AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs for atlas-scale datasets like Human Pancreas Analysis Program (HPAP), we develop AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX shows the higher performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulates known islet pathobiology and shows differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

A presynaptic source drives differing levels of surround suppression in two mouse retinal ganglion cell types.

In early sensory systems, cell-type diversity generally increases from the periphery into the brain, resulting in a greater heterogeneity of responses to the same stimuli. Surround suppression is a canonical visual computation that begins within the retina and is found at varying levels across retinal ganglion cell types. Our results show that heterogeneity in the level of surround suppression occurs subcellularly at bipolar cell synapses. Using single-cell electrophysiology and serial block-face scanning electron microscopy, we show that two retinal ganglion cell types exhibit very different levels of surround suppression even though they receive input from the same bipolar cell types. This divergence of the bipolar cell signal occurs through synapse-specific regulation by amacrine cells at the scale of tens of microns. These findings indicate that each synapse of a single bipolar cell can carry a unique visual signal, expanding the number of possible functional channels at the earliest stages of visual processing.

Optimal Burstiness in Populations of Spiking Neurons Facilitates Decoding of Decreases in Tonic Firing.

A stimulus can be encoded in a population of spiking neurons through any change in the statistics of the joint spike pattern, yet we commonly summarize single-trial population activity by the summed spike rate across cells: the population peristimulus time histogram (pPSTH). For neurons with a low baseline spike rate that encode a stimulus with a rate increase, this simplified representation works well, but for populations with high baseline rates and heterogeneous response patterns, the pPSTH can obscure the response. We introduce a different representation of the population spike pattern, which we call an "information train," that is well suited to conditions of sparse responses, especially those that involve decreases rather than increases in firing. We use this tool to study populations with varying levels of burstiness in their spiking statistics to determine how burstiness affects the representation of spike decreases (firing "gaps"). Our simulated populations of spiking neurons varied in size, baseline rate, burst statistics, and correlation. Using the information train decoder, we find that there is an optimal level of burstiness for gap detection that is robust to several other parameters of the population. We consider this theoretical result in the context of experimental data from different types of retinal ganglion cells and determine that the baseline spike statistics of a recently identified type support nearly optimal detection of both the onset and strength of a contrast step.

AnnoSpat annotates cell types and quantifies cellular arrangements from spatial proteomics.

Cellular composition and anatomical organization influence normal and aberrant organ functions. Emerging spatial single-cell proteomic assays such as Image Mass Cytometry (IMC) and Co-Detection by Indexing (CODEX) have facilitated the study of cellular composition and organization by enabling high-throughput measurement of cells and their localization directly in intact tissues. However, annotation of cell types and quantification of their relative localization in tissues remain challenging. To address these unmet needs, we developed AnnoSpat (Annotator and Spatial Pattern Finder) that uses neural network and point process algorithms to automatically identify cell types and quantify cell-cell proximity relationships. Our study of data from IMC and CODEX show the superior performance of AnnoSpat in rapid and accurate annotation of cell types compared to alternative approaches. Moreover, the application of AnnoSpat to type 1 diabetic, non-diabetic autoantibody-positive, and non-diabetic organ donor cohorts recapitulated known islet pathobiology and showed differential dynamics of pancreatic polypeptide (PP) cell abundance and CD8+ T cells infiltration in islets during type 1 diabetes progression.

Unified classification of mouse retinal ganglion cells using function, morphology, and gene expression.

Classification and characterization of neuronal types are critical for understanding their function and dysfunction. Neuronal classification schemes typically rely on measurements of electrophysiological, morphological, and molecular features, but aligning such datasets has been challenging. Here, we present a unified classification of mouse retinal ganglion cells (RGCs), the sole retinal output neurons. We use visually evoked responses to classify 1,859 mouse RGCs into 42 types. We also obtain morphological or transcriptomic data from subsets and use these measurements to align the functional classification to publicly available morphological and transcriptomic datasets. We create an online database that allows users to browse or download the data and to classify RGCs from their light responses using a machine learning algorithm. This work provides a resource for studies of RGCs, their upstream circuits in the retina, and their projections in the brain, and establishes a framework for future efforts in neuronal classification and open data distribution.

