Early T cell activation: integrating biochemical, structural, and biophysical cues.

T cells carry out the formidable task of identifying small numbers of foreign antigenic peptides rapidly and specifically against a very noisy environmental background of endogenous self-peptides. Early steps in T cell activation have thus fascinated biologists and are among the best-studied models of cell stimulation. This remarkable process, critical in adaptive immune responses, approaches and even seems to exceed the limitations set by the physical laws ruling molecular behavior. Despite the enormous amount of information concerning the nature of molecules involved in the T cell antigen receptor (TCR) signal transduction network, and the description of the nanoscale organization and real-time analysis of T cell responses, the general principles of information gathering and processing remain incompletely understood. Here we review currently accepted key data on TCR function, discuss the limitations of current research strategies, and suggest a novel model of TCR triggering and a few promising ways of going further into the integration of available data.

Comparison of the Capacity of Several Machine Learning Tools to Assist Immunofluorescence-Based Detection of Anti-Neutrophil Cytoplasmic Antibodies.

The success of artificial intelligence and machine learning is an incentive to develop new algorithms to increase the rapidity and reliability of medical diagnosis. Here we compared different strategies aimed at processing microscope images used to detect anti-neutrophil cytoplasmic antibodies, an important vasculitis marker: (i) basic classifier methods (logistic regression, k-nearest neighbors and decision tree) were used to process custom-made indices derived from immunofluorescence images yielded by 137 sera. (ii) These methods were combined with dimensional reduction to analyze 1733 individual cell images. (iii) More complex models based on neural networks were used to analyze the same dataset. The efficiency of discriminating between positive and negative samples and different fluorescence patterns was quantified with Rand-type accuracy index, kappa index and ROC curve. It is concluded that basic models trained on a limited dataset allowed for positive/negative discrimination with an efficiency comparable to that obtained by conventional analysis performed by humans (0.84 kappa score). More extensive datasets and more sophisticated models may be required for efficient discrimination between fluorescence patterns generated by different auto-antibody species.

Understanding How Cells Probe the World: A Preliminary Step towards Modeling Cell Behavior?

Cell biologists have long aimed at quantitatively modeling cell function. Recently, the outstanding progress of high-throughput measurement methods and data processing tools has made this a realistic goal. The aim of this paper is twofold: First, to suggest that, while much progress has been done in modeling cell states and transitions, current accounts of environmental cues driving these transitions remain insufficient. There is a need to provide an integrated view of the biochemical, topographical and mechanical information processed by cells to take decisions. It might be rewarding in the near future to try to connect cell environmental cues to physiologically relevant outcomes rather than modeling relationships between these cues and internal signaling networks. The second aim of this paper is to review exogenous signals that are sensed by living cells and significantly influence fate decisions. Indeed, in addition to the composition of the surrounding medium, cells are highly sensitive to the properties of neighboring surfaces, including the spatial organization of anchored molecules and substrate mechanical and topographical properties. These properties should thus be included in models of cell behavior. It is also suggested that attempts at cell modeling could strongly benefit from two research lines: (i) trying to decipher the way cells encode the information they retrieve from environment analysis, and (ii) developing more standardized means of assessing the quality of proposed models, as was done in other research domains such as protein structure prediction.

Is There a Need for a More Precise Description of Biomolecule Interactions to Understand Cell Function?

An important goal of biological research is to explain and hopefully predict cell behavior from the molecular properties of cellular components. Accordingly, much work was done to build extensive "omic" datasets and develop theoretical methods, including computer simulation and network analysis to process as quantitatively as possible the parameters contained in these resources. Furthermore, substantial effort was made to standardize data presentation and make experimental results accessible to data scientists. However, the power and complexity of current experimental and theoretical tools make it more and more difficult to assess the capacity of gathered parameters to support optimal progress in our understanding of cell function. The purpose of this review is to focus on biomolecule interactions, the interactome, as a specific and important example, and examine the limitations of the explanatory and predictive power of parameters that are considered as suitable descriptors of molecular interactions. Recent experimental studies on important cell functions, such as adhesion and processing of environmental cues for decision-making, support the suggestion that it should be rewarding to complement standard binding properties such as affinity and kinetic constants, or even force dependence, with less frequently used parameters such as conformational flexibility or size of binding molecules.

