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Gold standard imaging modalities in biological field are based on fluorescence signals providing high specificity and high resolution. Recently, Fluorescence Microscopy has been combined with microfluidics to develop instrumentations called Imaging Flow Cytometers, high-throughput tools that supply bright-field, darkfield and multiple-channels fluorescence images of each single cell passing in the Field Of View (FOV). Nevertheless, Fluorescence Microscopy has some drawbacks as phototoxicity, photobleaching, expensive costs for sample preparations and also the a-priori knowledge of the tags to be used. For these reasons label-free imaging methods greatly increase in the recent years as the Quantitative Phase Imaging (QPI) technologies for microscopy. One of the optical techniques to achieve QPI is Digital Holography. DH in microscopy has several advantages such as the possibility to numerically scan the focal distance, a properties that open to the integration of DH in microfluidics. Indeed DH combined with microfluidic circuits allows to image particles or cells flowing into the FOV at different depths. Here the capabilities of label-free single-cell imaging by DH are presented and their implications on next future biomedical applications discussed. Static or in-flow configurations will be showed describing recent results and perspectives also in combination with Artificial Intelligence architectures for future applications in biomedical and clinical fields.

This study presents an innovative methodology to analyze a blood sample from a healthy donor, providing a quantitative characterization of white blood cells (WBCs). It aims to evaluate the effectiveness of holographic quantitative phase imaging (QPI) flow cytometry (FC) in examining phase-contrast maps at the cellular level, thereby enabling the identification and classification of granulocyte types. Additionally, we demonstrate that an unsupervised method can differentiate granulocyte sub-types, i.e., neutrophils and eosinophils. The results instill strong confidence in the potential future use of QPI FC for liquid biopsies and/or for assessing the heterogeneity of WBCs and, more broadly, to facilitate label-free blood tests.

Lab-on-a-Chip microfluidic devices present an innovative and cost-effective platform in the current trend of miniaturization and simplification of imaging flow cytometry; they are excellent candidates for high-throughput single-cell analysis. In such microfluidic platforms, cell tracking becomes a fundamental tool for investigating biophysical processes, from intracellular dynamics to the characterization of cell motility and migration. However, high-throughput and long-term cell tracking puts a high demand on the consumption of computing resources. Here, we propose a novel strategy to achieve rapid 3D cell localizations along the microfluidic channel. This method is based on the spatiotemporal manipulation of recorded holographic interference fringes, and it allows fast and precise localization of cells without performing complete holographic reconstruction. Conventional holographic tracking is typically based on the phase contrast obtained by decoupling the calculation of optical axial and transverse coordinates. Computing time and resource consumption may increase because all the frames need to be calculated in the Fourier domain. In our proposed method, the 2D transverse positions are directly located by morphological calculation based on the hologram. The complex-amplitude wavefronts are directly reconstructed by spatiotemporal phase shifting to calculate the axial position by the refocusing criterion. Only spatial calculation is considered in the proposed method. We demonstrate that the computational time of transverse tracking is only one-tenth of the conventional method, while the total computational time of the proposed method decreases up to 54% with respect to the conventional approach. The proposed approach can open the route for analyzing flow cytometry in quantitative phase microscopy assays., Competing Interests: The authors have no conflicts to disclose., (© 2024 Author(s).)

Lysosomes are the terminal end of catabolic pathways in the cell, as well as signaling centers performing important functions such as the recycling of macromolecules, organelles, and nutrient adaptation. The importance of lysosomes in human health is supported by the fact that the deficiency of most lysosomal genes causes monogenic diseases called as a group Lysosomal Storage Diseases (LSDs). A common phenotypic hallmark of LSDs is the expansion of the lysosomal compartment that can be detected by using conventional imaging methods based on immunofluorescence protocols or overexpression of tagged lysosomal proteins. These methods require the alteration of the cellular architecture (i.e., due to fixation methods), can alter the behavior of cells (i.e., by the overexpression of proteins), and require sample preparation and the accurate selection of compatible fluorescent markers in relation to the type of analysis, therefore limiting the possibility of characterizing cellular status with simplicity. Therefore, a quantitative and label-free methodology, such as Quantitative Phase Imaging through Digital Holographic (QPI-DH), for the microscopic imaging of lysosomes in health and disease conditions may represent an important advance to study and effectively diagnose the presence of lysosomal storage in human disease. Here we proof the effectiveness of the QPI-DH method in accomplishing the detection of the lysosomal compartment using mouse embryonic fibroblasts (MEFs) derived from a Mucopolysaccharidosis type III-A (MSP-IIIA) mouse model, and comparing them with wild-type (WT) MEFs. We found that it is possible to identify label-free biomarkers able to supply a first pre-screening of the two populations, thus showing that QPI-DH can be a suitable candidate to surpass fluorescent drawbacks in the detection of lysosomes dysfunction. An appropriate numerical procedure was developed for detecting and evaluate such cellular substructures from in vitro cells cultures. Results reported in this study are encouraging about the further development of the proposed QPI-DH approach for such type of investigations about LSDs., (© 2024 International Society for Advancement of Cytometry.)

