Biology subjects

Das, M.

Publications and source records attributed to Das, M..

70 records · Page 4Linked to original sources

bioRxiv2021

Anti-diabetic effects of Holarrhena antidysentrica extracts: Results from a Longitudinal Meta-analysis

BackgroundHolarrhena antidysenterica (HA), a twining shrub belonging to the Apocynaceae family is found in tropical regions of Africa and over a large part of Asia including India, Philippines and Malayan Peninsula. In Indian traditional system of medicine, HA has been used to treat gastric ailments, for wound healing and also to improve glycaemic control. Glucose lowering activity of HA root, bark, seed, leaf and fruit extract in different parts of India as well as in Chinese traditional medicine is widely reported. PurposeIn the meta-analysis reported in this article, we summarize glucose-lowering effects of HA extracts from different plant parts as reported in multiple studies involving animal models of diabetes. Our analysis helps to quantify the glucose-lowering effect of HA in comparison with standard diabetes drugs. The analysis also sheds light on differential efficacy levels of HA extracted from different plant parts. Study designThe meta-analysis was carried out following PRISMA guidelines. Literature was searched to identify studies published between years 2011 to 2019 reporting glucose-lowering effects of HA extract on rodent models of diabetes. MethodsLongitudinal meta-analysis was carried out on time-course data extracted from selected studies to calculate standardized mean change of glucose value from day 1 to days 7, 14 and 21 post-treatment by HA extract or standard anti-diabetic drug. Subgroup analysis was carried out for studies reporting effects of HA on leaf and seed extracts. Standardized mean difference in levels of cholesterol, triglycerides and serum total protein between treatment and control groups were also assessed. ResultsWe shortlisted nine articles to be used for this meta-analysis. Summarized standardized mean changes of glucose value between day 1 and day 21 post-treatment indicated glucose-lowering effects of HA extracts to be marginally lower but comparable to that of standard anti-diabetic drugs like Glibenclamide or Sitagliptin. However, subgroup analysis revealed seed extracts of HA to be more potent than leaf extracts or even standard drugs. Effects of the extract on levels of cholesterol, triglyceride and serum total protein was also commensurate with its glucose-lowering property. ConclusionsOur results, summarized over multiple studies, present a clear quantitative assessment of the anti-diabetic property of HA, in particular the seed extracts compared to standard anti-diabetic drugs. Further differential analysis of the seed extracts will be useful to arrive at a herbal formulation with superior anti-diabetic property and possibly lesser side effects than chemical entities.

plant biology↗

bioRxiv2021

A Nanoceutical Agent for Chemoprevention of Bilirubin Encephalopathy

BackgroundTargeted degradation of bilirubin in vivo may enable safer and more effective approach to manage incipient bilirubin encephalopathy consequent to severe neonatal hyperbilirubinemia (SNH). This report builds on the use of a spinel structured mixed-valence transition metal oxide (trimanganese tetroxide) nanoparticle duly functionalized with biocompatible ligand citrate (C-Mn3O4 NP) having the ability to degrade bilirubin without photo-activation. MethodThe efficiency of C-Mn3O4 NP in in vivo degradation of serum bilirubin and amelioration of severe bilirubin encephalopathy and associated neurobehavioral changes was evaluated in C57BL/6j animal model of SNH. ResultsOral single dose (0.25 mg kg-1 body weight) of the NPs efficiently reduced serum bilirubin levels (both conjugated and unconjugated) in study mice. It prevents bilirubin-induced neurotoxicity with reduction of SNH as observed by neurobehavioral and movement studies of SNH-mice. Pharmacokinetic data suggests intestinal reabsorption of the NPs and explain sustainable action. Biodistribution, pharmacokinetics, and biocompatibility of the NPs were tested during sub-chronic exposure. ConclusionThus, we report preliminary studies that explore an affordable chemoprevention mechanism to acutely prevent or minimize bilirubin neurotoxicity in newborn infants. IMPACT STATEMENTO_LIDespite several attempts, no pharmaco-therapeutics are available for the treatment of severe neonatal hyperbilirubinemia (SNH) and associated neurotoxicity. C_LIO_LIOur newly developed nanodrug, citrate functionalized Mn3O4 nanoparticles (C-Mn3O4 NPs), can efficiently ameliorate SNH and associated neurotoxicity as investigated in preclinical rodent model. C_LIO_LIChemoprevention effect of the nanodrug is found to be safe and sustainable. C_LIO_LIIf successfully translated into clinical trials, C-Mn3O4 NPs could become the first drug to treat SNH. C_LI

pharmacology and toxicology↗

bioRxiv2020

Incorporation of a Biocompatible Nanozyme in Cellular Antioxidant Enzyme Cascade Reverses Huntington's Like Disorder in Preclinical Model

