Biology subjects

Mehta, A.

Publications and source records attributed to Mehta, A..

At least 55 records · Page 3Linked to original sources

bioRxiv2022

Perceptual stability reflected in neuronal pattern similarities in human visual cortex

The magnitude of neuronal activation is commonly considered a critical factor for conscious perception of visual content. However, this dogma contrasts with the phenomenon of rapid adaptation, in which the magnitude of neuronal activation drops dramatically in a rapid manner, while the visual stimulus and the conscious experience it elicits remain stable. Here we report that the profiles of multi-site activation patterns and their relational geometry -i.e. the similarity distances between activation patterns, as revealed using iEEG recordings, are sustained during extended stimulation despite the major magnitude decrease. These results are compatible with the hypothesis that conscious perceptual content is associated with the neuronal pattern profiles and their similarity distances, rather than by the overall activation magnitude, in human visual cortex.

neuroscience↗

bioRxiv2022

Semantic novelty modulates neural responses to visual change across the human brain

Our continuous visual experience in daily life is dominated by change. Previous research has focused on visual change due to stimulus motion, eye movements or unfolding events, but not their combined impact across the brain, or their interactions with semantic novelty. We investigate the neural responses to these sources of novelty during film viewing. We analyzed intracranial recordings in humans across 6328 electrodes from 23 individuals. Responses associated with saccades and film cuts were dominant across the entire brain. Film cuts at semantic event boundaries were particularly effective in the temporal and medial temporal lobe. Saccades to visual targets with high visual novelty were also associated with strong neural responses. Specific locations in higher-order association areas showed selectivity to either high or low-novelty saccades. We conclude that neural activity associated with film cuts and eye movements is widespread across the brain and is modulated by semantic novelty.

neuroscience↗

bioRxiv2022

Saccadic modulation of neural excitability in auditory areas of the neocortex

SummaryIn natural "active" vision, humans and other primates use eye movements (saccades) to sample bits of information from visual scenes. In this process, nonretinal signals linked to saccades shift visual cortical neurons to a high excitability state as each saccade ends. The extent of this saccadic modulation outside of the visual system is unknown. Here, we show that during natural viewing, saccades modulate excitability in numerous auditory cortical areas, with a pattern complementary to that seen in visual areas. Bi-directional functional connectivity patterns suggest that these effects may arise from regions involved in saccade generation. By using saccadic signals to yoke excitability states in auditory areas to those in visual areas, the brain can improve information processing in complex natural settings.

neuroscience↗

bioRxiv2022

Multiplexed measurement of binding- and neutralizing antibodies to SARS-CoV-2 variants in 12.000 post-vaccine sera

Diagnostic assays currently used to monitor the efficacy of COVID-19 vaccines measure levels of antibodies to the receptor-binding domain of ancestral SARS-CoV-2 (RBDwt). However, the predictive value for protection against new variants of concern (VOCs) has not been firmly established. Here, we used bead-based arrays and flow cytometry to measure binding of antibodies to spike proteins and receptor-binding domains (RBDs) from VOCs in 12,000 sera. Effects of sera on RBD-ACE2 interactions were measured as a proxy for neutralizing antibodies. The samples were obtained from healthy individuals or patients on immunosuppressive therapy who had received two to four doses of COVID-19 vaccines and from COVID-19 convalescents. The results show that anti-RBDwt titers correlate with the levels of binding- and neutralizing antibodies against the Alpha, Beta, Gamma, Delta, Epsilon and Omicron variants. The benefit of multiplexed analysis lies in the ability to measure a wide range of anti-RBD titers using a single dilution of serum for each assay. The reactivity patterns also yield an internal reference for neutralizing activity and binding antibody units per milliliter (BAU/ml). Results obtained with sera from vaccinated healthy individuals and patients confirmed and extended results from previous studies on time-dependent waning of antibody levels and effects of immunosuppressive agents. We conclude that anti-RBDwt titers correlate with levels of neutralizing antibodies against VOCs and propose that our method may be implemented to enhance the precision and throughput of immunomonitoring.

