Biology subjects

Jain, V.

Publications and source records attributed to Jain, V..

50 records · Page 3Linked to original sources

bioRxiv2020

A circulating T-cell differentiation marker to predict response to immune checkpoint inhibitors

Immune checkpoint inhibitors (ICI) have revolutionized treatment for various cancers; however, durable response is limited to only a subset of patients. Discovery of blood-based biomarkers that reflect dynamic change of the tumor microenvironment, and predict response to ICI will markedly improve current treatment regimens. Here, we investigated a role of CX3C chemokine receptor 1 (CX3CR1), a marker of T-cell differentiation, in predicting response to ICI therapy. Successful treatment of tumor-bearing mice with ICI increased the frequency and T-cell receptor clonality of the peripheral CX3CR1+CD8+ T-cell subset that included an enriched repertoire of tumor-specific and tumor-infiltrating CD8+ T cells. Furthermore, an increase in the frequency of the CX3CR1+ subset in circulating CD8+ T cells early after initiation of anti-PD-1 therapy correlated with response and survival in patients with non-small cell lung cancer (NSCLC). Taken together, these data support T-cell CX3CR1 expression as a blood-based dynamic biomarker to predict response to ICI therapy.

immunology↗

bioRxiv2020

Neuronal Subcompartment Classification and Merge Error Correction

Recent advances in 3d electron microscopy are yielding ever larger reconstructions of brain tissue, encompassing thousands of individual neurons interconnected by millions of synapses. Interpreting reconstructions at this scale demands advances in the automated analysis of neuronal morphologies, for example by identifying morphological and functional subcompartments within neurons. We present a method that for the first time uses full 3d input (voxels) to automatically classify reconstructed neuron fragments as axon, dendrite, or somal subcompartments. Based on 3d convolutional neural networks, this method achieves a mean f1-score of 0.972, exceeding the previous state of the art of 0.955. The resulting predictions can support multiple analysis and proofreading applications. In particular, we leverage finely localized subcompartment predictions for automated detection and correction of merge errors in the volume reconstruction, successfully detecting 90.6% of inter-class merge errors with a false positive rate of only 2.7%.

neuroscience↗

bioRxiv2020

Structured sampling of olfactory input by the fly mushroom body

Associative memory formation and recall in the adult fruit fly Drosophila melanogaster is subserved by the mushroom body (MB). Upon arrival in the MB, sensory information undergoes a profound transformation. Olfactory projection neurons (PNs), the main MB input, exhibit broadly tuned, sustained, and stereotyped responses to odorants; in contrast, their postsynaptic targets in the MB, the Kenyon cells (KCs), are nonstereotyped, narrowly tuned, and only briefly responsive to odorants. Theory and experiment have suggested that this transformation is implemented by random connectivity between KCs and PNs. However, this hypothesis has been challenging to test, given the difficulty of mapping synaptic connections between large numbers of neurons to achieve a unified view of neuronal network structure. Here we used a recent whole-brain electron microscopy (EM) volume of the adult fruit fly to map large numbers of PN- to-KC connections at synaptic resolution. Comparison of the observed connectome to precisely defined null models revealed unexpected network structure, in which a subset of food-responsive PN types converge on individual downstream KCs more frequently than expected. The connectivity bias is consistent with the neurogeometry: axons of the overconvergent PNs tend to arborize near one another in the MB main calyx, making local KC dendrites more likely to receive input from those types. Computational modeling of the observed PN-to-KC network showed that input from the overconvergent PN types is better discriminated than input from other types. These results suggest an associative fovea for olfaction, in that the MB is wired to better discriminate more frequently occurring and ethologically relevant combinations of food-related odors.

neuroscience↗

bioRxiv2020

Adhatoda Vasica ameliorates cellular hypoxia dependent mitochondrial dysfunction in acute and severe asthmatic mice.