Accumulation of bioavailable heavy metals in aquatic environment poses a serious threat to marine communities and human health due to possible trophic transfers through the food chain of toxic, non-degradable, exogenous pollutants. Copper (Cu) is one of the most spread heavy metals in water, and can severely affect primary producers at high doses. Here we show a novel imaging test to assay the dose-dependent effects of Cu on live microalgae identifying stress conditions when they are still capable of sustaining a positive growth. The method relies on Fourier Ptychographic Microscopy (FPM), capable to image large field of view in label-free phase-contrast mode attaining submicron lateral resolution. We uniquely combine FPM with a new multi-scale analysis method based on fractal geometry. The system is able to provide ensemble measurements of thousands of diatoms in the liquid sample simultaneously, while ensuring at same time single-cell imaging and analysis for each diatom. Through new image descriptors, we demonstrate that fractal analysis is suitable for handling the complexity and informative power of such multiscale FPM modality. We successfully tested this new approach by measuring how different concentrations of Cu impact on Skeletonema pseudocostatum diatom populations isolated from the Sarno River mouth., (© 2024. The Author(s).)

Breast cancer is one of the most spread and monitored pathologies in high-income countries. After breast biopsy, histological tissue is stored in paraffin, sectioned and mounted. Conventional inspection of tissue slides under benchtop light microscopes involves paraffin removal and staining, typically with H&E. Then, expert pathologists are called to judge the stained slides. However, paraffin removal and staining are operator-dependent, time and resources consuming processes that can generate ambiguities due to non-uniform staining. Here we propose a novel method that can work directly on paraffined stain-free slides. We use Fourier Ptychography as a quantitative phase-contrast microscopy method, which allows accessing a very wide field of view (i.e., mm 2 ) in one single image while guaranteeing high lateral resolution (i.e., 0.5 µm). This imaging method is multi-scale, since it enables looking at the big picture, i.e. the complex tissue structure and connections, with the possibility to zoom-in up to the single-cell level. To handle this informative image content, we introduce elements of fractal geometry as multi-scale analysis method. We show the effectiveness of fractal features in describing and classifying fibroadenoma and breast cancer tissue slides from ten patients with very high accuracy. We reach 94.0 ± 4.2% test accuracy in classifying single images. Above all, we show that combining the decisions of the single images, each patient's slide can be classified with no error. Besides, fractal geometry returns a guide map to help pathologist to judge the different tissue portions based on the likelihood these can be associated to a breast cancer or fibroadenoma biomarker. The proposed automatic method could significantly simplify the steps of tissue analysis and make it independent from the sample preparation, the skills of the lab operator and the pathologist., Competing Interests: The authors have no conflict of interests to declare., (© 2024 The Authors.)

Nowadays, label-free imaging flow cytometry at the single-cell level is considered the stepforward lab-on-a-chip technology to address challenges in clinical diagnostics, biology, life sciences and healthcare. In this framework, digital holography in microscopy promises to be a powerful imaging modality thanks to its multi-refocusing and label-free quantitative phase imaging capabilities, along with the encoding of the highest information content within the imaged samples. Moreover, the recent achievements of new data analysis tools for cell classification based on deep/machine learning, combined with holographic imaging, are urging these systems toward the effective implementation of point of care devices. However, the generalization capabilities of learning-based models may be limited from biases caused by data obtained from other holographic imaging settings and/or different processing approaches. In this paper, we propose a combination of a Mask R-CNN to detect the cells, a convolutional auto-encoder, used to the image feature extraction and operating on unlabelled data, thus overcoming the bias due to data coming from different experimental settings, and a feedforward neural network for single cell classification, that operates on the above extracted features. We demonstrate the proposed approach in the challenging classification task related to the identification of drug-resistant endometrial cancer cells.