The potentiality of nano-enzymes in therapeutic use has directed contemporary research to develop a substitute for natural enzymes, which are suffering from several disadvantages including low stability, high cost, and difficulty in storage. However, inherent toxicity, inefficiency in the physiological milieu, and incompatibility to function in cellular enzyme networks limit the therapeutic use of nanozymes in living systems. Here, we have shown that citrate functionalized manganese-based biocompatible nanoscale material (C-Mn3O4 NP) efficiently mimics glutathione peroxidase enzyme in the physiological milieu and easily incorporates into the cellular multienzyme cascade for H2O2 scavenging. A detailed computational study reveals the mechanism of the nanozyme action. We further established the in vivo therapeutic efficacy of C-Mn3O4 nanozyme in a preclinical animal model of Huntingtons disease, a prevalent progressive neurodegenerative disorder, which has no effective medication till date. SUMMARYAlthough, nano-enzymes have shown lots of promises in the management of several diseases, two major concerns limit their clinical translation. Apart from the inherent toxicity of the constituent materials (e.g., cerium, vanadium, gold, etc.), activities of contemporary nanozymes are often inhibited in physiological milieu. Furthermore, most of them are incapable of incorporation into the cellular metabolic networks for functioning in tandem and parallel with natural enzymes, a major criteria for potential therapeutics. Here, we have shown that citrate-functionalized spherical Mn3O4 nanoparticles can efficiently mimic glutathione peroxidase (GPX) enzyme without the limitations of contemporary nanozymes, and effectively manage neurodegenerative Huntingtons disease in preclinical animal model. The choice of the material in the nanozyme lies on the fact that Mn is an essential micronutrient for mammals, and the stabilizing ligand citrate helps the nanoparticles to cross the blood-brain-barrier to reach brain. We have shown that the nanozyme can easily be incorporated in cellular antioxidant enzyme cascade. The specificity and efficacy of the nanozyme in the cascade was significantly higher compared to other reported nanozymes. We have justified our experimental findings with a detailed computational study. Understanding the mode of operation and management of Huntingtons disease in preclinical animal trial using a biocompatible (non-toxic) nanozyme as a part of the metabolic network may uncover a new paradigm in nanozyme based therapeutic strategy.

pharmacology and toxicology↗

bioRxiv2020

Contextual Prediction Errors Reorganize Episodic Memories in Time

Episodic memories are contextual experiences ordered in time. This is underpinned by associative binding between events within the same contexts. The role of prediction errors in strengthening declarative memory is well established but has not been investigated in the time dimension of complex episodic memories. Here we used 3-day movie viewing paradigm to test the hypothesis that contextual prediction errors leads to temporal organization of sequential memory processing. Our main findings uncover that prediction errors lead to changes in temporal organization of events, secondly, new unexpected sequences show as high accuracy as control sequences viewed repeatedly, and these effects are specifically due to prediction errors, and not novel associations. A drift-diffusion modelling further revealed a lower decision threshold for the newer, unexpected sequences compared to older sequences reflected by their faster recall leads to reorganization of episodes in time. Moreover, we found individual decision threshold could significantly predict their relative speed of sequence memory recall. Taking together our results suggest a temporally distinct role for prediction errors in ordering sequences of events in episodic memory.

neuroscience↗

bioRxiv2020

Myosin-driven actin-microtubule networks exhibit self-organized contractile dynamics

The cytoskeleton is a dynamic network of proteins, including actin, microtubules, and myosin, that enables essential cellular processes such as motility, division, mechanosensing, and growth. While actomyosin networks are extensively studied, how interactions between actin and microtubules, ubiquitous in the cytoskeleton, influence actomyosin activity remains an open question. Here, we create a network of co-entangled actin and microtubules driven by myosin II. We combine dynamic differential microscopy, particle image velocimetry and particle-tracking to show that both actin and microtubules in the network undergo ballistic contraction with surprisingly indistinguishable characteristics. This controlled contractility is distinct from the faster turbulent motion and rupturing that active actin networks exhibit. Our results suggest that microtubules can enable self-organized myosin-driven contraction by providing flexural rigidity and enhanced connectivity to actin networks. These results provide important new insight into the diverse interactions cells can use to tune activity, and offer a powerful platform for designing multifunctional materials with well-regulated activity.