immunology↗

bioRxiv2022

Plasma proteomic biomarkers identify non-responders and reveal biological insights about the tumor microenvironment in melanoma patients after PD1 blockade

Most patients treated with immune checkpoint blockade (ICB) do not have durable treatment responses. Therefore, there is a critical need to identify early non-invasive biomarkers of response. We performed plasma proteomic analysis (>700 proteins) at three timepoints on 174 metastatic melanoma patients treated with ICB. We leverage independent training and testing cohorts to build a predictor of immunotherapy response that outperforms several tissue-based approaches. We found 217 differentially expressed proteins between ICB responders (R) and non-responders (NR), including a co-regulated module of proteins enriched in certain NR patients. By analyzing single-cell RNA-sequencing data of tumor biopsies from 32 patients, we dissected the relative contribution of cells in the tumor to proteins in circulation. The majority of proteins in the co-regulated NR module derived from tumor and myeloid cells. Amongst myeloid cells, we identified a subset of tumor-associated macrophages (TAMs) with a suppressive phenotype that expressed high levels of the co-regulated NR module, thus suggesting they are key drivers of non-response signatures. Together, our data demonstrates the utility of plasma proteomics in biomarker discovery and in understanding the biology of host response to tumors.

cancer biology↗

bioRxiv2021

Artificial Intelligence uncovers carcinogenic human metabolites

The genome of a eukaryotic cell is often vulnerable to both intrinsic and extrinsic threats due to its constant exposure to a myriad of heterogeneous compounds. Despite the availability of innate DNA damage response pathways, some genomic lesions trigger cells for malignant transformation. Accurate prediction of carcinogens is an ever-challenging task due to the limited information about bona fide (non)carcinogens. We developed Metabokiller, an ensemble classifier that accurately recognizes carcinogens by quantitatively assessing their electrophilicity as well as their potential to induce proliferation, oxidative stress, genomic instability, alterations in the epigenome, and anti-apoptotic response. Concomitant with the carcinogenicity prediction, Metabokiller is fully interpretable since it reveals the contribution of the aforementioned biochemical properties in imparting carcinogenicity. Metabokiller outperforms existing best-practice methods for carcinogenicity prediction. We used Metabokiller to unravel cells endogenous metabolic threats by screening a large pool of human metabolites and predicted a subset of these metabolites that could potentially trigger malignancy in normal cells. To cross-validate Metabokiller predictions, we performed a range of functional assays using Saccharomyces cerevisiae and human cells with two Metabokiller-flagged human metabolites namely 4-Nitrocatechol and 3,4-Dihydroxyphenylacetic acid and observed high synergy between Metabokiller predictions and experimental validations.

bioinformatics↗

bioRxiv2021

Marker-free characterization of single live circulating tumor cell full-length transcriptomes

The identification and characterization of circulating tumor cells (CTCs) are important for gaining insights into the biology of metastatic cancers, monitoring disease progression, and medical management of the disease. The limiting factor that hinders enrichment of purified CTC populations is their sparse availability, heterogeneity, and altered phenotypic traits relative to the tumor of origin. Intensive research both at the technical and molecular fronts led to the development of assays that ease CTC detection and identification from the peripheral blood. Most CTC detection methods use a mix of size selection, immune marker based white blood cells (WBC) depletion, and positive enrichment antibodies targeting tumor-associated antigens. However, the majority of these methods either miss out on atypical CTCs or suffer from WBC contamination. Single-cell RNA sequencing (scRNA-Seq) of CTCs provides a wealth of information about their tumors of origin as well as their fate and is a potent method of enabling unbiased identification of CTCs. We present unCTC, an R package for unbiased identification and characterization of CTCs from single-cell transcriptomic data. unCTC features many standard and novel computational and statistical modules for various analysis tasks. These include a novel method of scRNA-Seq clustering, named Deep Dictionary Learning using K-means clustering cost (DDLK), expression based copy number variation (CNV) inference, and combinatorial, marker-based verification of the malignant phenotypes. DDLK enables robust segregation of CTCs and WBCs in the pathway space, as opposed to the gene expression space. We validated the utility of unCTC on scRNA-Seq profiles of breast CTCs from six patients, captured and profiled using an integrated ClearCell(R) FX and PolarisTM workflow that works by the principles of size-based separation of CTCs and marker based WBC depletion.

