Oligoclonal expansion of TCR <Emphasis Type="Italic">V</Emphasis>δ T cells may be a potential immune biomarker for clinical outcome of acute myeloid leukemia

Background

Recent data have shown that γδ T cells can act as mediators for immune defense against tumors. Our previous study has demonstrated that persisting clonally expanded TRDV4 T cells might be relatively beneficial for the outcome of patients with T cell acute lymphoblastic leukemia after hematopoietic stem cell transplantation (HSCT). However, little is known about the distribution and clonality of the TRDV repertoire in T cell receptor (TCR) of γδ T cells and their effects on the clinical outcome of patients with acute myeloid leukemia (AML). The aim of this study was to assess whether the oligoclonal expansion of TCR Vδ T cells could be used as an immune biomarker for AML outcome.

Findings

γδ T cells were sorted from the peripheral blood of 30 patients with untreated AML and 12 healthy donors. The complementarity-determining region 3 (CDR3) sizes of eight TCR Vδ subfamily genes (TRDV1 to TRDV8) were analyzed in sorted γδ T cells using RT-PCR and GeneScan. The most frequently expressed TRDV subfamilies in the AML patients were TRDV8 (86.67 %) and TRDV2 (83.33 %), and the frequencies for TRDV1, TRDV3, TRDV4, and TRDV6 were significantly lower than those in healthy individuals. The most frequent clonally expanded TRDV subfamilies in the AML patients included TRDV8 (56.67 %) and TRDV4 (40 %). The clonal expansion frequencies of the TRDV2 and TRDV4 T cells were significantly higher than those in healthy individuals, whereas a significantly lower TRDV1 clonal expansion frequency was observed in those with AML. Moreover, the oligoclones of TRDV4 and TRDV8 were independent protective factors for complete remission. Furthermore, the oligoclonal expansion frequencies of TRDV5 and TRDV6 in patients with relapse were significantly higher than those in non-recurrent cases.

Conclusions

To the best of our knowledge, we characterized for the first time a significant alteration in the distribution and clonality of the TRDV subfamily members in γδ T cells sorted from AML patients. Clonally expanded TRDV4 and TRDV8 T cells might contribute to the immune response directed against AML, while oligoclonal TRDV5 and TRDV6 might occur in patients who undergo relapse. While the function of such γδ T cell clones requires further investigation, TRDV γδ T cell clones might be potential immune biomarkers for AML outcome.

     

Tyrosine phosphorylation of QKI mediates developmental signals to regulate mRNA metabolism

The selective RNA-binding protein QKI is essential for myelination in the central nervous system (CNS). QKI belongs to the family of signal transduction activators of RNA (STARs), characteristic of binding RNA and signaling molecules, therefore is postulated to regulate RNA homeostasis in response to developmental signals. Here we report that QKI acts downstream of the Src family protein tyrosine kinases (Src-PTKs) during CNS myelination. QKI selectively interacted with the mRNA encoding the myelin basic protein (MBP). Such interaction stabilized MBP mRNA and was required for the rapid accumulation of MBP mRNA during active myelinogenesis. We found that the interaction between QKI and MBP mRNA was negatively regulated by Src-PTK-dependent phosphorylation of QKI. During early myelin development, tyrosine phosphorylation of QKI in the developing myelin drastically declined, presumably leading to enhanced interactions between QKI and MBP mRNA, which was associated with the rapid accumulation of MBP mRNA and accelerated myelin production. Therefore, developmental regulation of Src-PTK-dependent tyrosine phosphorylation of QKI suggests a novel mechanism for accelerating CNS myelinogenesis via regulating mRNA metabolism.     

Secondary structure of cell‐penetrating peptides during interaction with fungal cells

Cell‐penetrating peptides (CPPs) are peptides that cross cell membranes, either alone or while carrying molecular cargo. Although their interactions with mammalian cells have been widely studied, much less is known about their interactions with fungal cells, particularly at the biophysical level. We analyzed the interactions of seven CPPs (penetratin, Pep‐1, MPG, pVEC, TP‐10, MAP, and cecropin B) with the fungal pathogen Candida albicans using experiments and molecular simulations. Circular dichroism (CD) of the peptides revealed a structural transition from a random coil or weak helix to an α‐helix occurs for all peptides when the solvent is changed from aqueous to hydrophobic. However, CD performed in the presence of C. albicans cells showed that proximity to the cell membrane is not necessarily sufficient to induce this structural transition, as penetratin, Pep‐1, and MPG did not display a structural shift in the presence of cells. Monte Carlo simulations were performed to further probe the molecular‐level interaction with the cell membrane, and these simulations suggested that pVEC, TP‐10, MAP, and cecropin B strongly penetrate into the hydrophobic domain of the membrane lipid bilayer, inducing a transition to an α‐helical conformation. In contrast, penetratin, Pep‐1 and MPG remained in the hydrophilic region without a shift in conformation. The experimental data and MC simulations combine to explain how peptide structure affects their interaction with cells and their mechanism of translocation into cells (direct translocation vs. endocytosis). Our work also highlights the utility of combining biophysical experiments, biological experiments, and molecular modeling to understand biological phenomena.     

A rational design of completely random shRNA library

It has been well established that the shRNA library has a significant advantage for screening the important genes involved in the interested biological pathways. Currently, the available libraries mainly target the known protein genes in human and mouse. With the expanding roles of lncRNA in biology, there is a great demand to design shRNAs targeting these non-coding RNAs. In this regard, a completely random shRNA library targeting all the genes with known or unknown sequences is of priority. Here we provide a practical workflow for construction of such a random shRNA library. In the novel shRNA library, there are about tens of different shRNAs targeting one gene, and thus significantly avoids the off-target effects.