MicroRNAs in Leukemias: A Clinically Annotated Compendium

Leukemias are a group of malignancies of the blood and bone marrow. Multiple types of leukemia are known, however reliable treatments have not been developed for most leukemia types. Furthermore, even relatively reliable treatments can result in relapses. MicroRNAs (miRNAs) are a class of short, noncoding RNAs responsible for epigenetic regulation of gene expression and have been proposed as a source of potential novel therapeutic targets for leukemias. In order to identify central miRNAs for leukemia, we conducted data synthesis using two databases: miRTarBase and DISNOR. A total of 137 unique miRNAs associated with 16 types of leukemia were retrieved from miRTarBase and 86 protein-coding genes associated with leukemia were retrieved from the DISNOR database. Based on these data, we formed a visual network of 248 miRNA-target interactions (MTI) between leukemia-associated genes and miRNAs associated with ≥4 leukemia types. We then manually reviewed the literature describing these 248 MTIs for interactions identified in leukemia studies. This manually curated data was then used to visualize a network of 64 MTIs identified in leukemia patients, cell lines and animal models. We also formed a visual network of miRNA-leukemia associations. Finally, we compiled leukemia clinical trials from the ClinicalTrials database. miRNAs with the highest number of MTIs were miR-125b-5p, miR-155-5p, miR-181a-5p and miR-19a-3p, while target genes with the highest number of MTIs were TP53, BCL2, KIT, ATM, RUNX1 and ABL1. The analysis of 248 MTIs revealed a large, highly interconnected network. Additionally, a large MTI subnetwork was present in the network visualized from manually reviewed data. The interconnectedness of the MTI subnetwork suggests that certain miRNAs represent central disease molecules for multiple leukemia types. Additional studies on miRNAs, their target genes and associated biological pathways are required to elucidate the therapeutic potential of miRNAs in leukemia.     

mPR-Specific Actions Influence Maintenance of the Blood–Brain Barrier (BBB)

Cerebral cavernous malformations (CCMs) are characterized by abnormally dilated intracranial microvascular sinusoids that result in increased susceptibility to hemorrhagic stroke. It has been demonstrated that three CCM proteins (CCM1, CCM2, and CCM3) form the CCM signaling complex (CSC) to mediate angiogenic signaling. Disruption of the CSC will result in hemorrhagic CCMs, a consequence of compromised blood–brain barrier (BBB) integrity. Due to their characteristically incomplete penetrance, the majority of CCM mutation carriers (presumed CCM patients) are largely asymptomatic, but when symptoms occur, the disease has typically reached a clinical stage of focal hemorrhage with irreversible brain damage. We recently reported that the CSC couples both classic (nuclear; nPRs) and nonclassic (membrane; mPRs) progesterone (PRG)-receptors-mediated signaling within the CSC-mPRs-PRG (CmP) signaling network in nPR(−) breast cancer cells. In this report, we demonstrate that depletion of any of the three CCM genes or treatment with mPR-specific PRG actions (PRG/mifepristone) results in the disruption of the CmP signaling network, leading to increased permeability in the nPR(−) endothelial cells (ECs) monolayer in vitro. Finally, utilizing our in vivo hemizygous Ccm mutant mice models, we demonstrate that depletion of any of the three CCM genes, in combination with mPR-specific PRG actions, is also capable of leading to defective homeostasis of PRG in vivo and subsequent BBB disruption, allowing us to identify a specific panel of etiological blood biomarkers associated with BBB disruption. To our knowledge, this is the first report detailing the etiology to predict the occurrence of a disrupted BBB, an indication of early hemorrhagic events.     

Transcriptome Profiling of the Dorsomedial Prefrontal Cortex in Suicide Victims

The default mode network (DMN) plays an outstanding role in psychiatric disorders. Still, gene expressional changes in its major component, the dorsomedial prefrontal cortex (DMPFC), have not been characterized. We used RNA sequencing in postmortem DMPFC samples to investigate suicide victims compared to control subjects. 1400 genes differed using log2FC > ±1 and adjusted p-value < 0.05 criteria between groups. Genes associated with depressive disorder, schizophrenia and impaired cognition were strongly overexpressed in top differentially expressed genes. Protein–protein interaction and co-expressional networks coupled with gene set enrichment analysis revealed that pathways related to cytokine receptor signaling were enriched in downregulated, while glutamatergic synaptic signaling upregulated genes in suicidal individuals. A validated differentially expressed gene, which is known to be associated with mGluR5, was the N-terminal EF-hand calcium-binding protein 2 (NECAB2). In situ hybridization histochemistry and immunohistochemistry proved that NECAB2 is expressed in two different types of inhibitory neurons located in layers II-IV and VI, respectively. Our results imply extensive gene expressional alterations in the DMPFC related to suicidal behavior. Some of these genes may contribute to the altered mental state and behavior of suicide victims.     

