Biology subjects

Tripathi, S.

Publications and source records attributed to Tripathi, S..

5 recordsLinked to original sources

bioRxiv2018

Murine MPDZ-Linked Hydrocephalus is Caused by Hyperpermeability of the Choroid Plexus

Though congenital hydrocephalus is heritable, it has been linked only to eight genes, one of which is MPDZ. Humans and mice that carry a truncated version of MPDZ incur severe hydrocephalus resulting in acute morbidity and lethality. We show by magnetic resonance imaging that contrast-medium penetrates into the brain ventricles of mice carrying a Mpdz loss-of-function mutation, whereas none is detected in the ventricles of normal mice, implying that the permeability of the choroid plexus epithelial cell monolayer is abnormally high. Comparative proteomic analysis of the cerebrospinal fluid of normal and hydrocephalic mice revealed up to a 53-fold increase in protein concentration, suggesting that transcytosis through the choroid plexus epithelial cells of Mpdz KO mice is substantially higher than in normal mice. These conclusions are supported by ultrastructural evidence, and by immunohistochemistry and cytology data. Our results provide a straight-forward and concise explanation for the pathophysiology of Mpdz-linked hydrocephalus.

neuroscience↗

bioRxiv2018

Modern botanical analogue of endangered Yak (Bos mutus) dung from India: Plausible linkage with living and extinct megaherbivores

The study present to document the micro and macrobotanical remain on wild Yak dung to understand the diet, habitat, and ecology in relation to determining possible ecological relationships with extant and extinct megaherbivores. Grasses are the primary diet of the yak as indicated by the abundance of grass pollen and phytoliths, though it is obvious. The other associates non-arboreal and arboreal taxa namely, Cyperacaeae, Rosaceae, Chenopodiaceae, Artemisia, Prunus, and Rhododendron are also important dietary plants for their survival. The observation of plant macrobotanical remains especially the vegetative part and seed of the grasses and Cyperaceae also indicates good agreement with the palynodata. The documented micro and macrobotanical data is indicative of both Alpine meadow and steppe vegetation under cold and dry climate which exactly reflected the current vegetation composition and climate in the region. The recovery of Botryococcus, Arcella, and diatom was marked though in trace values and suggestive of the perennial water system in the region which incorporated through the ingestion of water. Energy dispersive spectroscopy analysis marked that the element contained in dung samples has variation in relation to the summer and winter which might be the availability of the food plants and vegetation. This generated multiproxy data serves as a strong supplementary data for modern pollen and vegetation relationship based on surface soil samples in the region. The recorded multiproxy data could be useful to interpret the coprolites of herbivorous fauna in relation to the palaeodietary and paleoecology in the region and to correlate with other mega herbivores in a global context.

paleontology↗

bioRxiv2017

A deep convolutional neural network approach for astrocyte detection

Astrocytes are involved in brain pathologies such as trauma or stroke, neurodegenerative disorders like Alzheimers and Parkinsons disease, chronic pain, and many others. Determining cell density and timing of morphological and biochemical changes is important for a proper understanding of the role of astrocytes in physiological and pathological conditions. One of the most important of such analyses is astrocytes count within a complex tissue environment in microscopy images. The most widely used approaches for the quantification of microscopy images data are either manual stereological cell counting or semi-automatic segmentation techniques. Detecting astrocytes automatically is a highly challenging computational task, for which we currently lack efficient image analysis tools. In this study, we developed a fast and fully automated software that assesses the number of astrocytes using Deep Convolutional Neural Networks (DCNN). The method highly outperforms state-of-the-art image analysis and machine learning methods and provides detection accuracy and precision comparable to that of human experts. Additionally, the runtime of cell detection is significantly less than other three analyzed computational methods, and it is faster than human observers by orders of magnitude. We applied DCNN-based method to examine the number of astrocytes in different brain regions of rats with opioid-induced hyperalgesia/tolerance (OIH/OIT) as morphine tolerance is believed to activate glial cells in the brain. We observed strong positive correlation between manual cell detection and DCNN-based analysis method for counting astrocytes in the brains of experimental animals.

bioinformatics↗

bioRxiv2017

The standard genetic code facilitates exploration of the space of functional nucleotide sequences

The standard genetic code is well known to be optimized for minimizing the phenotypic effects of single nucleotide substitutions, a property that was likely selected for during the emergence of a universal code. Given the fitness advantage afforded by high standing genetic diversity in a population in a dynamic environment, it is possible that selection to explore a large fraction of the space of functional proteins also occurred. To determine whether selection for such a property played a role during the emergence of the nearly universal genetic code, we investigated the number of functional variants of the Escherichia coli PhoQ protein explored at different time scales under translation using different genetic codes. We found that the standard genetic code is highly optimal for exploring a large fraction of the space of functional PhoQ variants at intermediate time scales as compared to random codes. Environmental changes, in response to which genetic diversity in a population provides a fitness advantage, are likely to have occurred at these intermediate time scales. Our results indicate that the ability of the standard code to explore a large fraction of the space of functional sequence variants arises from a balance between robustness and flexibility and is largely independent of the property of the standard code to minimize the phenotypic effects of mutations. We propose that selection to explore a large fraction of the functional sequence space while minimizing the phenotypic effects of mutations contributed towards the emergence of the standard code as the universal genetic code.

evolutionary biology↗

bioRxiv2017

Analysis of hierarchical organization in gene expression networks reveals underlying principles of collective tumor cell dissemination and metastatic aggressiveness of inflammatory breast cancer

BackgroundClusters of circulating tumor cells (CTCs), despite being rare, may account for more than 95% of metastases. Cells in these clusters do not undergo a complete epithelial-to-mesenchymal transition (EMT) but retain some epithelial traits as compared to individually disseminating tumor cells. Determinants of single cell dissemination versus collective dissemination remain elusive. Inflammatory breast cancer (IBC), a highly aggressive breast cancer subtype that chiefly metastasizes via CTC clusters, is a promising model for studying mechanisms of collective tumor cell dissemination. Previous studies on breast cancer and adult acute myeloid leukemia, motivated by a theory that suggests physical systems with hierarchical organization tend to be more adaptable, have found that the expression of metastasis associated genes is more hierarchically organized in cases of successful metastases.\n\nMethodsWe used the cophenetic correlation coefficient (CCC) to quantify the hierarchical organization in the expression networks of two distinct gene sets, collective dissemination associated genes and IBC associated genes, in cancer cell lines and in tumor samples from breast cancer patients. Hypothesizing that a higher CCC for collective dissemination associated genes and for IBC associated genes would be associated with a more evident epithelial phenotype and with worse outcomes in breast cancer patients, we evaluated the correlation of CCC with different phenotypic groups.\n\nResultsThe CCC of both gene networks, the collective dissemination associated gene network and the IBC associated gene network, was higher in (a) epithelial cell lines as compared to mesenchymal cell lines and (b) tumor samples from IBC patients, as compared to samples from non-IBC breast cancer patients. A higher CCC of both networks was also correlated with a higher rate of metastatic relapse in breast cancer patients. Neither the levels of CDH1 gene expression, nor gene set enrichment analysis could provide similar insights.\n\nConclusionsThese results suggest that retention of some epithelial traits in disseminating tumor cells as IBC progresses promotes successful breast cancer metastasis to distant organs. The CCC provides additional information regarding the organizational complexity of gene expression in comparison to differential gene expression analyses. We have shown that the CCC may be a useful metric for investigating the collective dissemination phenotype and a prognostic factor for IBC.

cancer biology↗