Gap junctions and connexin hemichannels both contribute to the electrical properties of retinal pigment epithelium.

Gap junctions are intercellular channels that permit the transfer of ions and small molecules between adjacent cells. These cellular junctions are particularly dense in the retinal pigment epithelium (RPE), and their contribution to many retinal diseases has been recognized. While gap junctions have been implicated in several aspects of RPE physiology, their role in shaping the electrical properties of these cells has not been characterized in mammals. The role of gap junctions in the electrical properties of the RPE is particularly important considering the growing appreciation of RPE as excitable cells containing various voltage-gated channels. We used a whole-cell patch clamp to measure the electrical characteristics and connectivity between RPE cells, both in cultures derived from human embryonic stem cells and in the intact RPE monolayers from mouse eyes. We found that the pharmacological blockade of gap junctions eliminated electrical coupling between RPE cells, and that the blockade of gap junctions or Cx43 hemichannels significantly increased their input resistance. These results demonstrate that gap junctions function in the RPE not only as a means of molecular transport but also as a regulator of electrical excitability.

Single-cell multi-omics analysis of human pancreatic islets reveals novel cellular states in type 1 diabetes.

Type 1 diabetes (T1D) is an autoimmune disease in which immune cells destroy insulin-producing beta cells. The aetiology of this complex disease is dependent on the interplay of multiple heterogeneous cell types in the pancreatic environment. Here, we provide a single-cell atlas of pancreatic islets of 24 T1D, autoantibody-positive and nondiabetic organ donors across multiple quantitative modalities including ~80,000 cells using single-cell transcriptomics, ~7,000,000 cells using cytometry by time of flight and ~1,000,000 cells using in situ imaging mass cytometry. We develop an advanced integrative analytical strategy to assess pancreatic islets and identify canonical cell types. We show that a subset of exocrine ductal cells acquires a signature of tolerogenic dendritic cells in an apparent attempt at immune suppression in T1D donors. Our multimodal analyses delineate cell types and processes that may contribute to T1D immunopathogenesis and provide an integrative procedure for exploration and discovery of human pancreatic function.

Retinal patterns and the cellular repertoire of neuropsin (Opn5) retinal ganglion cells.

Obtaining a parts list of the sensory components of the retina is vital to understand the effects of light in behavior, health, and disease. Rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs) are the best described photoreceptors in the mammalian retina, but recent functional roles have been proposed for retinal neuropsin (Opn5)-an atypical opsin. However, little is known about the pattern of Opn5 expression in the retina. Using cre (Opn5cre ) and cre-dependent reporters, we uncover patterns of Opn5 expression and find that Opn5 is restricted to retinal ganglion cells (RGCs). Opn5-RGCs are nonhomogenously distributed through the retina, with greater densities of cells located in the dorsotemporal quadrant. In addition to the local topology of these cells, using cre-dependent AAV viral tracing, we surveyed their central targets and found that they are biased towards image-forming and image-stabilizing regions. Finally, molecular and electrophysiological profiling reveal that Opn5-RGCs comprise previously defined RGC types that respond optimally to edges and object-motion (F-mini-ONs, HD2, HD1, LEDs, ooDSRGCs, etc.). Together, these data describe the second collection of RGCs that express atypical opsins in the mouse, and expand the roles of image-forming cells in retinal physiology and function.

Predicting and Manipulating Cone Responses to Naturalistic Inputs.

