Biology subjects

Ahmad, S.

Publications and source records attributed to Ahmad, S..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

Sox9 Regulates Extracellular Matrix Stiffness during Vascular Smooth Muscle Cell ageing by increased secretion of LH3 via extracellular vesicles.

RationaleVascular calcification and increased extracellular matrix (ECM) stiffness are hallmarks of vascular ageing. Sox9 (SRY-Box Transcription Factor 9) is a master regulator of chondrogenesis, also expressed in the vasculature, that has been implicated in vascular smooth muscle cell (VSMC) osteo-chondrogenic conversion. ObjectiveHere, we investigated the relationship between vascular ageing, calcification and Sox9-driven ECM regulation in VSMCs. Methods and ResultsImmunohistochemistry in human aortic samples showed that Sox9 was not spatially associated with vascular calcification but correlated with the senescence marker p16. Analysis of Sox9 expression in vitro showed it was mechanosensitive with increased expression and nuclear translocation in senescent cells and on stiff matrices. Manipulation of Sox9 via overexpression and depletion, combined with atomic force microscopy (AFM) and proteomics, revealed that Sox9 regulates ECM stiffness and organisation by orchestrating changes in collagen expression and reducing VSMC contractility, leading to the formation of an ECM that mirrored that of senescent cells. These ECM changes promoted phenotypic modulation of VSMCs whereby senescent cells plated onto ECM synthesized from cells depleted of Sox9 returned to a proliferative state, while proliferating cells on a matrix produced by Sox9 expressing cells showed reduced proliferation and increased DNA damage, reiterating features of senescent cells. Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3 (LH3) was identified as a Sox9 target, and key regulator of ECM stiffness. LH3 is packaged into extracellular vesicles (EVs) and Sox9 promoted EV secretion, leading to increased LH3 deposition within the ECM. ConclusionsThese findings identify cellular senescence and Sox9 as a key regulators of ECM stiffness during VSMC ageing and highlight a crucial role for ECM structure and composition in regulating VSMC phenotype. We identify a positive feedback cycle whereby cellular senescence and increased ECM stiffening promote Sox9 expression which drives further ECM modifications that act to accelerate vascular stiffening and cellular senescence.

molecular biology↗

bioRxiv2023

RTCpredictor: Identification of Read-Through Chimeric RNAs from RNA Sequencing Data

Read-through chimeric RNAs are gaining attention in cancer and other research fields, yet current tools often fail in predicting them. We have thus developed the first read-through chimeric RNA specific prediction method, RTCpredictor, utilizing a fast ripgrep algorithm to search for all possible exon-exon combinations of parental gene pairs. Compared with other ten popular tools, RTCpredictor achieved top performance on both simulated and real datasets. We randomly selected up to 30 candidate read-through chimeras predicted from each software method and experimentally validated a total of 109 read-throughs and on this set, RTCpredictor outperformed all the other methods. In addition, RTCpredictor (https://github.com/sandybioteck/RTCpredictor) has less memory requirements and faster execution time.

genomics↗

bioRxiv2022

Candida khanbhai sp. nov., a new clinically relevant yeast within the Candida haemulonii species complex

Invasive fungal infections caused by non-albicans Candida species are increasingly reported. Recent advances in diagnostic and molecular tools enabled better identification and detection of these emerging pathogenic yeasts. Several of these emerging species belong to the Candida haemulonii species complex, which attracted much attention due to the rapid global emergence of its multi-drug resistant member Candida auris. Here, we describe a new clinically relevant yeast isolated from geographically distinct regions, representing the proposed novel species Candida khanbhai, member of the C. haemulonii species complex. Moreover, several members of the C. haemulonii species complex were observed to be invalidly described, including Candida auris and Candida vulturna. Hence, the opportunity was taken to correct this here, formally validating the names of various yeast species.

microbiology↗

bioRxiv2022

A study on packed cell volume for deducing hemoglobin: Cholistani camels in perspective