Despite remarkable progresses in quantitative phase imaging (QPI) microscopes, their wide acceptance is limited due to the lack of specificity compared with the well-established fluorescence microscopy. In fact, the absence of fluorescent tag prevents to identify subcellular structures in single cells, making challenging the interpretation of label-free 2D and 3D phase-contrast data. Great effort has been made by many groups worldwide to address and overcome such limitation. Different computational methods have been proposed and many more are currently under investigation to achieve label-free microscopic imaging at single-cell level to recognize and quantify different subcellular compartments. This route promises to bridge the gap between QPI and FM for real-world applications., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

In-flow phase-contrast tomography provides a 3D refractive index of label-free cells in cytometry systems. Its major limitation, as with any quantitative phase imaging approach, is the lack of specificity compared to fluorescence microscopy, thus restraining its huge potentialities in single-cell analysis and diagnostics. Remarkable results in introducing specificity are obtained through artificial intelligence (AI), but only for adherent cells. However, accessing the 3D fluorescence ground truth and obtaining accurate voxel-level co-registration of image pairs for AI training is not viable for high-throughput cytometry. The recent statistical inference approach is a significant step forward for label-free specificity but remains limited to cells' nuclei. Here, a generalized computational strategy based on a self-consistent statistical inference to achieve intracellular multi-specificity is shown. Various subcellular compartments (i.e., nuclei, cytoplasmic vacuoles, the peri-vacuolar membrane area, cytoplasm, vacuole-nucleus contact site) can be identified and characterized quantitatively at different phases of the cells life cycle by using yeast cells as a biological model. Moreover, for the first time, virtual reality is introduced for handling the information content of multi-specificity in single cells. Full fruition is proofed for exploring and interacting with 3D quantitative biophysical parameters of the identified compartments on demand, thus opening the route to a metaverse for 3D microscopy., (© 2023 The Authors. Small Methods published by Wiley-VCH GmbH.)

To efficiently tackle certain tumor types, finding new biomarkers for rapid and complete phenotyping of cancer cells is highly demanded. This is especially the case for the most common pediatric solid tumor of the sympathetic nervous system, namely, neuroblastoma (NB). Liquid biopsy is in principle a very promising tool for this purpose, but usually enrichment and isolation of circulating tumor cells in such patients remain difficult due to the unavailability of universal NB cell-specific surface markers. Here, we show that rapid screening and phenotyping of NB cells through stain-free biomarkers supported by artificial intelligence is a viable route for liquid biopsy. We demonstrate the concept through a flow cytometry based on label-free holographic quantitative phase-contrast microscopy empowered by machine learning. In detail, we exploit a hierarchical decision scheme where at first level NB cells are classified from monocytes with 97.9% accuracy. Then we demonstrate that different phenotypes are discriminated within NB class. Indeed, for each cell classified as NB its belonging to one of four NB sub-populations (i.e., CHP212, SKNBE2, SHSY5Y, and SKNSH) is evaluated thus achieving accuracy in the range 73.6%-89.1%. The achieved results solve the realistic problem related to the identification circulating tumor cell, i.e., the possibility to recognize and detect tumor cells morphologically similar to blood cells, which is the core issue in liquid biopsy based on stain-free microscopy. The presented approach operates at lab-on-chip scale and emulates real-world scenarios, thus representing a future route for liquid biopsy by exploiting intelligent biomedical imaging., Competing Interests: The authors have no conflicts to disclose., (© 2023 Author(s).)