Primates explore their visual environment by making frequent saccades, discrete and ballistic eye movements that direct the fovea to specific regions of interest. Saccades produce large and rapid changes in input. The magnitude of these changes and the limited signaling range of visual neurons mean that effective encoding requires rapid adaptation. Here, we explore how macaque cone photoreceptors maintain sensitivity under these conditions. Adaptation makes cone responses to naturalistic stimuli highly nonlinear and dependent on stimulus history. Such responses cannot be explained by linear or linear-nonlinear models but are well explained by a biophysical model of phototransduction based on well-established biochemical interactions. The resulting model can predict cone responses to a broad range of stimuli and enables the design of stimuli that elicit specific (e.g., linear) cone photocurrents. These advances will provide a foundation for investigating the contributions of cone phototransduction and post-transduction processing to visual function.SIGNIFICANCE STATEMENT We know a great deal about adaptational mechanisms that adjust sensitivity to slow changes in visual inputs such as the rising or setting sun. We know much less about the rapid adaptational mechanisms that are essential for maintaining sensitivity as gaze shifts around a single visual scene. We characterize how phototransduction in cone photoreceptors adapts to rapid changes in input similar to those encountered during natural vision. We incorporate these measurements into a quantitative model that can predict cone responses across a broad range of stimuli. This model not only shows how cone phototransduction aids the encoding of natural inputs but also provides a tool to identify the role of the cone responses in shaping those of downstream visual neurons.

TooManyPeaks identifies drug-resistant-specific regulatory elements from single-cell leukemic epigenomes.

Emerging single-cell epigenomic assays are used to investigate the heterogeneity of chromatin activity and its function. However, identifying cells with distinct regulatory elements and clearly visualizing their relationships remains challenging. To this end, we introduce TooManyPeaks to address the need for the simultaneous study of chromatin state heterogeneity in both rare and abundant subpopulations. Our analyses of existing data from three widely used single-cell assays for transposase-accessible chromatin using sequencing (scATAC-seq) show the superior performance of TooManyPeaks in delineating and visualizing pure clusters of rare and abundant subpopulations. Furthermore, the application of TooManyPeaks to new scATAC-seq data from drug-naive and drug-resistant leukemic T cells clearly visualizes relationships among these cells and stratifies a rare "resistant-like" drug-naive sub-clone with distinct cis-regulatory elements.

Color vision: More than meets the eye.

Mice can discriminate color, but unlike in primates, studies have so far failed to find robust cone-opponent cells in the retina. A new study shows that a sub-region of the mouse visual thalamus is specialized for processing color.

The vascular landscape of human cancer.

Tumors depend on a blood supply to deliver oxygen and nutrients, making tumor vasculature an attractive anticancer target. However, only a fraction of patients with cancer benefit from angiogenesis inhibitors. Whether antiangiogenic therapy would be more effective if targeted to individuals with specific tumor characteristics is unknown. To better characterize the tumor vascular environment both within and between cancer types, we developed a standardized metric - the endothelial index (EI) - to estimate vascular density in over 10,000 human tumors, corresponding to 31 solid tumor types, from transcriptome data. We then used this index to compare hyper- and hypovascular tumors, enabling the classification of human tumors into 6 vascular microenvironment signatures (VMSs) based on the expression of a panel of 24 vascular "hub" genes. The EI and VMS correlated with known tumor vascular features and were independently associated with prognosis in certain cancer types. Retrospective testing of clinical trial data identified VMS2 classification as a powerful biomarker for response to bevacizumab. Thus, we believe our studies provide an unbiased picture of human tumor vasculature that may enable more precise deployment of antiangiogenesis therapy.

An offset ON-OFF receptive field is created by gap junctions between distinct types of retinal ganglion cells.

In the vertebrate retina, the location of a neuron's receptive field in visual space closely corresponds to the physical location of synaptic input onto its dendrites, a relationship called the retinotopic map. We report the discovery of a systematic spatial offset between the ON and OFF receptive subfields in F-mini-ON retinal ganglion cells (RGCs). Surprisingly, this property does not come from spatially offset ON and OFF layer dendrites, but instead arises from a network of electrical synapses via gap junctions to RGCs of a different type, the F-mini-OFF. We show that the asymmetric morphology and connectivity of these RGCs can explain their receptive field offset, and we use a multicell model to explore the effects of receptive field offset on the precision of edge-location representation in a population. This RGC network forms a new electrical channel combining the ON and OFF feedforward pathways within the output layer of the retina.

Reversed Neurovascular Coupling on Optical Coherence Tomography Angiography Is the Earliest Detectable Abnormality before Clinical Diabetic Retinopathy.