Function Prediction and Analysis of Mycobacterium tuberculosis Hypothetical Proteins

High-throughput biology technologies have yielded complete genome sequences and functional genomics data for several organisms, including crucial microbial pathogens of humans, animals and plants. However, up to 50% of genes within a genome are often labeled "unknown", "uncharacterized" or "hypothetical", limiting our understanding of virulence and pathogenicity of these organisms. Even though biological functions of proteins encoded by these genes are not known, many of them have been predicted to be involved in key processes in these organisms. In particular, for Mycobacterium tuberculosis, some of these "hypothetical" proteins, for example those belonging to the Pro-Glu or Pro-Pro-Glu (PE/PPE) family, have been suspected to play a crucial role in the intracellular lifestyle of this pathogen, and may contribute to its survival in different environments. We have generated a functional interaction network for Mycobacterium tuberculosis proteins and used this to predict functions for many of its hypothetical proteins. Here we performed functional enrichment analysis of these proteins based on their predicted biological functions to identify annotations that are statistically relevant, and analysed and compared network properties of hypothetical proteins to the known proteins. From the statistically significant annotations and network information, we have tried to derive biologically meaningful annotations related to infection and disease. This quantitative analysis provides an overview of the functional contributions of Mycobacterium tuberculosis "hypothetical" proteins to many basic cellular functions, including its adaptability in the host system and its ability to evade the host immune response.     

Fusarium graminearum Infection Strategy in Wheat Involves a Highly Conserved Genetic Program That Controls the Expression of a Core Effectome

Fusarium graminearum, the main causal agent of Fusarium Head Blight (FHB), is one of the most damaging pathogens in wheat. Because of the complex organization of wheat resistance to FHB, this pathosystem represents a relevant model to elucidate the molecular mechanisms underlying plant susceptibility and to identify their main drivers, the pathogen’s effectors. Although the F. graminearum catalog of effectors has been well characterized at the genome scale, in planta studies are needed to confirm their effective accumulation in host tissues and to identify their role during the infection process. Taking advantage of the genetic variability from both species, a RNAseq-based profiling of gene expression was performed during an infection time course using an aggressive F. graminearum strain facing five wheat cultivars of contrasting susceptibility as well as using three strains of contrasting aggressiveness infecting a single susceptible host. Genes coding for secreted proteins and exhibiting significant expression changes along infection progress were selected to identify the effector gene candidates. During its interaction with the five wheat cultivars, 476 effector genes were expressed by the aggressive strain, among which 91% were found in all the infected hosts. Considering three different strains infecting a single susceptible host, 761 effector genes were identified, among which 90% were systematically expressed in the three strains. We revealed a robust F. graminearum core effectome of 357 genes expressed in all the hosts and by all the strains that exhibited conserved expression patterns over time. Several wheat compartments were predicted to be targeted by these putative effectors including apoplast, nucleus, chloroplast and mitochondria. Taken together, our results shed light on a highly conserved parasite strategy. They led to the identification of reliable key fungal genes putatively involved in wheat susceptibility to F. graminearum, and provided valuable information about their putative targets.     

A Cautionary Note on the Use of Split-YFP/BiFC in Plant Protein-Protein Interaction Studies

Since its introduction in plants 10 years ago, the bimolecular fluorescence complementation (BiFC) method, or split-YFP (yellow fluorescent protein), has gained popularity within the plant biology field as a method to study protein-protein interactions. BiFC is based on the restoration of fluorescence after the two non-fluorescent halves of a fluorescent protein are brought together by a protein-protein interaction event. The major drawback of BiFC is that the fluorescent protein halves are prone to self-assembly independent of a protein-protein interaction event. To circumvent this problem, several modifications of the technique have been suggested, but these modifications have not lead to improvements in plant BiFC protocols. Therefore, it remains crucial to include appropriate internal controls. Our literature survey of recent BiFC studies in plants shows that most studies use inappropriate controls, and a qualitative rather than quantitative read-out of fluorescence. Therefore, we provide a cautionary note and beginner’s guideline for the setup of BiFC experiments, discussing each step of the protocol, including vector choice, plant expression systems, negative controls, and signal detection. In addition, we present our experience with BiFC with respect to self-assembly, peptide linkers, and incubation temperature. With this note, we aim to provide a guideline that will improve the quality of plant BiFC experiments.     

