Gut flora metagenomic analysis coupled with metabolic and deep immune profiling in chronic kidney disease

BACKGROUND AND HYPOTHESIS

Perturbation of gut microbiota has been linked to chronic kidney disease (CKD), which was correlated with a sophisticated milieu of metabolic and immune dysregulation.

METHODS

To clarify the underlying host-microbe interaction in CKD, we performed multi-omics measurements, including systems-level gut microbiome, targeted serum metabolome, and deep immunotyping, in a cohort of patients and non-CKD controls.

RESULTS

Our analyses on functional profiles of gut microbiome showed a decrease in the diversity and abundance of carbohydrate-active enzyme (CAZyme) genes but an increase in the abundance of antibiotic resistance, nitrogen cycling enzyme, and virulence factor genes in CKD. Moreover, models generated using measurements of serum metabolites (amino acids, bile acids, and short-chain fatty acids) or immunotypes were predictive of renal impairment but less so than many of functional profiles derived from gut microbiota, with the CAZyme genes being the top performing model to accurately predict early stage of diseases. In addition, co-occurrence analyses revealed coordinated host-microbe relationships in CKD. Specifically, the highest fractions of significant correlations were identified with circulating metabolites by several taxonomic and functional profiles of gut microbiome, while immunotype features were moderately associated with the abundance of microbiome-encoded metabolic pathways and serum levels of amino acids (e.g. B cell cluster-tryptophan and B cell cluster-tryptophan metabolism).

CONCLUSION

Overall, our multi-omics integration revealed several signatures of systems-level gut microbiome in robust associations with host-microbe co-metabolites and renal function, which may be of etiological and diagnostic implications in CKD.

Phenotype-specific signatures of systems-level gut microbiome associated with childhood airway allergies

BACKGROUND

Perturbation of gut symbiosis has been linked to childhood allergic diseases. However, the underlying host-microbe interaction connected with specific phenotypes is poorly understood.

METHODS

To address this, integrative analyses of stool metagenomic and metabolomic profiles associated with IgE reactions in 56 children with mite-sensitized airway allergies (25 with rhinitis and 31 with asthma) and 28 nonallergic healthy controls were conducted.

RESULTS

We noted a decrease in the number and abundance of gut microbiome-encoded carbohydrate-active enzyme (CAZyme) genes, accompanied with a reduction in species richness, in the asthmatic gut microflora but not in that from allergic rhinitis. Such loss of CAZymes was consistent with the observation that a CAZyme-linked decrease in fecal butyrate was found in asthmatics and negatively correlated with mite-specific IgE responses. Different from the CAZymes, we demonstrated an increase in α diversity at the virulome levels in asthmatic gut microbiota and identified phenotype-specific variations of gut virulome. Moreover, use of fecal metagenomic and metabolomic signatures resulted in distinct effects on differentiating rhinitis and asthma from nonallergic healthy controls.

CONCLUSION

Overall, our integrative analyses reveal several signatures of systems-level gut microbiome in robust associations with fecal metabolites and disease phenotypes, which may be of etiological and diagnostic implications in childhood airway allergies.

Deep immune profiling of patients with renal impairment unveils distinct immunotypes associated with disease severity

Background

Chronic kidney disease (CKD) is pathologically correlated with a sophisticated milieu of innate and adaptive immune dysregulation, but the underlying immunological disturbances remain poorly understood.

Methods

To address this, we comprehensively interrogated cellular and soluble elements of the immune system by using high-dimensional flow cytometry to analyze peripheral blood mononuclear cells and performing cytokine/chemokine profiling of serum samples, respectively, in a cohort of 69 patients and 19 non-CKD controls.

Results

Altered serum levels of several cytokines/chemokines were identified, among which concentrations of stem cell factor (SCF) were found to be elevated with the progression of CKD and inversely correlated with estimated glomerular filtration rate (eGFR). Deep immunophenotyping analyses reveal a global change in immune modulation associated with CKD severity. Specifically, a decrease in the subsets of CD56^dim natural killer (NK) cells (KLRG-1⁺CD38⁺CD64⁺CD15⁺CD197⁺) and monocytes (KLRG-1⁺CD38⁺PD-1⁺) was detected in severe CKD compared with controls and mild CKD. In addition, comparisons between mild and severe CKD demonstrated a loss of a mature B cell population (PD-1⁺CD197⁺IgD⁺HLA-DR⁺) in the advanced stages of disease. Further, we identified immunophenotypic markers to discriminate mild CKD from the controls, among which the portion of CD38⁺ monocytes was of particular value in early diagnosis.

