Biology subjects

Mittal, A.

Publications and source records attributed to Mittal, A..

32 records · Page 2Linked to original sources

bioRxiv2022

Simultaneous visualization of cells and marker genes from scRNA-seq studies

The complexity of scRNA-sequencing datasets highlights the urgent need for enhanced clustering and visualization methods. Here, we propose Stardust, an iterative, force-directed graph layouting algorithm that enables the simultaneous embedding of cells and marker genes. Stardust, for the first time, allows a single-stop visualization of cells and marker genes on a single 2D map. While Stardust provides its own visualization pipeline, it can be plugged in with state-of-the-art methods such as Uniform Manifold Approximation and Projection (UMAP) and t-Distributed Stochastic Neighbor Embedding (tSNE). We benchmarked Stardust against popular visualization and clustering tools on both scRNA-seq and spatial transcriptomics datasets. In all cases, Stardust performs competitively in identifying and visualizing cell types in an accurate and spatially coherent manner.

bioinformatics↗

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

Novel genotyping algorithms for rare variants significantly improve the accuracy of Applied Biosystems™ Axiom™ array genotyping calls

ObjectiveTo significantly improve the positive predictive value (PPV) and sensitivity of Applied Biosystems Axiom array variant calling, by means of novel improvement to genotyping algorithms and careful quality control of array probesets. The improvement makes array genotyping more suitable for very rare variants. DesignRetrospective evaluation of UK Biobank array data re-genotyped with improved algorithms for rare variants. Participants488,359 people recruited to the UK Biobank with Axiom array genotyping data including 200,630 with exome sequencing data. Main Outcome MeasuresA comparison of genotyping calls from array data to genotyping calls on a subset of variants with exome sequencing data. ResultsAxiom genotyping [18] performed well, based on comparison to sequencing data, for over 100,000 common variants directly genotyped on the Axiom UK Biobank array and also exome sequenced by the UK Biobank Exome Sequencing Consortium. However, in a comparison to the initial exome sequencing results of the first 50K individuals, Weedon et al. [1] observed that when grouping these variants by the minor allele frequency (MAF) observed in UK Biobank, the concordance with sequencing and resulting positive predictive value (PPV) decreased with the number of heterozygous (Het) array calls per variant. An improved genotyping algorithm, Rare Heterozygous Adjustment (RHA) [16], released mid-2020 for genotyping on Axiom arrays, significantly improves PPV in all MAF ranges for the 50K data as well as when compared to the exome sequencing of 200K individuals, released after Weedon et al. [1] performed their comparison. The RHA algorithm improved PPVs in the 200K data in the lowest three frequency groups [0, 0.001%), [0.001%, 0.005%) and [0.005%, 0.01%) to 83%, 82% and 88%; respectively. PPV was above 95% for higher MAF ranges without algorithm improvement. PPVs are somewhat higher in the 200K dataset, due to a different "truth set" from exome sequencing and because monomorphic exome loci are not included in the joint genotyping calls for the 200K data set, as explained in the methods section. Sensitivity was higher in the 200K data set than in the original 50K data as well, especially for low MAF ranges. This increase is in part due to the larger data set over which sensitivity could be computed and in part due to the different WES algorithms used for the 200K data [7]. Filtering of a relatively small number of non-performing probesets (determined without reference to the exome sequencing data) significantly improved sensitivities for all MAF ranges, resulting in 70%, 88% and 94% respectively in the three lowest MAF ranges and greater than 98% and 99.9% for the two higher MAF ranges ([0.01%, 1%), [1%, 50%]). ConclusionsImproved algorithms for genotyping along with enhanced quality control of array probesets, significantly improve the positive predictive value and the sensitivity of array data, making it suitable for the detection of very rare variants. The probeset filtering methods developed have resulted in better probe designs for arrays and the new genotyping algorithm is part of the standard algorithm for all Axiom arrays since early 2020.

genetics↗

bioRxiv2021

Stromal-cell deletion of STAT3 protects mice from kidney fibrosis by inhibiting pericytes trans-differentiation and migration