TCR-pMHC kinetics under force in a cell-free system show no intrinsic catch bond, but a minimal encounter duration before binding.

The T cell receptor (TCR)-peptide-MHC (pMHC) interaction is the only antigen-specific interaction during T lymphocyte activation. Recent work suggests that formation of catch bonds is characteristic of activating TCR-pMHC interactions. However, whether this binding behavior is an intrinsic feature of the molecular bond, or a consequence of more complex multimolecular or cellular responses, remains unclear. We used a laminar flow chamber to measure, first, 2D TCR-pMHC dissociation kinetics of peptides of various activating potency in a cell-free system in the force range (6 to 15 pN) previously associated with catch-slip transitions and, second, 2D TCR-pMHC association kinetics, for which the method is well suited. We did not observe catch bonds in dissociation, and the off-rate measured in the 6- to 15-pN range correlated well with activation potency, suggesting that formation of catch bonds is not an intrinsic feature of the TCR-pMHC interaction. The association kinetics were better explained by a model with a minimal encounter duration rather than a standard on-rate constant, suggesting that membrane fluidity and dynamics may strongly influence bond formation.

T lymphocytes need less than 3 min to discriminate between peptide MHCs with similar TCR-binding parameters.

T lymphocytes need to detect rare cognate foreign peptides among numerous foreign and self-peptides. This discrimination seems to be based on the kinetics of TCRs binding to their peptide-MHC (pMHC) ligands, but there is little direct information on the minimum time required for processing elementary signaling events and deciding to initiate activation. Here, we used interference reflection microscopy to study the early interaction between transfected human Jurkat T cells expressing the 1G4 TCR and surfaces coated with five different pMHC ligands of 1G4. The pMHC concentration required for inducing 50% maximal IFN-γ production by T cells, and 1G4-pMHC dissociation rates measured in soluble phase or on surface-bound molecules, displayed six- to sevenfold variation among pMHCs. When T cells were dropped onto pMHC-coated surfaces, rapid spreading occurred after a 2-min lag. The initial spreading rate measured during the first 45 s, and the contact area, were strongly dependent on the encountered TCR ligand. However, the lag duration did not significantly depend on encountered ligand. In addition, spreading appeared to be an all-or-none process, and the fraction of spreading cells was tightly correlated to the spreading rate and spreading area. Thus, T cells can discriminate between fairly similar TCR ligands within 2 min.

The leukocyte-stiffening property of plasma in early acute respiratory distress syndrome (ARDS) revealed by a microfluidic single-cell study: the role of cytokines and protection with antibodies.

BACKGROUND: Leukocyte-mediated pulmonary inflammation is a key pathophysiological mechanism involved in acute respiratory distress syndrome (ARDS). Massive sequestration of leukocytes in the pulmonary microvasculature is a major triggering event of the syndrome. We therefore investigated the potential role of leukocyte stiffness and adhesiveness in the sequestration of leukocytes in microvessels. METHODS: This study was based on in vitro microfluidic assays using patient sera. Cell stiffness was assessed by measuring the entry time (ET) of a single cell into a microchannel with a 6 × 9-µm cross-section under a constant pressure drop (ΔP = 160 Pa). Primary neutrophils and monocytes, as well as the monocytic THP-1 cell line, were used. Cellular adhesiveness to human umbilical vein endothelial cells was examined using the laminar flow chamber method. We compared the properties of cells incubated with the sera of healthy volunteers (n = 5), patients presenting with acute cardiogenic pulmonary edema (ACPE; n = 6), and patients with ARDS (n = 22), of whom 13 were classified as having moderate to severe disease and the remaining 9 as having mild disease. RESULTS: Rapid and strong stiffening of primary neutrophils and monocytes was induced within 30 minutes (mean ET >50 seconds) by sera from the ARDS group compared with both the healthy subjects and the ACPE groups (mean ET <1 second) (p < 0.05). Systematic measurements with the THP-1 cell line allowed for the establishment of a strong correlation between stiffening and the severity of respiratory status (mean ET 0.82 ± 0.08 seconds for healthy subjects, 1.6 ± 1.0 seconds for ACPE groups, 10.5 ± 6.1 seconds for mild ARDS, and 20.0 ± 8.1 seconds for moderate to severe ARDS; p < 0.05). Stiffening correlated with the cytokines interleukin IL-1ß, IL-8, tumor necrosis factor TNF-α, and IL-10 but not with interferon-γ, transforming growth factor-ß, IL-6, or IL-17. Strong stiffening was induced by IL-1ß, IL-8, and TNF-α but not by IL-10, and incubations with sera and blocking antibodies against IL-1ß, IL-8, or TNF-α significantly diminished the stiffening effect of serum. In contrast, the measurements of integrin expression (CD11b, CD11a, CD18, CD49d) and leukocyte-endothelium adhesion showed a weak and slow response after incubation with the sera of patients with ARDS (several hours), suggesting a lesser role of leukocyte adhesiveness compared with leukocyte stiffness in early ARDS. CONCLUSIONS: The leukocyte stiffening induced by cytokines in the sera of patients might play a role in the sequestration of leukocytes in the lung capillary beds during early ARDS. The inhibition of leukocyte stiffening with blocking antibodies might inspire future therapeutic strategies.

