Biology subjects

Husic, M.

Publications and source records attributed to Husic, M..

9 recordsLinked to original sources

bioRxiv2026

Sound-evoked orofacial motion only affects a fraction of visually responsive V1 neurons in a multisensory detection task with delayed reward delivery

Auditory stimuli have been known to elicit neural responses in visual cortical areas, but such responses are partly associated with sound-evoked orofacial movements. However, it remains unclear to what extent neural correlates of movement can be dissociated from non-motor correlates. Here we developed a paradigm with a forced delayed-response mechanism by means of a moving reward apparatus in order to test whether this results in low amounts of movement-related neural activity shortly after stimulus onset. Animals performed a multisensory detection task, while we recorded neural activity from V1 and measured orofacial motion. During the delay, when only the stimulus was present, orofacial motion was relatively low. Reward-related motion increased after the delay, with a concomitant increase in motor-related spiking activity. Visual stimulation did neither elicit considerable motion nor corresponding neural responses in the delay period. Conversely, salient auditory stimuli led to modest, but increased orofacial motion and related neuronal activity during the delay. We identified a subpopulation of visually responsive V1 neurons that did not show correlations with orofacial movement, with only the stimulus being represented. These results present a forced delayed-response window as a method to help disentangle motor-related activity from visual (but not auditory) processing and show that motor-related activity only affects a fraction of visually selective neurons.

neuroscience↗

bioRxiv2022

Involvement of superior colliculus in complex figure detection of mice

Object detection is an essential function of the visual system. Although the visual cortex plays an important role in object detection, the superior colliculus can support detection when the visual cortex is ablated or silenced. Moreover, it has been shown that superficial layers of mouse SC (sSC) encode visual features of complex objects, and that this code is not inherited from the primary visual cortex. This suggests that mouse sSC may provide a significant contribution to complex object vision. Here, we use optogenetics to show that mouse sSC is causally involved in figure detection based on differences in figure contrast, orientation and phase. Additionally, our neural recordings show that in mouse sSC, image elements that belong to a figure elicit stronger activity than those same elements when they are part of the background. The discriminability of this neural code is higher for correct trials than incorrect trials. Our results provide new insight into the behavioral relevance of the visual processing that takes place in sSC.

neuroscience↗

bioRxiv2021

A corticothalamic circuit trades off speed for safety during decision-making under motivational conflict

Decisions to act while pursuing goals in the presence of danger must be made quickly but safely. Premature decisions risk injury or death whereas postponing decisions risk goal loss. Here we show how mice resolve these competing demands. Using microstructural behavioral analyses, we identified the spatiotemporal dynamics of approach-avoidance decisions under motivational conflict. Then we used cognitive modelling to show that these dynamics reflect the speeded decision-making mechanisms used by humans and non-human primates, with mice trading off decision speed for safety of choice when danger loomed. Using calcium imaging and functional circuit analyses, we show that this speed-safety trade off occurs because increases in paraventricular thalamus (PVT) activity increase decision caution, thereby increasing approach-avoid decision times in the presence of danger. Our findings demonstrate that a discrete brain circuit involving the PVT and its prefrontal cortical input dynamically adjusts decision caution during motivational conflict, trading off decision speed for decision safety when danger is close. They identify the corticothalamic pathway as central to cognitive control during decision-making under conflict.

neuroscience↗

bioRxiv2021

Regulation of skeletal muscle metabolism and contraction performance via teneurin-latrophilin action.

Skeletal muscle regulation is responsible for voluntary muscular movement in vertebrates. The genes of two essential proteins, teneurins and latrophilins (LPHN), evolving in ancestors of multicellular animals, form a ligand-receptor pair, and are now shown to be required for skeletal muscle function. Teneurins possess a bioactive peptide, termed the teneurin C-terminal associated peptide (TCAP) that interacts with the LPHNs to regulate skeletal muscle contractility strength and fatigue by an insulin-independent glucose importation mechanism. CRISPR-based knockouts and siRNA-associated knockdowns of LPHN-1 and-3 shows that TCAP stimulates an LPHN-mediated cytosolic Ca2+ signal transduction cascade to increase energy metabolism and enhance skeletal muscle function via increases in type-1 oxidative fiber formation and reduce the fatigue response. Thus, the teneurin/TCAP-LPHN system is presented as a novel mechanism likely to regulate the energy requirements and performance of skeletal muscle.

physiology↗

bioRxiv2021

CanDIG: Secure Federated Genomic Queries and Analyses Across Jurisdictions

Rapid expansions of bioinformatics and computational biology have broadened the collection and use of -omics data including genomic, transcriptomic, methylomic and a myriad of other health data types, in the clinic and the laboratory. Both clinical and research uses of such data require co-analysis with large datasets, for which participant privacy and the need for data custodian controls must remain paramount. This is particularly challenging in multi-jurisdictional settings, such as Canada, where health privacy and security requirements are often heterogeneous. Data federation presents a solution to this, allowing for integration and analysis of large datasets from various sites while abiding by local policies. The Canadian Distributed Infrastructure for Genomics platform (CanDIG) enables federated querying and analysis of -omics and health data while keeping that data local and under local control. It builds upon existing infrastructures to connect five health and research institutions across Canada, relies heavily on standards and tooling brought together by the Global Alliance for Genomics and Health (GA4GH), implements a clear division of responsibilities among its participants and adheres to international data sharing standards. Participating researchers and clinicians can therefore contribute to and quickly access a critical mass of -omics data across a national network in a manner that takes into account the multi-jurisdictional nature of our privacy and security policies. Through this, CanDIG gives medical and research communities the tools needed to use and analyze the ever-growing amount of -omics data available to them in order to improve our understanding and treatment of various conditions and diseases. CanDIG is being used to make genomic and phenotypic data available for querying across Canada as part of data sharing for five leading pan-Canadian projects including the Terry Fox Comprehensive Cancer Care Centre Consortium Network (TF4CN) and Terry Fox PRecision Oncology For Young peopLE (PROFYLE), and making data from provincial projects such as POG (Personalized Onco- Genomics) more widely available.

