Force generation is an integral part of cellular behavior. It plays a crucial role in cell adhesion, migration and division. Mechanical forces are also essential in cell-to-cell interactions, including the widespread interactions involving immune cells. Accurately measuring these forces remains a major challenge, yet it is essential for understanding the mechanobiological mechanisms driving these interactions. Here, we describe a methodology in which deformable and tunable hydrogel microparticles are used to quantify cellular forces. A specific type of acrylamide-based tunable hydrogel microparticles, deformable poly-acrylamide co-acrylic acid microparticles (DAAM-particles), are synthesized in batch using a membrane emulsification approach and conjugated with both biologically active molecules and fluorescent labels through a one-pot functionalization procedure. Cells are then incubated with functionalized DAAM-particles and imaged by confocal microscopy. With a custom image-analysis strategy, local microparticle deformations can be quantified with super-resolution accuracy (<50 nm). Elasticity theory calculations allow for the inference of normal and shear forces, revealing the direction and spatial distribution of cellular forces. The tunability of DAAM-particles enables their adaptation for investigating numerous cellular processes, making them a valuable tool for understanding mechanobiology. The entire protocol takes 2–3 d, requires only basic expertise in mammalian cell culture and fluorescence microscopy and utilizes less specialized equipment and facilities compared with other available techniques. As an example, we demonstrate how this methodology can reveal actin-based force generation during phagocytosis by macrophages. Deformable poly-acrylamide co-acrylic acid microparticles (DAAM-particles) are tunable hydrogel microparticles for quantifying cellular forces. This comprehensive protocol details their synthesis, functionalization and applications.

Natural killer (NK) cells are innate lymphocytes that play a critical role in host defense against viral infection. In addition to rapid effector cytokine production and direct cytotoxicity, NK cells exhibit features of adaptive immunity, including the capacity to undergo robust antigen-specific clonal proliferation and to generate immunological memory1–3. However, the transcriptional programs and regulators governing dynamic NK cell responses to viral infection have not been fully uncovered. In this study, we identified transcription factor 19 (TCF19) as a key driver of NK cell proliferation and calcium signaling in the context of mouse cytomegalovirus infection. Ablation of TCF19 was detrimental to NK cell clonal expansion and host protection against viral infection. Tcf19−/− NK cells were also unable to properly mobilize calcium downstream of antigen signaling to mediate cytotoxicity. Altogether, we find that TCF19 drives a transcriptional program that coordinates the innate and adaptive NK cell responses against viral infection. Sun and colleagues report that the transcription factor TCF19 regulates calcium signaling and cell cycling progression in NK cells and is required for innate and adaptive NK cell responses to viral infection.

Immune cells have intensely physical lifestyles characterized by structural plasticity and force exertion. To investigate whether specific immune functions require stereotyped mechanical outputs, we used super-resolution traction force microscopy to compare the immune synapses formed by cytotoxic T cells with contacts formed by other T cell subsets and by macrophages. T cell synapses were globally compressive, which was fundamentally different from the pulling and pinching associated with macrophage phagocytosis. Spectral decomposition of force exertion patterns from each cell type linked cytotoxicity to compressive strength, local protrusiveness, and the induction of complex, asymmetric topography. These features were validated as cytotoxic drivers by genetic disruption of cytoskeletal regulators, live imaging of synaptic secretion, and in silico analysis of interfacial distortion. Synapse architecture and force exertion were sensitive to target stiffness and size, suggesting that the mechanical potentiation of killing is biophysically adaptive. We conclude that cellular cytotoxicity and, by implication, other effector responses are supported by specialized patterns of efferent force.

Professional phagocytes like neutrophils and macrophages tightly control what they consume, how much they consume, and when they move after cargo uptake. We show that plasma membrane abundance is a key arbiter of these cellular behaviors. Neutrophils and macrophages lacking the G protein subunit Gβ 4 exhibited profound plasma membrane expansion, accompanied by marked reduction in plasma membrane tension. These biophysical changes promoted the phagocytosis of bacteria, fungus, apoptotic corpses, and cancer cells. We also found that Gβ 4 -deficient neutrophils are defective in the normal inhibition of migration following cargo uptake. Sphingolipid synthesis played a central role in these phenotypes by driving plasma membrane accumulation in cells lacking Gβ 4 . In Gβ 4 knockout mice, neutrophils not only exhibited enhanced phagocytosis of inhaled fungal conidia in the lung but also increased trafficking of engulfed pathogens to other organs. Together, these results reveal an unexpected, biophysical control mechanism central to myeloid functional decision-making.

