Approaches to reduce false positives and false negatives in the analysis of microarray data: applications in type 1 diabetes research

Multi-omics analysis of the gut microbiome and metabolites associated with the psychoneurological symptom cluster in children with cancer receiving chemotherapy

BACKGROUND

Children with cancer receiving chemotherapy commonly report a cluster of psychoneurological symptoms (PNS), including pain, fatigue, anxiety, depression, and cognitive dysfunction. The role of the gut microbiome and its functional metabolites in PNS is rarely studied among children with cancer. This study investigated the associations between the gut microbiome-metabolome pathways and PNS in children with cancer across chemotherapy as compared to healthy children.

METHODS

A case-control study was conducted. Cancer cases were recruited from Children's Healthcare of Atlanta and healthy controls were recruited via flyers. Participants reported PNS using the Pediatric Patient-Reported Outcomes Measurement Information System. Data for cases were collected pre-cycle two chemotherapy (T0) and post-chemotherapy (T1), whereas data for healthy controls were collected once. Gut microbiome and its metabolites were measured using fecal specimens. Gut microbiome profiling was performed using 16S rRNA V4 sequencing, and metabolome was performed using an untargeted liquid chromatography-mass spectrometry approach. A multi-omics network integration program analyzed microbiome-metabolome pathways of PNS.

RESULTS

Cases (n = 21) and controls (n = 14) had mean ages of 13.2 and 13.1 years. For cases at T0, PNS were significantly associated with microbial genera (e.g., Ruminococcus, Megasphaera, and Prevotella), which were linked with carnitine shuttle (p = 0.0003), fatty acid metabolism (p = 0.001) and activation (p = 0.001), and tryptophan metabolism (p = 0.008). Megasphaera, clustered with aspartate and asparagine metabolism (p = 0.034), carnitine shuttle (p = 0.002), and tryptophan (p = 0.019), was associated with PNS for cases at T1. Gut bacteria with potential probiotic functions, along with fatty acid metabolism, tryptophan, and carnitine shuttle, were more clustered in cancer cases than the control network and this linkage with PNS needs further studies.

CONCLUSIONS

Using multi-omics approaches, this study indicated specific microbiome-metabolome pathways linked with PNS in children with cancer across chemotherapy. Due to limitations such as antibiotic use in cancer cases, these findings need to be further confirmed in a larger cohort.

Transcriptome profiling of lncRNA and co-expression networks in esophageal squamous cell carcinoma by RNA sequencing

Long non-coding RNAs (lncRNAs) are emerging as crucial regulators of cancer. To identify novel targets for further study in esophageal squamous cell carcinoma (ESCC), we performed a genome-wide analysis of lncRNA expression in 12 ESCC tumor and normal tissues. Publicly available RNA-seq data were downloaded from the NCBI, GEO, and Co-LncRNA databases, and lncRNA and messenger RNA (mRNA) expression profiles were analyzed. In total, 127 lncRNAs were found to be differentially expressed, with a greater than fourfold change in ESCC tumor tissues compared with normal tissues. Among these lncRNAs, 98 were upregulated and 29 downregulated. Moreover, 1469 network nodes and 1720 connection edges between 119 lncRNAs and 1350 coding genes were integrated into the lncRNA and mRNA co-expression network. Bioinformatic analysis using GO terms revealed that these dysregulated lncRNAs are associated with developmental processes, proteinaceous extracellular matrix, and protein binding activity, with ECM-receptor interaction and the PI3K-Akt signaling pathway enrichment. Lastly, qRT-PCR results verified two significantly upregulated lncRNAs and three significantly downregulated lncRNAs in 50 pairs of ESCC tissues and adjacent normal tissues. These results reveal the landscape of ESCC-associated lncRNAs and co-expression networks, providing important insight regarding the lncRNAs involved in ESCC.

Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

Molecular pathway alterations in CD4 T-cells of nonobese diabetic (NOD) mice in the preinsulitis phase of autoimmune diabetes

Type 1 diabetes (T1D) is a multigenic disease caused by T-cell mediated destruction of the insulin producing pancreatic islet ß-cells. The earliest sign of islet autoimmunity in NOD mice, islet leukocytic infiltration or insulitis, is obvious at around 5 weeks of age. The molecular alterations that occur in T cells prior to insulitis and that may contribute to T1D development are poorly understood. Since CD4 T-cells are essential to T1D development, we tested the hypothesis that multiple genes/molecular pathways are altered in these cells prior to insulitis. We performed a genome-wide transcriptome and pathway analysis of whole, untreated CD4 T-cells from 2, 3, and 4 week-old NOD mice in comparison to two control strains (NOR and C57BL/6). We identified many differentially expressed genes in the NOD mice at each time point. Many of these genes (herein referred to as NOD altered genes) lie within known diabetes susceptibility (insulin-dependent diabetes, Idd) regions, e.g. two diabetes resistant loci, Idd27 (tripartite motif-containing family genes) and Idd13 (several genes), and the CD4 T-cell diabetogenic activity locus, Idd9/11 (2 genes, KH domain containing, RNA binding, signal transduction associated 1 and protein tyrosine phosphatase 4a2). The biological processes associated with these altered genes included, apoptosis/cell proliferation and metabolic pathways (predominant at 2 weeks); inflammation and cell signaling/activation (predominant at 3 weeks); and innate and adaptive immune responses (predominant at 4 weeks). Pathway analysis identified several factors that may regulate these abnormalities: eight, common to all 3 ages (interferon regulatory factor 1, hepatic nuclear factor 4, alpha, transformation related protein 53, BCL2-like 1 (lies within Idd13), interferon gamma, interleukin 4, interleukin 15, and prostaglandin E2); and two each, common to 2 and 4 weeks (androgen receptor and interleukin 6); and to 3 and 4 weeks (interferon alpha and interferon regulatory factor 7). Others were unique to the various ages, e.g. myelocytomatosis oncogene, jun oncogene, and amyloid beta (A4) to 2 weeks; tumor necrosis factor, transforming growth factor, beta 1, NF?B, ERK, and p38MAPK to 3 weeks; and interleukin 12 and signal transducer and activator of transcription 4 to 4 weeks. Thus, our study demonstrated that expression of many genes that lie within several Idds (e.g. Idd27, Idd13 and Idd9/11) was altered in CD4 T-cells in the early induction phase of autoimmune diabetes and identified their associated molecular pathways. These data offer the opportunity to test hypotheses on the roles played by the altered genes/molecular pathways, to understand better the mechanisms of CD4 T-cell diabetogenesis, and to develop new therapeutic strategies for T1D.

Modification of oxidative stress on gene expression profiling in the rat infarcted heart

Cardiac oxidative stress is developed following myocardial infarction (MI) particularly in the first week of MI. The influence of reactive oxygen species (ROS) on gene expression profiling and molecular pathways in the infarcted myocardium remains uncertain and is explored in the present study. Rats with MI were treated with or without antioxidants for 1 week. Normal rats served as controls. Cardiac oxidative stress and gene profiling were investigated. Compared to normal hearts, malondialdehyde, a marker of oxidative stress, was significantly increased in the infarcted myocardium, which was significantly suppressed by antioxidants. Microarray assay showed that over a thousand genes were differentially expressed in the infarcted myocardium. Antioxidants significantly altered the expression of 159 genes compared to untreated MI rats. Ingenuity pathway analysis indicated that multiple pathway networks were affected by antioxidants, including those related to cell movement, growth/development, death, and inflammatory/fibrotic responses. IPA further identified that these changes were primarily related to NFκB, p38 MAPK, and ERκ1/2 pathways. Hub genes were identified in the associated gene networks. This study reveals the gene networks associated with cardiac oxidative stress postMI. These observations indicate that ROS regulate various molecular and cellular actions related to cardiac repair/remodeling through multiple gene networks.