genomics↗

bioRxiv2020

TMExplorer: A Tumour Microenvironment Single-cell RNAseq Database and Search Tool

Tumour microenvironments (TME) contain a variety of cells including but not limited to stromal fibroblasts, endothelial cells, immune cells, malignant cells, and cells of the tissues of origin, whose interactions likely influence tumour behaviour and response to cancer treatment. The specific composition of the TME can be elucidated using single-cell RNA sequencing (scRNA-seq) by measuring expression profiles of individual cells. Several scRNA-seq datasets from multiple cancer types have been published in recent years, yet we still lack a comprehensive database for the collection and presentation of TME data from these studies in an easily accessible format. We have thus built a database of TME scRNA-seq data, containing 21 TME scRNA-seq datasets from 12 different cancer types. We have also created an R package called TMExplorer, which provides an interface to easily search and access all available datasets and their metadata. Data and metadata are kept in a consistent format across all datasets, with multiple expression formats available depending on the use case. Users can view a table of metadata and select individual datasets or filter them by specific characteristics. Users may also select a specific type of cancer and view all published scRNA-seq data for that cancer type available in our database. Users are provided with an option to save the data in multiple formats in order to view or process it outside of R. Thus, the TMExplorer database and search tool allows for thorough examination of the TME using scRNA-seq in a way that is streamlined and allows for easy integration into already existing scRNA-seq analysis pipelines.

bioinformatics↗

bioRxiv2020

MetaFusion: A high-confidence metacaller for filtering and prioritizing RNA-seq gene fusion candidates.

MotivationCurrent fusion detection tools use diverse calling approaches and provide varying results, making selection of the appropriate tool challenging. Ensemble fusion calling techniques appear promising; however, current options have limited accessibility and function. ResultsMetaFusion is a flexible meta-calling tool that amalgamates outputs from any number of fusion callers. Individual caller results are standardized by conversion into the new file type Common Fusion Format (CFF). Calls are annotated, merged using graph clustering, filtered, and ranked to provide a final output of high confidence candidates. MetaFusion consistently achieves higher precision and recall than individual callers on real and simulated datasets, and reaches up to 100% precision, indicating that ensemble calling is imperative for high confidence results. MetaFusion uses FusionAnnotator to annotate calls with information from cancer fusion databases, and is provided with a benchmarking toolkit to calibrate new callers. AvailabilityMetaFusion is freely available at https://github.com/ccmbioinfo/MetaFusion Contactarun.ramani@sickkids.ca Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2020

CReSCENT: CanceR Single Cell ExpressioN Toolkit

CReSCENTCanceR Single Cell ExpressioN Toolkit (https://crescent.cloud), is an intuitive and scalable web portal incorporating a containerized pipeline execution engine for standardized analysis of single-cell RNA sequencing (scRNA-seq) data. While scRNA-seq data for tumour specimens are readily generated, subsequent analysis requires high-performance computing infrastructure and user expertise to build analysis pipelines and tailor interpretation for cancer biology. CReSCENT uses public data sets and preconfigured pipelines that are accessible to computational biology non-experts and are user-editable to allow optimization, comparison, and reanalysis for specific experiments. Users can also upload their own scRNA-seq data for analysis and results can be kept private or shared with other users.

bioinformatics↗

bioRxiv2019

Found in Transcription: Gene fusions arise through defects in RNA processing in the absence of chromosomal rearrangements.

Recent advancements in high throughput sequencing analysis have enabled the characterization of cancer-driving fusions, improving our understanding of cancer development. Most fusion calling methods, however, examine either RNA or DNA information alone and are limited to a rigid definition of what constitutes a fusion. For this study we developed a pipeline that incorporates several fusion calling methods and considers both RNA and DNA to capture a more complete representation of the tumour fusion landscape. Interestingly, most of the fusions we identified were specific to RNA, with no evidence of corresponding genomic restructuring. Further, while the average total number of fusions in tumour and normal brain tissue samples is comparable, their overall fusion profiles vary significantly. Tumours have an over-representation of fusions occurring between coding genes, whereas fusions involving intergenic or non-coding regions comprised the vast majority of those in normals. Tumours were also more abundant in unique, sample-specific fusions compared to normals, though several fusions exhibited strong recurrence in the tumour type examined (diffuse intrinsic pontine glioma; DIPG) and were absent from both normal tissues and other cancers. Intriguingly, tumours also show broad up- or down-regulation of spliceosomal gene expression, which significantly correlates with fusion number (p=0.007). Our results show that RNA-specific fusions are abundant in both tumour and normal tissue and are associated with spliceosomal gene dysregulation. RNA-specific fusions should be considered as a potential mechanism that may contribute to cancer formation initiation and maintenance alongside more traditional structural events.

genomics↗