Conclusions

Our data unveil severity-specific immunological signatures perturbed in CKD patients.

Prognostic Significance of O-GlcNAc and PKM2 in Hormone Receptor-Positive and HER2-Nonenriched Breast Cancer

Predictive metabolic biomarkers for the recurrent luminal breast cancer (BC) with hormone receptor (HR)-positive and human epidermal growth factor receptor type 2 (HER2)-negative are lacking. High levels of O-GlcNAcylation (O-GlcNAc) and pyruvate kinase isoenzyme M2 (PKM2) are associated with malignancy in BC; however, the association with the recurrence risk remains unclear. We first conduct survival analysis by using the METABRIC dataset to assess the correlation of PKM2 expression with BC clinical outcomes. Next, patients with HR⁺/HER2- luminal BC were recruited for PKM2/O-GlcNAc testing. Logistic regression and receiver operating characteristic curve analysis were performed to evaluate the 10-year DFS predicted outcome. Survival analysis of the METABRIC dataset revealed that high expression of PKM2 was significantly associated with worse overall survival in luminal BC. The high expression of O-GlcNAc or PKM2 was a significant independent marker for poor 10-year DFS using immunohistochemical analysis. The PKM2 or O-GlcNAc status was a significant predictor of DFS, with the combination of PKM2–O-GlcNAc status and T stage greatly enhancing the predictive outcome potential. In summary, O-GlcNAc, PKM2, and T stage serve as good prognostic discriminators in HR⁺/HER2⁻ luminal BC.

Integrative metagenomic and metabolomic analyses reveal severity-specific signatures of gut microbiota in chronic kidney disease

Chronic kidney disease (CKD) is a serious healthcare dilemma, associated with specific changes in gut microbiota and circulating metabolome. Yet, the functional capacity of CKD microbiome and its intricate relationship with the host metabolism at different stages of disease are less understood. Methods: Here, shotgun sequencing of fecal samples and targeted metabolomics profiling of serum bile acids, short- and medium-chain fatty acids, and uremic solutes were performed in a cohort of CKD patients with different severities and non-CKD controls. Results: We identified that levels of 13 microbial species and 6 circulating metabolites were significantly altered across early to advanced stages or only in particular stage(s). Among these, Prevotella sp. 885 (decreased) was associated with urea excretion, while caproic acid (decreased) and p-cresyl sulfate (elevated) were positively and negatively correlated with the glomerular filtration rate, respectively. In addition, we identified gut microbial species linked to changes in circulating metabolites. Microbial genes related to secondary bile acid biosynthesis were differentially abundant at the early stage, while pathway modules related to lipid metabolism and lipopolysaccharide biosynthesis were enriched in the CKD microbiome at the advanced stage, suggesting that changes in microbial metabolism and host inflammation may contribute to renal health. Further, we identified metagenomic and metabolomic markers to discriminate cases of different severities from the controls, among which Bacteroides eggerthii individually was of particular value in early diagnosis. Conclusions: Our dual-omics data reveal the connections between intestinal microbes and circulating metabolites perturbed in CKD, which may be of etiological and diagnostic importance.

Gut Microbiota as Diagnostic Tools for Mirroring Disease Progression and Circulating Nephrotoxin Levels in Chronic Kidney Disease: Discovery and Validation Study

The interplay of the gut microbes with gut-producing nephrotoxins and the renal progression remains unclear in large human cohort. Significant compositional and functional differences in the intestinal microbiota (by 16S rRNA gene sequencing) were noted among 30 controls and 92 (31 mild, 30 moderate and 31 advanced) patients at different chronic kidney disease (CKD) stages (discovery cohort). A core CKD-associated microbiota consisted of 7 genera (Escherichia_Shigella, Dialister, Lachnospiraceae_ND3007_group, Pseudobutyrivibrio, Roseburia, Paraprevotella and Ruminiclostridium) and 2 species (Collinsella stercoris and Bacteroides eggerthii) were identified to be highly correlated with the stages of CKD. Paraprevotella, Pseudobutyrivibrio and Collinsella stercoris were superior in discriminating CKD from the controls than the use of urine protein/creatinine ratio, even at early-stage of disease. The performance was further confirmed in a validation cohort comprising 22 controls and 76 peritoneal dialysis patients. Bacterial genera highly correlated with indoxyl sulfate and p-cresyl sulfate levels were identified. Prediction of the functional capabilities of microbial communities showed that microbial genes related to the metabolism of aromatic amino acids (phenylalanine, tyrosine, and tryptophan) were differentially enriched among the control and different CKD stages. Collectively, our results provide solid human evidence of the impact of gut-metabolite-kidney axis on the severity of chronic kidney disease and highlight a usefulness of specific gut microorganisms as possible disease differentiate marker of this global health burden.