Diabetic retinopathy (DR) has traditionally been viewed as either a microvasculopathy or a neuropathy, though neurovascular coupling deficits have also been reported and could potentially be the earliest derangement in DR. To better understand neurovascular coupling in the diabetic retina, we investigated retinal hemodynamics by optical coherence tomography angiography (OCTA) in individuals with diabetes mellitus (DM) but without DR (DM no DR) and mild non-proliferative DR (mild NPDR) compared to healthy eyes. Using an experimental design to monitor the capillary responses during transition from dark adaptation to light, we examined 19 healthy, 14 DM no DR and 11 mild NPDR individuals. We found that the only structural vascular abnormality in the DM no DR group was increased superficial capillary plexus (SCP) vessel density (VD) compared to healthy eyes, while mild NPDR eyes showed significant vessel loss in the SCP at baseline. There was no significant difference in inner retinal thickness between the groups. During dark adaptation, the deep capillary plexus (DCP) VD was lower in mild NPDR individuals compared to the other two groups, which may leave the photoreceptors more susceptible to ischemia in the dark. When transitioning from dark to ambient light, both diabetic groups showed a qualitative reversal of VD trends in the SCP and middle capillary plexus (MCP), with significantly decreased SCP at 5 min and increased MCP VD at 50 s compared to healthy eyes, which may impede metabolic supply to the inner retina during light adaptation. Mild NPDR eyes also demonstrated DCP dilation at 50 s and 5 min and decreased adjusted flow index at 5 min in light. Our results show altered neurovascular responses in all three macular vascular plexuses in diabetic subjects in the absence of structural neuronal changes on high resolution imaging, suggesting that neurovascular uncoupling may be a key mechanism in the early pathogenesis of DR, well before the clinical appearance of vascular or neuronal loss.

Caffeine Delays Retinal Neurovascular Coupling during Dark to Light Adaptation in Healthy Eyes Revealed by Optical Coherence Tomography Angiography.

Purpose: The purpose of this study was to investigate the acute effects of caffeine on retinal hemodynamics during dark to light adaptation using optical coherence tomography angiography (OCTA). Methods: Thirteen healthy individuals (13 eyes) underwent OCTA imaging after dark adaptation and at repeated intervals during the transition to ambient light in two imaging sessions: control and after ingesting 200 mg of caffeine. We analyzed the parafoveal vessel density (VD) and adjusted flow index (AFI) of the superficial capillary plexus (SCP), middle capillary plexus (MCP), and deep capillary plexus (DCP), as well as the vessel length density (VLD) of the SCP. After adjusting for age, refractive error, and scan quality, we compared parameters between control and caffeine conditions. Results: In the dark, MCP VD decreased significantly after caffeine (-2.63 ± 1.28%). During the transition to light, initially, DCP VD increased (12.55 ± 2.52%), whereas SCP VD decreased (-2.09 ± 0.91%) significantly with caffeine compared to control. By 15 minutes in light, DCP VD reversed and was significantly decreased (-5.45 ± 2.62%), whereas MCP VD increased (4.65 ± 1.74%). There were no differences in AFI or VLD. Conclusions: We show that, overall, caffeine causes a trend of delayed vascular response in all three macular capillary plexuses in response to ambient light. Whereas the MCP is constricted in the dark, during the transition from dark to light, there is initially delay followed by prolonged constriction of the DCP and constriction followed by slow dilation of the SCP. We posit that these delayed vascular responses may present potential risk of capillary ischemia.

TooManyCells identifies and visualizes relationships of single-cell clades.

Identifying and visualizing transcriptionally similar cells is instrumental for accurate exploration of the cellular diversity revealed by single-cell transcriptomics. However, widely used clustering and visualization algorithms produce a fixed number of cell clusters. A fixed clustering 'resolution' hampers our ability to identify and visualize echelons of cell states. We developed TooManyCells, a suite of graph-based algorithms for efficient and unbiased identification and visualization of cell clades. TooManyCells introduces a visualization model built on a concept intentionally orthogonal to dimensionality-reduction methods. TooManyCells is also equipped with an efficient matrix-free divisive hierarchical spectral clustering different from prevalent single-resolution clustering methods. TooManyCells enables multiresolution and multifaceted exploration of single-cell clades. An advantage of this paradigm is the immediate detection of rare and common populations that outperforms popular clustering and visualization algorithms, as demonstrated using existing single-cell transcriptomic data sets and new data modeling drug-resistance acquisition in leukemic T cells.