In human medical practice, a hematological rule of three has been validated for healthy human populations. One such formula is estimating hemoglobin (Hb) levels as 1/3rd of Packed Cell Volume (PCV). However, no such hematological formulae have been devised and validated for veterinary medical practice. The present study was devised with an aim to evaluate the relationship between hemoglobin (Hb) concentration and Packed Cell Volume (PCV) in camels (n=215) being reared under pastoralism, and to devise a simple pen-side hematological formula for estimation of Hb from PCV. The PCV was determined through microhematocrit method whereas Hb estimation by cyanmethaemoglobin method (HbD). The Hb was also calculated as 1/3rd of PCV and was dubbed as calculated Hb (HbC). Overall HbD and HbC were significantly (P[≥]0.05) different. Similar results were attained for all study groups i.e. males (n=94) and females (n=121), and young (n=85) and adult (n=130) camels. The corrected Hb (CHb) was deduced through regression prediction equation attained from linear regression model. Scatter-plots were drawn, linear regression was carried out, and Bland Altman chart was built for agreement of both methods of Hb estimation. A non-significant (P[≥]0.05) difference was noticed between HbD and CHb. Bland Altman chart revealed good agreement between HbD and CHb and there was no proportional bias on the distribution of data around the mean difference line (Mean= 0.1436, 95% CI= 3.00, -2.72). We accordingly recommend a simplified pen-side hematological formula for deducing Hb concentration from PCV viz. Hb concentration (g/dL)=0.18(PCV)+5.4 for all age and gender groups of camels instead of its calculation as one-third of PCV.

physiology↗

bioRxiv2022

High Throughput Chromosome Conformation Capture identifies differential genome organization in virulent and avirulent strains of Mycobacterium tuberculosis

Recent studies have shown that three-dimensional architecture of bacterial chromatin plays an important role in gene expression regulation. However, genome topological organization in Mycobacterium tuberculosis (M. tuberculosis), the etiologic agent of tuberculosis, remains unknown. On the other hand, exact mechanism of differential pathogenesis in the canonical strains of M. tuberculosis H37Rv and H37Ra remains poorly understood in terms of their raw sequences. In this context, a detailed contact map from a Hi-C experiment is a candidate for what bridges the gap. Here we present the first comprehensive report on genome-wide contact maps between regions of H37Rv and H37Ra genomes. We tracked differences between the genome architectures of H37Rv and H37Ra, which could possibly explain the virulence attenuation in H37Ra. We confirm the existence of a differential organization between the two strains most significantly a higher Chromosome Interacting Domain (CID) size in attenuated H37Ra strain. CID boundaries are also found enriched with highly expressed genes and with higher operon density in H37Rv. Furthermore, most of the differentially expressed PE/PPE genes were present near the CID boundaries in H37Rv and not in H37Ra. Collectively our study proposes a differential genomic topological pattern between H37Rv and H37Ra, which could explain the virulence attenuation in H37Ra.

genomics↗

bioRxiv2022

Drought and flooding resistances of maize germplasm are compared and evaluated using a multivariate analysis method

Drought and flooding stress alternately and frequently occur in Guangxi, China, and the whole world, which seriously limit maize production. Few studies focus on the different responses and evaluations of maize to drought and flooding stresses. A pot experiment with 40 varieties was conducted under well water, drought and flooding stresses. A multivariate analysis method of principal component analysis, comprehensive evaluation value, correlation analysis, stepwise regression analysis, and cluster analysis was used to evaluate the resistance of maize. Most varieties had stronger drought resistance rather than flooding resistance because of the higher antioxidant enzyme activities, osmotic adjustment substances, less reactive oxygen species, and a greater than 1.0 drought-resistance coefficient. However, there was an increment of reactive oxygen species (especially O2-), ascorbate peroxidase, peroxidase, soluble sugar, and the decrement of superoxide dismutase, catalase, soluble protein, and a lower than 1.0 of flooding-resistance coefficient of most maize varieties in flooding stress compared with well water. The superoxide dismutase, peroxidase, catalase, ascorbate peroxidase, proline, soluble sugar and protein, plant height, leaf area/plant, and stem diameter were screened out to be accurate and representative indicators to evaluate the drought and flooding resistance of maize. The study provides an insight to comprehend the different mechanisms of maize in response to drought and flooding stresses and provides a multivariate analysis method for screening the resistance of maize germplasm which could be valuable for further research and breeding of drought and flooding resistances of maize. One-sentence summaryA multivariate analysis method for the screening the resistance of maize germplasm and the different physiological mechanisms of drought and flooding stresses were revealed.

physiology↗

bioRxiv2022

Primary Omicron infection elicits weak antibody response but robust cellularimmunity in children

Omicron variants of SARS-CoV-2 are globally dominant and infection rates are very high in children. We determined immune responses following Omicron BA.1/2 infection in children aged 6-14 years and related this to prior and subsequent SARS-CoV-2 infection or vaccination. Primary Omicron infection elicited a weak antibody response with poor functional neutralizing antibodies. Subsequent Omicron reinfection or COVID-19 vaccination elicited increased antibody titres with broad neutralisation of Omicron subvariants. Prior pre-Omicron SARS-CoV-2 virus infection or vaccination primed for robust antibody responses following Omicron infection but these remained primarily focussed against ancestral variants. Primary Omicron infection thus elicits a weak antibody response in children which is boosted after reinfection or vaccination. Cellular responses were robust and broadly equivalent in all groups, providing protection against severe disease irrespective of SARS-CoV-2 variant. Immunological imprinting is likely to act as an important determinant of long-term humoral immunity, the future clinical importance of which is unknown.