MetaSMC: a coalescent-based shotgun sequence simulator for evolving microbial populations

MOTIVATION

High-throughput sequencing technology has revolutionized the study of metagenomics and cancer evolution. In a relatively simple environment, a metagenomics sequencing data is dominated by a few species. By analyzing the alignment of reads from microbial species, single nucleotide polymorphisms can be discovered and the evolutionary history of the populations can be reconstructed. The ever-increasing read length will allow more detailed analysis about the evolutionary history of microbial or tumor cell population. A simulator of shotgun sequences from such populations will be helpful in the development or evaluation of analysis algorithms.

RESULTS

Here, we described an efficient algorithm, MetaSMC, which simulates reads from evolving microbial populations. Based on the coalescent theory, our simulator supports all evolutionary scenarios supported by other coalescent simulators. In addition, the simulator supports various substitution models, including Jukes-Cantor, HKY85 and generalized time-reversible models. The simulator also supports mutator phenotypes by allowing different mutation rates and substitution models in different subpopulations. Our algorithm ignores unnecessary chromosomal segments and thus is more efficient than standard coalescent when recombination is frequent. We showed that the process behind our algorithm is equivalent to Sequentially Markov Coalescent with an incomplete sample. The accuracy of our algorithm was evaluated by summary statistics and likelihood curves derived from Monte Carlo integration over large number of random genealogies.

AVAILABILITY AND IMPLEMENTATION

MetaSMC is written in C. The source code is available at https://github.com/tarjxvf/metasmc.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Decomposing the subclonal structure of tumors with two-way mixture models on copy number aberrations

Multistage tumorigenesis is a dynamic process characterized by the accumulation of mutations. Thus, a tumor mass is composed of genetically divergent cell subclones. With the advancement of next-generation sequencing (NGS), mathematical models have been recently developed to decompose tumor subclonal architecture from a collective genome sequencing data. Most of the methods focused on single-nucleotide variants (SNVs). However, somatic copy number aberrations (CNAs) also play critical roles in carcinogenesis. Therefore, further modeling subclonal CNAs composition would hold the promise to improve the analysis of tumor heterogeneity and cancer evolution. To address this issue, we developed a two-way mixture Poisson model, named CloneDeMix for the deconvolution of read-depth information. It can infer the subclonal copy number, mutational cellular prevalence (MCP), subclone composition, and the order in which mutations occurred in the evolutionary hierarchy. The performance of CloneDeMix was systematically assessed in simulations. As a result, the accuracy of CNA inference was nearly 93% and the MCP was also accurately restored. Furthermore, we also demonstrated its applicability using head and neck cancer samples from TCGA. Our results inform about the extent of subclonal CNA diversity, and a group of candidate genes that probably initiate lymph node metastasis during tumor evolution was also discovered. Most importantly, these driver genes are located at 11q13.3 which is highly susceptible to copy number change in head and neck cancer genomes. This study successfully estimates subclonal CNAs and exhibit the evolutionary relationships of mutation events. By doing so, we can track tumor heterogeneity and identify crucial mutations during evolution process. Hence, it facilitates not only understanding the cancer development but finding potential therapeutic targets. Briefly, this framework has implications for improved modeling of tumor evolution and the importance of inclusion of subclonal CNAs.

Somatic copy number alterations detected by ultra-deep targeted sequencing predict prognosis in oral cavity squamous cell carcinoma

Background

Ultra-deep targeted sequencing (UDT-Seq) has advanced our knowledge on the incidence and functional significance of somatic mutations. However, the utility of UDT-Seq in detecting copy number alterations (CNAs) remains unclear. With the goal of improving molecular prognostication and identifying new therapeutic targets, we designed this study to assess whether UDT-Seq may be useful for detecting CNA in oral cavity squamous cell carcinoma (OSCC).