Image-based identification of circulating tumor cells in microfluidic cytometry condition is one of the most challenging perspectives in the Liquid Biopsy scenario. Here we show a machine learning-powered tomographic phase imaging flow cytometry system capable to provide high-throughput 3D phase-contrast tomograms of each single cell. In fact, we show that discrimination of tumor cells against white blood cells is potentially achievable with the aid of artificial intelligence in a label-free flow-cyto-tomography method. We propose a hierarchical machine learning decision-maker, working on a set of features calculated from the 3D tomograms of the cells' refractive index. We prove that 3D morphological features are adequately distinctive to identify tumor cells versus the white blood cell background in the first stage and, moreover, in recognizing the tumor type at the second decision step. Proof-of-concept experiments are shown, in which two different tumor cell lines, namely neuroblastoma cancer cells and ovarian cancer cells, are used against monocytes. The reported results allow claiming the identification of tumor cells with a success rate higher than 97% and with an accuracy over 97% in discriminating between the two cancer cell types, thus opening in a near future the route to a new Liquid Biopsy tool for detecting and classifying circulating tumor cells in blood by stain-free method., (© 2023. The Author(s).)

Live cells act as biological lenses and can be employed as real-world optical components in bio-hybrid systems. Imaging at nanoscale, optical tweezers, lithography and also photonic waveguiding are some of the already proven functionalities, boosted by the advantage that cells are fully biocompatible for intra-body applications. So far, various cell types have been studied for this purpose, such as red blood cells, bacterial cells, stem cells and yeast cells. White Blood Cells (WBCs) play a very important role in the regulation of the human body activities and are usually monitored for assessing its health. WBCs can be considered bio-lenses but, to the best of our knowledge, characterization of their optical properties have not been investigated yet. Here, we report for the first time an accurate study of two model classes of WBCs (i.e., monocytes and lymphocytes) by means of a digital holographic microscope coupled with a microfluidic system, assuming WBCs bio-lens characteristics. Thus, quantitative phase maps for many WBCs have been retrieved in flow-cytometry (FC) by achieving a significant statistical analysis to prove the enhancement in differentiation among sphere-like bio-lenses according to their sizes (i.e., diameter d) exploiting intensity parameters of the modulated light in proximity of the cell optical axis. We show that the measure of the low intensity area (S: I z < I th z ) in a fixed plane, is a feasible parameter for cell clustering, while achieving robustness against experimental misalignments and allowing to adjust the measurement sensitivity in post-processing. 2D scatterplots of the identified parameters (d-S) show better differentiation respect to the 1D case. The results show that the optical focusing properties of WBCs allow the clustering of the two populations by means of a mere morphological analysis, thus leading to the new concept of cell-optical-fingerprint avoiding fluorescent dyes. This perspective can open new routes in biomedical sciences, such as the chance to find optical-biomarkers at single cell level for label-free diagnosis., (© 2022 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.)

Quantitative Phase Imaging (QPI) has gained popularity in bioimaging because it can avoid the need for cell staining, which in some cases is difficult or impossible. However, as a result, QPI does not provide labelling of various specific intracellular structures. Here we show a novel computational segmentation method based on statistical inference that makes it possible for QPI techniques to identify the cell nucleus. We demonstrate the approach with refractive index tomograms of stain-free cells reconstructed through the tomographic phase microscopy in flow cytometry mode. In particular, by means of numerical simulations and two cancer cell lines, we demonstrate that the nucleus can be accurately distinguished within the stain-free tomograms. We show that our experimental results are consistent with confocal fluorescence microscopy (FM) data and microfluidic cytofluorimeter outputs. This is a significant step towards extracting specific three-dimensional intracellular structures directly from the phase-contrast data in a typical flow cytometry configuration., Competing Interests: Competing interests D.Pi., J.L., L.M., V.B., P.M., D.Ps., P.F. have filed a patent pending (application number IT102021000019490) about some key aspects described in the paper. The authors declare no other competing interests.

Background: Epilepsy has been associated with an increased risk of cardiovascular events. Anti-seizure medication (ASM) may contribute to vascular risk by several mechanisms, including increased homocysteine levels. This study aims to assess the global vascular burden in hyperhomocysteinemic people with epilepsy (PWE) on long-term ASM before and after folic acid supplementation and in subgroups of PWE treated with single enzyme-inducing or single non-enzyme inducing ASM., Methods: One hundred and seventy-four hyperhomocysteinemic (HHcy) PWE who met the inclusion criteria were enrolled. Carotid Doppler ultrasonography, FMD and ultrasound assessment of the brachial artery properties at the baseline and after 90 days of folic acid supplementation were performed. The vascular biomarkers MMP-9 and TIMP-1 were also detected., Results: After folic acid supplementation, in HHcy patients homocysteine levels reduced from 26.8 ± 10.5 to 20.2 ± 5.3 μmol/L, carotid Intima-Media-Thickness reduced from 0.83+0.06 mm to 0.79±0.05 mm, and FMD, distensibility coefficient and β-stiffness improved (p < 0.05). Moreover, MMP-9 and TIMP-1 reduced after supplementation (p < 0.05). PWE treated with a single enzyme-inducing ASM showed an impairment of vascular parameters compared to patients treated with non-enzyme inducing ASM., Conclusions: The results highlight the importance of assessing homocysteine levels and estimating the cardiovascular risk of PWE, preferring non-enzyme inducing ASM in high cardiovascular-risk patients. An adequate correction of homocysteine levels with folate supplementation should be considered to improve the cardiovascular profile., Competing Interests: Declaration of Competing Interest The authors declare that they have no conflict of interest/competing interests., (Published by Elsevier Ltd.)