bioinformatics↗

bioRxiv2021

Spatial-proteomics reveal in-vivo phospho-signaling dynamics at subcellular resolution

Dynamic change in subcellular localization of signaling proteins is a general concept that eukaryotic cells evolved for eliciting a coordinated response to stimuli. Mass spectrometry (MS)-based proteomics in combination with subcellular fractionation can provide comprehensive maps of spatio-temporal regulation of cells, but involves laborious workflows that does not cover the phospho-proteome level. Here we present a high-throughput workflow based on sequential cell fractionation to profile the global proteome and phospho-proteome dynamics across six distinct subcellular fractions. We benchmarked the workflow by studying spatio-temporal EGFR phospho-signaling dynamics in-vitro in HeLa cells and in-vivo in mouse tissues. Finally, we investigated the spatio-temporal stress signaling, revealing cellular relocation of ribosomal proteins in response to hypertonicity and muscle contraction. Proteomics data generated in this study can be explored through https://SpatialProteoDynamics.github.io.

systems biology↗

bioRxiv2020

Plasma proteomics reveals tissue-specific cell death and mediators of cell-cell interactions in severe COVID-19 patients

COVID-19 has caused over 1 million deaths globally, yet the cellular mechanisms underlying severe disease remain poorly understood. By analyzing several thousand plasma proteins in 306 COVID-19 patients and 78 symptomatic controls over serial timepoints using two complementary approaches, we uncover COVID-19 host immune and non-immune proteins not previously linked to this disease. Integration of plasma proteomics with nine published scRNAseq datasets shows that SARS-CoV-2 infection upregulates monocyte/macrophage, plasmablast, and T cell effector proteins. By comparing patients who died to severely ill patients who survived, we identify dynamic immunomodulatory and tissue-associated proteins associated with survival, providing insights into which host responses are beneficial and which are detrimental to survival. We identify intracellular death signatures from specific tissues and cell types, and by associating these with angiotensin converting enzyme 2 (ACE2) expression, we map tissue damage associated with severe disease and propose which damage results from direct viral infection rather than from indirect effects of illness. We find that disease severity in lung tissue is driven by myeloid cell phenotypes and cell-cell interactions with lung epithelial cells and T cells. Based on these results, we propose a model of immune and epithelial cell interactions that drive cell-type specific and tissue-specific damage in severe COVID-19.

systems biology↗

bioRxiv2020

Induction of a regulatory myeloid program in bacterial sepsis and severe COVID-19

A recent estimate suggests that one in five deaths globally are associated with sepsis1. To date, no targeted treatment is available for this syndrome, likely due to substantial patient heterogeneity2,3 and our lack of insight into sepsis immunopathology4. These issues are highlighted by the current COVID-19 pandemic, wherein many clinical manifestations of severe SARS-CoV-2 infection parallel bacterial sepsis5-8. We previously reported an expanded CD14+ monocyte state, MS1, in patients with bacterial sepsis or non-infectious critical illness, and validated its expansion in sepsis across thousands of patients using public transcriptomic data9. Despite its marked expansion in the circulation of bacterial sepsis patients, its relevance to viral sepsis and association with disease outcomes have not been examined. In addition, the ontogeny and function of this monocyte state remain poorly characterized. Using public transcriptomic data, we show that the expression of the MS1 program is associated with sepsis mortality and is up-regulated in monocytes from patients with severe COVID-19. We found that blood plasma from bacterial sepsis or COVID-19 patients with severe disease induces emergency myelopoiesis and expression of the MS1 program, which are dependent on the cytokines IL-6 and IL-10. Finally, we demonstrate that MS1 cells are broadly immunosuppressive, similar to monocytic myeloid-derived suppressor cells (MDSCs), and have decreased responsiveness to stimulation. Our findings highlight the utility of regulatory myeloid cells in sepsis prognosis, and the role of systemic cytokines in inducing emergency myelopoiesis during severe bacterial and SARS-CoV-2 infections.

