Biology subjects

Sharma, N.

Publications and source records attributed to Sharma, N..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

In silico and In vitro evaluation of the anti-inflammatory and antioxidant potential of Cymbopogon citratus from North-western Himalayas

Cymbopogon citratus which is an aromatic perennial herb belonging to family Gramineae is known for its application in food and healthcare industry. The present study attempts to evaluate the potential of essential oil from Cymbopogon citratus (CEO) as an anti-inflammatory and antioxidant agent. CEO showed significant DPPH radical scavenging activity (IC50 - 91.0 ± 9.25 µg/ml), as compared to Ascorbic acid (IC50-33.38 ± 2.29 µg/ml). CEO also exhibited significant in-vitro anti-inflammatory activity with IC50 - 397.11± 1.45µg/ml) as compared to diclofenac sodium (IC50 - 682.98 ± 7.47 µg/ml). Chemical constituents of the oil was determined using Gas Chromatography/Mass Spectroscopy, showed that 8-methyl-3,7-Nonadien-2-one (E), α-Pinene, limonene, citral, limonene oxide and Epoxy-α-terpenyl acetate were the major constituents. The in silico molecular docking study showed phytocompounds of CEO (Caryophyllene oxide and β-caryophyllene) have considerable binding potential with 1HD2 and 5IKQ receptors. PASS prediction of these phytocompounds also confirmed strong anti-inflammatory activity of C. citratus. The ADMET analysis also showed that these phytocompounds are safer to replace the synthetic drugs with side effects. This work establishes the anti inflammatory potential of CEO as an alternative to existing therapeutic approach to treatment of inflammation and also natural source of antioxidant compounds.Competing Interest StatementThe authors have declared no competing interest.View Full Text

pharmacology and toxicology↗

bioRxiv2020

Insulin-like growth factor 2 (IGF2) protects against Huntington's disease through the extracellular disposal of protein aggregates

Impaired neuronal proteostasis is a salient feature of many neurodegenerative diseases, highlighting alterations in the function of the endoplasmic reticulum (ER). We previously reported that targeting the transcription factor XBP1, a key mediator of the ER stress response, delays disease progression and reduces protein aggregation in various models of neurodegeneration. To identify disease-modifier genes that may explain the neuroprotective effects of XBP1 deficiency, we performed gene expression profiling of brain cortex and striatum of these animals and uncovered insulin-like growth factor 2 (Igf2) as the major upregulated gene. Here we studied the impact of IGF2 signaling on protein aggregation in models of Huntingtons disease (HD) as proof-of-concept. Cell culture studies revealed that IGF2 treatment decreases the load of intracellular aggregates of mutant huntingtin and a polyglutamine peptide. These results were validated using induced pluripotent stem cells (iPSC)-derived medium spiny neurons from HD patients. The reduction in the levels of mutant huntingtin was associated with a decrease in the half-life of the intracellular protein. The decrease in the levels of abnormal protein aggregation triggered by IGF2 were independent of the activity of autophagy and the proteasome pathways, the two main routes for mutant huntingtin clearance. Conversely, IGF2 signaling enhanced the secretion of soluble mutant huntingtin species through exosomes and microvesicles involving changes in actin dynamics. Administration of IGF2 into the brain of HD mice using gene therapy led to a significant decrease in the levels of mutant huntingtin in three different animal models. Moreover, analysis of human post-mortem brain tissue, and blood samples from HD patients showed a reduction of IGF2 level. This study identifies IGF2 as a relevant factor deregulated in HD, operating as a disease modifier that buffers the accumulation of abnormal protein aggregates. One sentence summaryIGF2 reduces the load of intracellular protein aggregates through the extracellular disposal of the mutant protein.

neuroscience↗

bioRxiv2020

Machine learning analysis of the bleomycin-mouse model reveals the spatial and temporal pulmonary inflammatory fingerprint