Methods

We sequenced a panel of clinically actionable cancer mutations in 310 formalin-fixed paraffin-embedded OSCC specimens. A linear model was developed to overcome uneven coverage across target regions and multiple samples. The 5-year rates of secondary primary tumors, local recurrence, neck recurrence, distant metastases, and survival served as the outcome measures. We confirmed the prognostic significance of the CNA signatures in an independent sample of 105 primary OSCC specimens.

Results

The CNA burden across 10 targeted genes was found to predict prognosis in two independent cohorts. FGFR1 and PIK3CAamplifications were associated with prognosis independent of clinical risk factors. Genes exhibiting CNA were clustered in the proteoglycan metabolism, the FOXO signaling, and the PI3K-AKT signaling pathways, for which targeted drugs are already available or currently under development.

Conclusions

UDT-Seq is clinically useful to identify CNA, which significantly improve the prognostic information provided by traditional clinicopathological risk factors in OSCC patients.

O-GlcNAcylation of master growth repressor DELLA by SECRET AGENT modulates multiple signaling pathways in Arabidopsis

Zentella et al. show that DELLAs are modified by the O-linked N-acetylglucosamine (O-GlcNAc) transferase (OGT) SECRET AGENT (SEC) in Arabidopsis. O-GlcNAcylation of the DELLA protein REPRESSOR OF ga1-3 (RGA) inhibits RGA binding to four of its interactors—PHYTOCHROME-INTERACTING FACTOR3 (PIF3), PIF4, JASMONATE-ZIM DOMAIN1, and BRASSINAZOLE-RESISTANT1 (BZR1)—that are key regulators in light, jasmonate, and brassinosteroid signaling pathways, respectively.

The DELLA family of transcription regulators functions as master growth repressors in plants by inhibiting phytohormone gibberellin (GA) signaling in response to developmental and environmental cues. DELLAs also play a central role in mediating cross-talk between GA and other signaling pathways via antagonistic direct interactions with key transcription factors. However, how these crucial protein–protein interactions can be dynamically regulated during plant development remains unclear. Here, we show that DELLAs are modified by the O-linked N-acetylglucosamine (O-GlcNAc) transferase (OGT) SECRET AGENT (SEC) in Arabidopsis. O-GlcNAcylation of the DELLA protein REPRESSOR OF ga1-3 (RGA) inhibits RGA binding to four of its interactors—PHYTOCHROME-INTERACTING FACTOR3 (PIF3), PIF4, JASMONATE-ZIM DOMAIN1, and BRASSINAZOLE-RESISTANT1 (BZR1)—that are key regulators in light, jasmonate, and brassinosteroid signaling pathways, respectively. Consistent with this, the sec-null mutant displayed reduced responses to GA and brassinosteroid and showed decreased expression of several common target genes of DELLAs, BZR1, and PIFs. Our results reveal a direct role of OGT in repressing DELLA activity and indicate that O-GlcNAcylation of DELLAs provides a fine-tuning mechanism in coordinating multiple signaling activities during plant development.

The CrdRS two-component system in Helicobacter pylori responds to nitrosative stress

Helicobacter pylori inhabits the gastric mucosa where it senses and responds to various stresses via a two-component systems (TCSs) that enable its persistent colonization. The aim of this study was to investigate whether any of the three paired TCSs (ArsRS, FleRS and CrdRS) in H. pylori respond to nitrosative stress. The results showed that the expression of crdS was significantly increased upon exposure to nitric oxide (NO). crdS-knockout (ΔcrdS) and crdR/crdS-knockout (ΔcrdRS) H. pylori, but not arsS-knockout (ΔarsS) or fleS-knockout (ΔfleS) H. pylori, showed a significant loss of viability upon exposure to NO compared with wild-type strain. Knockin crdS (ΔcrdS-in) significantly restored viability in the presence of NO. Global transcriptional profiling analysis of wild-type and ΔcrdS H. pylori in the presence or absence of NO showed that 101 genes were differentially expressed, including copper resistance determinant A (crdA), transport, binding and envelope proteins. The CrdR binding motifs were investigated by competitive electrophoretic mobility shift assay, which revealed that the two AC-rich regions in the crdA promoter region are required for binding. These results demonstrate that CrdR-crdA interaction enables H. pylori to survive under nitrosative stress.

