples to benchmark and optimize the quality of microscopes, labels and imaging conditions. Here we exploit the stereotypic arrangement of proteins in the nucle...

Combining and multiplexing microscopy approaches is crucial to understand cellular events, but requires elaborate workflows. Here, we present a robust, open-source approach for treating, labelling and imaging live or fixed cells in automated sequences. NanoJ-Fluidics is based on low-cost Lego hardware controlled by ImageJ-based software, making hig...