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Bagheri, H.

Publications and source records attributed to Bagheri, H..

5 recordsLinked to original sources

Deep learning-based decoding of axonal ultrastructure in gene-edited mice using electron microscopy imaging

Myelin forms an insulating sheath around axons enabling both rapid and energy-efficient conduction of action potentials and myelin abnormalities or loss can lead to severe motor, sensory, and cognitive impairment. While electron microscopy can resolve multiple axonal components that are affected myelin, their large-scale quantitative analysis is both difficult and time consuming. To overcome such limitations, we developed a machine learning framework that automatically recognizes and quantifies multiple features of axons and myelin including axonal mitochondrial density and periaxonal area. Applying that framework to fibers in the spinal cord of variably hypomyelinated mice, we show here that reduction in the thickness and length of myelin sheaths results in correlating changes in mitochondrial density and periaxonal area. The machine learning framework introduced here should contribute to future insight into the axon, myelin, and mitochondrial relationships that change during neurological plasticity and myelin disease progression.

neuroscience↗

Mustard-DB: The Database of Cellular, Molecular, and Phenotypic Data in Sulphur Mustard Exposure

1The significance of sulfur mustard as a chemical hazard cannot be overstated. Its potential for causing severe morbidity and long-term health issues makes understanding its effects crucial. Mustard-DB is an essential database that consolidates extensive cellular, molecular, and clinical data on sulfur mustard exposure. It stands as a critical tool for the scientific community, shedding light on the pathophysiological mechanisms and potential therapeutic interventions for those affected by this noxious agent. The database provides a detailed account of the acute and chronic cellular responses, and clinical outcomes associated with sulfur mustard in in vitro, ex vivo and in vivo studies. By offering a multidimensional view of the data, Mustard-DB enables a comprehensive understanding of the agents impact on human health. This manuscript presents the development, structure, and application of Mustard-DB (www.Mustard-DB.com), emphasizing its role in enhancing our response to chemical threats and improving patient outcomes.

bioinformatics↗

Plethora of QTLs found in Arabidopsis thaliana reveals complexity of genetic variation for photosynthesis in dynamic light conditions

The environments in which plant species evolved are now generally understood to be dynamic rather than static. Photosynthesis has to operate within these dynamic environments, such as sudden changes to light intensities. Plants have evolved photoprotection mechanisms that prevent damage caused by sudden changes to high light intensities. The extent of genetic variation within plants species to deal with these dynamic light conditions remains largely unexplored. Here we show that one accession of A. thaliana has a more efficient photoprotection mechanism in dynamic light conditions, compared to six other accessions. The construction of a doubled haploid population and subsequent phenotyping in a dynamically controlled high-throughput system reveals up to 15 QTLs for photoprotection. Identifying the causal gene underlying one of the major QTLs shows that an allelic variant of cpFtsY results in more efficient photoprotection under high and fluctuating light intensities. Further analyses reveal this allelic variant to be overprotecting, reducing biomass in a range of dynamic environmental conditions. This suggests that within nature, adaptation can occur to more stressful environments and that revealing the causal genes and mechanisms can help improve the general understanding of photosynthetic functioning. The other QTLs possess different photosynthetic properties, and thus together they show how there is ample intraspecific genetic variation for photosynthetic functioning in dynamic environments. With photosynthesis being one of the last unimproved components of crop yield, this amount of genetic variation for photosynthesis forms excellent input for breeding approaches. In these breeding approaches, the interactions with the environmental conditions should however be precisely assessed. Doing so correctly, allows us to tap into natures solution to challenging environmental conditions.

plant biology↗

TRANSCRIPTIONAL REGULATORS OF THE GOLLI/MYELIN BASIC PROTEIN LOCUS INTEGRATE ADDITIVE AND STEALTH ACTIVITIES

Myelin is composed of plasma membrane spirally wrapped around axons and compacted into dense sheaths by myelin associated proteins. In the central nervous system (CNS), myelin is elaborated by neuroepithelial derived oligodendrocytes and in the peripheral nervous system (PNS) by neural crest derived Schwann cells. While some myelin proteins are unique to only one lineage, myelin basic protein (Mbp) is expressed in both. Overlapping the Mbp gene is Golli, a transcriptional unit that is expressed widely both within and beyond the nervous system. A super-enhancer domain within the Golli/Mbp locus contains multiple enhancers shown previously to drive reporter construct expression specifically in oligodendrocytes or Schwann cells. In order to determine the contribution of each enhancer to the Golli/Mbp expression program and examine if interactions among these enhancers occur, we derived mouse lines in which enhancers were deleted, either singly or in different combinations, and relative mRNA accumulation was measured at key stages of development. Although super-enhancers have been shown to facilitate interaction among their component enhancers, the enhancers investigated here demonstrated functions that were largely additive. However, enhancers demonstrating autonomous activity strictly in one cell lineage, when missing, were found to significantly reduce output in the other thus revealing cryptic "stealth" activity. Further, Golli accumulation in all cell types investigated was markedly and uniformly attenuated by the absence of a key oligodendrocyte enhancer. Our observations expose a novel level of enhancer interaction and are consistent with a model in which enhancer-mediated DNA looping underlies higher-order Golli/Mbp regulatory organization. AUTHOR SUMMARYThe control of transcription is mediated through regulatory sequences that engage in a lineage and developmentally contextual manner. The Golli/Mbp locus gives rise to several mRNAs and while Mbp mRNAs accumulate exclusively in the two glial cell types that elaborate myelin, Golli mRNAs accumulate in diverse cell types both within and beyond the nervous system. To determine how the different Golli/Mbp enhancers distribute their activities and to reveal if they operate as autonomous agents or have functionally significant interactions with each other we derived multiple enhancer knock-out lines. Comparing the developmental accumulation of Mbp and Golli mRNAs revealed that the autonomous targeting capacity of multiple enhancers accurately predicted their in-situ contributions. Also, they acted in a largely additive manner indicating significant individual autonomy that can be accounted for by a simple chromatin looping model. Unexpectedly, we also uncovered cryptic "stealth" activity emanating from these same enhancers in lineages where they show no autonomous targeting capacity thus providing new insight into the control of lineage specific gene expression.

genetics↗

Shared Data Science Infrastructure for Genomics Data

BackgroundCreating a computational infrastructure to analyze the wealth of information contained in data repositories that scales well is difficult due to significant barriers in organizing, extracting and analyzing relevant data. Shared Data Science Infrastructures like Boa can be used to more efficiently process and parse data contained in large data repositories. The main features of Boa are inspired from existing languages for data intensive computing and can easily integrate data from biological data repositories.\n\nResultsHere, we present an implementation of Boa for Genomic research (BoaG) on a relatively small data repository: RefSeqs 97,716 annotation (GFF) and assembly (FASTA) files and metadata. We used BoaG to query the entire RefSeq dataset and gain insight into the RefSeq genome assemblies and gene model annotations and show that assembly quality using the same assembler varies depending on species.\n\nConclusionsIn order to keep pace with our ability to produce biological data, innovative methods are required. The Shared Data Science Infrastructure, BoaG, can provide greater access to researchers to efficiently explore data in ways previously not possible for anyone but the most well funded research groups. We demonstrate the efficiency of BoaG to explore the RefSeq database of genome assemblies and annotations to identify interesting features of gene annotation as a proof of concept for much larger datasets.

bioinformatics↗