Molecular phenotyping of immune cells from young NOD mice reveals abnormal metabolic pathways in the early induction phase of autoimmune diabetes

Islet leukocytic infiltration (insulitis) is first obvious at around 4 weeks of age in the NOD mouse – a model for human type 1 diabetes (T1D). The molecular events that lead to insulitis and initiate autoimmune diabetes are poorly understood. Since TID is caused by numerous genes, we hypothesized that multiple molecular pathways are altered and interact to initiate this disease. We evaluated the molecular phenotype (mRNA and protein expression) and molecular networks of ex vivo unfractionated spleen leukocytes from 2 and 4 week-old NOD mice in comparison to two control strains. Analysis of the global gene expression profiles and hierarchical clustering revealed that the majority (∼90%) of the differentially expressed genes in NOD mice were repressed. Furthermore, analysis using a modern suite of multiple bioinformatics approaches identified abnormal molecular pathways that can be divided broadly into 2 categories: metabolic pathways, which were predominant at 2 weeks, and immune response pathways, which were predominant at 4 weeks. Network analysis by Ingenuity pathway analysis identified key genes/molecules that may play a role in regulating these pathways. These included five that were common to both ages (TNF, HNF4A, IL15, Progesterone, and YWHAZ), and others that were unique to 2 weeks (e.g. MYC/MYCN, TGFB1, and IL2) and to 4 weeks (e.g. IFNG, beta-estradiol, p53, NFKB, AKT, PRKCA, IL12, and HLA-C). Based on the literature, genes that may play a role in regulating metabolic pathways at 2 weeks include Myc and HNF4A, and at 4 weeks, beta-estradiol, p53, Akt, HNF4A and AR. Our data suggest that abnormalities in regulation of metabolic pathways in the immune cells of young NOD mice lead to abnormalities in the immune response pathways and as such may play a role in the initiation of autoimmune diabetes. Thus, targeting metabolism may provide novel approaches to preventing and/or treating autoimmune diabetes.

Reverse remodeling and recovery from cachexia in rats with aldosteronism

The congestive heart failure (CHF) syndrome with soft tissue wasting, or cachexia, has its pathophysiologic origins rooted in neurohormonal activation. Mechanical cardiocirculatory assistance reveals the potential for reverse remodeling and recovery from CHF, which has been attributed to device-based hemodynamic unloading whereas the influence of hormonal withdrawal remains uncertain. This study addresses the signaling pathways induced by chronic aldosteronism in normal heart and skeletal muscle at organ, cellular/subcellular, and molecular levels, together with their potential for recovery (Recov) after its withdrawal. Eight-week-old male Sprague-Dawley rats were examined at 4 wk of aldosterone/salt treatment (ALDOST) and following 4-wk Recov. Compared with untreated, age-/sex-/strain-matched controls, ALDOST was accompanied by 1) a failure to gain weight, reduced muscle mass with atrophy, and a heterogeneity in cardiomyocyte size across the ventricles, including hypertrophy and atrophy at sites of microscopic scarring; 2) increased cardiomyocyte and mitochondrial free Ca(2+), coupled to oxidative stress with increased H(2)O(2) production and 8-isoprostane content, and increased opening potential of the mitochondrial permeability transition pore; 3) differentially expressed genes reflecting proinflammatory myocardial and catabolic muscle phenotypes; and 4) reversal to or toward recovery of these responses with 4-wk Recov. Aldosteronism in rats is accompanied by cachexia and leads to an adverse remodeling of the heart and skeletal muscle at organ, cellular/subcellular, and molecular levels. However, evidence presented herein implicates that these tissues retain their inherent potential for recovery after complete hormone withdrawal.

The effect of gluten-free diet on Th1-Th2-Th3-associated intestinal immune responses in celiac disease

OBJECTIVE

To study T-helper (Th)1-Th2-Th3 gene activation profile in the small intestine and peripheral blood of children with celiac disease (CD) with special interest in the response to the gluten-free diet (GFD) treatment in order to elucidate an immune dysregulation not triggered by gluten.

MATERIAL AND METHODS

Small intestinal biopsies and venous blood were taken from seven children with CD (mean age: 8 years, four girls) at presentation and after 1 year of strict GFD. The Th1-Th2-Th3 gene expression profile was examined by real-time PCR arrays. The findings were compared with the corresponding expressions in peripheral blood and small intestinal biopsies from six reference children without CD (mean age: 6 years, four girls).

RESULTS

The Th1 gene expression profile including interferon (IFN)-γ, signal transducer and activator of transcription (STAT) 1 and interferon regulatory factor (IRF) 1 together with reduced interleukin (IL)-2 expression was pronounced in small intestinal biopsies from children with untreated CD. A downregulation of IFN-γ transcripts was seen after 1 year of GFD, but there was still increased expression of STAT1 and IRF1 in association with low IL-2 expression in spite of eliminated exposure to wheat gluten. By contrast, the decreased intestinal expression of Th2 gene markers observed at presentation was normalized with GFD. The alterations in the mucosal gene expression profile were not reflected in peripheral blood.