immunology↗

bioRxiv2020

Single-nucleus and spatial transcriptomics of archival pancreatic cancer reveals multi-compartment reprogramming after neoadjuvant treatment

Pancreatic ductal adenocarcinoma (PDAC) remains a treatment-refractory disease. Characterizing PDAC by mRNA profiling remains particularly challenging. Previously identified bulk expression subtypes were influenced by contaminating stroma and have not yet informed clinical management, whereas single cell RNA-seq (scRNA-seq) of fresh tumors under-represented key cell types. Here, we developed a robust single-nucleus RNA-seq (snRNA-seq) technique for frozen archival PDAC specimens and used it to study both untreated tumors and those that received neoadjuvant chemotherapy and radiotherapy (CRT). Gene expression programs learned across untreated malignant cell and fibroblast profiles uncovered a clinically relevant molecular taxonomy with improved prognostic stratification compared to prior classifications. Moreover, in the increasingly-adopted neoadjuvant treatment context, there was a depletion of classical-like phenotypes in malignant cells in favor of basal-like phenotypes associated with TNF-NFkB and interferon signaling as well as the presence of novel acinar and neuroendocrine classical-like states, which may be more resilient to cytotoxic treatment. Spatially-resolved transcriptomics revealed an association between malignant cells expressing these basal-like programs and higher immune infiltration with increased lymphocytic content, whereas those exhibiting classical-like programs were linked to sparser macrophage-predominant microniches, perhaps pointing to susceptibility to distinct therapeutic strategies. Our refined molecular taxonomy and spatial resolution can help advance precision oncology in PDAC through informative stratification in clinical trials and insights into differential therapeutic targeting leveraging the immune system.

genomics↗

bioRxiv2020

Functional characterization of human Heschl's gyrus in response to natural speech

Heschls gyrus (HG) is a brain area that includes the primary auditory cortex in humans. Due to the limitations in obtaining direct neural measurements from this region during naturalistic speech listening, the functional organization and the role of HG in speech perception remains uncertain. Here, we used intracranial EEG to directly record the neural activity in HG in eight neurosurgical patients as they listened to continuous speech stories. We studied the spatial distribution of acoustic tuning and the organization of linguistic feature encoding. We found a main gradient of change from posteromedial to anterolateral parts of HG. Along this direction, we observed a decrease in frequency and temporal modulation tuning, and an increase in phonemic representation, speaker normalization, speech-sensitivity, and response latency. We did not observe a difference between the two brain hemispheres. These findings reveal a functional role for HG in processing and transforming simple to complex acoustic features and informs neurophysiological models of speech processing in the human auditory cortex.

neuroscience↗

bioRxiv2020

Positioning of nucleosomes containing γ-H2AXprecedes active DNA demethylation and transcription initiation

In addition to nucleosomes, chromatin contains non-histone chromatin-associated proteins, of which the high-mobility group (HMG) proteins are the most abundant. Chromatin-mediated regulation of transcription involves DNA methylation and histone modifications. However, the order of events and the precise function of HMG proteins during transcription initiation remain unclear. Here we show that HMG AT-hook 2 protein (HMGA2) induces DNA nicks at the transcription start site, which are required by the histone chaperone FACT (facilitates chromatin transcription) complex to incorporate nucleosomes containing the histone variant H2A.X. Further, phosphorylation of H2A.X at S139 ({gamma}-H2AX) is required for repair-mediated DNA demethylation and transcription activation. The relevance of these findings is demonstrated within the context of TGFB1 signaling and idiopathic pulmonary fibrosis, suggesting therapies against this lethal disease. Our data support that chromatin opening during transcriptional initiation involves intermediates with DNA breaks that subsequently require DNA repair mechanisms to ensure the integrity of the genome.