Robustness analysis on interspecies interaction network for iron and glucose competition between Candida albicans and zebrafish during infection

Candida albicans has emerged as an important model organism for the study of infectious disease. Using high-throughput simultaneously quantified time-course transcriptomics, this study constructed host-pathogen interspecies interaction networks between C. albicans and zebrafish during the adhesion, invasion, and damage stages. Given that iron and glucose have been identified as crucial resources required during the infection process between C. albicans and zebrafish, we focused on the construction of the interspecies networks associated with them. Furthermore, a randomization technique was proposed to identify differentially regulated proteins that are statistically eminent for the three infection stages. The behaviors of the highly connected or differentially regulated proteins identified from the resulting networks were further investigated.

"Robustness" is an important system property that measures the ability of the system tolerating the intrinsic perturbations in a dynamic network. This characteristic provides a systematic and quantitative view to elucidate the dynamics of iron and glucose competition in terms of the interspecies interaction networks. Here, we further estimated the robustness of our constructed interspecies interaction networks for the three infection stages.

The constructed networks and robustness analysis provided significant insight into dynamic interactions related to iron and glucose competition during infection and enabled us to quantify the system's intrinsic perturbation tolerance ability during iron and glucose competition throughout the three infection stages. Moreover, the networks also assist in elucidating the offensive and defensive mechanisms of C. albicans and zebrafish during their competition for iron and glucose. Our proposed method can be easily extended to identify other such networks involved in the competition for essential resources during infection.

The role of TGF-β signaling and apoptosis in innate and adaptive immunity in zebrafish: a systems biology approach

Background

The immune system is a key biological system present in vertebrates. Exposure to pathogens elicits various defensive immune mechanisms that protect the host from potential threats and harmful substances derived from pathogens such as parasites, bacteria, and viruses. The complex immune system of humans and many other vertebrates can be divided into two major categories: the innate and the adaptive immune systems. At present, analysis of the complex interactions between the two subsystems that regulate host defense and inflammatory responses remains challenging.

Results

Based on time-course microarray data following primary and secondary infection of zebrafish by Candida albicans, we constructed two intracellular protein–protein interaction (PPI) networks for primary and secondary responses of the host. 57 proteins and 341 PPIs were identified for primary infection while 90 proteins and 385 PPIs were identified for secondary infection. There were 20 proteins in common while 37 and 70 proteins specific to primary and secondary infection. By inspecting the hub proteins of each network and comparing significant changes in the number of linkages between the two PPI networks, we identified TGF-β signaling and apoptosis as two of the main functional modules involved in primary and secondary infection.

Smad7, a member of the inhibitor SMADs, was identified to be a key protein in TGF-β signaling involved in secondary infection only. Indeed, the Smad7-dependent feedback system is related to the TGF-β signaling pathway and the immune response, suggesting that Smad7 may be an important regulator of innate and adaptive immune responses in zebrafish. Furthermore, we found that apoptosis was differentially involved in the two infection phases; more specifically, whereas apoptosis was promoted in response to primary infection, it was inhibited during secondary infection.

Conclusions

Our initial in silico analyses pave the way for further investigation into the interesting roles played by the TGF-β signaling pathway and apoptosis in innate and adaptive immunity in zebrafish. Such insights could lead to therapeutic advances and improved drug design in the continual battle against infectious diseases.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-014-0116-0) contains supplementary material, which is available to authorized users.

MicroRNAs MiR-218, MiR-125b, and Let-7g predict prognosis in patients with oral cavity squamous cell carcinoma

MicroRNAs (miRNAs) have a major impact on regulatory networks in human carcinogenesis. In this study, we sought to investigate the prognostic significance of miRNAs in patients with oral cavity squamous cell carcinoma (OSCC). In a discovery phase, RNA was extracted from 58 OSCC tumor samples and paired normal tissues. MiRNAs expression was evaluated with TaqMan Array Card and TaqMan MicroRNA assays. The prognostic significance of the miRNA signature identified in the discovery phase was validated by qRT-PCR in a replication set consisting of 141 formalin-fixed, paraffin-embedded (FFPE) samples. We identified a miRNA regulatory network centered on the three hub genes (SP1, MYC, and TP53) that predicted distinct clinical endpoints. Three miRNAs (miR-218, miR-125b, and let-7g) and their downstream response genes had a concordant prognostic significance on disease-free survival and disease-specific survival rates. In addition, patients with a reduced expression of miR-218, miR-125b, and let-7g have a higher risk of poor outcomes in presence of specific risk factors (p-stage III-IV, pT3-4, or pN+). Our findings indicate that specific miRNAs have prognostic significance in OSCC patients and may improve prognostic stratification over traditional risk factors.

