Nuclear Proteomics of Induced Leukemia Cell Differentiation

Systems Biology for Drug Target Discovery in Acute Myeloid Leukemia

Combining new therapeutics with all-trans-retinoic acid (ATRA) could improve the efficiency of acute myeloid leukemia (AML) treatment. Modeling the process of ATRA-induced differentiation based on the transcriptomic profile of leukemic cells resulted in the identification of key targets that can be used to increase the therapeutic effect of ATRA. The genome-scale transcriptome analysis revealed the early molecular response to the ATRA treatment of HL-60 cells. In this study, we performed the transcriptomic profiling of HL-60, NB4, and K562 cells exposed to ATRA for 3-72 h. After treatment with ATRA for 3, 12, 24, and 72 h, we found 222, 391, 359, and 1032 differentially expressed genes (DEGs) in HL-60 cells, as well as 641, 1037, 1011, and 1499 DEGs in NB4 cells. We also found 538 and 119 DEGs in K562 cells treated with ATRA for 24 h and 72 h, respectively. Based on experimental transcriptomic data, we performed hierarchical modeling and determined cyclin-dependent kinase 6 (CDK6), tumor necrosis factor alpha (TNF-alpha), and transcriptional repressor CUX1 as the key regulators of the molecular response to the ATRA treatment in HL-60, NB4, and K562 cell lines, respectively. Mapping the data of TMT-based mass-spectrometric profiling on the modeling schemes, we determined CDK6 expression at the proteome level and its down-regulation at the transcriptome and proteome levels in cells treated with ATRA for 72 h. The combination of therapy with a CDK6 inhibitor (palbociclib) and ATRA (tretinoin) could be an alternative approach for the treatment of acute myeloid leukemia (AML).

Integrated transcriptomic and proteomic analyses uncover the early response mechanisms of Catharanthus roseus under ultraviolet-B radiation

Catharanthus roseus produces a large array of terpenoid indole alkaloids (TIAs) that are important natural source for many drugs. Ultraviolet B (UVB) radiation have been proved to have regulatory effect towards biosynthesis of TIAs, which were meaningful for boost of TIA production. To decipher more comprehensive molecular characteristics in C. roseus under UVB radiation, integrated analysis of the nuclear proteome together with the transcriptome data under UVB radiation were performed. Expression of genes related to transmembrane transporters gradually increased during the prolonged exposure to UVB radiation. Some of known TIA transporters were affected by UVB. Abundance of proteins associated with spliceosome and nucleocytoplasmic transport increased. Homologs belonging to ORCA and CrWRKY transcription factors family increased at both transcriptomic and proteomic levels. At the same time, the numbers of differential alternative splicing events between UVB-radiated and white-light-treated plants continuously increased. These results suggest that the nucleus participated in early response of C. roseus under UVB radiation, where alternative splicing events occurred and might regulate multiple pathways. Furthermore, integrative omics analysis indicates that expression of enzymes at the terminal stages of seco-iridoid pathway decreased with the prolonged radiation exposure, potentially inhibiting further rise of TIA synthesis under extended UVB exposure.

Proteomic Approach to Investigating Expression, Localization, and Functions of the SOWAHD Gene Protein Product during Granulocytic Differentiation

Cataloging human proteins and evaluation of their expression, cellular localization, functions, and potential medical significance are important tasks for the global proteomic community. At present, localization and functions of protein products for almost half of protein-coding genes remain unknown or poorly understood. Investigation of organelle proteomes is a promising approach to uncovering localization and functions of human proteins. Nuclear proteome is of particular interest because many nuclear proteins, e.g., transcription factors, regulate functions that determine cell fate. Meta-analysis of the nuclear proteome, or nucleome, of HL-60 cells treated with all-trans-retinoic acid (ATRA) has shown that the functions and localization of a protein product of the SOWAHD gene are poorly understood. Also, there is no comprehensive information on the SOWAHD gene expression at the protein level. In HL-60 cells, the number of mRNA transcripts of the SOWAHD gene was determined as 6.4 ± 0.7 transcripts per million molecules. Using targeted mass spectrometry, the content of the SOWAHD protein was measured as 0.27 to 1.25 fmol/μg total protein. The half-life for the protein product of the SOWAHD gene determined using stable isotope pulse-chase labeling was ~19 h. Proteomic profiling of the nuclear fraction of HL-60 cells showed that the content of the SOWAHD protein increased during the ATRA-induced granulocytic differentiation, reached the peak value at 9 h after ATRA addition, and then decreased. Nuclear location and involvement of the SOWAHD protein in the ATRA-induced granulocytic differentiation have been demonstrated for the first time.

Quality Control of Human Pluripotent Stem Cell Colonies by Computational Image Analysis Using Convolutional Neural Networks

Human pluripotent stem cells are promising for a wide range of research and therapeutic purposes. Their maintenance in culture requires the deep control of their pluripotent and clonal status. A non-invasive method for such control involves day-to-day observation of the morphological changes, along with imaging colonies, with the subsequent automatic assessment of colony phenotype using image analysis by machine learning methods. We developed a classifier using a convolutional neural network and applied it to discriminate between images of human embryonic stem cell (hESC) colonies with "good" and "bad" morphological phenotypes associated with a high and low potential for pluripotency and clonality maintenance, respectively. The training dataset included the phase-contrast images of hESC line H9, in which the morphological phenotype of each colony was assessed through visual analysis. The classifier showed a high level of accuracy (89%) in phenotype prediction. By training the classifier on cropped images of various sizes, we showed that the spatial scale of ~144 μm was the most informative in terms of classification quality, which was an intermediate size between the characteristic diameters of a single cell (~15 μm) and the entire colony (~540 μm). We additionally performed a proteomic analysis of several H9 cell samples used in the computational analysis and showed that cells of different phenotypes differentiated at the molecular level. Our results indicated that the proposed approach could be used as an effective method of non-invasive automated analysis to identify undesirable developmental anomalies during the propagation of pluripotent stem cells.