biophysics↗

bioRxiv2020

Tumor neoantigen heterogeneity impacts bystander immune inhibition of pancreatic cancer growth

The threshold for immunogenic clonal fraction in a heterogeneous solid tumor required to induce effective bystander killing of non-immunogenic subclones is unknown. Pancreatic cancer poses crucial challenges for immune therapeutic interventions due to low mutational burden and consequent lack of neoantigens. Here, we designed a model to incorporate artificial neoantigens into genes of interest in cancer cells and to test the potential of said antigens to actuate bystander killing. By precisely controlling the abundance of a neoantigen in the tumor, we studied the impact of neoantigen frequency on immune response and immune escape. Our results showed that a single, strong, widely expressed neoantigen could lead to a robust antitumor response when at least 80% of cancer cells express the neoantigen. Further, immunological assays revealed induction of T-cell responses against a non-target self-antigen on KRAS oncoprotein, when we inoculated animals with a high frequency of tumor cells expressing a test neoantigen. Using nanoparticle-based gene therapy, we successfully altered the tumor microenvironment by perturbing interleukin-12 and interleukin-10 gene expression. The subsequent remodeling of the microenvironment reduced the threshold of neoantigen frequency at which bioluminescent signal intensity for tumor burden decreased 1.5-logfold, marking a robust tumor growth inhibition, from 83% to as low as 29%. Our results thus suggest that bystander killing is rather inefficient in immunologically cold tumors like pancreatic cancer and requires an extremely high abundance of neoantigens. However, the bystander killing mediated antitumor response can be rescued, when supported by adjuvant immune therapy.

cancer biology↗

bioRxiv2020

Sequence-based Prediction of Metamorphic Behavior in Proteins

An increasing number of proteins have been demonstrated in recent years to adopt multiple three-dimensional folds with different functions. These metamorphic proteins are characterized by having two or more folds with significant differences in their secondary structure, where each fold is stabilized by a distinct local environment. So far, about 90 metamorphic proteins have been identified in the Protein Databank (PDB), but we and others hypothesize that a far greater number of metamorphic proteins remain undiscovered. In this work, we introduce a computational model to predict metamorphic behavior in proteins using only knowledge of the sequence. In this model, secondary structure prediction programs are used to calculate diversity indices, which are measures of uncertainty in predicted secondary structure at each position in the sequence; these are then used to assign protein sequences as likely to be metamorphic vs. monomorphic (i.e. having just one-fold). We constructed a reference dataset to train our classification method, which includes a novel compilation of 140 likely-monomorphic proteins, and a set of 201 metamorphic proteins taken from the literature. Our model is able to classify proteins as metamorphic vs. monomorphic with a Matthews correlation coefficient of [~]0.4 and true positive / true negative rates of [~]65% / 80%, suggesting that it is possible to predict metamorphic behavior in proteins using only sequence information. Statement of SignificanceThis paper introduces the diversity index as a descriptor to distinguish metamorphic proteins, which possess multiple stable folds, from monomorphic proteins that possess only one fold. The diversity index is designed to measure uncertainty in computationally predicted secondary structure, which we hypothesize is elevated for metamorphic proteins. We tested our hypothesis by training a binary classifier using the diversity index and an annotated dataset of metamorphic and monomorphic proteins, and found an optimal Matthews correlation coefficient of 0.4, supporting the hypothesis and demonstrating for the first time that it is possible to predict metamorphic behavior in proteins using only sequence information. The sequence-based classifier has broader applicability compared to methods that rely on making comparison to experimentally measured structures.

biophysics↗

bioRxiv2019

How do thalamocortical connections shape causal structure among resting state brain networks during aging?

