V1 Cells Research Articles

Border-ownership tuning determines the connectivity between V4 and V1 in the macaque visual system

Cortical feedback connections are extremely numerous but the logic of connectivity between higher and lower areas remains poorly understood. Feedback from higher visual areas to primary visual cortex (V1) has been shown to enhance responses on perceptual figures compared to backgrounds, an effect known as figure-background modulation (FBM). A likely source of this feedback are border-ownership (BO) selective cells in mid-tier visual areas (e.g. V4) which represent the location of figures. We examined the connectivity between V4 cells and V1 cells using noise-correlations and micro-stimulation to estimate connectivity strength. We show that connectivity is consistent with a model in which BO-tuned V4 cells send positive feedback in the direction of their preferred figure and negative feedback in the opposite direction. This connectivity scheme can recreate patterns of FBM observed in previous studies. These results provide insights into the cortical connectivity underlying figure-background perception and establish a link between FBM and BO-tuning.

Binocular luster elicited by isoluminant chromatic stimuli relies on mechanisms similar to those in the achromatic case.

The phenomenon of binocular luster can be evoked by simple dichoptic center-surround stimuli showing a luminance contrast difference between the eyes. Previous findings support the idea that this phenomenon is mediated by a low-level conflict mechanism that integrates the monocular signals from different types of contrast detector cells. Also, isoluminant stimuli with different chromatic contrasts between eyes can trigger sensations of luster. Here, we investigate whether the lustrous impression in such purely chromatic stimuli depends on interocular contrast differences and in particular on interocular contrast polarity pairings in a similar way as in the achromatic case. In our experiments, we measured the magnitude of the lustrous response using a series of isoluminant dichoptic center-ring-surround stimuli with varying ring width whose chromatic properties were varied along the red-green and blue-yellow cardinal directions. The trends in the data were very similar to those of our former study with achromatic stimuli, indicating similar mechanisms in both cases. The empirical luster data could also be predicted fairly well by a chromatic version of our interocular conflict model (with overall R2 values between 0.577 and 0.639), for which two different receptive field models were used, simulating the behavior of color-sensitive double-opponent cells in V1.

Binocular properties of contrast adaptation in human vision

Adaptation to contrast has been known and studied for 50 years, and the functional importance of dynamic gain control mechanisms is widely recognized. Understanding of binocular combination and binocular fusion has also advanced in the last 20 years, but aside from interocular transfer (IOT), we still know little about binocular properties of contrast adaptation. Our observers adapted to a high contrast 3.6 c/deg grating, and we assessed contrast detection and discrimination across a wide range of test contrasts (plotted as threshold vs contrast [TvC] functions). For each combination of adapt/test eye(s), the adapted TvC data followed a 'dipper' curve similar to the unadapted data, but displaced obliquely to higher contrasts. Adaptation had effectively re-scaled all contrasts by a common factor Cs that varied with the combination of adapt and test eye(s). Cs was well described by a simple 2-parameter model that had separate monocular and binocular gain controls, sited before and after binocular summation respectively. When these two levels of adaptation were inserted into an existing model for contrast discrimination, the extended 2-stage model gave a good account of the TvC functions, their shape invariance with adaptation, and the contrast scaling factors. The underlying contrast-response function is of almost constant shape, and adaptation shifts it to higher contrasts by the factor log10(Cs) – a 'pure contrast gain control'. Evidence of partial IOT in cat V1 cells supports the 2-stage scheme, but is not consistent with a classic (single-stage) model.

Spatial Attention Modulates Neuronal Interactions between Simple and Complex Cells in V1.

