RESUMO
The fusion index is a key indicator for quantifying the differentiation of a myoblast population, which is often calculated manually. In addition to being time-consuming, manual quantification is also error prone and subjective. Several software tools have been proposed for addressing these limitations but suffer from various drawbacks, including unintuitive interfaces and limited performance. In this study, we describe MyoFInDer, a Python-based program for the automated computation of the fusion index of skeletal muscle. At the core of MyoFInDer is a powerful artificial intelligence-based image segmentation model. MyoFInDer also determines the total nuclei count and the percentage of stained area and allows for manual verification and correction. MyoFInDer can reliably determine the fusion index, with a high correlation to manual counting. Compared with other tools, MyoFInDer stands out as it minimizes the interoperator variability, minimizes process time and displays the best correlation to manual counting. Therefore, it is a suitable choice for calculating fusion index in an automated way, and gives researchers access to the high performance and flexibility of a modern artificial intelligence model. As a free and open-source project, MyoFInDer can be modified or extended to meet specific needs.
RESUMO
Mesenchymal stem cells (MSCs) are a promising candidate for both human and veterinary regenerative medicine applications because of their abundance and ability to differentiate into several lineages. Mesenchymal stem cells are however a heterogeneous cell population and as such, it is imperative that they are unequivocally characterized to acquire reproducible results in clinical trials. Although the tri-lineage differentiation potential of MSCs is reported in most veterinary studies, a qualitative evaluation of representative histological images does not always unambiguously confirm tri-lineage differentiation. Moreover, potential differences in differentiation capacity are not identified. Therefore, quantification of tri-lineage differentiation would greatly enhance proper characterization of MSCs. In this study, a method to quantify the tri-lineage differentiation potential of MSCs is described using digital image analysis, based on the color deconvolution plug-in (ImageJ). Mesenchymal stem cells from three species, i.e., bovine, equine, and porcine, were differentiated toward adipocytes, chondrocytes, and osteocytes. Subsequently, differentiated MSCs were stained with Oil Red O, Alcian Blue, and Alizarin Red S, respectively. Next, a differentiation ratio (DR) was obtained by dividing the area % of the differentiation signal by the area % of the nuclear signal. Although MSCs isolated from all donors in all species were capable of tri-lineage differentiation, differences were demonstrated between donors using this quantitative DR. Our straightforward, simple but robust method represents an elegant approach to determine the degree of MSC tri-lineage differentiation across species. As such, differences in differentiation potential within the heterogeneous MSC population and between different MSC sources can easily be identified, which will support further optimization of regenerative therapies.
RESUMO
Lactococcus lactis is a food-grade lactic acid bacterium that is used in the dairy industry as a cell factory and as a host for recombinant protein expression. The nisin-controlled inducible expression (NICE) system is frequently applied in L. lactis; however new tools for its genetic modification are highly desirable. In this work NICE was adapted for dual protein expression. Plasmid pNZDual, that contains two nisin promoters and multiple cloning sites (MCSs), and pNZPolycist, that contains a single nisin promoter and two MCSs separated by the ribosome binding site, were constructed. Genes for the infrared fluorescent protein and for the human IgG-binding DARPin were cloned in all possible combinations to assess the protein yield. The dual promoter plasmid pNZDual enabled balanced expression of the two model proteins. It was exploited for the development of a single-plasmid inducible CRISPR-Cas9 system (pNZCRISPR) by using a nisin promoter, first to drive Cas9 expression and, secondly, to drive single guide RNA transcription. sgRNAs against htrA and ermR directed Cas9 against genomic or plasmid DNA and caused changes in bacterial growth and survival. Replacing Cas9 by dCas9 enabled CRISPR interference-mediated silencing of the upp gene. The present study introduces a new series of plasmids for advanced genetic modification of lactic acid bacterium L. lactis.