molecular biology↗

bioRxiv2020

Diversity and Distribution of a Novel Genus of Hyperthermophilic Aquificae Viruses Encoding a Proof-reading Family-A DNA Polymerase

Despite the high abundance of Aquificae in many geothermal systems, these bacteria are difficult to culture and no viruses infecting members of this phylum have been isolated. Here, we describe the complete, circular dsDNA Uncultivated Virus Genome (UViG) of Thermocrinis Octopus Spring virus (TOSV), derived from metagenomic data, along with eight related UViGs representing three additional species, Thermocrinis Great Boiling Spring virus (TGBSV), Aquificae Josephs Coat Spring Virus (AJCSV), and Aquificae Conch Spring Virus (ACSV). Four near-complete UViGs, ranged from 37,256 bp to 41,208 bp and encoded 48 to 53 open reading frames. Despite low overall similarity between viruses from different hot springs, the genomes shared a high degree of synteny, and encoded numerous genes for nucleotide metabolism, including a polyprotein PolA-type polymerase with likely accessory functions, a DNA Pol III beta subunit (sliding clamp), a thymidylate kinase, a DNA gyrase, a helicase, and a DNA methylase. Also present were conserved genes predicted to code for phage capsids, large and small terminases, portal protein, holin, and lytic transglycosylase, all consistent with a distant relatedness to cultivated Caudovirales. TOSV and TGBSV had the highest coverage in their respective metagenomes and are predicted to infect Thermocrinis ruber and Thermocrinis jamiesonii, respectively, as multiple CRISPR spacers matching the viral genomes were identified within Thermocrinis ruber OC1/4T and Thermocrinis jamiesonii GBS1T. Based on the predicted, unusual bi-directional replication strategy, low sequence similarity to known viral genomes, and a unique position in gene-sharing networks, we propose a new putative genus, Pyrovirus, in the order Caudovirales.

microbiology↗

bioRxiv2019

C9orf72-derived arginine-containing dipeptide repeats associate with axonal transport machinery and impede microtubule-based motility

Hexanucleotide repeat expansions in the C9orf72 gene are the most common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). How this mutation leads to these neurodegenerative diseases remains unclear. Here, we use human induced pluripotent stem cell-derived motor neurons to show that C9orf72 repeat expansions impair microtubule-based transport of mitochondria, a process critical for maintenance of neuronal function. Cargo transport defects are recapitulated by treating healthy neurons with the arginine-rich dipeptide repeat proteins (DPRs) that are produced by the hexanucleotide repeat expansions. Single-molecule imaging shows that these DPRs perturb motility of purified kinesin-1 and cytoplasmic dynein-1 motors along microtubules in vitro. Additional in vitro and in vivo data indicate that the DPRs impair transport by interacting with both microtubules and the motor complexes. We also show that kinesin-1 is enriched in DPR inclusions in patient brains and that increasing the level of this motor strongly suppresses the toxic effects of arginine-rich DPR expression in a Drosophila model. Collectively, our study implicates an inhibitory interaction of arginine-rich DPRs with the axonal transport machinery in C9orf72-associated ALS/FTD and thereby points to novel potential therapeutic strategies.

neuroscience↗

bioRxiv2019

Estimating and interpreting nonlinear receptive fields of sensory responses with deep neural network models

Sensory processing by neural circuits includes numerous nonlinear transformations that are critical to perception. Our understanding of these nonlinear mechanisms, however, is hindered by the lack of a comprehensive and interpretable computational framework that can model and explain nonlinear signal transformations. Here, we propose a data-driven framework based on deep neural network regression models that can directly learn any nonlinear stimulus-response mapping. A key component of this approach is an analysis method that reformulates the exact function of the trained neural network as a collection of stimulus-dependent linear functions. This locally linear receptive field interpretation of the network function enables straightforward comparison with conventional receptive field models and uncovers nonlinear encoding properties. We demonstrate the efficacy of this framework by predicting the neural responses recorded invasively from the auditory cortex of neurosurgical patients as they listened to speech. Our method significantly improves the prediction accuracy of auditory cortical responses particularly in nonprimary areas. Moreover, interpreting the functions learned by neural networks uncovered three distinct types of nonlinear transformations of speech that varied considerably in primary and nonprimary auditory regions. By combining two desired properties of a computational sensory-response model; the ability to capture arbitrary stimulus-response mappings and maintaining model interpretability, this data-driven method can lead to better neurophysiological models of the sensory processing.