Visual perception is profoundly modulated by spatial attention, which can selectively prioritize goal-related information. Previous studies found spatial attention facilitated the efficacy of neuronal communication between visual cortices with hierarchical organizations. In the primary visual cortex (V1), there is also a hierarchical connection between simple (S) and complex (C) cells. We wonder whether and how spatial attention modulates neuronal communication within V1, especially for neuronal pairs with heterogeneous visual input. We simultaneously recorded the pairs' activity from macaque monkeys when they performed a spatial-attention-involved task, then applied likelihood-based Granger causality analysis to explore attentional modulation of neuronal interactions. First, a significant attention-related decrease in Granger causality was found in S-C pairs, which primarily displayed in the S-to-C feedforward connection. Second, the interaction strength of the feedforward connection was significantly higher than that of the feedback under attend toward (AT) conditions. Although information flow did not alter as the attentional focus shifted, the strength of communications between target- and distractor-stimuli-covered neurons differed only when attending to complex cells' receptive fields (RFs). Furthermore, pairs' communications depended on the attentional modulation of neurons' firing rates. Our findings demonstrate spatial attention does not induce specific information flow but rather amplifies directed communication within V1.

Learning a Model of Shape Selectivity in V4 Cells Reveals Shape Encoding Mechanisms in the Brain.

The mechanisms involved in transforming early visual signals to curvature representations in V4 are unknown. We propose a hierarchical model that reveals V1/V2 encodings that are essential components for this transformation to the reported curvature representations in V4. Then, by relaxing the often-imposed prior of a single Gaussian, V4 shape selectivity is learned in the last layer of the hierarchy from Macaque V4 responses. We found that V4 cells integrate multiple shape parts from the full spatial extent of their receptive fields with similar excitatory and inhibitory contributions. Our results uncover new details in existing data about shape selectivity in V4 neurons that with additional experiments can enhance our understanding of processing in this area. Accordingly, we propose designs for a stimulus set that allow removing shape parts without disturbing the curvature signal to isolate part contributions to V4 responses.SIGNIFICANCE STATEMENT Selectivity to convex and concave shape parts in V4 neurons has been repeatedly reported. Nonetheless, the mechanisms that yield such selectivities in the ventral stream remain unknown. We propose a hierarchical computational model that incorporates findings of the various visual areas involved in shape processing and suggest mechanisms that transform the shape signal from low-level features to convex/concave part representations. Learning shape selectivity from Macaque V4 responses in the final processing stage in our model, we found that V4 neurons integrate shape parts from the full spatial extent of their receptive field with both facilitatory and inhibitory contributions. These results reveal hidden information in existing V4 data that with additional experiments can enhance our understanding of processing in V4.

Spontaneous variations in arousal modulate subsequent visual processing and local field potential dynamics in the ferret during quiet wakefulness.

Behavioral states affect neuronal responses throughout the cortex and influence visual processing. Quiet wakefulness (QW) is a behavioral state during which subjects are quiescent but awake and connected to the environment. Here, we examined the effects of pre-stimulus arousal variability on post-stimulus neural activity in the primary visual cortex and posterior parietal cortex in awake ferrets, using pupil diameter as an indicator of arousal. We observed that the power of stimuli-induced alpha (8-12Hz) decreases when the arousal level increases. The peak of alpha power shifts depending on arousal. High arousal increases inter- and intra-areal coherence. Using a simplified model of laminar circuits, we show that this connectivity pattern is compatible with feedback signals targeting infragranular layers in area posterior parietal cortex and supragranular layers in V1. During high arousal, neurons in V1 displayed higher firing rates at their preferred orientations. Broad-spiking cells in V1 are entrained to high-frequency oscillations (>80Hz), whereas narrow-spiking neurons are phase-locked to low- (12-18Hz) and high-frequency (>80Hz) rhythms. These results indicate that the variability and sensitivity of post-stimulus cortical responses and coherence depend on the pre-stimulus behavioral state and account for the neuronal response variability observed during repeated stimulation.