Mechanics of the Toxoplasma gondii oocyst wall.

The ability of microorganisms to survive under extreme conditions is closely related to the physicochemical properties of their wall. In the ubiquitous protozoan parasite Toxoplasma gondii, the oocyst stage possesses a bilayered wall that protects the dormant but potentially infective parasites from harsh environmental conditions until their ingestion by the host. None of the common disinfectants are effective in killing the parasite because the oocyst wall acts as a primary barrier to physical and chemical attacks. Here, we address the structure and chemistry of the wall of the T. gondii oocyst by combining wall surface treatments, fluorescence imaging, EM, and measurements of its mechanical characteristics by using atomic force microscopy. Elasticity and indentation measurements indicated that the oocyst wall resembles common plastic materials, based on the Young moduli, E, evaluated by atomic force microscopy. Our study demonstrates that the inner layer is as robust as the bilayered wall itself. Besides wall mechanics, our results suggest important differences regarding the nonspecific adhesive properties of each layer. All together, these findings suggest a key biological role for the oocyst wall mechanics in maintaining the integrity of the T. gondii oocysts in the environment or after exposure to disinfectants, and therefore their potential infectivity to humans and animals.

Genotype combinations of two IL4 polymorphisms influencing IL-4 plasma levels are associated with different risks of severe malaria in the Malian population.

We have previously found that children heterozygous for IL4 variable-number tandem repeat (VNTR) (rs8179190) or IL4-33 (rs2070874) variants were at risk for severe malaria (SM), whereas homozygous children were protected suggesting a complex genetic control. Hence, to dissect this complex genetic control of IL4 VNTR and IL4-33, we performed further investigation by conditional logistic regression analysis and found a strong interaction between both markers (p < 10(-6)). The best-fit model revealed three genotype combinations associated with different levels of SM risk. The highest risk (odds ratio (OR) = 4.8, 95% confidence interval (CI) = 2.0-11.5) was observed for subjects carrying at least one copy of both IL4-33 allele T and IL4 VNTR allele 1, who exhibited higher interleukin (IL)-4 plasma levels (p = 0.007). Children homozygous for IL4 VNTR allele 2 had a lower SM risk as well as lower IL-4 plasma levels. Our findings indicate that the genetic interaction between these two IL-4 variants is a key factor of SM susceptibility, probably because of its direct role in IL-4 regulation.

T lymphocytes sense antigens within seconds and make a decision within one minute.

Adaptive immune responses are triggered by the rapid and sensitive detection of MHC-bound peptides by TCRs. The kinetics of early TCR/APC contacts are incompletely known. In this study, we used total internal reflection fluorescence microscopy to image human T cell membranes near model surfaces: contact was mediated by mobile protrusions of <0.4 µm diameter. The mean lifetime of contacts with a neutral surface was 8.6 s. Adhesive interactions increased mean contact time to 27.6 s. Additional presence of TCR ligands dramatically decreased contact to 13.7 s, thus evidencing TCR-mediated triggering of a pulling motion within seconds after ligand encounter. After an interaction typically involving 30-40 contacts formed during a 1-min observation period, TCR stimulation triggered a rapid and active cell spreading. Pulling events and cell spreading were mimicked by pharmacological phospholipase Cγ1 activation, and they were prevented by phospholipase Cγ1 inhibition. These results provide a quantitative basis for elucidating the earliest cell response to the detection of foreign Ags.