neuroscience↗

bioRxiv2019

Plasma-derived exosomal analysis and deconvolution enables prediction and tracking of melanoma checkpoint blockade response

PurposeImmune checkpoint inhibitors (ICI) have demonstrated promising therapeutic benefit although a majority will not respond. Here we identify and validate predictive biomarkers from plasma-derived exosomes that allow non-invasive monitoring of tumor intrinsic and host immune status and prediction of ICI success.\n\nExperimental DesignTranscriptomic profiling of peripheral blood bulk exosomes and tumors from a discovery cohort of 50 patients with metastatic melanoma treated with ICI was undertaken; a further validation cohort of 30 patients was utilized to validate findings from the discovery cohort. We designed a Bayesian probabilistic model to partition bulk exosomes into tumor-specific and non-tumor-specific proportions.\n\nResultsExosomal RNA signatures exhibit significant correlations with tumor transcriptomes. Exosomal profiles reflect several key biological drivers of ICI resistance or melanoma progression, exhibit significantly differentially expressed genes and pathways, and correlate with and are predictive of clinical response to therapy. Our deconvolution model estimates contributions from tumor and non-tumor sources, enabling more precise interpretation of differentially-expressed genes and pathways. Exosomal RNA-seq mutational information can be used to segregate responders and non-responders.\n\nConclusionsPeripheral blood-derived exosomes can serve as a non-invasive biomarker to jointly probe tumor-intrinsic and immune changes to ICI, and can potentially function as predictive markers of ICI responsiveness and a monitoring tool for tumor persistence and immune activation.\n\nStatement of SignificanceWe use transcriptomic analysis of bulk, non-selected, peripheral blood derived exosomes to reveal both tumor-intrinsic and immune-derived signatures predictive of early response to immune checkpoint inhibitor therapy. We develop a novel computational model to classify exosomal transcripts into tumor and non-tumor components and establish relevance in immune checkpoint blockade therapy. We show that tumor driver load from RNA-seq mutational calls are significantly different between responders and non-responders.

cancer biology↗

bioRxiv2019

Cortical encoding of melodic expectations in human temporal cortex

Humans engagement in music rests on underlying elements such as the listeners cultural background and general interest in music, all shaping the way music is processed in the brain and perceived. Crucially, these factors modulate how listeners anticipate musical events, a process inducing instantaneous neural responses as the music confronts these expectations. Measuring such neural correlates would represent a direct window into high-level brain processing of music. Here we recorded electroencephalographic and electrocorticographic brain responses as participants listened to Bach melodies. We assessed the relative contributions of the acoustic versus melodic components of the music to the neural signal. Acoustic features included envelope and its derivative. Melodic features included information on melodic progressions (pitch) and their tempo (onsets), which were extracted from a Markov model predicting the next note based on a corpus of Western music and the preceding proximal musical context. We related the music to brain activity with a linear temporal response function, and demonstrated that cortical responses to music encode melodic expectations. Specifically, individual-subject neural signals were better predicted by a combination of acoustic and melodic expectation features than by either alone. This effect was most pronounced at response latencies up to 350ms, and in both planum temporale and Heschls gyrus. Finally, expectations of pitch and onset-time of musical notes exerted independent cortical effects, and such influences were modulated by the listeners musical expertise. Overall, this study demonstrates how the interplay of experimental and theoretical approaches can yield novel insights into the cortical encoding of melodic expectations.

neuroscience↗