immunology↗

bioRxiv2022

Multifaceted Atlases of the Human Brain in its Infancy

Brain atlases agglomerate structural and functional features of a population of individuals in a standard coordinate space. Here, we introduce for the first time a collection of atlases that charts postnatal development of the human brain in a spatio-temporally dense manner from two weeks to two years of age. Atlases capturing month-to-month changes of the human brain are essentially nonexistent for the first two years of life -- the critical developmental period during which the brain is evolving in virtually all facets at an exponential pace. This unmet need is compounded by the lack of atlases that provide a unified and holistic picture of the brain from both the perspectives of cortical surface convolutions and tissue volumetric characteristics. Existing surface and volumetric atlases are typically constructed independently in different coordinate spaces, causing discrepancies and complications in multifaceted analyses. Our month-specific conjoint surface and volumetric atlases chart normative patterns and capture key traits of early brain development and are therefore critical for identifying aberrations from normal developmental trajectories. Our atlases represent a major advance toward providing the neuroscience community an invaluable resource to facilitate the understanding of early structural and functional development by mapping multiple measurements of infant brains in a common reference frame for precise spatio-temporal quantification of cortical and subcortical changes.

neuroscience↗

bioRxiv2022

A reduced-memory multi-layer perceptron withsystematic network weights generated and trainedthrough distribution hyper-parameters

A multi-layer perceptron (MLP) consists of a number of forward-connected weights (Wijk) from each feeding layer node (nij) to the many initially equivalent nodes (ni+1,k) in the next layer. Exact a priori order and search space of these weights (Wijk) is random and prone to redundancy, irreproducibility and non-optimality. We demonstrate that a weight subspace (Wijk for each i and j), generated systematically using a statistical distribution with predefined breakpoints and Genetic algorithm-trained hyper-parameters substantially reduces the computational complexity of an MLP and produces comparable or better performance than similarly trained equivalent models with fully defined weights. This distribution based neural network (DBNN) provides a novel framework to create very large neural network models with currently prohibitive memory requirements.

bioinformatics↗

bioRxiv2022

SARS-CoV-2 variants show a gradual declining pathogenicity and pro-inflammatory cytokine stimulation and an increasing antigenic and anti-inflammatory cytokine induction

Hyper-transmissibility with decreased disease severity are typical characteristics of Omicron variant. To understand this phenomenon, we used various bioinformatics approaches to analyze randomly selected genome sequences (one each) of the Gamma, Delta, and Omicron variants submitted to NCBI from 15 to 31 December 2021. We show that: (i) Pathogenicity of SARS-CoV-2 variants decreases in the order: Wuhan > Gamma > Delta > Omicron; however, the antigenic property follows the order: Omicron > Gamma > Wuhan > Delta. (ii) Omicron Spike RBD has lower pathogenicity but higher antigenicity than other variants. (iii) Decreased disease severity by Omicron variant may be due to its decreased pro-inflammatory and IL-6 stimulation and increased IFN-{gamma} and IL-4 induction efficacy. (iv) Mutations in N protein are associated with decreased IL-6 induction and human DDX21-mediated increased IL-4 production in Omicron. (v) Due to mutations, the stability of S, M, N, and E proteins decreases in the order: Omicron > Gamma > Delta > Wuhan. (vi) Stronger Spike RBD-hACE2 binding in Omicron is associated with increased transmissibility. However, the lowest stability of the Omicron Spike protein makes Spike RBD-hACE2 interaction weak for systemic infection and for causing severe disease. Finally (vii), the highest instability of Omicron E protein may also be associated with decreased viral maturation and low viral load leading to less severe disease and faster recovery. Our method may be used for other similar viruses, and these findings will contribute to the understanding of the dynamics of SARS-CoV-2 variants and the management of emerging variants.

bioinformatics↗

bioRxiv2021

Fascicles split or merge every ~560 microns within the human cervical vagus nerve

1Vagus nerve stimulation (VNS) is FDA approved for stroke rehabilitation, epilepsy, and depression; however, the vagus functional anatomy underlying the implant is poorly understood. We used microCT to quantify fascicular structure and neuroanatomy within human cervical vagus nerves. Fascicles split or merged every ~560 m (17.8 {+/-} 6.1 events/cm). The high degree of fascicular splitting and merging in humans may explain the clinical heterogeneity in patient responses.

