Biology subjects

Singh, M.

Publications and source records attributed to Singh, M..

At least 127 records · Page 7Linked to original sources

bioRxiv2022

Electroencephalogram Data Collection for Student Engagement Analysis with Audio-Visual Content

Recognizing and monitoring students attention during learning is crucial to successful knowledge acquisition since it influences cognitive function. As a result, gaining a precise picture of a learners mental state may enable interactive learning systems to alter tutoring content, devise effective help tactics, and improve learning outcomes. In computer-based learning environments, keeping track of students mental states is vital. Investigating the feasibility of utilizing active learning in enhancing student engagement index when exposed to various visual stimuli is the genesis of this work. The research includes collecting EEG data from 20 participants (ten males, ten females) while resting and being subjected to various virtual infotainment/educational content. The EEG data were collected using the Allengers Neuro PLOT, a 40-channel wet electrode system. The work includes raw and pre-processed EEG data under quiescent and audio-visual continuous cues. The recorded data is accommodated by a sophisticated EEG data pre-processing pipeline and will be available to the research community for usage. Specifications Table O_TBL View this table: org.highwire.dtl.DTLVardef@340852org.highwire.dtl.DTLVardef@e5c51org.highwire.dtl.DTLVardef@cefb1borg.highwire.dtl.DTLVardef@c7d208org.highwire.dtl.DTLVardef@ae4824_HPS_FORMAT_FIGEXP M_TBL C_TBL

neuroscience↗

bioRxiv2022

Harmonin homology domains of human RTEL1 interact with replication protein A and DNA

The regulator of telomere elongation helicase 1 (RTEL1) is an Fe-S cluster containing helicase that plays important roles in telomere DNA maintenance, DNA repair, and genome stability. It is a modular protein comprising a helicase domain, two tandem harmonin homology domains 1 & 2 (HHD1 and HHD2), and a Zn2+ binding RING domain. In this study, we have unravelled a novel interaction between RTEL1 and replication protein A (RPA) and shown their co-localization upon DNA damage in the cells. Using NMR spectroscopy, we show that 32C domain of RPA and DNA competitively bind with HHD2 of RTEL1. To understand the structural basis of HHD2 - 32C and HHD2 - DNA interactions, we have determined a 1.6 [A] resolution crystal structure of HHD2. NMR chemical shift perturbations-based mapping revealed the 32C and DNA binding surface on HHD2 of RTEL1. Together, these results establish an interplay among RTEL1, RPA, and DNA that provide mechanistic insights into the RTEL1 recruitment at DNA during the processes of replication, repair, and recombination.

biophysics↗

bioRxiv2022

SARS-CoV-2 Omicron BA.1 and BA.2 are attenuated in rhesus macaques as compared to Delta

Since the emergence of SARS-CoV-2, five different variants of concern (VOCs) have been identified: Alpha, Beta, Gamma, Delta, and Omicron. Due to confounding factors in the human population, such as pre-existing immunity, comparing severity of disease caused by different VOCs is challenging. Here, we investigate disease progression in the rhesus macaque model upon inoculation with the Delta, Omicron BA.1, and Omicron BA.2 VOCs. Disease severity in rhesus macaques inoculated with Omicron BA.1 or BA.2 was lower than those inoculated with Delta and resulted in significantly lower viral loads in nasal swabs, bronchial cytology brush samples, and lung tissue in rhesus macaques. Cytokines and chemokines were upregulated in nasosorption samples of Delta animals compared to Omicron BA.1 and BA.2 animals. Overall, these data suggests that in rhesus macaques, Omicron replicates to lower levels than the Delta VOC, resulting in reduced clinical disease.

microbiology↗

bioRxiv2022

Yield Prediction Through Integration of Genetic, Environment, and Management Data Through Deep Learning

