RESUMEN
Tuberculosis (TB) is a grave public health concern and is considered the foremost contributor to human mortality resulting from infectious disease. Due to the stringent clonality and extremely restricted genomic diversity, conventional methods prove inefficient for in-depth exploration of minor genomic variations and the evolutionary dynamics operating in Mycobacterium tuberculosis (M.tb) populations. Until now, the majority of reviews have primarily focused on delineating the application of whole-genome sequencing (WGS) in predicting antibiotic resistant genes, surveillance of drug resistance strains, and M.tb lineage classifications. Despite the growing use of Next Generation Sequencing (NGS) and WGS analysis in tuberculosis (TB) research, there are limited studies that provide a comprehensive summary of its role in studying macroevolution, minor genetic variations, assessing mixed TB infections, and tracking transmission networks at an individual level. This highlights the need for systematic effort to fully explore the potential of WGS and its associated tools in advancing our understanding of TB epidemiology and disease transmission. We delve into the recent bioinformatics pipelines and Next-Generation Sequencing (NGS) strategies that leverage various genetic features and simultaneous exploration of host-pathogen protein expression profile to decipher the genetic heterogeneity and host-pathogen interaction dynamics of the M.tb infections. This review highlights the potential benefits and limitations of NGS and bioinformatics tools and discusses their role in TB detection and epidemiology. Overall, this review could be a valuable resource for researchers and clinicians interested in NGS-based approaches in TB research.
RESUMEN
In vitro cell line model systems are essential in supporting the research community due to their low cost, uniform culturing conditions, homogeneous biological resources, and easy experimental design to study the cause and effect of a gene or a molecule. Human leukemia 60 (HL60) is an in-vitro hematopoietic model system that has been used for decades to study normal myeloid differentiation and leukemia biology. Here, we show that IMDM supplemented with 20% FBS is an optimal culturing condition and induces effective myeloid differentiation compared with RPMI supplemented with 10% FBS when HL60 is induced with 1α,25-dihydroxyvitamin D3 (Vit D3) and all-trans retinoic acid (ATRA). The chromatin organization is compacted, and the repressive epigenetic mark H3K27me3 is enhanced upon HL60-mediated terminal differentiation. Differential gene expression analysis obtained from RNA sequencing in HL60 cells during myeloid differentiation showed the induction of pathways involved in epigenetic regulation, myeloid differentiation, and immune regulation. Using high-throughput transcriptomic data (GSE74246), we show the similarities (genes that did not satisfy |log2FC|>1 and FDR<0.05) and differences (FDR <0.05 and |log2FC|>1) between granulocyte-monocyte progenitor vs HL60 cells, Vit D3 induced monocytes (vMono) in HL60 cells vs primary monocytes (pMono), and HL60 cells vs leukemic blasts at the transcriptomic level. We found striking similarities in biological pathways between these comparisons, suggesting that the HL60 model system can be effectively used for studying myeloid differentiation and leukemic aberrations. The differences obtained could be attributed to the fact that the cellular programs of the leukemic cell line and primary cells are different. We validated several gene expression patterns for different comparisons with CD34+ cells derived from cord blood for myeloid differentiation and AML patients. In addition to the current knowledge, our study further reveals the significance of using HL60 cells as in vitro model system under optimal conditions to understand its potential as normal myeloid differentiation model as well as leukemic model at the molecular level.
RESUMEN
Acute myeloid leukemia (AML) is a common and aggressive hematological malignancy. Acquisition of heterogeneous genetic aberrations and epigenetic dysregulation lead to the transformation of hematopoietic stem cells (HSC) into leukemic stem cells (LSC), which subsequently gives rise to immature blast cells and a leukemic phenotype. LSCs are responsible for disease relapse as current chemotherapeutic regimens are not able to completely eradicate these cellular sub-populations. Therefore, it is critical to improve upon the existing knowledge of LSC specific markers, which would allow for specific targeting of these cells more effectively allowing for their sustained eradication from the cellular milieu. Although significant milestones in decoding the aberrant transcriptional network of various cancers, including leukemia, have been achieved, studies on the involvement of post-transcriptional gene regulation (PTGR) in disease progression are beginning to unfold. RNA binding proteins (RBPs) are key players in mediating PTGR and they regulate the intracellular fate of individual transcripts, from their biogenesis to RNA metabolism, via interactions with RNA binding domains (RBDs). In this study, we have used an integrative approach to systematically profile RBP expression and identify key regulatory RBPs involved in normal myeloid development and AML. We have analyzed RNA-seq datasets (GSE74246) of HSCs, common myeloid progenitors (CMPs), granulocyte-macrophage progenitors (GMPs), monocytes, LSCs, and blasts. We observed that normal and leukemic cells can be distinguished on the basis of RBP expression, which is indicative of their ability to define cellular identity, similar to transcription factors. We identified that distinctly co-expressing modules of RBPs and their subclasses were enriched in hematopoietic stem/progenitor (HSPCs) and differentiated monocytes. We detected expression of DZIP3, an E3 ubiquitin ligase, in HSPCs, knockdown of which promotes monocytic differentiation in cell line model. We identified co-expression modules of RBP genes in LSCs and among these, distinct modules of RBP genes with high and low expression. The expression of several AML-specific RBPs were also validated by quantitative polymerase chain reaction. Network analysis identified densely connected hubs of ribosomal RBP genes (rRBPs) with low expression in LSCs, suggesting the dependency of LSCs on altered ribosome dynamics. In conclusion, our systematic analysis elucidates the RBP transcriptomic landscape in normal and malignant myelopoiesis, and highlights the functional consequences that may result from perturbation of RBP gene expression in these cellular landscapes.