HUA ENHANCER1 is involved in posttranscriptional regulation of positive and negative regulators in Arabidopsis photomorphogenesis

Light regulates growth and developmental processes in plants via global transcriptome adjustment, translational control, and multilayered posttranslational modification of proteins. The transcriptional activation and repression of light-responsive genes has been well documented; however, the impact of posttranscriptional regulation on conveying light signals has been less addressed. Here, we examined whether optimal photomorphogenesis in Arabidopsis thaliana requires the proper biogenesis of small regulatory RNAs that play pivotal roles in the posttranscriptional regulation of gene expression. Arabidopsis carrying a mutation in HUA ENHANCER1 (HEN1), required for stabilization of small regulatory RNAs, showed defects in multiple aspects of photomorphogenic and skotomorphogenic development. HEN1 negatively regulated Arabidopsis photomorphogenesis. Light-activated HEN1 expression depended on the photoreceptors phytochrome A (phyA), phyB, cryptochrome 1 (cry1), and cry2 and key transcriptional regulators ELONGATED HYPOCOTYL5 (HY5) and HY5-HOMOLOG. We also demonstrate the involvement of the small regulatory RNAs miR157d and miR319 in modulating the expression of a positive regulator, HY5, and negative regulators TEOSINTE BRANCHED1, CYCLOIDEA AND PCF family proteins, respectively, for optimal photomorphogenic development in Arabidopsis.

Responses of Candida albicans to the human antimicrobial peptide LL-37

Candida albicans is amajor fungal pathogen in humans. Antimicrobial peptides (AMPs) are critical components of the innate immune response in vertebrates and represent the first line of defense against microbial infection. LL-37 is the only member of the human family of cathelicidin AMPs and is commonly expressed by various tissues and cells, including surfaces of epithelia. The candidacidal effects of LL-37 have been well documented, but the mechanisms by which LL-37 kills C. albicans are not completely understood. In this study, we examined the effects of LL-37 on cell wall and cellular responses in C. albicans. Using transmission electron microscopy, carbohydrate analyses, and staining for β-1,3-glucan, changing of C. albicans cell wall integrity was detected upon LL-37 treatment. In addition, LL-37 also affected cell wall architecture of the pathogen. Finally, DNA microarray analysis and quantitative PCR demonstrated that sub-lethal concentrations of LL-37 modulated the expression of genes with a variety of functions, including transporters, regulators for biological processes, response to stress or chemical stimulus, and pathogenesis. Together, LL-37 induces complex responses in C. albicans, making LL-37 a promising candidate for use as a therapeutic agent against fungal infections.

HaplotypeCN: copy number haplotype inference with Hidden Markov Model and localized haplotype clustering

Copy number variation (CNV) has been reported to be associated with disease and various cancers. Hence, identifying the accurate position and the type of CNV is currently a critical issue. There are many tools targeting on detecting CNV regions, constructing haplotype phases on CNV regions, or estimating the numerical copy numbers. However, none of them can do all of the three tasks at the same time. This paper presents a method based on Hidden Markov Model to detect parent specific copy number change on both chromosomes with signals from SNP arrays. A haplotype tree is constructed with dynamic branch merging to model the transition of the copy number status of the two alleles assessed at each SNP locus. The emission models are constructed for the genotypes formed with the two haplotypes. The proposed method can provide the segmentation points of the CNV regions as well as the haplotype phasing for the allelic status on each chromosome. The estimated copy numbers are provided as fractional numbers, which can accommodate the somatic mutation in cancer specimens that usually consist of heterogeneous cell populations. The algorithm is evaluated on simulated data and the previously published regions of CNV of the 270 HapMap individuals. The results were compared with five popular methods: PennCNV, genoCN, COKGEN, QuantiSNP and cnvHap. The application on oral cancer samples demonstrates how the proposed method can facilitate clinical association studies. The proposed algorithm exhibits comparable sensitivity of the CNV regions to the best algorithm in our genome-wide study and demonstrates the highest detection rate in SNP dense regions. In addition, we provide better haplotype phasing accuracy than similar approaches. The clinical association carried out with our fractional estimate of copy numbers in the cancer samples provides better detection power than that with integer copy number states.