Tomographic flow cytometry by digital holography is an emerging imaging modality capable of collecting multiple views of moving and rotating cells with the aim of recovering their refractive index distribution in 3D. Although this modality allows us to access high-resolution imaging with high-throughput, the huge amount of time-lapse holographic images to be processed (hundreds of digital holograms per cell) constitutes the actual bottleneck. This prevents the system from being suitable for lab-on-a-chip platforms in real-world applications, where fast analysis of measured data is mandatory. Here we demonstrate a significant speeding-up reconstruction of phase-contrast tomograms by introducing in the processing pipeline a multi-scale fully-convolutional context aggregation network. Although it was originally developed in the context of semantic image analysis, we demonstrate for the first time that it can be successfully adapted to a holographic lab-on-chip platform for achieving 3D tomograms through a faster computational process. We trained the network with input-output image pairs to reproduce the end-to-end holographic reconstruction process, i.e. recovering quantitative phase maps (QPMs) of single cells from their digital holograms. Then, the sequence of QPMs of the same rotating cell is used to perform the tomographic reconstruction. The proposed approach significantly reduces the computational time for retrieving tomograms, thus making them available in a few seconds instead of tens of minutes, while essentially preserving the high-content information of tomographic data. Moreover, we have accomplished a compact deep convolutional neural network parameterization that can fit into on-chip SRAM and a small memory footprint, thus demonstrating its possible exploitation to provide onboard computations for lab-on-chip devices with low processing hardware resources.

Single-cell phase-contrast tomography promises to become decisive for studying 3D intracellular structures in biology. It involves probing cells with light at wide angles, which unfortunately requires complex systems. Here we show an intriguing concept based on an inherent natural process for plants biology, i.e., dehydration, allowing us to easily obtain 3D-tomography of onion-epidermal cells' nuclei. In fact, the loss of water reduces the turgor pressure and we recognize it induces significant rotation of cells' nuclei. Thanks to the holographic focusing flexibility and an ad-hoc angles' tracking algorithm, we combine different phase-contrast views of the nuclei to retrieve their 3D refractive index distribution. Nucleolus identification capability and a strategy for measuring morphology, dry mass, biovolume, and refractive index statistics are reported and discussed. This new concept could revolutionize the investigation in plant biology by enabling dynamic 3D quantitative and label-free analysis at sub-nuclear level using a conventional holographic setup., (© 2021. The Author(s).)

Interaction of nanoparticles (NPs) with cells is of fundamental importance in biology and biomedical sciences. NPs can be taken up by cells, thus interacting with their intracellular elements, modifying the life cycle pathways, and possibly inducing death. Therefore, there is a great interest in understanding and visualizing the process of cellular uptake itself or even secondary effects, for example, toxicity. Nowadays, no method is reported yet in which 3D imaging of NPs distribution can be achieved for suspended cells in flow-cytometry. Here we show that, by means of label-free tomographic flow-cytometry, it is possible to obtain full 3D quantitative spatial distribution of nanographene oxide (nGO) inside each single flowing cell. This can allow the setting of a class of biomarkers that characterize the 3D spatial intracellular deployment of nGO or other NPs clusters, thus opening the route for quantitative descriptions to discover new insights in the realm of NP-cell interactions.