Signal transducer and activator of transcription 3 (STAT3) is a key transcription factor implicated in the pathogenesis of kidney fibrosis. Although tubular Stat3 deletion in tubular epithelial cells is known to protect mice from kidney fibrosis, the exact function of STAT3 in stromal cells remains unknown. We utilized stromal-cell Stat3 knock-out (KO) mice, CRISPR and pharmacologic activators and inhibitors of STAT3 to investigate its function in pericyte-like cells. STAT3 is phosphorylated in tubular epithelial cells in acute kidney injury whereas its activation expanded to interstitial cells in chronic kidney disease in mice and humans. Stromal cell-specific deletion of Stat3 protects mice from folic acid- and aristolochic acid-induced kidney fibrosis. Mechanistically, STAT3 directly regulates the inflammatory pathway, differentiation of pericytes into myofibroblasts. Specifically, STAT3 activation leads to an increase in migration and profibrotic signaling in genome-edited pericyte-like cells, 10T1/2. Conversely, Stat3 KO or blocking STAT3 function inhibits detachment, spreading, migration, and profibrotic signaling. Furthermore, STAT3 binds to Collagen1a1 promoter of fibrotic mouse kidneys and in pericyte-like cells. Together, our study identifies a previously unknown function of STAT3 in stromal cells that promotes kidney fibrosis and may have therapeutic value in fibrotic kidney disease. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=73 SRC="FIGDIR/small/456872v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@35dcbforg.highwire.dtl.DTLVardef@2fc055org.highwire.dtl.DTLVardef@fc0d92org.highwire.dtl.DTLVardef@1def2e6_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2021

Vibrio cholerae motility in aquatic and mucus-mimicking environments

Cholera disease is caused by Vibrio cholerae infecting the lining of the small intestine and results in severe diarrhea. V. choleraes swimming motility is known to play a crucial role in pathogenicity and may aid the bacteria in crossing the intestinal mucus barrier to reach sites of infection, but the exact mechanisms are unknown. The cell can be either pushed or pulled by its single polar flagellum, but there is no consensus on the resulting repertoire of motility behaviors. We use high-throughput 3D bacterial tracking to observe V. cholerae swimming in buffer, in viscous solutions of the synthetic polymer PVP, and in mucin solutions that may mimic the host environment. We perform a statistical characterization of its motility behavior on the basis of large 3D trajectory datasets. We find that V. cholerae performs asymmetric run-reverse-flick motility, consisting of a sequence of a forward run, reversal, and a shorter backward run, followed by a turn by approximately 90{degrees}, called a flick, preceding the next forward run. Unlike many run-reverse-flick swimmers, V. choleraes backward runs are much shorter than its forward runs, resulting in an increased effective diffusivity. We also find that the swimming speed is not constant, but subject to frequent decreases. The turning frequency in mucin matches that observed in buffer. Run-reverse-flick motility and speed fluctuations are present in all environments studied, suggesting that these behaviors may also occur in natural aquatic habitats as well as the host environment. ImportanceCholera disease produces vomiting and severe diarrhea and causes approximately 100,000 deaths per year worldwide. The disease is caused by the bacterium Vibrio cholerae colonizing the lining of the small intestine. V. choleraes ability to swim is known to increase its infectivity, but the underlying mechanisms are not known. One possibility is that swimming may aid in crossing the protective mucus barrier that covers the lining of the small intestine. Our work characterizing how V. cholerae swims in environments that mimic properties of the host environment may advance the understanding of how motility contributes to infection.

microbiology↗

bioRxiv2021

Robust Brain State Decoding using Bidirectional Long Short Term Memory Networks in functional MRI

Decoding brain states of the underlying cognitive processes via learning discriminative feature representations has recently gained a lot of interest in brain imaging studies. Particularly, there has been an impetus to encode the dynamics of brain functioning by analyzing temporal information available in the fMRI data. Long-short term memory (LSTM), a class of machine learning model possessing a "memory" component, is increasingly being observed to perform well in various applications with dynamic temporal behavior, including brain state decoding. Because of the dynamics and inherent latency in fMRI BOLD responses, future temporal context is crucial. However, it is neither encoded nor captured by the conventional LSTM model. This paper performs robust brain state decoding via information encapsulation from both the past and future instances of fMRI data via bi-directional LSTM. This allows for explicitly modeling the dynamics of BOLD response without any delay adjustment. The two hidden activations of forward and reverse directions in bi-LSTM are collated to build the "memory" of the model and are used to robustly predict the brain states at every time instance. Working memory data from the Human Connectome Project (HCP) is utilized for validation and was observed to perform 18% better than its unidirectional counterpart in terms of accuracy in predicting the brain states.