Accurate prediction of the phenotypic outcomes produced by different combinations of genotypes, environments, and management interventions remains a key goal in biology with direct applications to agriculture, research, and conservation. The past decades have seen an expansion of new methods applied towards this goal. Here we predict maize yield using deep neural networks, compare the efficacy of two model development methods, and contextualize model performance using linear models, which are the conventional method for this task, and machine learning models We examine the usefulness of incorporating interactions between disparate data types. We find a deep learning model with interactions has the best average performance. Optimizing submodules for each datatype improved model performance relative to optimizing the whole model for all data types at once. Examining the effect of interactions in the best performing model revealed that including interactions altered the models sensitivity to weather and management features, including a reduction of the importance scores for timepoints expected to have limited physiological basis for influencing yield - those at the extreme end of the season, nearly 200 days post planting. Based on these results, deep learning provides a promising avenue for phenotypic prediction of complex traits in complex environments and a potential mechanism to better understand the influence of environmental and genetic factors.

plant biology↗

bioRxiv2022

Effect of Single Nucleotide Polymorphisms on the structure of long noncoding RNAs and their interaction with RNA Binding Proteins

Long non-coding RNAs (lncRNA) are emerging as a new class of regulatory RNAs with remarkable potential to be utilized as therapeutic targets against many human diseases. Several genome-wide association studies (GWAS) have catalogued Single Nucleotide Polymorphisms (SNPs) present in the noncoding regions of the genome, transcribing lncRNAs. In this study, we have selected 67 lncRNAs with GWAS-tagged SNPs and have also investigated their role in affecting the local secondary structures. The majority of the SNPs lead to changes in the secondary structure of lncRNA to a different extent by altering the base pairing patterns. These structural changes in lncRNA are also manifested in form of alteration in the binding site for RNA binding proteins (RBPs) along with affecting their binding efficacies. Ultimately, these structural modifications may influence the transcriptional and post-transcriptional pathways of these RNAs, leading to the causation of diseases. Hence, it is important to understand the possible underlying mechanism of RBPs in association with GWAS-tagged SNPs in human diseases.

bioinformatics↗

bioRxiv2022

Site-specific analysis reveals candidate cross-kingdom small RNAs, tRNA and rRNA fragments, and signs of fungal RNA phasing in the barley-powdery mildew interaction

The establishment of host-microbe interactions requires molecular communication between both partners, which involves the mutual transfer of noncoding small RNAs. Previous evidence suggests that this is also true for the barley powdery mildew disease, which is caused by the fungal pathogen Blumeria hordei. However, previous studies lacked spatial resolution regarding the accumulation of small RNAs upon host infection by B. hordei. Here, we analysed site-specific small RNA repertoires in the context of the barley-B. hordei interaction. To this end, we dissected infected leaves into separate fractions representing different sites that are key to the pathogenic process: epiphytic fungal mycelium, infected plant epidermis, isolated haustoria, a vesicle-enriched fraction from infected epidermis, and extracellular vesicles. Unexpectedly, we discovered enrichment of specific 31- to 33-base long 5-terminal fragments of barley 5.8S ribosomal RNA (rRNA) in extracellular vesicles and infected epidermis, as well as particular B. hordei tRNA fragments in haustoria. We describe canonical small RNAs from both the plant host and the fungal pathogen that may confer cross-kingdom RNA interference activity. Interestingly, we found first evidence of phased small RNAs (phasiRNAs) in B. hordei, a feature usually attributed to plants, which may be associated with the post-transcriptional control of fungal coding genes, pseudogenes, and transposable elements. Our data suggests a key and possibly site-specific role for cross-kingdom RNA interference and noncoding RNA fragments in the host-pathogen communication between B. hordei and its host barley.

plant biology↗

bioRxiv2022

Monkey Pox Virus (MPXV): Phylogenomics, Host-Pathogen Interactome, and Mutational Cascade

