TRANSIT - A Software Tool for Himar1 TnSeq Analysis

TnSeq has become a popular technique for determining the essentiality of genomic regions in bacterial organisms. Several methods have been developed to analyze the wealth of data that has been obtained through TnSeq experiments. We developed a tool for analyzing Himar1 TnSeq data called TRANSIT. TRANSIT provides a graphical interface to three different statistical methods for analyzing TnSeq data. These methods cover a variety of approaches capable of identifying essential genes in individual datasets as well as comparative analysis between conditions. We demonstrate the utility of this software by analyzing TnSeq datasets of M. tuberculosis grown on glycerol and cholesterol. We show that TRANSIT can be used to discover genes which have been previously implicated for growth on these carbon sources. TRANSIT is written in Python, and thus can be run on Windows, OSX and Linux platforms. The source code is distributed under the GNU GPL v3 license and can be obtained from the following GitHub repository: https://github.com/mad-lab/transit

Microtubules gate tau condensation to spatially regulate microtubule functions.

Tau is an abundant microtubule-associated protein in neurons. Tau aggregation into insoluble fibrils is a hallmark of Alzheimer's disease and other types of dementia1, yet the physiological state of tau molecules within cells remains unclear. Using single-molecule imaging, we directly observe that the microtubule lattice regulates reversible tau self-association, leading to localized, dynamic condensation of tau molecules on the microtubule surface. Tau condensates form selectively permissible barriers, spatially regulating the activity of microtubule-severing enzymes and the movement of molecular motors through their boundaries. We propose that reversible self-association of tau molecules, gated by the microtubule lattice, is an important mechanism of the biological functions of tau, and that oligomerization of tau is a common property shared between the physiological and disease-associated forms of the molecule

The inner centromere is a biomolecular condensate scaffolded by the chromosomal passenger complex.

The inner centromere is a region on every mitotic chromosome that enables specific biochemical reactions that underlie properties, such as the maintenance of cohesion, the regulation of kinetochores and the assembly of specialized chromatin, that can resist microtubule pulling forces. The chromosomal passenger complex (CPC) is abundantly localized to the inner centromeres and it is unclear whether it is involved in non-kinase activities that contribute to the generation of these unique chromatin properties. We find that the borealin subunit of the CPC drives phase separation of the CPC in vitro at concentrations that are below those found on the inner centromere. We also provide strong evidence that the CPC exists in a phase-separated state at the inner centromere. CPC phase separation is required for its inner-centromere localization and function during mitosis. We suggest that the CPC combines phase separation, kinase and histone code-reading activities to enable the formation of a chromatin body with unique biochemical activities at the inner centromere

Improved long-term outcome after transient cerebral ischemia in aquaporin-4 knockout mice.

A hallmark of stroke is water accumulation (edema) resulting from dysregulation of osmotic homeostasis. Brain edema contributes to tissue demise and may lead to increased intracranial pressure and lethal herniation. Currently, there are only limited treatments to prevent edema formation following stroke. Aquaporin 4 (AQP4), a brain water channel, has become a focus of interest for therapeutic approaches targeting edema. At present, there are no pharmacological tools to block AQP4. The role of AQP4 in edema after brain injury remains unclear with conflicting results from studies using AQP4(-/-) mice and of AQP4 expression following stroke. Here, we studied AQP4 and its role in edema formation by testing AQP4(-/-) mice in a model of middle cerebral artery occlusion using novel quantitative MRI water content measurements, histology and behavioral changes as outcome measures. Absence of AQP4 was associated with decreased mortality and increased motor recovery 3 to 14 days after stroke. Behavioral improvement was associated with decreased lesion volume, neuronal cell death and neuroinflammation in AQP4(-/-) compared to wild type mice. Our data suggest that the lack of AQP4 confers an overall beneficial role at long term with improved neuronal survival and reduced neuroinflammation, but without a direct effect on edema formation

Table of results obtained from resampling, comparing replicates grown in glycerol versus cholesterol.

<p>Table of results obtained from resampling, comparing replicates grown in glycerol versus cholesterol.</p

Table of results for comparative analysis between glycerol and cholesterol.

<p>Breakdown of the number of differentially essential genes identified by the resampling method, in each condition (glycerol and cholesterol). Differentially essential genes are those with an adjusted p-value <i>q</i> < 0.05.</p><p>Table of results for comparative analysis between glycerol and cholesterol.</p

Table of HMM Results for H37Rv grown in glycerol.

<p>Distribution of state calls for the glycerol datasets obtained by the HMM method. Essential states represent those regions which are mostly devoid of insertions. Non-Essential regions contain read-counts that are close to the mean read-count in the dataset. Growth-Defect regions and Growth-Advantage regions represent those regions which have significantly suppressed or increased read-counts.</p><p>Table of HMM Results for H37Rv grown in glycerol.</p

Picture of the main TRANSIT interface.

<p>Picture of the main TRANSIT interface.</p

Hidden Markov Model Diagram.

<p>The HMM is fully connected, allowing transitions between each of the states. Transition probabilities and parameters are estimated in such a way that the HMM will remain in the state which best represents the read-counts observed. (a) Essential regions (“ES”) are mostly devoid of insertions, (c) while non-essential regions (“NE”) contain read-counts around the global mean. (b) Growth-defect regions (“GD”), and (d) growth-advantage regions (“GA”) represent those areas with significantly suppressed or inflated read-counts.</p

Track View of read counts for datasets grown in glycerol and cholesterol.

<p>This region spans approximately 12 kb, and includes 5 genes. TA dinucleotides, which are candidate insertion sites, are indicated in the middle track. Vertical height of each bar reflects # of reads or Tn insertions at each TA site. Some sites with no insertions are probably missing from the library, while others may reflect essential regions. Note that GlpK lacks insertions in the glycerol condition, indicating that it is essential when grown on glycerol.</p