neuroscience↗

bioRxiv2021

Going Beyond the Point Neuron: Active Dendrites and Sparse Representations for Continual Learning

Biological neurons integrate their inputs on dendrites using a diverse range of non-linear functions. However the majority of artificial neural networks (ANNs) ignore biological neurons structural complexity and instead use simplified point neurons. Can dendritic properties add value to ANNs? In this paper we investigate this question in the context of continual learning, an area where ANNs suffer from catastrophic forgetting (i.e., ANNs are unable to learn new information without erasing what they previously learned). We propose that dendritic properties can help neurons learn context-specific patterns and invoke highly sparse context-specific subnetworks. Within a continual learning scenario, these task-specific subnetworks interfere minimally with each other and, as a result, the network remembers previous tasks significantly better than standard ANNs. We then show that by combining dendritic networks with Synaptic Intelligence (a biologically motivated method for complex weights) we can achieve significant resilience to catastrophic forgetting, more than either technique can achieve on its own. Our neuron model is directly inspired by the biophysics of sustained depolarization following dendritic NMDA spikes. Our research sheds light on how biological properties of neurons can be used to solve scenarios that are typically impossible for traditional ANNs to solve.

neuroscience↗

bioRxiv2021

In vivo emergence of high-level resistance during treatment reveals the first identified mechanism of amphotericin B resistance in Candida auris

Candida auris has emerged as a healthcare-associated and multidrug-resistant fungal pathogen of great clinical concern. While as much as 50% of C. auris clinical isolates are reported to be resistant to amphotericin B, to date, no mechanisms contributing to this resistance have been identified. We report here mutations in the C. auris sterol-methyltransferase gene, ERG6, as the first identified mechanism of amphotericin B resistance in this emerging pathogen and describe the clinical case in which this high-level amphotericin B resistance was acquired in vivo during therapy. Whole genome sequencing revealed the four C. auris isolates obtained from this single patient case to be genetically related and identified a mutation in ERG6 as being associated with amphotericin B resistance. Cas9-mediated genetic manipulations confirmed this mutation alone to confer a >32-fold increase in amphotericin B resistance, and comprehensive sterol profiling revealed an abrogation of ergosterol biosynthesis and a corresponding accumulation of cholesta-type sterols in isolates and strains harboring the clinically derived ERG6 mutation. Together these findings represent the first significant step forward in the understanding of clinical amphotericin B resistance in C. auris.

microbiology↗

bioRxiv2021

Structure of a bacterial Rhs effector exported by the type VI secretion system

The type VI secretion system (T6SS) is a widespread protein export apparatus found in Gram-negative bacteria. The majority of T6SSs deliver toxic effector proteins into competitor bacteria. Yet, the structure, function, and activation of many of these effectors remains poorly understood. Here, we present the structures of the T6SS effector RhsA from Pseudomonas protegens and its cognate T6SS spike protein, VgrG1, at 3.3 [A] resolution. The structures reveal that the rearrangement hotspot (Rhs) repeats of RhsA assemble into a closed anticlockwise {beta}-barrel spiral similar to that found in bacterial insecticidal Tc toxins and in metazoan teneurin proteins. We find that the C-terminal toxin domain of RhsA is autoproteolytically cleaved but remains inside the Rhs cocoon where, with the exception of three ordered structural elements, most of the toxin is disordered. The N-terminal plug domain is unique to T6SS Rhs proteins and resembles a champagne cork that seals the Rhs cocoon at one end while also mediating interactions with VgrG1. Interestingly, this domain is also autoproteolytically cleaved inside the cocoon but remains associated with it. We propose that mechanical force is required to remove the cleaved part of the plug, resulting in the release of the toxin domain as it is delivered into a susceptible bacterial cell by the T6SS.

biochemistry↗

bioRxiv2021

Substrate access mechanism in a novel membrane-bound phospholipase A of Pseudomonas aeruginosa concordant with specificity and regioselectivity

