Mesenchymal stromal cells: misconceptions and evolving concepts

Nearly half a century has passed since the publication of the first articles describing plastic-adherent cells from bone marrow, referred to initially as colony-forming unit fibroblasts, then marrow stromal cells, mesenchymal stem cells and most recently multipotent mesenchymal stromal cells (MSCs). As expected, our understanding of the nature and biologic functions of MSCs has undergone major paradigm shifts over this time. Despite significant advances made in deciphering their complex biology and therapeutic potential in both experimental animal models and human clinical trials, numerous misconceptions regarding the nature and function of MSCs have persisted in the field. Continued propagation of these misconceptions in some cases may significantly impede the advancement of MSC-based therapies in clinical medicine. We have identified six prevalent misconceptions about MSCs that we believe affect the field, and we attempt to rectify them based on current available data.     

ABRF-PRG07: Advanced Quantitative Proteomics Study

A major challenge for core facilities is determining quantitative protein differences across complex biological samples. Although there are numerous techniques in the literature for relative and absolute protein quantification, the majority is nonroutine and can be challenging to carry out effectively. There are few studies comparing these technologies in terms of their reproducibility, accuracy, and precision, and no studies to date deal with performance across multiple laboratories with varied levels of expertise. Here, we describe an Association of Biomolecular Resource Facilities (ABRF) Proteomics Research Group (PRG) study based on samples composed of a complex protein mixture into which 12 known proteins were added at varying but defined ratios. All of the proteins were present at the same concentration in each of three tubes that were provided. The primary goal of this study was to allow each laboratory to evaluate its capabilities and approaches with regard to: detection and identification of proteins spiked into samples that also contain complex mixtures of background proteins and determination of relative quantities of the spiked proteins. The results returned by 43 participants were compiled by the PRG, which also collected information about the strategies used to assess overall performance and as an aid to development of optimized protocols for the methodologies used. The most accurate results were generally reported by the most experienced laboratories. Among laboratories that used the same technique, values that were closer to the expected ratio were obtained by more experienced groups.     

Model based dynamics analysis in live cell microtubule images

Background

The dynamic growing and shortening behaviors of microtubules are central to the fundamental roles played by microtubules in essentially all eukaryotic cells. Traditionally, microtubule behavior is quantified by manually tracking individual microtubules in time-lapse images under various experimental conditions. Manual analysis is laborious, approximate, and often offers limited analytical capability in extracting potentially valuable information from the data.

Results

In this work, we present computer vision and machine-learning based methods for extracting novel dynamics information from time-lapse images. Using actual microtubule data, we estimate statistical models of microtubule behavior that are highly effective in identifying common and distinct characteristics of microtubule dynamic behavior.

Conclusion

Computational methods provide powerful analytical capabilities in addition to traditional analysis methods for studying microtubule dynamic behavior. Novel capabilities, such as building and querying microtubule image databases, are introduced to quantify and analyze microtubule dynamic behavior.

     

The Association of Biomolecular Resource Facilities Proteomics Research Group 2006 study: relative protein quantitation

The determination of differences in relative protein abundance is a critical aspect of proteomics research that is increasingly used to answer diverse biological questions. The Association of Biomolecular Resource Facilities Proteomics Research Group 2006 study was a quantitative proteomics project in which the aim was to determine the identity and the relative amounts of eight proteins in two mixtures. There are numerous methodologies available to study the relative abundance of proteins between samples, but to date, there are few examples of studies that have compared these different approaches. For the 2006 Proteomics Research Group study, there were 52 participants who used a wide variety of gel electrophoresis-, HPLC-, and mass spectrometry-based methods for relative quantitation. The quantitative data arising from this study were evaluated along with several other experimental details relevant to the methodologies used.     

Extracellular glycosylphosphatidylinositol-anchored mannoproteins and proteases of Cryptococcus neoformans

Extracellular proteins of Cryptococcus neoformans are involved in the pathogenesis of cryptococcosis, and some are immunoreactive antigens that may potentially serve as candidates for vaccine development. To further study the extracellular proteome of the human fungal pathogen Cry. neoformans, we conducted a proteomic analysis of secreted and cell wall-bound proteins with an acapsular strain of Cry. neoformans. Proteins were identified from both intact cells and cell walls. In both cases, extracellular proteins were removed with trypsin or beta-glucanase, and then all proteins/peptides were purified by solid-phase extraction, spin dialysis, and HPLC, and identified by liquid chromatography-mass spectrometry. This study identified 29 extracellular proteins with a predicted N-terminal signal sequence and also a predicted glycosylphosphatidylinositol anchor motif in more than half. Among the novel proteins identified were five glycosylphosphatidylinositol-anchored proteins with extensive Ser/Thr-rich regions but no apparent functional domains, a glycosylphosphatidylinositol-anchored aspartic protease, and a metalloprotease with structural similarity to an elastinolytic metalloprotease of Aspergillus fumigatus. This study suggests that Cry. neoformans has the machinery required to target glycosylphosphatidylinositol-anchored proteins to the cell wall, and it confirms the extracellular proteolytic ability of Cry. neoformans.     

Donor variation in the growth properties and osteogenic potential of human marrow stromal cells.

Human marrow stromal cells (MSCs) were isolated from posterior illiac crest marrow aspirates obtained from 17 healthy donors, ages 19-45 years, with no apparent physical disability. First passage hMSCs exhibited growth rates in vitro that varied up to 12-fold between donors. No correlation between growth rate and the age or gender of the donor was evident (P 相似文献   

Internode length in Zea mays L.

[¹³C, ³H]Gibberellin A₂₀ (GA₂₀) has been fed to seedlings of normal (tall) and dwarf-5 and dwarf-1 mutants of maize (Zea mays L.). The metabolites from these feeds were identified by combined gas chromatography-mass spectrometry. [¹³C, ³H]Gibberellin A₂₀ was metabolized to [¹³C, ³H]GA₂₉-catabolite and [¹³C, ³H]GA₁ by the normal, and to [¹³C, ³H]GA₂₉ and [¹³C, ³H]GA₁ by the dwarf-5 mutant. In the dwarf-1 mutant, [¹³C, ³H]GA₂₀ was metabolized to [¹³C, ³H]GA₂₉ and [¹³C, ³H]GA₂₉-catabolite; no evidence was found for the metabolism of [¹³C, ³H]GA₂₀ to [¹³C, ³H]GA₁. [¹³C, ³H]Gibberellin A₈ was not found in any of the feeds. In all feeds no dilution of ¹³C in recovered [¹³C, ³H]GA₂₀ was observed. Also in the dwarf-5 mutant, the [¹³C]label in the metabolites was apparently undiluted by endogenous [¹³C]GAs. However, dilution of the [¹³C]label in metabolites from [¹³C, ³H]GA₂₀ was observed in normal and dwarf-1 seedlings. The results from the feeding studies provide evidence that the dwarf-1 mutation of maize blocks the conversion of GA₂₀ to GA₁.Abbreviations GA_n gibberellin A_n - GC-MS combined gas chromatography-mass spectrometry - HPLC high-performance liquid chromatography - RP reverse phase