A molecular design approach was used to create asymmetrical visible light-triggered azo-derivatives that can be good candidates for polymer functionalization. The specific electron-donor substituted molecules were characterized and studied by means of NMR analyses and UV-visible spectroscopy, comparing the results with Time Dependent Density Functional (TD-DFT) calculations. A slow rate of isomerization (k i = 1.5 × 10 -4 s -1 ) was discovered for 4-((2-hydroxy-5methylphenyl) diazenyl)-3-methoxybenzoic acid (AZO1). By methylating this moiety, it was possible to unlock the isomerization mechanism for the second molecule, methyl 3-methoxy-4-((2-methoxy-5-methylphenyl) diazenyl)benzoate (AZO2), reaching promising isomerization rates with visible light irradiation in different solvents. It was discovered that this rate was heightened by one order of magnitude (k i = 3.1 × 10 -3 s -1 ) for AZO2. A computational analysis using density functional (DFT/PBE0) and wavefunction (QD-NEVPT2) methodologies provided insight into the photodynamics of these systems. Both molecules require excitation to the second (S 2 ) excited state situated in the visible region to initiate the isomerization. Two classic mechanisms were considered, namely rotation and inversion, with the former being energetically more favorable. These azo-derivatives show potential that paves the way for future applications as building blocks of functional polymers. Likewise, they could be really effective for the modification of existing commercial polymers, thus transferring their stimuli responsive properties to polymeric bulky structures, converting them into smart materials.

The development of photo-responsive capsules to tune and control the sustained-release of encapsulated actives is a fascinating and challenging route to improve the performances and effectiveness of a wide range of delivery applications. In this work, we report the preparation of visible light-responsive capsules obtained via oil-in-water interfacial polycondensation between modified diacyl-chloride azobenzene moiety and diamine flexible spacer in the presence of cross-linkers with different structures and functionalities. The effect on the release profile of the encapsulated perfume oil was investigated using three flexible spacers with different lengths (1,8-diaminooctane; 1,6-diaminohexane and 1,4-diaminobutane) and two types of cross-linkers (1,3,5-benzenetricarbonyl trichloride and melamine). We analyzed how the properties of microcapsules can be tailored changing the design of the shell structure. Fine tuning of the perfume release profiles was obtained. The changes in capsules size and morphology due to visible light irradiation were monitored via light scattering, optical microscopy and atomic force microscopy. Perfume release was 50% faster in the systems prepared with melamine as the cross-linker. Modelling studies were carried out to support the discussion of the experimental results.

Low-modified liquid-crystalline polyether (CP36), as a model compound, was synthesised with the purpose of preparing a membrane with columnar ionic channels. A free-standing cation permselective biomimetic membrane was successfully prepared and found to have channels made of polymeric columns homeotropically oriented, which was confirmed in X-ray diffraction (XRD) analysis. A first insight into a real-time interaction between two selected cations: H⁺ and Na⁺, and polyether during transport through the polymeric membrane was demonstrated using joined chronoamperometry and Raman spectroscopy techniques. Raman studies unveiled the possibility for smaller protons to bypass the usual ionic pathway via polyetheric chain and use outer part of ionic channel for conduction thanks to ester bonds., Competing Interests: The authors declare no conflict of interest.

We describe a structured inquiry laboratory exercise that examines transcriptional regulation of the NOS2 gene under conditions that simulate the inflammatory response in macrophages. Using quantitative PCR and the comparative CT method, students are able determine whether transcriptional activation of NOS2 occurs and to what degree. The exercise is aimed at second year undergraduates who possess basic knowledge of gene expression events. It requires only 4-5 hr of dedicated laboratory time and focuses on use of the primary literature, data analysis, and interpretation. Importantly, this exercise provides a mechanism to introduce the concept of differential gene expression and provides a starting point for development of more complex guided or open inquiry projects for students moving into upper level molecular biology, immunology, and biochemistry course work., (© 2015 The International Union of Biochemistry and Molecular Biology.)