While the world is still managing to recover from Covid-19 pandemic, Monkeypox awaits to bring in another global outbreak as a challenge to the entire mankind. However, Covid-19 pandemic have taught us lessons to move fast in viral genomic research to implement prevention and treatment strategies. One of the important aspects in Monkeypox virus should be immediately taken up is to gather insights of its evolutionary lineage based on the genomic studies. We have thus analysed the genome sequences of reported isolates of Monkeypox in the present study through phylogenomics. Host-pathogen interactions, mutation prevalence and evolutionary dynamics of this virus were investigated for all the documented isolates. Phylogenetic exploration revealed the clustering of strain Israel 2018 (MN 648051.1) from Clade I with the four isolates reported from the recent outbreak. An in-depth scrutiny of the host-pathogen interactome identified protein E3, serine protease inhibitor-2 (SPI-2), protein K7, and cytokine response-modifying protein B (CrmB) as the major regulatory hubs. Among these, the CrmB protein (dN/dS {approx} 1.61) was detected to be operating through positive selection. It possibly attests a selective advantage with the monkeypox virus in protecting the infected cells from antiviral responses elicited by the host. Studies also revealed that CrmB protein exhibited several mutations, the majority of which were destabilizing ({Delta}{Delta}G >0). While this study identified a large number of mutations within the newly outbreak clade, it also reflected that we need to move fast with the genomic analysis of the newly detected strains from around the world to develop better prevention and treatment methods

microbiology↗

bioRxiv2022

MITE infestation of germline accommodated by genome editing in Blepharisma

During a sophisticated developmental process, ciliates excise numerous internally eliminated sequences (IESs) from a germline genome copy, producing a functional somatic genome. Most IESs ultimately originate from transposons but homology is obscured by sequence decay. To obtain more representative perspectives on ciliate genome editing, we assembled forty thousand IESs of Blepharisma stoltei, from a much earlier-diverging lineage than existing models. Short IESs (< 115 bp) were largely non-repetitive, with a pronounced ~10 bp length periodicity, whereas longer IESs (max 7 kbp) were non-periodic and contained abundant interspersed repeats. Contrary to current models, the Blepharisma germline genome encodes few transposases. Instead, its most abundant repeat (8000 copies) was a Miniature Inverted-repeat Transposable Element (MITE), apparently a deletion derivative of a germline-limited Pogo-family transposon. We propose MITEs as an important and eventually self-limiting IES source. Rather than defending germline genomes against mobile elements, we argue that transposase domestication actually facilitates junk DNA accumulation.

genomics↗

bioRxiv2022

Biophysical, Molecular and Proteomic profiling of Human Retinal Organoids derived Exosomes

Extracellular vesicles (EVs) are phospholipid bilayer-bound particles released by cells that play a role in cell-cell communication, signal transduction, and extracellular matrix remodeling. There is a growing interest in EVs for ocular applications as therapeutics, biomarkers, and drug delivery vehicles. EVs secreted from mesenchymal stem cells (MSCs) have shown to provide therapeutic benefits in ocular conditions. However, very little is known about the properties of bioreactors cultured-3D human retinal organoids secreted EVs. This study provides a comprehensive morphological, nanomechanical, molecular, and proteomic characterization of retinal organoid EVs and compares it with human umbilical cord (hUC) MSCs. Nanoparticle tracking analysis indicated the average size of EV as 100-250 nm. Atomic force microscopy showed that retinal organoid EVs are softer and rougher than the hUCMSC EVs. Gene expression analysis by qPCR showed a high expression of exosome biogenesis genes in late retinal organoids derived EVs (>120 days). Immunoblot analysis showed highly expressed exosomal markers Alix, CD63, Flotillin-2, HRS and Hsp70 in late retinal organoids compared to early retinal organoids EVs (<120 days). Protein profiling of retinal organoid EVs displayed a higher differential expression of retinal function-related proteins and EV biogenesis/marker proteins than hUCMSC EVs, implicating that the use of retinal organoid EVs may have a superior therapeutic effect on retinal disorders. This study adds supplementary knowledge on the properties of EVs secreted by retinal organoids and suggests their potential use in the diagnostic and therapeutic treatments for ocular diseases.

bioengineering↗

bioRxiv2022

MR-DoC2: bidirectional causal modeling with instrumental variables and data from relatives

Establishing causality is an essential step towards developing interventions for psychiatric disorders, substance use and many other conditions. While randomized controlled trials (RCTs) are considered the gold standard for causal inference, they are unethical in many scenarios. Mendelian randomization (MR) can be used in such cases, but importantly both RCTs and MR assume unidirectional causality. In this paper, we developed a new model, MRDoC2, that can be used to identify bidirectional causation in the presence of confounding due to both familial and non- familial sources. Our model extends the MRDoC model (Minic[a] et al 2018), by simultaneously including risk scores for each trait. Furthermore, the power to detect causal effects in MRDoC2 does not require the phenotypes to have different additive genetic or shared environmental sources of variance, as is the case in the direction of causation twin model (Heath et al., 1993).

genetics↗

bioRxiv2022

Cell-specific regulation of gene expression using splicing-dependent frameshifting.