scientific communication and education↗

bioRxiv2020

South Asian patient population genetics reveal strong founder effects and high rates of homozygosity - new resources for precision medicine

Population-scale genetic studies can identify drug targets and allow disease risk to be predicted with resulting benefit for management of individual health risks and system-wide allocation of health care delivery resources. Although population-scale projects are underway in many parts of the world, genetic variation between population groups means that additional projects are warranted. South Asia has a population whose genetics is the least characterized of any of the worlds major populations. Here we describe GenomeAsia studies that characterize population structure in South Asia and that create tools for economical and accurate genotyping at population-scale. Prior work on population structure characterized isolated population groups, the relevance of which to large-scale studies of disease genetics is unclear. For our studies we used whole genome sequence information from 4,807 individuals recruited in the health care delivery systems of Pakistan, India and Bangladesh to ensure relevance to population-scale studies of disease genetics. We combined this with WGS data from 927 individuals from isolated South Asian population groups, and developed a custom SNP array (called SARGAM) that is optimized for future human genetic studies in South Asia. We find evidence for high rates of reproductive isolation, endogamy and consanguinity that vary across the subcontinent and that lead to levels of homozygosity that approach 100 times that seen in outbred populations. We describe founder effects that increase the power to associate functional variants with disease processes and that make South Asia a uniquely powerful place for population-scale genetic studies.

genomics↗

bioRxiv2020

Ultra-compact Dual-band Smart NEMS Magnetoelectric Antennas for Simultaneous Wireless Energy Harvesting and Magnetic Field Sensing

Ultra-compact wireless implantable medical devices (IMDs) are in great demand for healthcare applications, in particular for neural recording and stimulation. Current implantable technologies based on miniaturized micro-coils suffer from low wireless power transfer efficiency (PTE) and are not always compliant with the specific absorption rate imposed by the Federal Communications Commission, particularly for deep brain implantation where field attenuation and tissue loss are significant. Moreover, current implantable devices are reliant on recordings of voltage or current. This has two major weaknesses: 1) the necessary direct contact between electrode and tissue degrades over time due to electrochemical fouling and tissue reactions, and 2) the necessity for differential recordings across space. Here, we report, for the first time, an ultra-compact dual-band smart nanoelectromechanical systems magnetoelectric (ME) antenna with a size of 250×174 µm2 that can efficiently perform wireless energy harvesting and sense ultra-small magnetic fields such as those arising from neural activities. The proposed smart ME antenna has a wireless PTE 1∼2 orders of magnitude higher than any other reported miniaturized micro-coil, allowing the wireless IMDs to be compliant with the specific absorption rate (SAR) limit and to operate under safe exposure of radio frequency energy. Furthermore, the magnetic sensing capability of the proposed smart ME antenna, with a limit of detection of 300∼500pT at > 200Hz, should allow the IMDs to record neural magnetic fields from the brain without requiring differential recording.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗

bioRxiv2019

A custom genotyping array reveals population-level heterogeneity for the genetic risks of prostate cancer and other cancers in Africa

Although prostate cancer is the leading cause of cancer mortality for African men, the vast majority of known disease associations have been detected in European study cohorts. Furthermore, most genome-wide association studies have used genotyping arrays that are hindered by SNP ascertainment bias. To overcome these disparities in genomic medicine, the Men of African Descent and Carcinoma of the Prostate (MADCaP) Network has developed a genotyping array that is optimized for African populations. The MADCaP Array contains more than 1.5 million markers and an imputation backbone that successfully tags over 94% of common genetic variants in African populations. This array also has a high density of markers in genomic regions associated with cancer susceptibility, including 8q24. We assessed the effectiveness of the MADCaP Array by genotyping 399 prostate cancer cases and 403 controls from seven urban study sites in sub-Saharan Africa. We find that samples from Ghana and Nigeria cluster together, while samples from Senegal and South Africa yield distinct ancestry clusters. Using the MADCaP array, we identified cancer-associated loci that have large allele frequency differences across African populations. Polygenic risk scores were also generated for each genome in the MADCaP pilot dataset, and we found that predicted risks of CaP are lower in Senegal and higher in Nigeria.\n\nSignificanceWe have developed an Africa-specific genotyping array which enables investigators to identify novel disease associations and to fine-map genetic loci that are associated with prostate and other cancers.