Horizontal connectivity in V1: Prediction of coherence in contour and motion integration

This study demonstrates the functional importance of the Surround context relayed laterally in V1 by the horizontal connectivity, in controlling the latency and the gain of the cortical response to the feedforward visual drive. We report here four main findings: 1) a centripetal apparent motion sequence results in a shortening of the spiking latency of V1 cells, when the orientation of the local inducer and the global motion axis are both co-aligned with the RF orientation preference; 2) this contextual effects grows with visual flow speed, peaking at 150–250°/s when it matches the propagation speed of horizontal connectivity (0.15–0.25 mm/ms); 3) For this speed range, the axial sensitivity of V1 cells is tilted by 90° to become co-aligned with the orientation preference axis; 4) the strength of modulation by the surround context correlates with the spatiotemporal coherence of the apparent motion flow. Our results suggest an internally-generated binding process, linking local (orientation /position) and global (motion/direction) features as early as V1. This long-range diffusion process constitutes a plausible substrate in V1 of the human psychophysical bias in speed estimation for collinear motion. Since it is demonstrated in the anesthetized cat, this novel form of contextual control of the cortical gain and phase is a built-in property in V1, whose expression does not require behavioral attention and top-down control from higher cortical areas. We propose that horizontal connectivity participates in the propagation of an internal “prediction” wave, shaped by visual experience, which links contour co-alignment and global axial motion at an apparent speed in the range of saccade-like eye movements.

Learning V1 Simple Cells with Vector Representation of Local Content and Matrix Representation of Local Motion

This paper proposes a representational model for image pairs such as consecutive video frames that are related by local pixel displacements, in the hope that the model may shed light on motion perception in primary visual cortex (V1). The model couples the following two components: (1) the vector representations of local contents of images and (2) the matrix representations of local pixel displacements caused by the relative motions between the agent and the objects in the 3D scene. When the image frame undergoes changes due to local pixel displacements, the vectors are multiplied by the matrices that represent the local displacements. Thus the vector representation is equivariant as it varies according to the local displacements. Our experiments show that our model can learn Gabor-like filter pairs of quadrature phases. The profiles of the learned filters match those of simple cells in Macaque V1. Moreover, we demonstrate that the model can learn to infer local motions in either a supervised or unsupervised manner. With such a simple model, we achieve competitive results on optical flow estimation.

Classical-Contextual Interactions in V1 May Rely on Dendritic Computations

A signature feature of the neocortex is the dense network of horizontal connections (HCs) through which pyramidal neurons (PNs) exchange “contextual” information. In primary visual cortex (V1), HCs are thought to facilitate boundary detection, a crucial operation for object recognition, but how HCs modulate PN responses to boundary cues within their classical receptive fields (CRF) remains unknown. We began by “asking” natural images, through a structured data collection and ground truth labeling process, what function a V1 cell should use to compute boundary probability from aligned edge cues within and outside its CRF. The “answer” was an asymmetric 2-D sigmoidal function, whose nonlinear form provides the first normative account for the “multiplicative” center-flanker interactions previously reported in V1 neurons (Kapadia et al., 1995, 2000; Polat et al., 1998). Using a detailed compartmental model, we then show that this boundary-detecting classical-contextual interaction function can be computed by NMDAR-dependent spatial synaptic interactions within PN dendrites – the site where classical and contextual inputs first converge in the cortex. In additional simulations, we show that local interneuron circuitry activated by HCs can powerfully leverage the nonlinear spatial computing capabilities of PN dendrites, providing the cortex with a highly flexible substrate for integration of classical and contextual information.

A Computational Model of Direction Selectivity in Macaque V1 Cortex Based on Dynamic Differences between On and Off Pathways.

