Biology subjects

Mukherjee, P.

Publications and source records attributed to Mukherjee, P..

5 recordsLinked to original sources

bioRxiv2018

Co-translation drives the assembly of mammalian nuclear multisubunit complexes

AO_SCPLOWBSTRACTC_SCPLOWCells dedicate significant energy to build proteins often organized in multiprotein assemblies with tightly regulated stoichiometries. As genes encoding proteins assembling in the same multisubunit complexes are dispersed in the genome of eukaryotes, it is unclear how multisubunit complexes assemble. We show that mammalian nuclear transcription complexes (TFIID, TREX-2 and SAGA) composed of a large number of subunits but lacking precise architectural details are built co-translationally. We demonstrate that the dimerization domains and their positions in the interacting subunits determine the co-translational assembly pathway (simultaneous or sequential). Our results indicate that protein translation and complex assembly are linked in building mammalian multisubunit complexes and suggest that co-translational assembly is a general principle in mammalian cells to avoid non-specific interactions and protein aggregation. These findings will significantly advance structural biology by defining endogenous co-translational building blocks in the architecture of multisubunit complexes.

molecular biology↗

bioRxiv2018

Sensory Over-Responsivity: Parent Report, Direct Assessment Measures, and Neural Architecture

BackgroundSensory processing differences are common across neurodevelopmental disorders. Thus, reliable measures are needed to understand biologic underpinnings of these differences. This study aims to define a scoring methodology specific to tactile (TOR) and auditory (AOR) over-responsivity. Second, using MRI Diffusion Tensor Imaging, we seek to determine whether children with AOR show measurable differences in their white matter integrity.\n\nMethodsThis study includes children with AOR and TOR from a mixed neurodevelopmental disorders cohort including autism and sensory processing dysfunction (n= 176) as well as neurotypical children (n= 128). We established cut-off scores for over-responsivity using the parent report: Short Sensory Profile (SSP), and the direct assessment: Sensory Processing-Three Dimensions:Assessment (SP-3D:A). Group comparisons, based on AOR phenotype, were then conducted comparing the white matter fractional anisotropy in 23 regions of interest.\n\nResultsUsing the direct assessment, 31% of the children with neurodevelopmental disorders had AOR and 27% had TOR. The Inter-test-agreement between SSP and SP-3D:A for AOR was 65% and TOR was 50%. Children with AOR had three white matter tracts showing decreased fractional anisotropy relative to children without AOR.\n\nConclusionsThis study identified cut scores for AOR and TOR using the SSP parent report and SP-3D:A observation. A combination of questionnaire and direct observation measures should be used in clinical and research settings. The SSP parent report and SP-3D:A direct observation ratings overlapped moderately for sensory related behaviors. Based on these initial structural neuroimaging results, we suggest a putative neural network may contribute to AOR.

neuroscience↗

bioRxiv2018

The Evolution of White Matter Microstructural Changes After Mild Traumatic Brain Injury: A Longitudinal DTI and NODDI Study

Neuroimaging biomarkers show promise for improving precision diagnosis and prognosis after mild traumatic brain injury (mTBI), but none has yet been adopted in routine clinical practice. Biophysical modeling of multishell diffusion MRI, using the neurite orientation dispersion and density imaging (NODDI) framework, may improve upon conventional diffusion tensor imaging (DTI) in revealing subtle patterns of underlying white matter microstructural pathology, such as diffuse axonal injury (DAI) and neuroinflammation, that are important for detecting mTBI and determining patient outcome. With a cross-sectional and longitudinal design, we assessed structural MRI, DTI and NODDI in 40 mTBI patients at 2 weeks and 6 months after injury and 14 matched control participants with orthopedic trauma but not suffering from mTBI at 2 weeks. Self-reported and performance-based cognitive measures assessing postconcussive symptoms, memory, executive functions and processing speed were investigated in post-acute and chronic phase after injury for the mTBI subjects. Machine learning analysis was used to identify mTBI patients with the best neuropsychological improvement over time and relate this outcome to DTI and NODDI biomarkers. In the cross-sectional comparison with the trauma control group at 2 weeks post-injury, mTBI patients showed decreased fractional anisotropy (FA) and increased mean diffusivity (MD) on DTI mainly in anterior tracts that corresponded to white matter regions of elevated free water fraction (FISO) on NODDI, signifying vasogenic edema. Patients showed decreases from 2 weeks to 6 months in white matter neurite density on NODDI, predominantly in posterior tracts. No significant longitudinal changes in DTI metrics were observed. The machine learning analysis divided the mTBI patients into two groups based on their recovery. Voxel-wise group comparison revealed associations between white matter orientation dispersion index (ODI) and FISO with degree and trajectory of improvement within the mTBI group. In conclusion, white matter FA and MD alterations early after mTBI might reflect vasogenic edema, as shown by elevated free water on NODDI. Longer-term declines in neurite density on NODDI suggest progressive axonal degeneration due to DAI, especially in tracts known to be integral to the structural connectome. Overall, these results show that the NODDI parameters appear to be more sensitive to longitudinal changes than DTI metrics. Thus, NODDI merits further study in larger cohorts for mTBI diagnosis, prognosis and treatment monitoring.

