Decoding early myelopoiesis from dynamics of core endogenous network

A decade ago mainstream molecular biologists regarded it impossible or biologically ill-motivated to understand the dynamics of complex biological phenomena, such as cancer genesis and progression, from a network perspective. Indeed, there are numerical difficulties even for those who were determined to explore along this direction. Undeterred, seven years ago a group of Chinese scientists started a program aiming to obtain quantitative connections between tumors and network dynamics. Many interesting results have been obtained. In this paper we wish to test such idea from a different angle: the connection between a normal biological process and the network dynamics. We have taken early myelopoiesis as our biological model. A standard roadmap for the cell-fate diversification during hematopoiesis has already been well established experimentally, yet little was known for its underpinning dynamical mechanisms. Compounding this difficulty there were additional experimental challenges, such as the seemingly conflicting hematopoietic roadmaps and the cell-fate inter-conversion events. With early myeloid cell-fate determination in mind, we constructed a core molecular endogenous network from well-documented gene regulation and signal transduction knowledge. Turning the network into a set of dynamical equations, we found computationally several structurally robust states. Those states nicely correspond to known cell phenotypes. We also found the states connecting those stable states.They reveal the developmental routes—how one stable state would most likely turn into another stable state. Such interconnected network among stable states enabled a natural organization of cell-fates into a multi-stable state landscape. Accordingly, both the myeloid cell phenotypes and the standard roadmap were explained mechanistically in a straightforward manner. Furthermore,recent challenging observations were also explained naturally. Moreover, the landscape visually enables a prediction of a pool of additional cell states and developmental routes, including the non-sequential and cross-branch transitions, which are testable by future experiments. In summary, the endogenous network dynamics provide an integrated quantitative framework to understand the heterogeneity and lineage commitment in myeloid progenitors.

Comprehensive Analysis of the Molecular Mechanism for Gastric Cancer Based on Competitive Endogenous RNA Network

Objective: To explore the regulatory mechanism of competitive endogenous RNAs(ce RNA) in gastric cancer(GC) and to predict the prognosis of GC. Materials and Methods: Expression profiles of long noncoding RNAs(lnc RNAs), micro RNAs(mi RNAs), and m RNAs were obtained from The Cancer Genome Atlas platform. Differentially expressed RNAs(DERNAs) were screened to construct a lnc RNA-mi RNA-m RNA ce RNA network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed on the ce RNA network-related differentially expressed m RNAs(DEm RNAs). Next, the DERNAs were subjected to Cox regression and survival analyses to identify crucial prognostic factors for patients with GC. Results: We detected 1029 differentially expressed lnc RNAs, 104 differentially expressed mi RNAs, and 1659 DEm RNAs in patients with GC. Next, we performed bioinformatic analysis to construct the lnc RNA-mi RNA-m RNA ce RNA network, which included 10 mi RNAs, 65 lnc RNAs, and 10 m RNAs. Subsequently, Kaplan Meier(K-M) analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group, and the area under the curve value of the receiver operating characteristic curve revealed that the polygenic model had good predictive ability. The results indicated that ADAMTS9-AS1, ATAD2, and CADM2 might be potential therapeutic targets and prognostic biomarkers for GC. Conclusions: Our study has implications for predicting prognosis and monitoring surveillance of GC and provides a new theoretical and experimental basis for the clinical prognosis of GC.

Identification of lncRNA-miRNA-mRNA networks in late-onset pre-eclampsia

Objective:Long non-coding RNAs(lncRNAs)are implicated in multiple pathophysiological processes in placenta-related disorders;however,their expression and function in late-onset pre-eclampsia(LOPE)remain unclear.This study aimed to investigate the expression of lncRNAs in LOPE,construct a competing endogenous RNA(ceRNA)network,and identify the pathways associated with LOPE pathogenesis.Methods:We performed lncRNA and mRNAs microarray profiling to identify the differential expression profiles of lncRNAs and mRNAs in LOPE compared to those in normal pregnancy.Quantitative reverse transcription polymerase chain reaction(qRT-PCR)was performed to validate differentially expressed genes.Subsequently,we generated an interaction network between lncRNAs,(micro-RNAs)miRNAs,and mRNAs based on the Pearson’s correlation coefficient between lncRNAs and mRNAs.Gene ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were performed to understand the functional significance of differentially expressed lncRNAs(DElncRNAs)in LOPE.Results:We identified 29 DElncRNAs(25 upregulated and four downregulated)and 212 differentially expressed mRNAs(DEmRNAs;203 upregulated and nine downregulated)in LOPE placentas.Within them,six lncRNAs and four mRNAs were verified by qRT-PCR.GO and KEGG analyses revealed the potential pathways affected by these mRNAs,such as positive regulation of leukocyte chemotaxis,chemokine signaling pathway,and response to hypoxia.Finally,we constructed a ceRNA network including three DElncRNAs and 124 DEmRNAs,whose competing interactions may be mediated by 17 miRNAs.Two DElncRNAs,ENST00000515376 and ENST00000520544,were found to be hub genes,as they interacted with most miRNAs and mRNAs.ENST00000515376 is most likely related to the metabolic process of arachidonic acid,whereas ENST00000520544 is more likely related to the coagulation system,such as the regulation of blood coagulation and platelet degranulation.Conclusion:Differential expression profile of lncRNAs and the lncRNA-miRNA-mRNA network in LOPE provide potential therapeutic targets for this disease.

Application of the sodium hyaluronate-CNTF scaffolds in repairing adult rat spinal cord injury and facilitating neural network formation

The present study aimed to explore the potential of the sodium hyaluronate-CNTF (ciliary neurotrophic factor) scaffold in activating endogenous neurogenesis and facilitating neural network re-formation after the adult rat spinal cord injury (SCI). After completely cutting and removing a 5-mm adult rat T8 segment, a sodium hyaluronate-CNTF scaffold was implanted into the lesion area. Dil tracing and immunofluorescence staining were used to observe the proliferation, differentiation and integration of neural stem cells (NSCs) after SCI. A planar multielectrode dish system (MED64) was used to test the electrophysiological characteristics of the regenerated neural network in the lesioned area. Electrophysiology and behavior evaluation were used to evaluate functional recovery of paraplegic rat hindlimbs. The Dil tracing and immunofluorescence results suggest that the sodium hyaluronate-CNTF scaffold could activate the NSCs originating from the spinal cord ependymal, and facilitate their migration to the lesion area and differentiation into mature neurons, which were capable of forming synaptic contact and receiving glutamatergic excitatory synaptic input. The MED64 results suggest that functional synapsis could be established among regenerated neurons as well as between regenerated neurons and the host tissue, which has been evidenced to be glutamatergic excitatory synapsis. The electrophysiology and behavior evaluation results indicate that the paraplegic rats’ sensory and motor functions were recovered in some degree. Collectively, this study may shed light on paraplegia treatment in clinics.