Precise and reliable cell-specific gene delivery remains technically challenging. Here we report a splicing-based approach for controlling gene expression whereby separate translational reading frames are coupled to the inclusion or exclusion of cell-specific alternative exons. Candidate exons are identified by analyzing thousands of publicly available RNA sequencing datasets and filtering by cell specificity, sequence conservation, and local intron length. This method, which we denote splicing-linked expression design (SLED), can be combined in a Boolean manner with existing techniques such as minipromoters and viral capsids. SLED vectors can leverage the strong expression of constitutive promoters, without sacrificing precision, by decoupling the tradeoff between promoter strength and selectivity. We generated SLED vectors to selectively target all neurons, photoreceptors, or excitatory neurons, and demonstrated that specificity was retained in vivo when delivered using AAVs. We further demonstrated the utility of SLED by creating what would otherwise be unobtainable research tools, specifically a GluA2 flip/flop reporter and a dual excitatory/inhibitory neuronal calcium indicator. Finally, we show the translational potential of SLED by rescuing photoreceptor degeneration in Prph2rds/rds mice and by developing an oncolytic vector that can selectively induce apoptosis in SF3B1 mutant cancer cells. The flexibility of SLED technology enables new avenues for basic and translational research.

molecular biology↗

bioRxiv2022

STAT3 gain-of-function mutations connect leukemia with autoimmune disease by pathological dysregulation of NKG2Dhi CD8 killer T cells

The association between cancer and autoimmune disease is unexplained, exemplified by T-cell large granular lymphocytic leukemia (T-LGL) where gain-of-function somatic mutations in STAT3 correlate with co-existing autoimmunity. To resolve whether these mutations are the cause or consequence of CD8 clonal expansions and autoimmunity, here we analyse patients with germline STAT3 GOF syndrome and mice with the T-LGL mutation STAT3K658Nor the most common germline mutation, STAT3T716M. STAT3 GOF mutations drove accumulation of effector CD8 T cell clones highly expressing the NKG2D receptor for MHC-I-related molecules expressed on stressed cells, and the genes for inflammatory/cytotoxic granzymes, perforin, interferon-{gamma} and Ccl5/Rantes. CD8 cells were essential to lethal disease in Stat3K658Nmice and their accumulation required NKG2D and the receptor for IL-15 and IL-2, IL2RB. These results demonstrate that STAT3 GOF mutations cause effector CD8 T cell oligoclonal accumulation and that these rogue T cells contribute to autoimmune pathology, supporting the hypothesis that somatic mutations in leukemia/lymphoma driver genes contribute to autoimmune disease. IN BRIEFLeukemia and autoimmune-associated STAT3 gain-of-function mutations dysregulate CD8 T cells to cause autoimmune pathology and oligoclonal expansion of cytotoxic killer CD8 T cells, that depend upon NKG2D and IL2RB receptors for signals displayed on stressed, damaged, infected, or mutated tissues.

immunology↗

bioRxiv2022

An AI-assisted Tool For Efficient Prostate Cancer Diagnosis

Pathologists diagnose prostate cancer by core needle biopsy. For low-grade and low-volume cases, the pathologists look for the few malignant glands out of hundreds within a core. They may miss the few malignant glands, resulting in repeat biopsies or missed therapeutic opportunities. This study developed a multi-resolution deep learning pipeline detecting malignant glands in core needle biopsies to help pathologists effectively and accurately diagnose prostate cancer in low-grade and low-volume cases. The pipeline consisted of two stages: the gland segmentation model detected the glands within the sections and the multi-resolution model classified each detected gland into benign vs. malignant. Analyzing a gland at multiple resolutions provided the classification model to exploit both morphology information (of nuclei and glands) and neighborhood information (for architectural patterns), important in prostate gland classification. We developed and tested our pipeline on the slides of a local cohort of 99 patients in Singapore. The images were made publicly available, becoming the first digital histopathology dataset of prostatic carcinoma patients of Asian ancestry. Our pipeline successfully classified the core needle biopsy parts (81 parts: 50 benign and 31 malignant) into benign vs. malignant. It achieved an AUROC value of 0.997 (95% CI: 0.987 - 1.000). Moreover, it produced heatmaps highlighting the malignancy of each gland in core needle biopsies. Hence, our pipeline can effectively assist pathologists in core needle biopsy analysis.