SNPs in 3′UTR miRNA Target Sequences Associated with Individual Drug Susceptibility

The complementary interaction of microRNAs (miRNAs) with their binding sites in the 3′untranslated regions (3′UTRs) of target gene mRNAs represses translation, playing a leading role in gene expression control. MiRNA recognition elements (MREs) in the 3′UTRs of genes often contain single nucleotide polymorphisms (SNPs), which can change the binding affinity for target miRNAs leading to dysregulated gene expression. Accumulated data suggest that these SNPs can be associated with various human pathologies (cancer, diabetes, neuropsychiatric disorders, and cardiovascular diseases) by disturbing the interaction of miRNAs with their MREs located in mRNA 3′UTRs. Numerous data show the role of SNPs in 3′UTR MREs in individual drug susceptibility and drug resistance mechanisms. In this review, we brief the data on such SNPs focusing on the most rigorously proven cases. Some SNPs belong to conventional genes from the drug-metabolizing system (in particular, the genes coding for cytochromes P450 (CYP 450), phase II enzymes (SULT1A1 and UGT1A), and ABCB3 transporter and their expression regulators (PXR and GATA4)). Other examples of SNPs are related to the genes involved in DNA repair, RNA editing, and specific drug metabolisms. We discuss the gene-by-gene studies and genome-wide approaches utilized or potentially utilizable to detect the MRE SNPs associated with individual response to drugs.     

CFH Loss in Human RPE Cells Leads to Inflammation and Complement System Dysregulation via the NF-κB Pathway

Age-related macular degeneration (AMD), the leading cause of vision loss in the elderly, is a degenerative disease of the macula, where retinal pigment epithelium (RPE) cells are damaged in the early stages of the disease, and chronic inflammatory processes may be involved. Besides aging and lifestyle factors as drivers of AMD, a strong genetic association to AMD is found in genes of the complement system, with a single polymorphism in the complement factor H gene (CFH), accounting for the majority of AMD risk. However, the exact mechanism of CFH dysregulation confers such a great risk for AMD and its role in RPE cell homeostasis is unclear. To explore the role of endogenous CFH locally in RPE cells, we silenced CFH in human hTERT-RPE1 cells. We demonstrate that endogenously expressed CFH in RPE cells modulates inflammatory cytokine production and complement regulation, independent of external complement sources, or stressors. We show that loss of the factor H protein (FH) results in increased levels of inflammatory mediators (e.g., IL-6, IL-8, GM-CSF) and altered levels of complement proteins (e.g., C3, CFB upregulation, and C5 downregulation) that are known to play a role in AMD. Moreover, our results identify the NF-κB pathway as the major pathway involved in regulating these inflammatory and complement factors. Our findings suggest that in RPE cells, FH and the NF-κB pathway work in synergy to maintain inflammatory and complement balance, and in case either one of them is dysregulated, the RPE microenvironment changes towards a proinflammatory AMD-like phenotype.     

Inferring Time-Lagged Causality Using the Derivative of Single-Cell Expression

Many computational methods have been developed to infer causality among genes using cross-sectional gene expression data, such as single-cell RNA sequencing (scRNA-seq) data. However, due to the limitations of scRNA-seq technologies, time-lagged causal relationships may be missed by existing methods. In this work, we propose a method, called causal inference with time-lagged information (CITL), to infer time-lagged causal relationships from scRNA-seq data by assessing the conditional independence between the changing and current expression levels of genes. CITL estimates the changing expression levels of genes by “RNA velocity”. We demonstrate the accuracy and stability of CITL for inferring time-lagged causality on simulation data against other leading approaches. We have applied CITL to real scRNA data and inferred 878 pairs of time-lagged causal relationships. Furthermore, we showed that the number of regulatory relationships identified by CITL was significantly more than that expected by chance. We provide an R package and a command-line tool of CITL for different usage scenarios.     