PlaF is a cytoplasmic membrane-bound phospholipase A1 from Pseudomonas aeruginosa that alters the membrane glycerophospholipid (GPL) composition and fosters the virulence of this human pathogen. PlaF activity is regulated by a dimer-to-monomer transition followed by tilting of the monomer in the membrane. However, how substrates reach the active site and how the characteristics of the active site tunnels determine the activity, specificity, and regioselectivity of PlaF for natural GPL substrates has remained elusive. Here, we combined unbiased and biased all-atom molecular dynamics (MD) simulations and configurational free energy computations to identify access pathways of GPL substrates to the catalytic center of PlaF. Our results map out a distinct tunnel through which substrates access the catalytic center. PlaF variants with bulky tryptophan residues in this tunnel revealed decreased catalysis rates due to tunnel blockage. The MD simulations suggest that GPLs preferably enter the active site with the sn-1 acyl chain first, which agrees with the experimentally demonstrated PLA1 activity of PlaF. We propose that the acyl chain-length specificity of PlaF is determined by the structural features of the access tunnel, which results in favorable free energy of binding of medium-chain GPLs. The suggested egress route conveys fatty acid products to the dimerization interface and, thus, contributes to understanding the product feedback regulation of PlaF by fatty acid-triggered dimerization. These findings open up opportunities for developing potential PlaF inhibitors, which may act as antibiotics against P. aeruginosa.

biochemistry↗

bioRxiv2021

Genomic Surveillance of COVID-19 Variants with Language Models and Machine Learning

The global efforts to control COVID-19 are threatened by the rapid emergence of novel SARS-CoV-2 variants that may display undesirable characteristics such as immune escape, increased transmissibility or pathogenicity. Early prediction for emergence of new strains with these features is critical for pandemic preparedness. We present Strainflow, a supervised and causally predictive model using unsupervised latent space features of SARS-CoV-2 genome sequences. Strainflow was trained and validated on 0.9 million sequences for the period December, 2019 to June, 2021 and the frozen model was prospectively validated from July, 2021 to December, 2021. Strainflow captured the rise in cases two months ahead of the Delta and Omicron surges in most countries including the prediction of a surge in India as early as beginning of November, 2021. Entropy analysis of Strainflow unsupervised embeddings clearly reveals the explore-exploit cycles in genomic feature-space, thus adding interpretability to the deep learning based model. We also conducted codon-level analysis of our model for interpretability and biological validity of our unsupervised features. Strainflow application is openly available as an interactive web-application for prospective genomic surveillance of COVID-19 across the globe.

bioinformatics↗

bioRxiv2021

Evaluating Sample Augmentation in Microarray Datasets with Generative Models: A Comparative Pipeline and Insights in Tuberculosis.

High throughput screening technologies have created a fundamental challenge for statistical and machine learning analyses, i.e., the curse of dimensionality. Gene expression data are a quintessential example, high dimensional in variables (Large P) and comparatively much smaller in samples (Small N). However, the large number of variables are not independent. This understanding is reflected in Systems Biology approaches to the transcriptome as a network of coordinated biological functioning or through principal Axes of variation underlying the gene expression. Recent advances in generative deep learning offers a new paradigm to tackle the curse of dimensionality by generating new data from the underlying latent space captured as a deep representation of the observed data. These have led to widespread applications of approaches such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs), especially in domains where millions of data points exist, such as in computer vision and single cell data. Very few studies have focused on generative modeling of bulk transcriptomic data and microarrays, despite being one of the largest types of publicly available biomedical data. Here we review the potential of Generative models in recapitulating and extending biomedical knowledge from microarray data, which may thus limit the potential to yield hundreds of novel biomarkers. Here we review the potential of generative models and conduct a comparative analysis of VAE, GAN and gaussian mixture model (GMM) in a dataset focused on Tuberculosis. We further review whether previously known axes genes can be used as an effective strategy to employ domain knowledge while designing generative models as a means to further reduce biological noise and enhance signals that can be validated by standard enrichment approaches or functional experiments.

genomics↗

bioRxiv2021

Stress granules are shock absorbers that prevent excessive innate immune responses to dsRNA

Proper defense against microbial infection depends on the controlled activation of the immune system. This is particularly important for the RIG-I-like receptors (RLRs), which recognize viral dsRNA and initiate antiviral innate immune responses with the potential of triggering systemic inflammation and immunopathology. Here we show that stress granules (SGs), molecular condensates that form in response to various stresses including viral dsRNA, play key roles in controlled activation of RLR signaling. Without the SG nucleators G3BP1/2 and UBAP2L, dsRNA triggers excessive inflammation and immune-mediated apoptosis. In addition to exogenous dsRNA, we find that host-derived dsRNA generated in response to ADAR1 deficiency is also controlled by SG biology. Intriguingly, SGs can function beyond immune control by suppressing viral replication independent of the RLR pathway. These observations thus highlight the multi-functional nature of SGs as cellular "shock absorbers" that converge on protecting cell homeostasis-by dampening both toxic immune response and viral replication.

immunology↗