Biology subjects

Muller, H.

Publications and source records attributed to Muller, H..

4 recordsLinked to original sources

bioRxiv2018

Deep learning based retrieval system for gigapixel histopathology cases and open access literature

Clinical practice is getting increasingly stressful for pathologists due to increasing complexity and time constraints. Histopathology is slowly shifting to digital pathology, thus creating opportunities to allow pathologists to improve reading quality or save time using Artificial Intelligence (AI)-based applications. We aim to enhance the practice of pathologists through a retrieval system that allows them to simplify their workflow, limit the need for second opinions, while also learning in the process. In this work, an innovative retrieval system for digital pathology is integrated within a Whole Slide Image (WSI) viewer, allowing to define regions of interest in images as queries for finding visually similar areas using deep representations. The back-end similarity computation algorithms are based on a multimodal approach, allowing to exploit both text information and content-based image features. Shallow and deep representations of the images were evaluated, the later showed a better overall retrieval performance in a set of 112 whole slide images from biopsies. The system was also tested by pathologists, highlighting its capabilities and suggesting possible ways to improve it and make it more usable in clinical practice. The retrieval system developed can enhance the practice of pathologists by enabling them to use their experience and knowledge to properly control artificial intelligence tools for navigating repositories of images for decision support purposes.

pathology↗

bioRxiv2018

Glucocerebrosidase rescues alpha-synuclein from amyloid formation

Aggregation of the protein -synuclein (Syn) Into amyloid fibrils is associated with Parkinsons disease (PD), a process accelerated by lipids. Recently, the lysosomal protein glucocerebrosidase (GCase) has been identified as a major risk factor in both genetic and sporadic PD. Here, we use solution state NMR to reveal that GCase directly inhibits lipid induced Syn amyloidogenesis. Structurally, we show that the mechanism for this requires competition between lipids and GCase for Syn, binding the N and C termini respectively. The affinity of GCase for the C-terminus of Syn is such that not only does it inhibit lipid induced amyloid formation, but also it destabilizes mature Syn amyloid fibrils. These results reveal a competitive molecular \"tug-of-war\" for Syn termini by GCase and lipid, providing a mechanistic link between the clinically observed links between changes in GCase abundance and Parkinsons disease.

biophysics↗

bioRxiv2017

Redesigning chromosomes to optimize conformation capture (Hi-C) assays

In all chromosome conformation capture based experiments the accuracy with which contacts are detected varies considerably because of the uneven distribution of restriction sites along genomes. In addition, repeated sequences as well as homologous, large identical regions remain invisible to the assay because of the ambiguities they introduce during the alignment of the sequencing reads along the genome. As a result, the investigation of homologs during meiosis prophase through 3C studies has been limited. Here, we redesigned and reassembled in yeast a 145kb region with regularly spaced restriction sites for various enzymes. Thanks to this Syn-3C design, we enhanced the signal to noise ratio and improved the visibility of the entire region. We also improved our understanding of Hi-C data and definition of resolution. The redesigned sequence is now distinguishable from its native homologous counterpart in an isogenic diploid strain. As a proof of principle, we track the establishment of homolog pairing during meiotic prophase in a synchronized population. This provides new insights on the individualization and pairing of homologs, as well as on their internal restructuration into arrays of loops during meiosis prophase. Overall, we show the interest of redesigned genomic regions to explore complex biological questions otherwise difficult to address.

synthetic biology↗

bioRxiv2016

Choreography of budding yeast chromosomes during the cell cycle

To ensure the proper transmission of the genetic information, DNA molecules must be faithfully duplicated and segregated. These processes involve dynamic modifications of chromosomes internal structure to promote their individualization, as well as their global repositioning into daughter cells (Guacci et al., 1994; Kleckner et al., 2014; Mizuguchi et al., 2014). In eukaryotes, these events are regulated by conserved architectural proteins, such as structural maintenance of chromosomes (SMC i.e. cohesin and condensin) complexes (Aragon et al., 2013a; Uhlmann, 2016). Although the roles of these factors have been actively investigated, the genome-wide chromosomal architecture and dynamics both at small and large-scales during cell division remains elusive. Here we report a comprehensive Hi-C (Dekker et al., 2002; Lieberman-Aiden et al., 2009) analysis of the dynamic changes of chromosomes structure over the Saccharomyces cerevisiae cell cycle. We uncover specific SMC-dependent structural transitions between the different phases of the mitotic cycle. During replication, cohesion establishment promotes the increase of long-range intra-chromosomal contacts. This process correlates with the individualization of chromosomes, which culminates at metaphase. Mitotic chromosomes are then abruptly reorganized in anaphase by the mechanical forces exerted by the mitotic spindle on the centromere cluster. The formation of a condensin-dependent loop, that bridges centromere cluster with the cenproximal flanking region of the rDNA, suggests that these forces may directly facilitate nucleolus segregation. This work provides a comprehensive overview of chromosome dynamics during the cell cycle of a unicellular eukaryote that recapitulates and unveils new features of highly conserved stages of the cell division.

genetics↗