Adhesion to the extracellular matrix regulates numerous changes in the actin cytoskeleton by regulating the activity of the Rho family of small GTPases. Here, we report that adhesion and the associated changes in cell shape and cytoskeletal tension are all required for GTP-bound RhoA to activate its downstream effector, ROCK. Using an in vitro kinase assay for endogenous ROCK, we found that cells in suspension, attached on substrates coated with low density fibronectin, or on spreading-restrictive micropatterned islands all exhibited low ROCK activity and correspondingly low myosin light chain phosphorylation, in the face of high levels of GTP-bound RhoA. In contrast, allowing cells to spread against substrates rescued ROCK and myosin activity. Interestingly, inhibition of tension with cytochalasin D or blebbistatin also inhibited ROCK activity within 20 min. The abrogation of ROCK activity by cell detachment or inhibition of tension could not be rescued by constitutively active RhoA-V14. These results suggest the existence of a feedback loop between cytoskeletal tension, adhesion maturation, and ROCK signaling that likely contributes to numerous mechanochemical processes.

Cdc42, a Rho GTPase, regulates the organization of the actin cytoskeleton by its interaction with several distinct families of downstream effector proteins. Here, we report the identification of four new Cdc42-binding proteins that, along with MSE55, constitute a new family of effector proteins. These molecules, designated CEPs, contain three regions of homology, including a Cdc42 binding domain and two unique domains called CI and CII. Experimentally, we have verified that CEP2 and CEP5 bind Cdc42. Expression of CEP2, CEP3, CEP4, and CEP5 in NIH-3T3 fibroblasts induced pseudopodia formation. Fibroblasts coexpressing dominant negative Cdc42 with CEP2 or expressing a Cdc42/Rac interactive binding domain mutant of CEP2 did not induce pseudopodia formation. In primary keratinocytes, CEP2- and CEP5-expressing cells showed reduced F-actin localization at the adherens junctions with an increase in thin stress fibers that extended the length of the cell body. Keratinocytes expressing CEPs also showed an altered vinculin distribution and a loss of E-cadherin from adherens junctions. Similar effects were observed in keratinocytes expressing constitutively active Cdc42, but were not seen with a Cdc42/Rac interactive binding domain mutant of CEP2. These results suggest that CEPs act downstream of Cdc42 to induce actin filament assembly leading to cell shape changes.

The Rho GTPase, Cdc42, regulates a wide variety of cellular activities including actin polymerization, focal complex assembly, and kinase signaling. We have identified a new family of very small Cdc42-binding proteins, designated SPECs (for Small Protein Effector of Cdc42), that modulates these regulatory activities. The two human members, SPEC1 and SPEC2, encode proteins of 79 and 84 amino acids, respectively. Both contain a conserved N-terminal region and a centrally located CRIB (Cdc42/Rac Interactive Binding) domain. Using a yeast two-hybrid system, we found that both SPECs interact strongly with Cdc42, weakly with Rac1, and not at all with RhoA. Transfection analysis revealed that SPEC1 inhibited Cdc42-induced c-Jun N-terminal kinase (JNK) activation in COS1 cells in a manner that required an intact CRIB domain. Immunofluorescence experiments in NIH-3T3 fibroblasts demonstrated that both SPEC1 and SPEC2 showed a cortical localization and induced the formation of cell surface membrane blebs, which was not dependent on Cdc42 activity. Cotransfection experiments demonstrated that SPEC1 altered Cdc42-induced cell shape changes both in COS1 cells and in NIH-3T3 fibroblasts and that this alteration required an intact CRIB domain. These results suggest that SPECs act as novel scaffold molecules to coordinate and/or mediate Cdc42 signaling activities.

Two cDNAs encoding PAK kinases were isolated from a mouse embryo library by screening with a PCR-generated probe derived from the kinase domain of a rat PAK kinase. These cDNAs, designated PAK-1 and PAK-3, encode mouse PAK kinases of 545 and 544 amino acids, respectively. Both proteins possess an N-terminal Cdc42/Rac interacting binding domain (CRIB) and a C-terminal serine/threonine kinase domain. Comparison of the two mouse PAK kinases revealed that the proteins show 87% amino acid identity. Northern analysis of a multiple mouse tissue blot with a PAK-1 probe detected a 3.0kb transcript that was almost exclusively expressed in the brain and spinal cord compared to other tissues such as lung, liver and kidney. A similar pattern of central nervous system tissue expression of PAK-3 transcripts of 3.6 and 8kb was also observed. Analysis of two multilocus genetic crosses localized Pak1 and Pak3 to a position on chromosome 7 and X, respectively. The high level of PAK-1 and PAK-3 kinase expression in the mouse brain and spinal cord suggests a potentially important role for these kinases in the control of the cellular architecture and/or signaling in the central nervous system.