cancer biology↗

bioRxiv2022

Bi-steric mTORC1-selective Inhibitors activate 4EBP1 reversing MYC-induced tumorigenesis and synergize with immunotherapy

The MYC oncogene is causally involved in the pathogenesis of most types of human cancer but it remains therapeutically untargeted. The mTORC1 protein complex regulates cap-dependent translation through 4EBP1 and S6K and thereby, downstream MYC protein expression. However, to date, agents such as rapalogs that selectively target mTORC1 (as compared to mTORC2) fail to reactivate 4EBP1 and thus, to block MYC in vivo. In contrast, agents that nonselectively inhibit both protein complexes of the mTOR pathway, mTORC1 and mTORC2, can activate 4EBP1, but often suffer from a lack of tolerability including in vivo hepatotoxicity and immunosuppression. Here, we report the anti-tumor activity of bi-steric mTORC1-selective inhibitors, including Revolution Medicines clinical candidate RMC-5552, that potently and selectively target mTORC1 over mTORC2. In an autochthonous transgenic mouse model of MYC-amplified and MYC-driven hepatocellular carcinoma (HCC), representative bi-steric mTORC1-selective inhibitors suppress translation initiation via activation of 4EBP1, thereby suppressing MYC protein expression and blocking tumor growth. Furthermore, in human HCC samples, the low levels of 4EBP1 and MYC is correlated with immune reactivation. Immunohistochemistry, CIBERSORT, and CODEX reveal that selective mTORC1 inhibition results in activation of both CD4+ T cell- and NKp46+ NK cell-mediated immune surveillance. Moreover, bi-steric mTORC1-selective inhibitors synergize with -PD-1 to induce sustained tumor regression, with immune cell degranulation and release of perforins and granzyme B. These agents also exhibit anti-tumor activity in human patient-derived xenografts of HCC, colorectal cancer, head and neck cancer, and ovarian cancer harboring genomic amplifications in MYC. We infer that selective mTORC1 inhibition is a potential therapeutic strategy to drive effective MYC inactivation in cancer, and the consequent restoration of immune surveillance against neoplasia.

cancer biology↗

bioRxiv2022

Clonal dynamics of SARS-CoV-2-specific T cells in children and adults with COVID-19

Children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) develop less severe coronavirus disease 2019 (COVID-19) than adults. The mechanisms for the age-specific differences and the implications for infection-induced immunity are beginning to be uncovered. We show by longitudinal multimodal analysis that SARS-CoV-2 leaves a small footprint in the circulating T cell compartment in children with mild/asymptomatic COVID-19 compared to adult household contacts with the same disease severity who had more evidence of systemic T cell interferon activation, cytotoxicity and exhaustion. Children harbored diverse polyclonal SARS-CoV- 2-specific naive T cells whereas adults harbored clonally expanded SARS-CoV-2-specific memory T cells. More naive interferon-activated CD4+ T cells were recruited into the memory compartment and recovery was associated with the development of robust CD4+ memory T cell responses in adults but not children. These data suggest that rapid clearance of SARS-CoV-2 in children may compromise their cellular immunity and ability to resist reinfection. HIGHLIGHTSO_LIChildren have diverse polyclonal SARS-CoV-2-specific naive T cells C_LIO_LIAdults have clonally expanded exhausted SARS-CoV-2-specific memory T cells C_LIO_LIInterferon-activated naive T cells differentiate into memory T cells in adults but not children C_LIO_LIAdults but not children develop robust memory T cell responses to SARS-CoV-2 C_LI O_FIG O_LINKSMALLFIG WIDTH=177 HEIGHT=200 SRC="FIGDIR/small/478400v1_ufig1.gif" ALT="Figure 1"> View larger version (44K): org.highwire.dtl.DTLVardef@e9586org.highwire.dtl.DTLVardef@17aaf37org.highwire.dtl.DTLVardef@18575e0org.highwire.dtl.DTLVardef@fde4ae_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2022