The bleomycin mouse-model is the extensively used model to study pulmonary fibrosis, however, the inflammatory cell kinetics and their compartmentalisation is still incompletely understood. Here we assembled historical flow cytometry data, totalling 303 samples and 16 inflammatory-cell populations, and applied advanced data modelling and machine learning methods to conclusively detail these kinetics. Three days post-bleomycin, the inflammatory profile was typified by acute innate inflammation, pronounced neutrophilia, especially of SiglecF+ neutrophils, and alveolar macrophage loss. Between 14 and 21 days, rapid-responders were increasingly replaced by T and B cells, and monocyte-derived alveolar macrophages. Multi-colour imaging revealed the spatial-temporal cell distribution and the close association of T cells with deposited collagen. Unbiased immunophenotyping and data modelling exposed the dynamic shifts in immune-cell composition over the course of bleomycin-triggered lung injury. These results and workflow provides a reference point for future investigations, and can easily be applied in the analysis of other datasets.

immunology↗

bioRxiv2020

Bioengineered ciprofloxacin loaded chitosan nanoparticles for the treatment of Bovine Mastitis

Mastitis is the most devastating economic disease of dairy cattle. Mastitis in dairy cattle frequently occurs during the dry period or in early lactation. E. coli. and S. aureus is the main causative agent of mastitis. S. aureus has an ability to form encapsulated focuses in the udder and develop subclinical form of mastitis. This property of bacteria hinders the effective cure during lactation period. Antibiotics used for treatments have a short half-life span at the site of action because of frequent milking, therefore unable to maintain desired drug concentration for effective clearance of bacteria. We demonstrated the potential of ciprofloxacin encapsulated nanocarriers which can improve availability of drugs and could provide effective means of the treatment of mastitis. These drug loaded nanoparticles show low toxicity & slow clearance from the site of action. Antimicrobial studied against clinical strain of E.coli. and Staphylococcus aureus zone of inhibition depend on dose 0.5 mg to 2 mg/ml nanoparticles solution from 11.6 to 14.5 mm and 15 to 18mm. These nanoparticles show good antimicrobial activity in broth culture as well against bacteria.

pharmacology and toxicology↗

bioRxiv2020

Rapid, field-deployable nucleobase detection and identification using FnCas9

Detection of pathogenic sequences or variants in DNA and RNA through a point-of-care diagnostic approach is valuable for rapid clinical prognosis. In recent times, CRISPR based detection of nucleic acids has provided an economical and quicker alternative to sequencing-based platforms which are often difficult to implement in the field. Here, we present FnCas9 Editor Linked Uniform Detection Assay (FELUDA) that employs a highly accurate enzymatic readout for detecting nucleotide sequences, identifying nucleobase identity and inferring zygosity with precision. We demonstrate that FELUDA output can be adapted to multiple signal detection platforms and can be quickly designed and deployed for versatile applications including rapid diagnosis during infectious disease outbreaks like COVID-19.

molecular biology↗

bioRxiv2020

AntiCP 2.0: An updated model for predicting anticancer peptides

Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides (ACPs). ACPs residue composition analysis revealed the preference of A, F, K, L and W. Positional preference analysis revealed that residue A, F and K are preferred at N-terminus and residue L and K are preferred at C-terminus. Motif analysis revealed the presence of motifs like LAKLA, AKLAK, FAKL, LAKL in ACPs. Prediction models were developed using various input features and implementing different machine learning classifiers on two datasets main and alternate dataset. In the case of main dataset, ETree Classifier based model developed using dipeptide composition achieved maximum MCC of 0.51 and 0.83 AUROC on the training dataset. In the case of alternate dataset, ETree Classifier based model developed using amino acid composition performed best and achieved the highest MCC of 0.80 and AUROC of 0.97 on the training dataset. Models were trained and tested using five-fold cross validation technique and their performance was also evaluated on the validation dataset. Best models were implemented in the webserver AntiCP 2.0, freely available at https://webs.iiitd.edu.in/raghava/anticp2. The webserver is compatible with multiple screens such as iPhone, iPad, laptop, and android phones. The standalone version of the software is provided in the form of GitHub package as well as in docker technology.