genomics↗

bioRxiv2018

Myocardin ablation in a cardiac-renal rat model

Cardiorenal syndrome is defined by primary heart failure conditions influencing or leading to renal injury or dysfunction. Dilated cardiomyopathy (DCM) is a major co-existing form of heart failure (HF) with renal diseases. Myocardin (MYOCD), a cardiac-specific co-activator of serum response factor (SRF), is increased in DCM mice and patient cardiac tissues and plays a crucial role in the pathophysiology of DCM. Inhibiting the increased MYOCD has shown to be partially rescuing the DCM mice phenotype. However, expression levels of MYOCD in the cardiac tissues of the cardiorenal syndromic patients and the beneficial effect of inhibiting MYOCD in a cardiorenal syndrome model remains to be explored. Here, we analyzed the expression levels of MYOCD in the DCM patients with and without renal diseases. We also explored, whether cardiac specific silencing of MYOCD expression could ameliorate the cardiac remodeling and improve cardiac function in a renal artery ligated rat model (RAL). We observed an increase in MYOCD levels in the endomyocardial biopsies of DCM patients associated with renal failure compared to DCM alone. Silencing of MYOCD in RAL rats by a cardiac homing peptide conjugated MYOCD siRNA resulted in attenuation of cardiac hypertrophy, fibrosis and restoration of the left ventricular functions. Our data suggest hyper-activation of MYOCD in the pathogenesis of the cardiorenal failure cases. Also, MYOCD silencing showed beneficial effects by rescuing cardiac hypertrophy, fibrosis, size and function in a cardiorenal rat model.

molecular biology↗

bioRxiv2018

Pharmacophore-driven Identification of N-Methyl-D-Receptor Antagonists as Potent Neuroprotective Agents Validated Using In-Vivo Studies

Alzheimers disease (AD), the most widespread cause of dementia is delineated by progressive cognitive impairment in the elderly people. During its progression, N-Methyl-D-Aspartate receptor antagonists are known to play a key role in the mechanisms of learning and memory. Extensive side effects alongside other effects on learning and memory have limited the therapeutic significance of various blockers and antagonists of the NMDA receptor. In this study, we identify potential compounds targeted against NMDA. In order to reveal the essential structural features for NMDA receptor, three-dimensional pharmacophore models are constructed based on a set of known NMDA inhibitors. This is followed by virtual screening which results in novel chemical compounds having the potential to inhibit NMDA. The lead compounds are then subjected to molecular docking and assessed by a scoring function, which results in two compounds with high Libdock scores. These compounds also show interactions with important residues at the active site. The compounds are shortlisted on the basis of high estimated activity, fit values, LibDock score, no violation to Lipinskis and availability for procuring.\n\nOf the shortlisted compounds, one compound satisfying the entire aforementioned criterion is further tested using in-vivo studies on mice with the help of an eight-arm radial maze. The pharmacophore-based virtual screening protocol presented in this study pave the way forward to address the unmet medical need of Alzheimer disease.

bioinformatics↗

bioRxiv2018

Identification of novel and structurally diverse N-Methyl-D-Aspartate Receptor Antagonists: Successful Application of Pharmacophore Modeling, Virtual Screening and Molecular Docking

