In this article, we hear from Dr. Dennis Nurjadi, Head of Molecular Bacteriology at the University Hospital Heidelberg, about his team’s work on Staphylococcus aureus and the importance of understanding its mechanisms in order to develop novel strategies to decolonize high-risk patients and prevent S. aureus infections. Here, Nurjadi explains the current challenges labs face when quantifying bacteria and how Logos Biosystems’ QUANTOM Tx addresses these issues by producing reliable, accurate, and reproducible quantifications.
Macrogen, Inc. is a leading expert in genomic analysis, proactively seeking to improve the fields of genetic and genomic analyses through research and development. To further this mission, Macrogen is working to identify the causal genes for rare diseases with a view to building a big data system that brings together patient genomic and medical data. Using this integrated database, the team aims to help predict disease onset and prognosis, and innovate personalized medicines at an individual level.
Single-cell multi-omics analysis takes multiple measures from the same individual cell, which provides a more comprehensive picture of cellular diversity and heterogeneity than traditional methods. This approach can also be applied to uncover the molecular mechanisms underlying disease-related processes and reveal new diagnostic markers and therapeutic targets.
We use many different kinds of models for studying spinal cord injury. We have projects that look at the mechanism of locomotion and how to restore this mechanism after an injury. The X-CLARITY system helps us understand how the network reorganizes after injury. The X-CLARITY allows you to visualize and follow the course of an axon coming from the motor cortex, coming down to the lumbar spinal cord. You can visualize, in 3D, the course of single or several axons when they go around the lesion for example. This is extremely useful for our work, to see how a network gets reorganized after an injury.
I work mainly on ischemia-reperfusion syndrome. Because we work at a hospital, our main aim is to understand the pathology and then find new targets to help heal patients subjected to this syndrome. What we want to understand is what is happening in the cells – in all cardiac cells – that could lead to failure at the organ level. We’ve got to be able to label and report the expression in the organ. Thanks to X-CLARITY, we now have access to the three dimensions of the whole heart organ.
[The X-CLARITY] has actually been fundamental to the Data Brain Project because without being able to clear tissues of the lipids, we wouldn’t be able to image deep into brains. So we wouldn’t be able to extract that structural information that is so important to understand the function of mammalian brains. It’s been a huge advantage and a great leap forward in imaging.