bioinformatics↗

bioRxiv2020

A Combined Evidence Approach to Prioritize Nipah Virus Inhibitors

Nipah Virus (NiV) came into limelight due to an outbreak in Kerala, India. NiV causes severe disease and death in people with over 75% case fatality rate. It is a public health concern and has the potential to become a global pandemic. Lack of treatment has forced the containment methods to be restricted to isolation and surveillance. WHOs R&D Blueprint list of priority diseases (2018) indicates that there is an urgent need for accelerated research & development for addressing NiV. In the quest for druglike NiV inhibitors (NVIs) a thorough literature search followed by systematic data curation was conducted. Rigorous data analysis was done with curated NVIs for prioritizing druglike compounds. For the same, more than 1800 descriptors of NVIs were computed and comparative analysis was performed with the FDA approved small molecules and antivirals. These compounds were further evaluated through PAINS filter to study their toxicity profile. Simultaneously, compounds were also prioritized based on the robustness of the assays through which they were identified. Our efforts lead to the creation of a well-curated structured knowledgebase of 182 NVIs with 98 small molecule inhibitors. The reported IC50/EC50 values for some of these inhibitors are in the nanomolar range - as low as 0.47 nM. In order to prioritize these inhibitors, we performed several tests and applied filters to identify drug-like non-toxic compounds. Of 98, a few compounds passed DruLito & PAINS filters exhibiting drug-like properties and were also prioritized in an independent screen based only the assay robustness. The NVIs have diverse structural features and offer a wide spectrum of ways in which they can be developed further as druglike molecules. We report a knowledgebase for furthering the development of NVIs. The platform has a diverse set of 98 NVIs of which a few have been prioritized based on a combined evidence strategy. The platform has the provision to submit new inhibitors as and when reported by the community for further enhancement of NiV inhibitor landscape.

bioinformatics↗

bioRxiv2020

LC/MS-QToF Profiling, Anti-Diabetic and Anti-Adipogenic potential of Divya MadhuKalp: A Novel Herbo-mineral Formulation

The incidence rate of diabetes mellitus is increasing worldwide. Herbal formulations have recently gained importance as an alternative therapeutic option in controlling diabetes without causing any side effects. In the present study, we have demonstrated maintenance of glycemic homeostasis and anti-adipogenic potential of a herbo-mineral formulation Divya MadhuKalp (DMK). Initially, we evaluated the presence of bioactive compounds in DMK using LC/MS-QToF analysis. In-vitro analysis of DMK in L6 (skeletal muscle) cells showed a significant increase in cellular glucose uptake. Similarly, a human equivalent dose of DMK significantly reduced blood glucose level in normoglycemic and oral glucose tolerance rat model. DMK extract also inhibited formation of advanced glycation end product and showed anti--glucosidase activity. Further analysis of DMK in 3T3 L1 pre-adipocytes demonstrated anti-adipogenic activity through reduction in intracellular lipid accumulation and triglyceride contents along with downregulation of major adipogenic transcriptional factors (PPAR-{gamma} and C/EBP) and, adipocytes marker genes (LPL, AP2 and adiponectin). In conclusion, DMK exhibited anti-diabetic and anti-adipogenic activities by synergistic effect of its bioactive compounds and can be considered as a potent herbo-mineral formulation for treating metabolic diseases.

cell biology↗

bioRxiv2020

Comparison between conventional electrodes and ultrasound monitoring to measure TMS evoked muscle contraction