Trib1 regulates T cell differentiation during chronic infection by restraining the effector program.

In chronic infections, the immune response fails to control virus, leading to persistent antigen stimulation and the progressive development of T cell exhaustion. T cell effector differentiation is poorly understood in the context of exhaustion, but targeting effector programs may provide new strategies for reinvigorating T cell function. We identified Tribbles pseudokinase 1 (Trib1) as a central regulator of antiviral T cell immunity, where loss of Trib1 led to a sustained enrichment of effector-like KLRG1+ T cells, enhanced function, and improved viral control. Single-cell profiling revealed that Trib1 restrains a population of KLRG1+ effector CD8 T cells that is transcriptionally distinct from exhausted cells. Mechanistically, we identified an interaction between Trib1 and the T cell receptor (TCR) signaling activator, MALT1, which disrupted MALT1 signaling complexes. These data identify Trib1 as a negative regulator of TCR signaling and downstream function, and reveal a link between Trib1 and effector versus exhausted T cell differentiation that can be targeted to improve antiviral immunity.

Molecular signatures of retinal ganglion cells revealed through single cell profiling.

Retinal ganglion cells can be classified into more than 40 distinct subtypes, whether by functional classification or transcriptomics. The examination of these subtypes in relation to their physiology, projection patterns, and circuitry would be greatly facilitated through the identification of specific molecular identifiers for the generation of transgenic mice. Advances in single cell transcriptomic profiling have enabled the identification of molecular signatures for cellular subtypes that are only rarely found. Therefore, we used single cell profiling combined with hierarchical clustering and correlate analyses to identify genes expressed in distinct populations of Parvalbumin-expressing cells and functionally classified RGCs. RGCs were manually isolated based either upon fluorescence or physiological distinction through cell-attached recordings. Microarray hybridization and RNA-Sequencing were employed for the characterization of transcriptomes and in situ hybridization was utilized to further characterize gene candidate expression. Gene candidates were identified based upon cluster correlation, as well as expression specificity within physiologically distinct classes of RGCs. Further, we identified Prph, Ctxn3, and Prkcq as potential candidates for ipRGC classification in the murine retina. The use of these genes, or one of the other newly identified subset markers, for the generation of a transgenic mouse would enable future studies of RGC-subtype specific function, wiring, and projection.

Serine substitutions are linked to codon usage and differ for variable and conserved protein regions.

Serine is the only amino acid that is encoded by two disjoint codon sets (TCN & AGY) so that a tandem substitution of two nucleotides is required to switch between the two sets. We show that these codon sets underlie distinct substitution patterns at positions subject to purifying and diversifying selections. We found that in humans, positions that are conserved among ~100 vertebrates, and thus subjected to purifying selection, are enriched for substitutions involving serine (TCN, denoted S'), proline, and alanine, (S'PA). In contrast, the less conserved positions are enriched for serine encoded with AGY codons (denoted S″), glycine and asparagine, (GS″N). We tested this phenomenon in the HIV envelope glycoprotein (gp120), and the V-gene that encodes B-cell receptors/antibodies. These fast evolving proteins both have hypervariable positions, which are under diversifying selection, closely adjacent to highly conserved structural regions. In both instances, we identified an opposite abundance of two groups of serine substitutions, with enrichment of S'PA in the conserved positions, and GS″N in the hypervariable regions. Finally, we analyzed the substitutions across 60,000 individual human exomes to show that, when serine has a specific functional constraint of phosphorylation capability, S' codons are 32-folds less prone than S″ to substitutions to Threonine or Tyrosine that could potentially retain the phosphorylation site capacity. Combined, our results, that cover evolutionary signals at different temporal scales, demonstrate that through its encoding by two codon sets, serine allows for the existence of alternating substitution patterns within positions of functional maintenance versus sites of rapid diversification.