Learning probabilistic protein-DNA recognition codes from DNA-binding specificities using structural mappings

Knowledge of how proteins interact with DNA is essential for understanding gene regulation. While DNA-binding specificities for thousands of transcription factors (TFs) have been determined, the specific amino acid-base interactions comprising their structural interfaces are largely unknown. This lack of resolution hampers attempts to leverage these data in order to predict specificities for uncharacterized TFs or TFs mutated in disease. Here we introduce rCLAMPS (Recognition Code Learning via Automated Mapping of Protein-DNA Structural interfaces), a probabilistic approach that uses DNA-binding specificities for TFs from the same structural family to simultaneously infer both which nucleotide positions are contacted by particular amino acids within the TF as well as a recognition code that relates each base-contacting amino acid to nucleotide preferences at the DNA positions it contacts. We apply rCLAMPS to homeodomains, the second largest family of TFs in metazoans, and demonstrate that it learns a highly effective recognition code that can predict de novo DNA-binding specificities for TFs. Furthermore, we show that the inferred amino acid-nucleotide contacts reveal whether and how nucleotide preferences at individual binding site positions are altered by mutations within TFs. Our approach is an important step towards automatically uncovering the determinants of protein-DNA specificity from large compendia of DNA-binding specificities, and inferring the altered functionalities of TFs mutated in disease.

molecular biology↗

bioRxiv2022

Characterization of the minimal residual disease state reveals distinct evolutionary trajectories of human glioblastoma

Recurrence of solid tumors renders patients vulnerable to a distinctly advanced, highly treatment-refractory disease state that has an increased mutational burden and novel oncogenic drivers not detected at initial diagnosis. Improving outcomes for recurrent cancers requires a better understanding of cancer cell populations that expand from the post-therapy, minimal residual disease (MRD) state. We profiled barcoded tumor stem cell populations through therapy at tumor initiation/engraftment, MRD and recurrence in our therapy-adapted, patient-derived xenograft models of glioblastoma (GBM). Tumors showed distinct patterns of recurrence in which clonal populations exhibited either an a priori, pre-existing fitness advantage, or a priori equipotency fitness acquired through therapy. Characterization of the MRD state by single-cell and bulk RNA sequencing revealed a tumor-intrinsic immunomodulatory signature with strong prognostic significance at the transcriptomic level and in proteomic analysis of cerebrospinal fluid (CSF) collected from GBM patients at all stages of disease. Our results provide insight into the innate and therapy-driven dynamics of human GBM, and the prognostic value of interrogating the MRD state in solid cancers.

cancer biology↗

bioRxiv2021

Overactive STAT3 drives accumulation of disease-associated CD21low B cells

Dysregulated STAT3 signalling is correlated with antibody-mediated autoimmunity and B- cell neoplasia, but its effect on B cells is underexplored. Here we address this in children with STAT3 gain-of-function (GOF) syndrome and in mice with STAT3T716M, the most common STAT3 GOF syndrome human mutation, or STAT3K658N, a dimerization interface mutation responsible for STAT3 GOF syndrome in two children. The main B cell consequence of overactive STAT3 was accumulation of CD19high CD21low atypical memory B cells in humans and of CD21low CD23low B cells in mice resembling age-associated B cells expressing T-bet, CD11c and plasma cell differentiation genes. Overactive STAT3 within B cells increased expression of many genes in the B cell receptor and T cell help pathways, increased the tolerogenic receptor CD22, but opposed B cell tolerance checkpoints and increased formation of T-bet+ B cells upon BCR and CD40 stimulation. These results reveal overactive STAT3 as a central driver of a key class of disease- associated B-lymphocytes in humans and mice.

immunology↗