Identifying Drug Targets of Oral Squamous Cell Carcinoma through a Systems Biology Method and Genome-Wide Microarray Data for Drug Discovery by Deep Learning and Drug Design Specifications

In this study, we provide a systems biology method to investigate the carcinogenic mechanism of oral squamous cell carcinoma (OSCC) in order to identify some important biomarkers as drug targets. Further, a systematic drug discovery method with a deep neural network (DNN)-based drug–target interaction (DTI) model and drug design specifications is proposed to design a potential multiple-molecule drug for the medical treatment of OSCC before clinical trials. First, we use big database mining to construct the candidate genome-wide genetic and epigenetic network (GWGEN) including a protein–protein interaction network (PPIN) and a gene regulatory network (GRN) for OSCC and non-OSCC. In the next step, real GWGENs are identified for OSCC and non-OSCC by system identification and system order detection methods based on the OSCC and non-OSCC microarray data, respectively. Then, the principal network projection (PNP) method was used to extract core GWGENs of OSCC and non-OSCC from real GWGENs of OSCC and non-OSCC, respectively. Afterward, core signaling pathways were constructed through the annotation of KEGG pathways, and then the carcinogenic mechanism of OSCC was investigated by comparing the core signal pathways and their downstream abnormal cellular functions of OSCC and non-OSCC. Consequently, HES1, TCF, NF-κB and SP1 are identified as significant biomarkers of OSCC. In order to discover multiple molecular drugs for these significant biomarkers (drug targets) of the carcinogenic mechanism of OSCC, we trained a DNN-based drug–target interaction (DTI) model by DTI databases to predict candidate drugs for these significant biomarkers. Finally, drug design specifications such as adequate drug regulation ability, low toxicity and high sensitivity are employed to filter out the appropriate molecular drugs metformin, gefitinib and gallic-acid to combine as a potential multiple-molecule drug for the therapeutic treatment of OSCC.     

Recombinant Expression of a Novel Fungal Immunomodulatory Protein with Human Tumor Cell Antiproliferative Activity from Nectria haematococca

To our best knowledge, all of the fungal immunomodulatory proteins (FIPs) have been successfully extracted and identified in Basidomycetes, with only the exception of FIP from ascomycete Nectria haematococca (FIP-nha) discovered through homology alignment most recently. In this work, a gene encoding FIP-nha was synthesized and recombinantly expressed in an Escherichia coli expression system. SDS-PAGE and MALDI-MS analyses of recombinant FIP-nha (rFIP-nha) indicated that the gene was successfully expressed. The yield of the bioactive FIP-nha protein was 42.7 mg/L. In vitro assays of biological activity indicated that the rFIP-nha caused hemagglutination of human and rabbit red blood cells, significantly stimulated mouse spleen lymphocyte proliferation, and enhanced expression of interleukin-2 (IL-2) released from mouse splenocytes, revealing a strong antitumor effect against HL60, HepG2 and MGC823. Through this work, we constructed a rapid and efficient method of FIP production, and suggested that FIP-nha is a valuable candidate for use in future medical care and pharmaceutical products.     

Major histocompatibility complex (MHC) markers in conservation biology

Human impacts through habitat destruction, introduction of invasive species and climate change are increasing the number of species threatened with extinction. Decreases in population size simultaneously lead to reductions in genetic diversity, ultimately reducing the ability of populations to adapt to a changing environment. In this way, loss of genetic polymorphism is linked with extinction risk. Recent advances in sequencing technologies mean that obtaining measures of genetic diversity at functionally important genes is within reach for conservation programs. A key region of the genome that should be targeted for population genetic studies is the Major Histocompatibility Complex (MHC). MHC genes, found in all jawed vertebrates, are the most polymorphic genes in vertebrate genomes. They play key roles in immune function via immune-recognition and -surveillance and host-parasite interaction. Therefore, measuring levels of polymorphism at these genes can provide indirect measures of the immunological fitness of populations. The MHC has also been linked with mate-choice and pregnancy outcomes and has application for improving mating success in captive breeding programs. The recent discovery that genetic diversity at MHC genes may protect against the spread of contagious cancers provides an added impetus for managing and protecting MHC diversity in wild populations. Here we review the field and focus on the successful applications of MHC-typing for conservation management. We emphasize the importance of using MHC markers when planning and executing wildlife rescue and conservation programs but stress that this should not be done to the detriment of genome-wide diversity.