BackgroundTranscranial Magnetic stimulation (TMS) is a non-invasive cortical stimulation method that has been widely employed to explore cortical physiology in health and a range of diseases. At the core of many TMS protocols is the measurement of evoked muscle contractions using surface electromyography (sEMG). While sEMG is appropriate for many superficial muscles such as abductor pollicis brevis (ABP) and first dorsal interosseous (FDI), there are situations where the study of less accessible muscles may be of interest. Peripheral ultrasound is a non-invasive method that could provide a solution. We explore the relationship between TMS evoked sMEP and TMS evoked muscle contractions measured with muscle ultrasound. We hypothesise that in a healthy population, we expect a positive correlation between EMG and ultrasound measures. MethodsIn 10 participants we performed a standard TMS recruitment curve and simultaneously measured MEP and peripheral muscle ultrasound (pUS). We targeted the following muscles: biceps (BI), first dorsal interosseous (FDI), tibialis anterior (TA) and the tongue (TO). ResultsWe report a very close relationship between the MEP and pUS contraction. Resting motor threshold (RMT) measurements and recruitment curves are consistent in sEMG and pUS. A key aspect of this work is the ability to examine clinically relevant muscles that are difficult to probe using surface EMG electrodes, such as the tongue. ConclusionWe find that TMS muscle contractions can be measured with muscle ultrasound in superficial and deep muscles, enable additional, previously hard to study muscles, to be investigated. This could be valuable for allowing TMS to be used to explore a new range of muscles in disorders such as ALS. In muscles less accessible by sEMG, such as the tongue, it may be possible to use pUS as an alternative output. This may be useful in conditions such as ALS and stroke that can differentially affect the tongue.

neuroscience↗

bioRxiv2020

Cellular internalization of Godanti Bhasma (anhydrous CaSO4) induces massive cytoplasmic reversible vacuolation and survival response of mammalian cells.

Bhasmas are Ayurvedic herbo-mineral formulations that have been used since ancient times for therapeutic benefits. Godanti Bhasma (GB) is an anhydrous calcium sulfate preparation processed by heating of gypsum powder with herbal extracts. Thermo-transformation of gypsum into the anhydrous GB was confirmed by Raman and FT-IR spectroscopy. GB particle showed size range of 0.5-5 {micro}m and neutral surface charge. Exposure to mammalian cells with GB particles showed massive vacuolation in their cytoplasm. Interestingly, no vacuolation was observed with parent gypsum particle. The result indicated that the cytoplasmic vacuolation by GB was due to its unique physicochemical property obtained during the thermo-transformation of gypsum. Using lysosomal inhibitors Bafilomycin A1 (BFA1) and Chloroquine (CQ), the process of vacuole formation was suppressed indicating GB induced vacuolation require acidic environment. The GB induced vacuolation was also found to follow dose and time dependent manner. Vacuolation often accompany with the sign of cell death whereas, in our study, massive vacuolation by GB did not induce any cell death. Moreover, GB treated cells survive with massive vacuolar process, which was reversed following post-treatment with vacuole inhibitors in GB treated cells, suggesting normal vacuolar function is essential for cell survival. Treatment of cells with GB was also found to induce translocation of LC3 protein from the nucleus to vacuolar membrane, indicating LC3 associated phagocytosis (LAP) is involved in the vacuolar process. Interestingly, the LAP function was found to be reversed in the cells treated with vacuole inhibitors. Our results provide a mechanistic correlation with GB induced vacuolation and associated LAP function, essential for cell survival. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/930594v3_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@169ed89org.highwire.dtl.DTLVardef@169c339org.highwire.dtl.DTLVardef@900004org.highwire.dtl.DTLVardef@1f13823_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2020

Multi-Object Tracking in Heterogeneous environments (MOTHe) for animal space-use studies