The human brain undergoes significant structural and functional changes across the lifespan. Our current understanding of the underlying causal relationships of dynamical changes in functional connectivity with age is limited. On average, functional connectivity within resting-state networks (RSNs) weakens in magnitude, while connections between RSNs tend to increase with age. Recent studies show that effective connectivity within and between large scale resting-state functional networks changes over the healthy lifespan. The vast majority of previous studies have focused primarily on characterizing cortical networks, with little work exploring the influence of subcortical nodes such as the thalamus on large-scale network interactions across the lifespan. Using directed connectivity and weighted net causal outflow measures applied to resting-state fMRI data, we examine the age-related changes in both cortical and thalamocortical causal interactions within and between RSNs. The three core neurocognitive networks from the triple network theory (default mode: DMN, salience: SN, and central executive: CEN) were identified independently using ICA and spatial matching of hub regions with these important RSNs previously reported in the literature. Multivariate granger causal analysis (GCA) was performed to test for directional connectivity and weighted causal outflow between selected nodes of RSNs accounting for thalamo-cortical interactions. Firstly, we observe that within-network causal connections become progressively weaker with age, and network dynamics are substantially reconfigured via strong thalamic drive particularly in the young group. Our findings manifest stronger between-network directional connectivity, which is further strongly mediated by the SN in flexible co-ordination with the CEN, and DMN in the old group compared with the young group. Hence, causal within- and between- triple network connectivity largely reflects age-associated effects of resting-state functional connectivity. Thalamo-cortical causality effects on the triple networks with age were next explored. We discovered that left and right thalamus exhibit substantial interactions with the triple networks and play a crucial role in the reconfiguration of directed connections and within network causal outflow. The SN displayed directed functional connectivity in strongly driving both the CEN and DMN to a greater extent in the older group. Notably, these results were largely replicated on an independent dataset of matched young and old individuals. Our findings based on directed functional connectivity and weighted causal outflow measures strengthen the hypothesis that balancing within and between network connectivity is perhaps critical for the preservation and flexibility of cognitive functioning with aging.

neuroscience↗

bioRxiv2019

IPCO: Inference of Pathways from Co-variance analysis

Key aspects of microbiome research are accurate identification of taxa followed by the profiling of their functionality. Amplicon profiling based on the 16S ribosomal DNA sequence is a ubiquitous technique to identify and profile the abundances of the various taxa. However, it does not provide information on their encoded functionality. Predictive tools which can accurately extrapolate the functional information of a microbiome based on taxonomic profile composition is essential. At present the applicability of these tools is however limited due to requirement of reference genomes from known species. We present IPCO (Inference of Pathways from Co-variance analysis), a new method of inferring functionality for 16S-based microbiome profiles independent of reference genomes. IPCO utilises the biological co-variance observed between paired taxonomic and functional profiles and co-varies it with the queried dataset. It outperforms other established methods both in terms of sample and feature profile prediction. Validation results confirmed that IPCO can replicate observed biological signals seen within shotgun and metabolite profiles. Comparative analysis of predicted functionality profiles with other popular 16S-based functional prediction tools indicates significantly lower performance with predicted functionality showing little to no correlation with paired shotgun features across samples. IPCO is implemented in R and available from https://github.com/IPCO-Rlibrary/IPCO.

bioinformatics↗

bioRxiv2019

Computational Saturation Mutagenesis of the β subunit of RNA polymerase in Mycobacterium leprae

In contrast to the situation with tuberculosis, rifampin resistance in leprosy may remain undetected due to the lack of rapid and effective diagnostic methods. A quick and reliable method is essential to determine the impacts of emerging detrimental mutations. The functional consequences of missense mutations within the {beta}-subunit of RNA polymerase in Mycobacterium leprae (M. leprae) contribute to phenotypic rifampin resistance outcomes in leprosy. Here we report in-silico saturation mutagenesis of all residues in the {beta}-subunit of RNA polymerase to all other 19 amino acid types and predict their impacts on overall thermodynamic stability, on interactions at subunit interfaces, and on {beta}-subunit-RNA and rifampin affinities using state-of-the-art structure, sequence and normal mode analysis-based methods. A total of 21,394 mutations were analysed, and it was noted that mutations in the conserved residues that line the active-site cleft show largely destabilizing effects, resulting in increased relative solvent accessibility and concomitant decrease in depth of the mutant residues. The mutations at residues S437, G459, H451, P489, K884 and H1035 are identified as extremely detrimental as they induce highly destabilizing effects on the overall stability, nucleic acid and rifampin affinities. Destabilizing effects were predicted for all the experimentally identified rifampin-resistant mutations in M. leprae indicating that this model can be used as a surveillance tool to monitor emerging detrimental mutations conferring rifampin resistance in leprosy.\n\nAUTHOR SUMMARYEmergence of primary and secondary drug resistance to rifampin in leprosy is a growing concern and poses threat to the leprosy control and elimination measures globally. In the absence of an effective in-vitro system to detect and monitor phenotypic rifampin resistance in leprosy, most of the diagnosis relies on detecting mutations in the drug resistance determining regions of the rpoB gene that encodes the {beta} subunit of RNA polymerase in M. leprae. Few labs in the world perform mouse food pad propagation of M. leprae in the presence of drugs (rifampin) to determine growth patterns and confirm resistance, however the duration of these methods lasts from 8 to 12 months making them impractical for diagnosis. Understanding molecular mechanisms of drug resistance is vital to associating mutations to clinical resistance outcomes in leprosy. Here we propose an in-silico saturation mutagenesis approach to comprehensively elucidate the structural implications of any mutations that exist or can arise in the {beta} subunit of RNA polymerase in M. leprae. Most of the predicted mutations may not occur in M. leprae due to fitness costs but the information thus generated by this approach help decipher the impacts of mutations across the structure and conversely enable identification of stable regions in the protein that are least impacted by mutations (mutation coolspots) which can be a choice for small molecule binding and structure guided drug discovery.