CONCLUSION

The GFD did not correct the increased activation of the IFN-γ signaling pathway related markers and reduced IL-2 expression, suggesting that they represent an immune dysregulation not dependent on gluten exposure.

Effects of a spaceflight environment on heritable changes in wheat gene expression

Once it was established that the spaceflight environment was not a drastic impediment to plant growth, a remaining space biology question was whether long-term spaceflight exposure could cause changes in subsequent generations, even if they were returned to a normal Earth environment. In this study, we used a genomic approach to address this question. We tested whether changes in gene expression patterns occur in wheat plants that are several generations removed from growth in space, compared to wheat plants with no spaceflight exposure in their lineage. Wheat flown on Mir for 167 days in 1991 formed viable seeds back on Earth. These seeds were grown on the ground for three additional generations. Gene expression of fourth-generation Mir flight leaves was compared to that of the control leaves by using custom-made wheat microarrays. The data were evaluated using analysis of variance, and transcript abundance of each gene was contrasted among samples with t-tests. After corrections were made for multiple tests, none of the wheat genes represented on the microarrays showed a statistically significant difference in expression between wheat that has spaceflight exposure in their lineage and plants with no spaceflight exposure. This suggests that exposure to the spaceflight environment in low Earth orbit space stations does not cause significant, heritable changes in gene expression patterns in plants.

Genomics, molecular imaging, bioinformatics, and bio-nano-info integration are synergistic components of translational medicine and personalized healthcare research

Supported by National Science Foundation (NSF), International Society of Intelligent Biological Medicine (ISIBM), International Journal of Computational Biology and Drug Design and International Journal of Functional Informatics and Personalized Medicine, IEEE 7th Bioinformatics and Bioengineering attracted more than 600 papers and 500 researchers and medical doctors. It was the only synergistic inter/multidisciplinary IEEE conference with 24 Keynote Lectures, 7 Tutorials, 5 Cutting-Edge Research Workshops and 32 Scientific Sessions including 11 Special Research Interest Sessions that were designed dynamically at Harvard in response to the current research trends and advances. The committee was very grateful for the IEEE Plenary Keynote Lectures given by: Dr. A. Keith Dunker (Indiana), Dr. Jun Liu (Harvard), Dr. Brian Athey (Michigan), Dr. Mark Borodovsky (Georgia Tech and President of ISIBM), Dr. Hamid Arabnia (Georgia and Vice-President of ISIBM), Dr. Ruzena Bajcsy (Berkeley and Member of United States National Academy of Engineering and Member of United States Institute of Medicine of the National Academies), Dr. Mary Yang (United States National Institutes of Health and Oak Ridge, DOE), Dr. Chih-Ming Ho (UCLA and Member of United States National Academy of Engineering and Academician of Academia Sinica), Dr. Andy Baxevanis (United States National Institutes of Health), Dr. Arif Ghafoor (Purdue), Dr. John Quackenbush (Harvard), Dr. Eric Jakobsson (UIUC), Dr. Vladimir Uversky (Indiana), Dr. Laura Elnitski (United States National Institutes of Health) and other world-class scientific leaders. The Harvard meeting was a large academic event 100% full-sponsored by IEEE financially and academically. After a rigorous peer-review process, the committee selected 27 high-quality research papers from 600 submissions. The committee is grateful for contributions from keynote speakers Dr. Russ Altman (IEEE BIBM conference keynote lecturer on combining simulation and machine learning to recognize function in 4D), Dr. Mary Qu Yang (IEEE BIBM workshop keynote lecturer on new initiatives of detecting microscopic disease using machine learning and molecular biology, http://ieeexplore.ieee.org/servlet/opac?punumber=4425386) and Dr. Jack Y. Yang (IEEE BIBM workshop keynote lecturer on data mining and knowledge discovery in translational medicine) from the first IEEE Computer Society BioInformatics and BioMedicine (IEEE BIBM) international conference and workshops, November 2-4, 2007, Silicon Valley, California, USA.