Phagocytosis is an intensely physical process that depends on the mechanical properties of both the phagocytic cell and its chosen target. Here, we employed differentially deformable hydrogel microparticles to examine the role of cargo rigidity in the regulation of phagocytosis by macrophages. Whereas stiff cargos elicited canonical phagocytic cup formation and rapid engulfment, soft cargos induced an architecturally distinct response, characterized by filamentous actin protrusions at the center of the contact site, slower cup advancement, and frequent phagocytic stalling. Using phosphoproteomics, we identifiedβ2 integrins and their downstream effectors as critical mediators of this mechanically regulated phagocytic switch. Indeed, comparison of wild type andβ2 integrin deficient macrophages indicated that integrin signaling acts as a mechanical checkpoint by shaping filamentous actin to enable distinct phagocytic engulfment strategies. Collectively, these results illuminate the molecular logic of leukocyte mechanosensing and reveal potential avenues for modulating phagocyte function in immunotherapeutic contexts.

Immune cells live intensely physical lifestyles characterized by structural plasticity, mechanosensitivity, and force exertion. Whether specific immune functions require stereotyped patterns of mechanical output, however, is largely unknown. To address this question, we used super-resolution traction force microscopy to compare cytotoxic T cell immune synapses with contacts formed by other T cell subsets and macrophages. T cell synapses were globally and locally protrusive, which was fundamentally different from the coupled pinching and pulling of macrophage phagocytosis. By spectrally decomposing the force exertion patterns of each cell type, we associated cytotoxicity with compressive strength, local protrusiveness, and the induction of complex, asymmetric interfacial topographies. These features were further validated as cytotoxic drivers by genetic disruption of cytoskeletal regulators, direct imaging of synaptic secretory events, and in silico analysis of interfacial distortion. We conclude that T cell-mediated killing and, by implication, other effector responses are supported by specialized patterns of efferent force.

Abstract (Note: a correction was made to the Index Reverse primer 20 Sep2023) CRISPR-Cas9 RNA-guided endonucleases are widely used in genome engineering, yet information on biochemical and cellular off-target cleavage activity is lacking. Here, we present a biochemical method, based on the selective enrichment and identification of adapter-tagged DNA ends by sequencing \(SITE-Seq). SITE-Seq can be used to identify off-target cleavage sites within a genomic DNA sample. This protocol details the preparation of SITE-Seq libraries for high throughput Next Generation Sequencing on the Illumina platform.

Cellular immunity demands that individual effector leukocytes execute their protective functions in peripheral tissues of the body, which could exhibit a wide range of biochemical and biophysical characteristics. We hypothesized that this is accomplished in part by various efferent, cell-type-specific immune-mechanical patterns of activity. To mechanically profile immune contacts, we developed a novel experimental system by which cells interacting with biomimetic hydrogel spheres (microparticles) are imaged with high resolution.

RNA-guided CRISPR-Cas9 endonucleases are widely used for genome engineering, but our understanding of Cas9 specificity remains incomplete. Here, we developed a biochemical method (SITE-Seq), using Cas9 programmed with single-guide RNAs (sgRNAs), to identify the sequence of cut sites within genomic DNA. Cells edited with the same Cas9-sgRNA complexes are then assayed for mutations at each cut site using amplicon sequencing. We used SITE-Seq to examine Cas9 specificity with sgRNAs targeting the human genome. The number of sites identified depended on sgRNA sequence and nuclease concentration. Sites identified at lower concentrations showed a higher propensity for off-target mutations in cells. The list of off-target sites showing activity in cells was influenced by sgRNP delivery, cell type and duration of exposure to the nuclease. Collectively, our results underscore the utility of combining comprehensive biochemical identification of off-target sites with independent cell-based measurements of activity at those sites when assessing nuclease activity and specificity.

Machine learning–enabled perception-based detection of protein biomarkers was achieved in gynecologic cancer patient biofluids.