Severe asthma is a chronic airway disease that exhibits poor response to conventional asthma therapies. Growing evidence suggests that elevated hypoxia increases the severity of asthmatic inflammation among patients and in model systems. In this study, we elucidate the therapeutic effects and mechanistic basis of Adhatoda Vasica (AV) aqueous extract on mouse models of acute allergic as well as severe asthma subtypes at physiological, histopathological, and molecular levels. Oral administration of AV extract attenuates the increased airway resistance and inflammation in acute allergic asthmatic mice and alleviates the molecular signatures of steroid (dexamethasone) resistance like IL-17A, KC, and HIF-1 (hypoxia inducible factor-1alpha) in severe asthmatic mice. AV inhibits HIF-1 levels through restoration of expression of its negative regulator-PHD2 (prolyl hydroxylase domain-2). Alleviation of hypoxic response mediated by AV is further confirmed in the acute and severe asthma model. AV reverses cellular hypoxia-induced mitochondrial dysfunction in human bronchial epithelial cells - evident from bioenergetic profiles and morphological analysis of mitochondria. In silico docking of AV constituents reveal higher negative binding affinity for C and O-glycosides for HIF-1, IL-6, Janus kinase 1/3, TNF- and TGF-{beta}-key players of hypoxia-inflammation. This study for the first time provides a molecular basis of action and effect of AV whole extract that is widely used in Ayurveda practice for diverse respiratory ailments. Further, through its effect on hypoxia-induced mitochondrial dysfunction, the study highlights its potential to treat severe steroid-resistant asthma. Significance StatementSevere asthma is a global health concern with a large fraction unresponsive to current treatment modalities involving corticosteroids. Recent findings suggest that elevated hypoxia has a critical role in severity of asthma. Here, we report therapeutic treatment with aqueous extract of Adhatoda Vasica (AV), an ayurvedic medicine, attenuates sever steroid insensitive asthmatic features in mice. The observed effects of AV are through inhibition of hypoxic response, both in vivo and in vitro. AV also reverses mitochondrial dysfunction, a key consequence associated with hypoxia, and asthma. This study highlights the translational potential of AV for the treatment of severe asthma and provides opportunities for its usage in other disease conditions where hypoxia is pertinent.

immunology↗

bioRxiv2020

Spatial integration during active tactile sensation drives elementary shape perception

Active haptic sensation is critical for object identification and manipulation, such as for tool use in humans, or prey capture in rodents. The neural circuit basis for recognizing objects through active touch alone is poorly understood. To address this gap, we combined optogenetics, two photon imaging, and high-speed behavioral tracking in mice solving a novel surface orientation discrimination task with their whiskers. We found that orientation discrimination required animals to summate input from multiple whiskers specifically along the whisker arc. Many animals discriminated the orientation of the stimulus per se, as their performance was invariant to the specific location of the presented stimulus. Two photon imaging showed that populations of neurons in the barrel cortex encoded each of the discriminated orientations, and this coding depended on integration over the whisker array. Finally, acute optogenetic inactivation of the barrel cortex strongly impaired surface orientation discrimination, and even cell-type specific optogenetic suppression of layer 4 excitatory neurons degraded performance, implying a role for superficial layers in this computation. These data suggest a model in which spatial summation over an active haptic array generates representations of an objects surface orientations. These computations may facilitate the encoding of complex three-dimensional objects during active exploration.

neuroscience↗

bioRxiv2020

An anatomical substrate of credit assignment in reinforcement learning

A key problem in learning is credit assignment. Biological systems lack a plausible mechanism to implement the backpropagation approach, a method that underlies much of the dramatic progress in artificial intelligence. Here, we use automated connectomic analysis to show that the synaptic architecture of songbird basal ganglia (Area X) supports local credit assignment using a variant of a node perturbation algorithm proposed in a model of reinforcement learning. Using two volume electron microscopy (vEM) datasets, we find that key predictions of the model hold true: axons that encode exploratory variability terminate predominantly on dendritic shafts, while axons that encode song timing (context) terminate predominantly on spines. Based on the detailed EM data, we then built a biophysical model of reinforcement learning that suggests that the synaptic dichotomy between variability and context encoding axons facilitates efficient learning. In combination, these findings provide strong evidence for a general, biologically plausible credit assignment model in vertebrate basal ganglia learning. One Sentence SummaryUsing automated connectomic analysis and biophysical modeling, we show how the basal ganglia could solve the credit assignment problem on the synaptic level.