neuroscience↗

bioRxiv2018

A Combined Numerical and Experimental Investigation of Localized Electroporation-based Transfection and Sampling

Localized electroporation has evolved as an effective technology for the delivery of foreign molecules into adherent cells, and more recently, for the sampling of cytosolic content from a small population of cells. Unlike bulk electroporation, where the electric field is poorly controlled, localized electroporation benefits from the spatial localization of the electric field on a small areal fraction of the cell membrane, resulting in efficient molecular transport and high cell-viability. Although there have been numerous experimental reports, a mechanistic understanding of the different parameters involved in localized electroporation is lacking. In this work, we developed a multiphysics model that a) predicts the electro-pore distribution in response to the local transmembrane potential and b) calculates the molecular transport into and out of the cell based on the predicted pore-sizes. Using the model, we identify that cell membrane tension plays a crucial role in enhancing both the amount and the uniformity of molecular transport, particularly for large proteins and plasmids. We qualitatively validate the model predictions by delivering large molecules (fluorescent-tagged bovine serum albumin and mCherry encoding plasmid) and by sampling an exogeneous protein (tdTomato) in an engineered cell line. The findings presented here should inform the future design of microfluidic devices for localized electroporation based sampling, eventually paving the way for temporal, single-cell analysis.

biophysics↗

bioRxiv2018

Functional rerouting via the structural connectome is associated with better recovery after mild TBI

Traumatic brain injury damages white matter pathways that connect brain regions, disrupting transmission of electrochemical signals and causing cognitive and emotional dysfunction. Connectome-level mechanisms for how the brain compensates for injury have not been fully characterized. Here, we collected serial MRI-based structural and functional connectome metrics and neuropsychological scores in 26 mild traumatic brain injury subjects (29.4{+/-}8.0 years, 20 male) at 1 and 6 months post-injury. We quantified the relationship between functional and structural connectomes using network diffusion model propagation time, a measure that can be interpreted as how much of the structural connectome is being utilized for the spread of functional activation, as captured via the functional connectome. Overall cognition showed significant improvement from 1 to 6 months (t25=-2.15, p=0.04). None of the structural or functional global connectome metrics were significantly different between 1 and 6 months, or when compared to 34 age- and gender-matched controls (28.6{+/-}8.8 years, 25 male). We predicted longitudinal changes in overall cognition from changes in global connectome measures using a partial least squares regression model (cross-validated R2 = 0.27). We observe that increased network diffusion model propagation time, increased structural connectome segregation and increased functional connectome integration were related to better cognitive recovery. We interpret these findings as suggesting two connectome-based post-injury recovery mechanisms: one of neuroplasticity that increases functional connectome integration and one of remote white matter degeneration that increases structural connectome segregation. We hypothesize that our inherently multi-modal measure of network diffusion model propagation time captures the interplay between these two mechanisms.\n\nAbbreviationsmild traumatic brain injury (mTBI), structural connectome (SC), functional connectome (FC), network diffusion (ND), functional MRI (fMRI), diffusion MRI (dMRI), principal component analysis (PCA), partial least squares regression (PLSR), confidence interval (CI), Attention Network Test (ANT), California Verbal Learning Test II (CVLT-II), Coma Recovery Scale - Revised (CRS-R)

neuroscience↗