This paper is about neural mechanisms of direction selectivity (DS) in macaque primary visual cortex, V1. We present data (on male macaque) showing strong DS in a majority of simple cells in V1 layer 4Cα, the cortical layer that receives direct afferent input from the magnocellular division of the lateral geniculate nucleus (LGN). Magnocellular LGN cells are not direction-selective. To understand the mechanisms of DS, we built a large-scale, recurrent model of spiking neurons called DSV1. Like its predecessors, DSV1 reproduces many visual response properties of V1 cells including orientation selectivity. Two important new features of DSV1 are (1) DS is initiated by small, consistent dynamic differences in the visual responses of OFF and ON Magnocellular LGN cells, and (2) DS in the responses of most model simple cells is increased over those of their feedforward inputs; this increase is achieved through dynamic interaction of feedforward and intracortical synaptic currents without the use of intracortical direction-specific connections. The DSV1 model emulates experimental data in the following ways: (1) most 4Cα Simple cells were highly direction-selective but 4Cα Complex cells were not; (2) the preferred directions of the model's direction-selective Simple cells were invariant with spatial and temporal frequency (TF); (3) the distribution of the preferred/opposite ratio across the model's population of cells was very close to that found in experiments. The strong quantitative agreement between DS in data and in model simulations suggests that the neural mechanisms of DS in DSV1 may be similar to those in the real visual cortex.SIGNIFICANCE STATEMENT Motion perception is a vital part of our visual experience of the world. In monkeys, whose vision resembles that of humans, the neural computation of the direction of a moving target starts in the primary visual cortex, V1, in layer 4Cα that receives input from the eye through the lateral geniculate nucleus (LGN). How direction selectivity (DS) is generated in layer 4Cα is an outstanding unsolved problem in theoretical neuroscience. In this paper, we offer a solution based on plausible biological mechanisms. We present a new large-scale circuit model in which DS originates from slightly different LGN ON/OFF response time-courses and is enhanced in cortex without the need for direction-specific intracortical connections. The model's DS is in quantitative agreement with experiments.

Analytic Model for Feature Maps in the Primary Visual Cortex.

A compact analytic model is proposed to describe the combined orientation preference (OP) and ocular dominance (OD) features of simple cells and their mutual constraints on the spatial layout of the combined OP-OD map in the primary visual cortex (V1). This model consists of three parts: (i) an anisotropic Laplacian (AL) operator that represents the local neural sensitivity to the orientation of visual inputs; and (ii) obtain a receptive field (RF) operator that models the anisotropic spatial projection from nearby neurons to a given V1 cell over scales of a few tenths of a millimeter and combines with the AL operator to give an overall OP operator; and (iii) a map that describes how the parameters of these operators vary approximately periodically across V1. The parameters of the proposed model maximize the neural response at a given OP with an OP tuning curve fitted to experimental results. It is found that the anisotropy of the AL operator does not significantly affect OP selectivity, which is dominated by the RF anisotropy, consistent with Hubel and Wiesel's original conclusions that orientation tuning width of V1 simple cell is inversely related to the elongation of its RF. A simplified and idealized OP-OD map is then constructed to describe the approximately periodic local OP-OD structure of V1 in a compact form. It is shown explicitly that the OP map can be approximated by retaining its dominant spatial Fourier coefficients, which are shown to suffice to reconstruct its basic spatial structure. Moreover, this representation is a suitable form to analyze observed OP maps compactly and to be used in neural field theory (NFT) for analyzing activity modulated by the OP-OD structure of V1. Application to independently simulated V1 OP structure shows that observed irregularities in the map correspond to a spread of dominant coefficients in a circle in Fourier space. In addition, there is a strong bias toward two perpendicular directions when only a small patch of local map is included. The bias is decreased as the amount of V1 included in the Fourier transform is increased.

A Polytherapy Strategy Using Vincristine and ALK Inhibitors to Sensitise EML4-ALK-Positive NSCLC.