O_LIVideo recordings of animals are used for many areas of research such as collective movement, animal space-use, animal censuses and behavioural neuroscience. They provide us with behavioural data at scales and resolutions not possible with manual observations. Many automated methods are being developed to extract data from these high-resolution videos. However, the task of animal detection and tracking for videos taken in natural settings remains challenging due to heterogeneous environments. C_LIO_LIWe present an open-source end-to-end pipeline called Multi-Object Tracking in Heterogenous environments (MOTHe), a python-based application that uses a basic convolutional neural network for object detection. MOTHe allows researchers with minimal coding experience to track multiple animals in their natural habitats. It identifies animals even when individuals are stationary or partially camouflaged. C_LIO_LIMOTHe has a command-line-based interface with one command for each action, for example, finding animals in an image and tracking each individual. Parameters used by the algorithm are well described in a configuration file along with example values for different types of tracking scenario. MOTHe doesnt require any sophisticated infrastructure and can be run on basic desktop computing units. C_LIO_LIWe demonstrate MOTHe on six video clips from two species in their natural habitat - wasp colonies on their nests (up to 12 individuals per colony) and antelope herds in four different types of habitats (up to 156 individuals in a herd). Using MOTHe, we are able to detect and track all individuals in these animal group videos. MOTHes computing time on a personal computer with 4 GB RAM and i5 processor is 5 minutes for a 30-second long ultra-HD (4K resolution) video recorded at 30 frames per second. C_LIO_LIMOTHe is available as an open-source repository with a detailed user guide and demonstrations at Github (https://github.com/tee-lab/MOTHe). C_LI

ecology↗

bioRxiv2019

GPSRdocker: A Docker-based Resource for Genomics, Proteomics and Systems biology

BackgroundIn past number of web-based resources has been developed in the field of Bioinformatics. These resources are heavily used by scientific community to provide solution for challenges faced by experimental researchers particularly in the field of biomedical sciences. There are number of challenges in utilizing full potential of these services that includes internet speed, limits on computing power, and security of data. In order to enhance utilities of these web-based assets, we developed a docker-based container that integrates large number resources available in literature.\n\nResultsThis paper describes GPSRdocker a docker-based container developed for providing wide-range of computational tools in the field of bioinformatics particularly in genomics, proteomics and system biology. Majority of tools integrated in GPSRdocker are based on web services developed at Raghavas group in last two decades. Broadly, these tools can be categorized in three categories; i) general scripts, ii) supporting software and iii) major standalone software. In order to facilitate students or developers working in the field of bioinformatics, we developed general scripts in Perl and Python. These general-purpose scripts serve as building block for any bioinformatics tools like computing features/descriptors of a protein. Supporting software packages includes SCIKIT, WEKA, SVMlight, and PSI-BLAST; these software packages allow one to develop/implement bioinformatics software. Major Standalone software is core of this container which allows predicting function/class of biomolecules. These tools can be classified broadly in following categories; protein annotation, epitope-based vaccines, prediction of interaction and drug discovery.\n\nConclusionA docker-based container has been developed which can be easily run on any operating system as well as it can be directly ported on cloud. Scripts can be run to build pipelines for addressing problems at system level like prediction of vaccine candidate for a pathogen. GPSRdocker including manual is available free for academic use from https://webs.iiitd.edu.in/gpsrdocker.

bioinformatics↗

bioRxiv2019

Short interval intracortical inhibition as measured by TMS-EEG

The diagnosis of amyotrophic lateral sclerosis (ALS) relies on involvement of both upper (UMN) lower motor neurons (LMN). Yet, there remains no objective marker of UMN involvement, limiting early diagnosis of ALS. This study establishes whether TMS combined with EEG can be used to measure short-interval intracortical inhibition (SICI) via TMS evoked potentials (TEP) in healthy volunteers - an essential first step in developing an independent marker of UMN involvement in ALS.\n\nWe hypothesised that a SICI paradigm would result in characteristic changes in the TMS-evoked EEG potentials that directly mirror the changes in MEP.\n\nTMS was delivered to the left motor cortex using single-pulse and three inhibitory stimulation paradigms. SICI was present in all three conditions. TEP peaks were reduced predominantly under the SICI 70 protocol but less so for SICI 80 and not at all for SICI 90. There was a significant negative correlation between MEPs and N45 TEP peak for SICI 70 (rho = -0.54, p = 0.04). In other words, as MEPs becomes inhibited the N45 increases. The same trend was maintained across SICI 80 and 90 (SICI 80, rho = -0.5, p = 0.06; SICI 90, rho = -0.48, p = 0.07). Additional experiments suggest these results cannot be explained by artefact.\n\nWe establish that motor cortical inhibition can be measured during a SICI 70 protocol expanding on previous work. We have carefully considered the role of artefact in TEPs and have taken a number of steps to show that artefact cannot explain these results and we suggesting the differences are cortical in origin. TMS-EEG has potential to aid early diagnosis and to further understand central and peripheral pathophysiology in MND.