bioinformatics↗

bioRxiv2019

Diurnal variations in serum metabolites of wintering redheaded buntings.

Daily behavioural and physiological changes in bird may reflect in biofluid metabolite composition. Locomotor activity, food intake and body temperature of group (n=7) of male migratory redheaded buntings held under short days (8L:16D, SD) were monitored besides blood sampling at midday (ZT4: 4 hours zeitgeber time starting ZT0 as lights on) and midnight (ZT16). The birds exhibited higher activity and increased feeding during daytime with negligible activity and feeding at night. Gas chromatography mass spectrometry and chemo-metric analyses of bird serum revealed higher levels of lipid (palmitic, oleic and linoleic acids) and protein (uric acid and proline) catabolites in daytime serum samples as compared to night samples. Higher night-time levels of short chain fatty acids indicated utilization of glucose and lipolysis in night fasted birds. High night-time levels of taurine, a sulphur amino acid has adaptive advantage to night migratory song birds. The diurnal differences in metabolite patterns suggests differential energy expenditure during day and renders survival benefit to buntings as night migrants. We propose a GCMS method that could be useful to unravel different annual life-history stages including migration.

animal behavior and cognition↗

bioRxiv2019

Varying crosslinking motifs drive the mesoscale mechanics of actin-microtubule composites

The cytoskeleton dynamically tunes its mechanical properties by altering the interactions between semiflexible actin filaments, rigid microtubules, and crosslinking proteins. Here, we use optical tweezers microrheology and confocal microscopy to characterize how varying crosslinking motifs impact the microscopic and mesoscale mechanics and mobility of actin-microtubule composites. We show that, upon subtle changes in the crosslinking pattern, composites separate into two distinct classes of force response - primarily elastic versus more viscous behavior. For example, a composite in which actin and microtubules are crosslinked to each other is markedly more elastic than one in which both filaments are crosslinked but cannot link together. Notably, this distinction only emerges at mesoscopic scales in response to nonlinear forcing, whereas varying crosslinking motifs have little impact on the microscale mechanics and steady-state mobility of composites. Our unexpected scale-dependent results not only inform the physics underlying key cytoskeleton processes and structures, but, more generally, provide valuable perspective to materials engineering endeavors focused on polymer composites.

biophysics↗

bioRxiv2018

The Cdc42 GEF, Gef1, promotes uniform protein distribution along the actomyosin ring to enable concentric furrowing

During cytokinesis, fission yeast coordinates actomyosin ring constriction with septum ingression, resulting in concentric furrow formation. Mechanisms coordinating septum ingression with the actomyosin ring remain unclear. We report that cells lacking the Cdc42 activator Gef1, combined with an activated allele of the formin, Cdc12, display non-concentric furrowing. Although cells that furrow non-concentrically display normal actomyosin rings, the scaffold Cdc15 is unevenly distributed along the ring. This suggests that after ring assembly, uniform Cdc15 distribution along the ring drives proper furrow formation. We find that Cdc15 levels at the ring are reduced in the activated cdc12 mutant, or upon disruption of Arp2/3 complex-dependent endocytic patches. Furthermore, Cdc15 levels in endocytic patches increase in gef1 mutants. We hypothesize that assembled rings recruit Cdc15 from endocytic patches. Patches with higher Cdc15 levels and slower ring-association rate lead to uneven Cdc15 distribution. Based on this hypothesis we developed a mathematical model that captures experimentally observed Cdc15 distributions along the ring. We propose that, at the ring, Gef1 and endocytic events promote uniform Cdc15 distribution to enable proper septum ingression and concentric furrow formation.\n\nSummary StatementGef1 and endocytic events at the assembled actomyosin ring facilitate uniform Cdc15 distribution along the ring thus enabling concentric furrow formation.