Simple SummaryLung cancer is the third most common cancer worldwide with poor survival after initial diagnosis. A large proportion, approximately 85%, of patients with lung cancer are classified as non-small cell lung cancer (NSCLC). The most common genetic alterations in NSCLCs are KRAS, EGFR and ALK mutations. Patients carrying the EML4-ALK mutation are treated with potent ALK drugs. Up to date, there are 15 different EML4-ALK mutations found in NSCLC patients. Of note, patients carrying the EML4-ALK V3 mutation respond poorly to ALK chemotherapeutic regime and acquire resistance. The aim of the present study was to assess the potential of a combination chemotherapy using vincristine, a traditional chemotherapeutic drug, and potent ALK drugs. We demonstrated that vincristine sensitises cells carrying EML4-ALK V1 mutation but not V3. Cells carrying the EML4-ALK V3 mutation confer low response to drug combination due to high levels of tubulin acetylation and active proliferation pathways compared to V1 cells.The oncogenic fusion of EML4-ALK is present in about 4–6% of non-small cell lung cancer (NSCLC). A targeted approach with ALK tyrosine kinase inhibitors (TKIs) has been proven highly effective in ALK-positive NSCLC patients. However, despite the initial responses, the outcome of the treatment is variable. Previous studies have shown that the differential response depends in part on the type of EML4-ALK variant. Here, we examined the combination of ALK inhibitors and microtubule poison, vincristine, in cells expressing EML4-ALK V1 and V3, the two most common variants in NSCLC. We showed that combination therapy of ALK-TKIs with vincristine had anti-proliferative effects and blocked RAS/MAPK, PI3K/AKT and JAK/STAT3 signalling pathways in EML4-ALK V1 but not V3 cells. Our results demonstrate that high levels of tubulin acetylation are associated with poor response to vincristine in EML4-ALK V3 cells. Additionally, we demonstrated differences in microtubule stability between the two EML4-ALK fusions. EML4-ALK V3 cells exhibited dynamic microtubules that confer poor response to vincristine compared to V1 cells. Hence, we suggested that the portion of EML4 in the fusion has an important role for the outcome of the combination treatment.

Increasing neural network robustness improves match to macaque V1 eigenspectrum, spatial frequency preference and predictivity.

Task-optimized convolutional neural networks (CNNs) show striking similarities to the ventral visual stream. However, human-imperceptible image perturbations can cause a CNN to make incorrect predictions. Here we provide insight into this brittleness by investigating the representations of models that are either robust or not robust to image perturbations. Theory suggests that the robustness of a system to these perturbations could be related to the power law exponent of the eigenspectrum of its set of neural responses, where power law exponents closer to and larger than one would indicate a system that is less susceptible to input perturbations. We show that neural responses in mouse and macaque primary visual cortex (V1) obey the predictions of this theory, where their eigenspectra have power law exponents of at least one. We also find that the eigenspectra of model representations decay slowly relative to those observed in neurophysiology and that robust models have eigenspectra that decay slightly faster and have higher power law exponents than those of non-robust models. The slow decay of the eigenspectra suggests that substantial variance in the model responses is related to the encoding of fine stimulus features. We therefore investigated the spatial frequency tuning of artificial neurons and found that a large proportion of them preferred high spatial frequencies and that robust models had preferred spatial frequency distributions more aligned with the measured spatial frequency distribution of macaque V1 cells. Furthermore, robust models were quantitatively better models of V1 than non-robust models. Our results are consistent with other findings that there is a misalignment between human and machine perception. They also suggest that it may be useful to penalize slow-decaying eigenspectra or to bias models to extract features of lower spatial frequencies during task-optimization in order to improve robustness and V1 neural response predictivity.

Primary visual cortex straightens natural video trajectories

Many sensory-driven behaviors rely on predictions about future states of the environment. Visual input typically evolves along complex temporal trajectories that are difficult to extrapolate. We test the hypothesis that spatial processing mechanisms in the early visual system facilitate prediction by constructing neural representations that follow straighter temporal trajectories. We recorded V1 population activity in anesthetized macaques while presenting static frames taken from brief video clips, and developed a procedure to measure the curvature of the associated neural population trajectory. We found that V1 populations straighten naturally occurring image sequences, but entangle artificial sequences that contain unnatural temporal transformations. We show that these effects arise in part from computational mechanisms that underlie the stimulus selectivity of V1 cells. Together, our findings reveal that the early visual system uses a set of specialized computations to build representations that can support prediction in the natural environment.