neuroscience↗

bioRxiv2019

Semaphorin 3A induces cytoskeletal paralysis in tumor-specific CD8+ T cells

Semaphorin-3A (Sema3A) regulates tumor angiogenesis, but its role in modulating anti-tumor immunity is unclear. We demonstrate that Sema3A secreted within the tumor microenvironment (TME) suppresses tumor-specific CD8+ T cell function via Neuropilin-1 (NRP1), a receptor that is upregulated upon activation with T cells cognate antigen. Sema3A inhibits T cell migration, assembly of the immunological synapse, and tumor killing. It achieves these functional effects through hyper-activating the acto-myosin system in T cells leading to cellular paralysis. Finally, using a clear cell renal cell carcinoma patient cohort, we demonstrate that human tumor-specific CD8+ T cells express NRP1 and are trapped in Sema3A rich regions of tumors. Our study establishes Sema3A as a potent inhibitor of anti-tumor immunity.

immunology↗

bioRxiv2019

PDGFRA Defines the Mesenchymal Stem Cell Kaposi’s Sarcoma Progenitors by Enabling KSHV Oncogenesis in an Angiogenic Environment

Kaposis sarcoma (KS) is an AIDS-defining cancer caused by the KS-associated herpesvirus (KSHV). Unanswered questions regarding KS are its cellular ontology and the conditions conducive to viral oncogenesis. We identify PDGFRA(+)/SCA-1(+) bone marrow-derived mesenchymal stem cells (P(+)S MSCs) as KS spindle-cell progenitors and found that pro-angiogenic environmental conditions typical of KS are critical for KSHV sarcomagenesis. This is because growth in KS-like conditions generates a de-repressed KSHV epigenome allowing oncogenic KSHV gene expression in infected P(+)S MSCs. Furthermore, these growth conditions allow KSHV-infected P(+)S MSCs to overcome KSHV-driven oncogene-induced senescence and cell cycle arrest via a PDGFRA-signaling mechanism; thus identifying PDGFRA not only as a phenotypic determinant for KS-progenitors but also as a critical enabler for viral oncogenesis.\n\nAUTHOR SUMMARYIdentification of the KS progenitor cell creates the possibility of studying viral oncogenesis and its determinants from its initial steps as a continuum. It also increases our understanding of pathogenic mechanisms and disease preferential tropism. Hereby we identify P(+)S-MSCs as KS progenitors, in which KSHV infection has oncogenic consequences; only when these cells are in a pro-angiogenic environment in which PDGFRA activation enables an oncogenic de-repressed KSHV epigenome. These results identify a KS-progenitor population in the P(+)S-MSCs and point to pro-angiogenic environmental conditions as essential for oncogenic viral gene expression and transformation. We designed a novel model of KSHV oncogenesis, creating a very robust platform to identify KSHV oncogenic pathways and their relationship with cellular lineages and extracellular growth environments.

cancer biology↗

bioRxiv2019

Precise subcellular functional organization of excitation and inhibition in the direction-selective ganglion cell circuit

Recent studies indicate that the precise timing and location of excitation and inhibition (E/I) within active dendritic trees can significantly impact neuronal function. How excitatory and inhibitory inputs are functionally organized at the subcellular level in intact circuits remains unclear. To address this issue, we took advantage of the retinal direction-selective ganglion cell circuit, in which directionally tuned inhibitory GABAergic input arising from starburst amacrine cells shape direction-selective dendritic responses. We combined two-photon Ca2+ imaging with genetic, pharmacological, and single-cell ablation methods to examine local E/I. We demonstrate that when active dendritic conductances are blocked, direction selectivity emerges semi-independently within unusually small dendritic segments (<10 {micro}m). Impressively, the direction encoded by each segment is relatively homogenous throughout the ganglion cells dendritic tree. Together the results demonstrate a precise subcellular functional organization of excitatory and inhibitory input, which suggests that the parallel processing scheme proposed for direction encoding could be more fine-grained than previously envisioned.

neuroscience↗

bioRxiv2019

Automated Reconstruction of a Serial-Section EM Drosophila Brain with Flood-Filling Networks and Local Realignment

Reconstruction of neural circuitry at single-synapse resolution is a key target for improving understanding of the nervous system in health and disease. Serial section transmission electron microscopy (ssTEM) is among the most prolific imaging methods employed in pursuit of such reconstructions. We demonstrate how Flood-Filling Networks (FFNs) can be used to computationally segment a forty-teravoxel whole-brain Drosophila ssTEM volume. To compensate for data irregularities and imperfect global alignment, FFNs were combined with procedures that locally re-align serial sections as well as dynamically adjust and synthesize image content. The proposed approach produced a largely merger-free segmentation of the entire ssTEM Drosophila brain, which we make freely available. As compared to manual tracing using an efficient skeletonization strategy, the segmentation enabled circuit reconstruction and analysis workflows that were an order of magnitude faster.