neuroscience↗

bioRxiv2019

GATA2 Expression by Intima-Infiltrating Macrophages Drives Early Atheroma Formation

Aberrant macrophage polarization is a major contributor to the onset and progression of atherosclerosis. Despite this, macrophage polarization during in early stages of human atherosclerotic disease is poorly understood. Using transcriptomic analysis of macrophages recovered from early-stage human atherosclerotic lesions, we have identified a unique gene expression profile dissimilar to that observed in later stages of disease that is characterized by upregulation of the hematopoietic transcription factor GATA2. GATA2 overexpression in vitro recapitulated defects observed in patient macrophages, including deficiencies in the uptake and processing of apoptotic cells, and in the catalysis of atherogenic protein modifications, with GATA2 knockdown abrogating these defects. Our data describe a previously unreported macrophage differentiation state present in early atheroma formation and identifies GATA2 as a driver of macrophage functional defects during the early stages of atherosclerosis in humans.

immunology↗

bioRxiv2019

Physiotherapist confidence level in mobilising stroke patients after decompressive hemicraniectomy: are helmets useful?

IntroductionDecompressive hemicraniectomy is a lifesaving measure in malignant middle cerebral artery infarction; however, this leaves patients with a skull defect. There is variability of helmet use in this patient group across Britain. We aimed to examine whether (1) specialist physiotherapist were more confident mobilising a patient with hemiparesis and skull defect than a non-specialist physiotherapist (2) non-specialist and specialist physiotherapists would be more comfortable mobilising this patient with a helmet as opposed to without a helmet.\n\nMethodsWe carried out a cross-sectional online survey of specialist physiotherapists and non-specialist physiotherapists in Britain. Recruitment was through mailing lists. Physiotherapists were asked to rank their confidence level on a 5-point Likert scale of mobilising an example patient with and without a helmet. They were also asked about the number of additional therapists needed to safely mobilise the patient.\n\nFindings96 physiotherapists completed the survey; 44 were specialists and 52 were non-specialists. Specialist physiotherapists felt more comfortable mobilising patients (mean difference = 0.68, p < 0.001). Non-specialist physiotherapists felt significantly more comfortable mobilising patients with a helmet (mean difference = 0.96, p value < 0.001), as did specialist physiotherapists (mean difference = 0.68, p value < 0.001). There was no difference in confidence level arising from helmet use between the two groups (p = 0.72).\n\nConclusionsUse of helmets may allow specialist and non-specialist physiotherapists to feel more comfortable when mobilising stroke patients post-decompressive hemicraniectomy. Consideration should be made by hospitals and health systems for the provision of helmets this patient group, to maximise functional gains.

neuroscience↗

bioRxiv2019

Computing wide range of protein/peptide features from their sequence and structure