Polarity-dependent orientation illusions: Review, model, and simulations

Polarity-dependent orientation illusions are manifested in figures in which the impression of target orientation does not depend only on geometrical relations between the elements of the figure, but also on the relations between their luminances, that is, on luminance polarities. The best-known phenomenon belonging to this class of effects is the Münsterberg/Café Wall illusion. In this paper a considerable number of examples of this type of illusions are presented, many of which are novel variants. A two-level convolutional model of such illusions is introduced, in which the first level corresponds to the stimulus input and the second level contains units fashioned after simple cells in V1, whose spatial patterns of activity represent the model’s reaction to the stimulus. The main finding of numerous simulations of the model is that the figures inducing illusory impressions of tilt share a common spatial pattern of neural activation, labeled ‘oblique clusters’, which is absent in related non-illusory figures. Furthermore, a similar pattern is also present in simulations of figures which induce veridical impressions of tilt. The simulations suggest that the neural basis of perception of a specific degree of tilt may not be the activity of neurons tuned narrowly to that particular degree of tilt, but rather the presence of certain signature spatial patterns of activity of populations of neurons.

Learning a model of shape selectivity in V4 cells reveals shape encoding mechanisms in the brain

The mechanisms involved in transforming early visual signals to curvature representations in V4 are unknown. We propose a hierarchical model that reveals V1/V2 encodings that are essential components for this transformation to the reported curvature representations in V4. Then, by relaxing the often-imposed prior of a single Gaussian, V4 shape selectivity is learned in the last layer of the hierarchy from Macaque V4 responses. We found that V4 cells integrate multiple shape parts from the full spatial extent of their receptive fields with similar excitatory and inhibitory contributions. Our results uncover new details in existing data about shape selectivity in V4 neurons that with further experiments can enhance our understanding of processing in this area. Accordingly, we propose designs for a stimulus set that allow removing shape parts without disturbing the curvature signal to isolate part contributions to V4 responses.

A multiplicity of color-responsive cortical mechanisms revealed by the dynamics of cVEPs

Our results connect higher-order color mechanisms deduced from psychophysics with the known diversity of populations of double-opponent, color-responsive cells in V1. We used the chromatic visual evoked potential, the cVEP, to study responses in human visual cortex to equiluminant color patterns. Stimuli were modulated along three directions in color space: the cardinal directions, L-M and S, and along the line in color space from the white point to the color of the Red LED in the display screen (the Red direction). The Red direction is roughly intermediate between L-M and S in DKL space in cone-contrast coordinates. While cVEP response amplitude, latency, and width--and their dependences on cone contrast-- were similar in the L-M and Red directions, the Transientness of the Red response was significantly greater than for responses to stimuli in the L-M direction and in the S direction. This difference in response dynamics supports the concept that there are multiple, distinct neuronal populations, so-called higher- order color mechanisms, for color perception within human V1 cortex.

An Anatomically Constrained Model of V1 Simple Cells Predicts the Coexistence of Push-Pull and Broad Inhibition.

The spatial organization and dynamic interactions between excitatory and inhibitory synaptic inputs that define the receptive field (RF) of simple cells in the cat primary visual cortex (V1) still raise the following paradoxical issues: (1) stimulation of simple cells in V1 with drifting gratings supports a wiring schema of spatially segregated sets of excitatory and inhibitory inputs activated in an opponent way by stimulus contrast polarity and (2) in contrast, intracellular studies using flashed bars suggest that although ON and OFF excitatory inputs are indeed segregated, inhibitory inputs span the entire RF regardless of input contrast polarity. Here, we propose a biologically detailed computational model of simple cells embedded in a V1-like network that resolves this seeming contradiction. We varied parametrically the RF-correlation-based bias for excitatory and inhibitory synapses and found that a moderate bias of excitatory neurons to synapse onto other neurons with correlated receptive fields and a weaker bias of inhibitory neurons to synapse onto other neurons with anticorrelated receptive fields can explain the conductance input, the postsynaptic membrane potential, and the spike train dynamics under both stimulation paradigms. This computational study shows that the same structural model can reproduce the functional diversity of visual processing observed during different visual contexts.SIGNIFICANCE STATEMENT Identifying generic connectivity motives in cortical circuitry encoding for specific functions is crucial for understanding the computations implemented in the cortex. Indirect evidence points to correlation-based biases in the connectivity pattern in V1 of higher mammals, whereby excitatory and inhibitory neurons preferentially synapse onto neurons respectively with correlated and anticorrelated receptive fields. A recent intracellular study questions this push-pull hypothesis, failing to find spatial anticorrelation patterns between excitation and inhibition across the receptive field. We present here a spiking model of V1 that integrates relevant anatomic and physiological constraints and shows that a more versatile motif of correlation-based connectivity with selectively tuned excitation and broadened inhibition is sufficient to account for the diversity of functional descriptions obtained for different classes of stimuli.