neuroscience↗

bioRxiv2019

Segmentation-Enhanced CycleGAN

Algorithmic reconstruction of neurons from volume electron microscopy data traditionally requires training machine learning models on dataset-specific ground truth annotations that are expensive and tedious to acquire. We enhanced the training procedure of an unsupervised image-to-image translation method with additional components derived from an automated neuron segmentation approach. We show that this method, Segmentation-Enhanced CycleGAN (SECGAN), enables near perfect reconstruction accuracy on a benchmark connectomics segmentation dataset despite operating in a "zero-shot" setting in which the segmentation model was trained using only volumetric labels from a different dataset and imaging method. By reducing or eliminating the need for novel ground truth annotations, SECGANs alleviate one of the main practical burdens involved in pursuing automated reconstruction of volume electron microscopy data.

neuroscience↗

bioRxiv2018

Learning cellular morphology with neural networks

Reconstruction and annotation of volume electron microscopy data sets of brain tissue is challenging, but can reveal invaluable information about neuronal circuits. Significant progress has recently been made in automated neuron reconstruction, as well as automated detection of synapses. However, methods for automating the morphological analysis of nanometer-resolution reconstructions are less established, despite their diverse application possibilities. Here, we introduce cellular morphology neural networks (CMNs), based on multi-view projections sampled from automatically reconstructed cellular fragments of arbitrary size and shape. Using unsupervised training we inferred morphology embeddings (\"Neuron2vec\") of neuron reconstructions and trained CMNs to identify glia cells in a supervised classification paradigm which was then used to resolve neuron reconstruction errors. Finally, we demonstrate that CMNs can be used to identify subcellular compartments and the cell types of neuron reconstructions.

neuroscience↗

bioRxiv2018

Cell-intrinsic genetic regulation of peripheral memory-phenotype T cell frequencies

Memory T and B lymphocyte numbers are thought to be regulated by recent and cumulative microbial exposures. We report here that memory-phenotype lymphocyte frequencies in B, CD4 and CD8 T-cells in 3-monthly serial bleeds from healthy young adult humans were relatively stable over a 1-year period, while recently activated -B and -CD4 T cell frequencies were not, suggesting that recent environmental exposures affected steady state levels of recently activated but not of memory lymphocyte subsets. Frequencies of memory B and CD4 T cells were not correlated, suggesting that variation in them was unlikely to be determined by cumulative antigenic exposures. Immunophenotyping of adult siblings showed high concordance in memory, but not of recently activated lymphocyte subsets, suggesting genetic regulation of memory lymphocyte frequencies. To explore this possibility further, we screened effector memory (EM)-phenotype T cell frequencies in common independent inbred mice strains. Using two pairs from these strains that differed predominantly in either CD4EM and/or CD8EM frequencies, we constructed bi-parental bone marrow chimeras in F1 recipient mice, and found that memory T cell frequencies in recipient mice were determined by donor genotypes. Together, these data suggest cell-autonomous determination of memory T niche size, and suggest mechanisms maintaining immune variability.

immunology↗

bioRxiv2017

High-Precision Automated Reconstruction of Neurons with Flood-filling Networks

Reconstruction of neural circuits from volume electron microscopy data requires the tracing of complete cells including all their neurites. Automated approaches have been developed to perform the tracing, but without costly human proofreading their error rates are too high to obtain reliable circuit diagrams. We present a method for automated segmentation that, like the majority of previous efforts, employs convolutional neural networks, but contains in addition a recurrent pathway that allows the iterative optimization and extension of the reconstructed shape of individual neural processes. We used this technique, which we call flood-filling networks, to trace neurons in a data set obtained by serial block-face electron microscopy from a male zebra finch brain. Our method achieved a mean error-free neurite path length of 1.1 mm, an order of magnitude better than previously published approaches applied to the same dataset. Only 4 mergers were observed in a neurite test set of 97 mm path length.

neuroscience↗