Single wall carbon nanotube (SWCNT) based biosensors provide opportunities for building an ultra-sensitive biosensing system due to their unique optical properties and strong sensitivity to changes in the local environment. Consequently, much effort has been made to develop SWCNT-based sensors. However, the usual method is based on one-to-one recognition which is a difficult way to detect various molecules since it requires the same number of highly specific receptors as the number of molecules one wishes to detect. To detect a combination of various analytes simultaneously, an effective and automatic data processing system is essential. In this study, we propose a new perception-based sensing system using weakly-specific sensor arrays that can be analyzed by an artificial perception model, which we call the Molecular Perceptron. We show how machine learning algorithms along with choice of feature representation is designed to predict presence and concentration of biomarkers or direct prediction of disease states. For example, we demonstrate that the Molecular Perceptron can detect Human epididymis protein 4 (HE4) in the presence or absence of other analytes; HE4 is one of two FDA-approved serum biomarkers for ovarian cancer which provides noticeable sensitivity and specificity for ovarian cancer diagnosis. DNA/SWCNT hybrids were utilized to optically detect the analytes by observing changes in the fluorescence spectra of each SWCNT. Using the experimental data, machine learning models were trained using three different algorithms: Support Vector Machine, Random Forest, and Artificial Neural Network. The models were then validated using new experimental data for different analyte concentrations. Overall, the machine learning models successfully predict the presence of HE4 at the concentrations of 10 nM or higher by giving F1-scores of ~0.85. This is strongly suggestive of the idea that the perception mode of sensing can make accurate judgements in a noisy sensing environment.

Table S8. Primer sequences used for on- and off-target deep sequencing analysis for all genomic editing sites analyzed by SITE-Seq. (XLSX 48 kb)

Background: The development of CRISPR genome editing has transformed biomedical research. Most applications reported thus far rely upon the Cas9 protein from Streptococcus pyogenes SF370 (SpyCas9). With many RNA guides, wildtype SpyCas9 can induce significant levels of unintended mutations at near-cognate sites, necessitating substantial efforts toward the development of strategies to minimize off-target activity. Although the genome-editing potential of thousands of other Cas9 orthologs remains largely untapped, it is not known how many will require similarly extensive engineering to achieve single-site accuracy within large genomes. In addition to its off-targeting propensity, SpyCas9 is encoded by a relatively large open reading frame, limiting its utility in applications that require size-restricted delivery strategies such as adeno-associated virus vectors. In contrast, some genome-editing-validated Cas9 orthologs are considerably smaller and therefore better suited for viral delivery. Results: Here we show that wildtype NmeCas9, when programmed with guide sequences of the natural length of 24 nucleotides, exhibits a nearly complete absence of unintended editing in human cells, even when targeting sites that are prone to off-target activity with wildtype SpyCas9. We also validate at least six variant protospacer adjacent motifs (PAMs), in addition to the preferred consensus PAM (5'-N(4)GATT-3'), for NmeCas9 genome editing in human cells. Conclusions: Our results show that NmeCas9 is a naturally high-fidelity genome-editing enzyme and suggest that additional Cas9 orthologs may prove to exhibit similarly high accuracy, even without extensive engineering.

RNA structure is a primary determinant of its function, and methods that merge chemical probing with next generation sequencing have created breakthroughs in the throughput and scale of RNA structure characterization. However, little work has been done to examine the effects of library preparation and sequencing on the measured chemical probe reactivities that encode RNA structural information. Here, we present the first analysis and optimization of these effects for selective 2'-hydroxyl acylation analyzed by primer extension sequencing (SHAPE-Seq). We first optimize SHAPE-Seq, and show that it provides highly reproducible reactivity data over a wide range of RNA structural contexts with no apparent biases. As part of this optimization, we present SHAPE-Seq v2.0, a 'universal' method that can obtain reactivity information for every nucleotide of an RNA without having to use or introduce a specific reverse transcriptase priming site within the RNA. We show that SHAPE-Seq v2.0 is highly reproducible, with reactivity data that can be used as constraints in RNA folding algorithms to predict structures on par with those generated using data from other SHAPE methods. We anticipate SHAPE-Seq v2.0 to be broadly applicable to understanding the RNA sequence-structure relationship at the heart of some of life's most fundamental processes.