Pseudomonas arcuscaelestis sp. nov., isolated from rainbow trout and water.

Cells of strains P66T, V1 and W15Feb18 are Gram-stain-negative short rods and motile by one polar flagellum. Strain P66T was isolated from rainbow trout (Oncorhynchus mykiss) cultivated at a fish farm in Turkey. Strain V1 was isolated from sand of an intertidal shore on the Galicia coast in Spain and strain W15Feb18 was isolated from water collected at the Woluwe River in Belgium. Based on 16S rRNA sequence similarity values, the strains were grouped under the genus Pseudomonas and the Pseudomonas putida phylogenetic group of species. The DNA G+C content ranged from 58.5 to 58.9 mol%. The strains were characterized phenotypically by the API 20NE and Biolog GEN III tests, and chemotaxonomically by their whole-cell MALDI-TOF MS protein profiles and fatty acid contents. The absence of the hydrolysis of gelatin and the assimilation of arabinose, mannose and mannitol differentiated these strains from the closest species, Pseudomonas alkylphenolica. The major fatty acid components were C16:0 (29.91-31.68 %) and summed feature 3 (36.44-37.55 %). Multilocus sequence analysis with four and 83 housekeeping gene sequences and a core proteome analysis showed that these strains formed a phylogenetic cluster in the P. putida group of species. Genome comparisons by the average nucleotide identity based on blast and the Genome-to-Genome Distance Calculator demonstrated that the three strains belonged to the same genomic species and were distant from any known species, with similarity values lower than the thresholds established for species in the genus Pseudomonas. These data permitted us to conclude that strains P66T, V1 and W15Feb18 belong to a novel species in the genus Pseudomonas, for which the name Pseudomonas arcuscaelestis sp. nov. is proposed. The type strain is P66T (=CECT 30176T=CCUG 74872T). The other strains have been deposited in the CECT with the corresponding collection numbers: V1 (=CECT 30356) and W15Feb18 (=CECT 30355).

VSIG4(+) peritoneal macrophages induce apoptosis of double-positive thymocyte via the secretion of TNF-\u03b1 in a CLP-induced sepsis model resulting in thymic atrophy

Thymic atrophy in sepsis is a critical disadvantage because it induces immunosuppression and increases the mortality rate as the disease progresses. However, the exact mechanism of thymic atrophy has not been fully elucidated. In this study, we discovered a novel role for VSIG4-positive peritoneal macrophages (V4(+) cells) as the principal cells that induce thymic atrophy and thymocyte apoptosis. In CLP-induced mice, V4(+) cells were activated after ingestion of invading microbes, and the majority of these cells migrated into the thymus. Furthermore, these cells underwent a phenotypic shift from V4(+) to V4(−) and from MHC II(low) to MHC II(+). In coculture with thymocytes, V4(+) cells mainly induced apoptosis in DP thymocytes via the secretion of TNF-α. However, there was little effect on CD4 or CD8 SP and DN thymocytes. V4(−) cells showed low levels of activity compared to V4(+) cells. Thymic atrophy in CLP-induced V4(KO) mice was much less severe than that in CLP-induced wild-type mice. In addition, V4(KO) peritoneal macrophages also showed similar activity to V4(−) cells. Taken together, the current study demonstrates that V4(+) cells play important roles in inducing immunosuppression via thymic atrophy in the context of severe infection. These data also suggest that controlling the function of V4(+) cells may play a crucial role in the development of new therapies to prevent thymocyte apoptosis in sepsis.