MotivationIn last three decades, a wide range of protein descriptors/features have been discovered to annotate a protein with high precision. A wide range of features have been integrated in numerous software packages (e.g., PROFEAT, PyBioMed, iFeature, protr, Rcpi, propy) to predict function of a protein. These features are not suitable to predict function of a protein at residue level such as prediction of ligand binding residues, DNA interacting residues, post translational modification etc.\n\nResultsIn order to facilitate scientific community, we have developed a software package that computes more than 50,000 features, important for predicting function of a protein and its residues. It has five major modules for computing; composition-based features, binary profiles, evolutionary information, structure-based features and patterns. The composition-based module allows user to compute; i) simple compositions like amino acid, dipeptide, tripeptide; ii) Properties based compositions; iii) Repeats and distribution of amino acids; iv) Shannon entropy to measure the low complexity regions; iv) Miscellaneous compositions like pseudo amino acid, autocorrelation, conjoint triad, quasi-sequence order. Binary profile of amino acid sequences provides complete information including order of residues or type of residues; specifically, suitable to predict function of a protein at residue level. Pfeature allows one to compute evolutionary information-based features in form of PSSM profile generated using PSIBLAST. Structure based module allows computing structure-based features, specifically suitable to annotate chemically modified peptides/proteins. Pfeature also allows generating overlapping patterns and feature from whole protein or its parts (e.g., N-terminal, C-terminal). In summary, Pfeature comprises of almost all features used till now, for predicting function of a protein/peptide including its residues.\n\nAvailabilityIt is available in form of a web server, named as Pfeature (https://webs.iiitd.edu.in/raghava/pfeature/), as well as python library and standalone package (https://github.com/raghavagps/Pfeature) suitable for Windows, Ubuntu, Fedora, MacOS and Centos based operating system.

bioinformatics↗

bioRxiv2019

Francisella novicida Cas9 interrogates genomic DNA with very high specificity and can be used for mammalian genome editing

Genome editing using the CRISPR Cas9 system has been used to manipulate eukaryotic DNA and make precise heritable changes. Although the widely used Streptococcus pyogenes Cas9 (SpCas9) and its engineered variants have been efficiently harnessed for numerous gene-editing applications across different platforms, concerns remain, regarding their putative off targeting at multiple loci across the genome. Here we report that Francisella novicida Cas9 (FnCas9) shows a very high specificity of binding to its intended targets and negligible binding to off-target loci. The specificity is determined by its minimal binding affinity with DNA when mismatches to the target sgRNA are present in the sgRNA:DNA heteroduplex. FnCas9 produces staggered cleavage, higher HDR rates and very low non-specific genome editing compared to SpCas9. We demonstrate FnCas9 mediated correction of the sickle cell mutation in patient derived iPSCs and propose that it can be used for precise therapeutic genome editing for a wide variety of genetic disorders.\n\nSIGNIFICANCE STATEMENTTherapeutic genome editing has been significantly accentuated by the advent of CRISPR based gene correction. However, genomic off-targeting has been a major setback for clinical translation. Although high fidelity versions of Cas9 have been rationally designed, they recognize and bind to off-targets. In this study, we characterize a naturally occurring Cas9 from Francisella novicida (FnCas9) that shows negligible binding affinity to off targets differing by one or more mismatches, rendering it highly specific in target recognition and editing. We show that FnCas9 can direct both HDR and NHEJ mediated DNA repair, generates higher rate of HDR and negligible off-target editing. Finally we show its potential in therapeutic genome editing by correcting the sickle cell anemia mutation in patient derived iPSCs.

molecular biology↗

bioRxiv2019

Effects of healthy ageing on activation pattern within the brain during movement and motor imagery: an fMRI study.

IntroductionMotor imagery (MI) has potential as an intervention to improve performance in neurological disease affecting the motor system and to modulate brain computer interfaces (BCI). We hypothesized that the shared networks of MI and executed movement (EM) would be affected by age. Understanding these changes is important in application of MI in neurological disorders.\n\nMethodsUsing tensor-independent component analysis (TICA), we mapped the neural networks involved during MI and EM in 31 healthy volunteers (ages 20-72), who were recruited and screened for their ability to perform imagery. We used an fMRI block-design with MI & rest and EM & rest.\n\nResultsTICA defined 37 independent components (ICs). Eight remained after excluding ICs representing artifacts. These ICs accounted for 35% of variance. While all ICs had greater activation in EM than MI. Two ICs increased with greater age for EM only. These ICs contained a bilateral network of brain areas, including primary motor cortex and cerebellum.\n\nConclusionThis study demonstrates the prominence of shared cerebral networks between MI and EM. There are age-dependent changes to EM activation, while MI activation appeared age independent. This strengthens the rationale for using MI to access the motor networks independent of age.

neuroscience↗