In view of \"excitotoxic\" effects of glutamate, wherein excessive excitatory input causes increase in intracellular Ca2+ and ultimately cell death, NMDA receptor has emerged as an important target for treatment and prevention of several neurological disorders, like Alzheimer disease. Prompted by the successful application of in-silico pharmacophore-based virtual screening in lead identification, we have made an effort to implement in-silico protocols to identify novel NMDA receptor antagonist. A series of novel benzo[b]quinolizinium cations as NMDA receptor antagonists have been used as a starting point to develop prognostic pharmacophore models. The most predictive pharmacophore model (hypothesis 1), consisting of four features, namely, one hydrogen bond acceptor, one hydrophobic and two ring aromatic, showed a correlation (r) of 0.89, root mean square of 0.259, and the cost difference of 43.01 bits between null and fixed cost. The model was thoroughly validated and subjected to a chemical database search, which lead to the identification of 400 hits from NCI and Maybridge databases which were checked for Lipinskis violation and predictive potency.\n\nThis reduced the list to 10 compounds, out of which, two most potent compounds were subjected to molecular docking using Libdock software and interestingly, all the docked conformations showed hydrogen bond interactions with important amino acids Tyr214, His88, Thr174, Val169 and Arg121. In summary, through our validated pharmacophore-based virtual screening protocol, we have identified two potent, structurally diverse, druggable and novel NMDA receptor antagonist which might be of great help to address the unmet medical need of Alzheimer disease.

bioinformatics↗

bioRxiv2018

Evolved sequence features within the intrinsically disordered tail influence FtsZ assembly and bacterial cell division

Intrinsically disordered regions (IDRs) challenge the well-established sequence-structure-function paradigm for describing protein function and evolution. Here, we direct a combination of biophysical and cellular studies to further our understanding of how the intrinsically disordered C-terminal tail of FtsZ contributes to cell division in rod-shaped bacteria. FtsZ is a modular protein that encompasses a conserved GTPase domain and a highly variable intrinsically disordered C-terminal tail (CTT). The CTT is essential for forming the cytokinetic Z-ring. Despite poor sequence conservation of the CTT, the patterning of oppositely charged residues, which refers to the extent of linear mixing / segregation of oppositely charged residues within CTT sequences is bounded within a narrow range. To assess the impact of evolutionary bounds on charge patterning within CTT sequences we performed experiments, aided by sequence design, to quantify the impact of changing the patterning of oppositely charged residues within the CTT on the functions of FtsZ from B. subtilis. Z-ring formation is robust if and only if the extent of linear mixing / segregation of oppositely charged residues within the CTT sequences is within evolutionarily observed bounds. Otherwise, aberrant, CTT-mediated, FtsZ assemblies impair Z-ring formation. The complexities of CTT sequences also have to be above a threshold value because FtsZ variants with low complexity CTTs are not tolerated in cells. Taken together, our results suggest that CTT sequences have evolved to be \"just right\" and that this is achieved through an optimal extent of charge patterning while maintaining the sequence complexity above a threshold value.

biophysics↗

bioRxiv2017

Reverse Watson-Crick purine-purine base pairs : the Sharp-turn motif and other structural consequences in functional RNAs

Identification of static and/or dynamic roles of different noncanonical base pairs is essential for a comprehensive understanding of the sequence-structure-function space of RNA. In this context, reverse Watson-Crick purine-purine base pairs (A:A, G:G&A:GW:W Trans) constitute an interesting class of noncanonical base pairs in RNA due to their characteristic C1'-C1' distance (highest among all base pairing geometries) and parallel local strand orientation. Structural alignment of the RNA stretches containing these W:W Trans base pairs with their corresponding homologous sites in a non-redundant set of RNA crystal structures show that, as expected, these base pairs are associated with specific structural folds or functional roles. Detailed analysis of these contexts further revealed a bimodal distribution in the local backbone geometry parameters associated with these base pairs. One mode, populated by both A:A and G:G W:W Trans pairs, manifests itself as a characteristic backbone fold. We call this fold a Sharp-turn motif. The other mode is exclusively associated with A:A W:W Trans pairs involved in mediating higher order interactions. The same trend is also observed in available solution NMR structures. We have also characterized the importance of recurrent hydrogen bonding interactions between adenine and guanine in W:W Trans geometry. Quantum chemical calculations performed at M05-2X/6-31++(2d,2p) level explain how the characteristic electronic properties of these W:W Trans base pairs facilitate their occurrence in such exclusive structural folds that are important for RNA functionalities.

biophysics↗