cell biology↗

bioRxiv2018

Molecular basis for a novel systemic form of human hereditary apoA-I amyloidosis with vision loss

Hereditary apolipoprotein A-I (apoA-I) amyloidosis (AApoAI) is a life-threatening incurable genetic disorder whose molecular underpinnings and the full spectrum of afflicted organs are unclear. We report a new form of AApoAI with amyloid deposition in multiple organs, including an unprecedented retinal amyloidosis. Genetic and proteomic analyses identified Glu34Lys apoA-I as the fibrillar protein causing the clinical manifestations. A life-saving combined hepatorenal transplantation was performed for one Glu34Lys carrier. To elucidate structural underpinnings for amyloidogenic properties of Glu34Lys, we generated its recombinant globular domain and compared the conformation and dynamics of its lipid-free form with those of two other naturally occurring apoA-I variants, Phe71Tyr (amyloidogenic) and Leu159Arg (non-amyloidogenic). All variants showed reduced stability and altered aromatic residue packing. Molecular dynamics simulations revealed local helical unfolding and suggested that transient opening of Trp72 induced mutation-dependent structural perturbations in a sensitive region, including the major amyloid hotspot residues 14-22. We posit that a shift from the \"closed\" to an \"open\" orientation of Trp72 modulates structural protection of amyloid hotspots, suggesting a previously unknown early step in protein misfolding.

molecular biology↗

bioRxiv2017

BCL11A interacts with SOX2 to control the expression of epigenetic regulators in lung squamous cell carcinoma

Patients diagnosed with lung squamous cell carcinoma (LUSC) have limited targeted therapeutic options. We report here the identification and characterisation of the transcriptional regulator, BCL11A, as a LUSC oncogene. Analysis of cancer genomics datasets revealed BCL11A to be upregulated in LUSC but not lung adenocarcinoma (LUAD). We demonstrated that knockdown of BCL11A in LUSC cell lines abolished xenograft tumour growth and its overexpression in vivo led to lung airway hyperplasia and the development of reserve cell hyperplastic lesions. In addition, deletion of Bcl11a in the tracheal basal cells abolished the development of tracheosphere organoids while its overexpression led to solid tracheospheres with a squamous phenotype. At the molecular level we found BCL11A to be a target of SOX2 and we show that it is required for the oncogenic role of SOX2 in LUSC. Furthermore, we showed that BCL11A and SOX2 interact at the protein level and that together they co-regulated the expression of several transcription factors. We demonstrate that pharmacological inhibition of SETD8, a gene co-regulated by BCL11A and SOX2, alone or in combination with cisplatin treatment, shows significant selectivity to LUSC in comparison to LUAD cells. Collectively, these results indicate that the disruption of the BCL11A-SOX2 transcriptional program provides a future framework for the development of targeted therapeutic intervention for LUSC patients.

cancer biology↗

bioRxiv2017

Ancient exapted transposable elements drive nuclear localisation of lncRNAs

The sequence domains underlying long noncoding RNA (lncRNA) activities, including their characteristic nuclear enrichment, remain largely unknown. It has been proposed that these domains can originate from neofunctionalised fragments of transposable elements (TEs), otherwise known as RIDLs (Repeat Insertion Domains of Long Noncoding RNA), although just a handful have been identified. It is challenging to distinguish functional RIDL instances against a numerous genomic background of neutrally-evolving TEs. We here show evidence that a subset of TE types experience evolutionary selection in the context of lncRNA exons. Together these comprise an enrichment group of 5374 TE fragments in 3566 loci. Their host lncRNAs tend to be functionally validated and associated with disease. This RIDL group was used to explore the relationship between TEs and lncRNA subcellular localisation. Using global localisation data from ten human cell lines, we uncover a dose-dependent relationship between nuclear/cytoplasmic distribution, and evolutionarily-conserved L2b, MIRb and MIRc elements. This is observed in multiple cell types, and is unaffected by confounders of transcript length or expression. Experimental validation with engineered transgenes shows that these TEs drive nuclear enrichment in a natural sequence context. Together these data reveal a role for TEs in regulating the subcellular localisation of lncRNAs.

genomics↗