The role of Mss11 in Candida albicans biofilm formation

Candida albicans is an opportunistic human pathogen that can form a biofilm on biotic or inert surfaces such as epithelia and clinical devices. In this study, we examine the formation of C. albicans biofilm by establishing a key gene-centered network based on protein-protein interaction (PPI) and gene expression datasets. Starting from C. albicans Cph1 and Efg1, transcription factors associated with morphogenesis of biofilm formation, a network elucidates the complex cellular process and predicts potential unknown components related to biofilm formation. Subsequently, we analyzed the functions of Mss11 among these identified proteins to test the efficiency of the proposed computational approach. MSS11-deleted mutants were compared with a wild-type strain, indicating that the mutant is defective in forming a mature biofilm and partially attenuates the virulence of C. albicans in an infected mouse model. Finally, a DNA microarray analysis was conducted to identify the potential target genes of C. albicans Mss11. The findings of this study clarify complex gene or protein interaction during the biofilm formation process of C. albicans, supporting the application of a systems biology approach to study fungal pathogenesis.

Whole-exome sequencing to identify a novel LMNA gene mutation associated with inherited cardiac conduction disease

Background

Inherited cardiac conduction diseases (CCD) are rare but are caused by mutations in a myriad of genes. Recently, whole-exome sequencing has successfully led to the identification of causal mutations for rare monogenic Mendelian diseases.

Objective

To investigate the genetic background of a family affected by inherited CCD.

Methods and Results

We used whole-exome sequencing to study a Chinese family with multiple family members affected by CCD. Using the pedigree information, we proposed a heterozygous missense mutation (c.G695T, Gly232Val) in the lamin A/C (LMNA) gene as a candidate mutation for susceptibility to CCD in this family. The mutation is novel and is expected to affect the conformation of the coiled-coil rod domain of LMNA according to a structural model prediction. Its pathogenicity in lamina instability was further verified by expressing the mutation in a cellular model.

Conclusions

Our results suggest that whole-exome sequencing is a feasible approach to identifying the candidate genes underlying inherited conduction diseases.

Causal inference of gene regulation with subnetwork assembly from genetical genomics data

Deciphering the causal networks of gene interactions is critical for identifying disease pathways and disease-causing genes. We introduce a method to reconstruct causal networks based on exploring phenotype-specific modules in the human interactome and including the expression quantitative trait loci (eQTLs) that underlie the joint expression variation of each module. Closely associated eQTLs help anchor the orientation of the network. To overcome the inherent computational complexity of causal network reconstruction, we first deduce the local causality of individual subnetworks using the selected eQTLs and module transcripts. These subnetworks are then integrated to infer a global causal network using a random-field ranking method, which was motivated by animal sociology. We demonstrate how effectively the inferred causality restores the regulatory structure of the networks that mediate lymph node metastasis in oral cancer. Network rewiring clearly characterizes the dynamic regulatory systems of distinct disease states. This study is the first to associate an RXRB-causal network with increased risks of nodal metastasis, tumor relapse, distant metastases and poor survival for oral cancer. Thus, identifying crucial upstream drivers of a signal cascade can facilitate the discovery of potential biomarkers and effective therapeutic targets.

The chromatin modification by SUMO-2/3 but not SUMO-1 prevents the epigenetic activation of key immune-related genes during Kaposi's sarcoma associated herpesvirus reactivation

BACKGROUND

SUMOylation, as part of the epigenetic regulation of transcription, has been intensively studied in lower eukaryotes that contain only a single SUMO protein; however, the functions of SUMOylation during mammalian epigenetic transcriptional regulation are largely uncharacterized. Mammals express three major SUMO paralogues: SUMO-1, SUMO-2, and SUMO-3 (normally referred to as SUMO-1 and SUMO-2/3). Herpesviruses, including Kaposi's sarcoma associated herpesvirus (KSHV), seem to have evolved mechanisms that directly or indirectly modulate the SUMO machinery in order to evade host immune surveillance, thus advancing their survival. Interestingly, KSHV encodes a SUMO E3 ligase, K-bZIP, with specificity toward SUMO-2/3 and is an excellent model for investigating the global functional differences between SUMO paralogues.

RESULTS

We investigated the effect of experimental herpesvirus reactivation in a KSHV infected B lymphoma cell line on genomic SUMO-1 and SUMO-2/3 binding profiles together with the potential role of chromatin SUMOylation in transcription regulation. This was carried out via high-throughput sequencing analysis. Interestingly, chromatin immunoprecipitation sequencing (ChIP-seq) experiments showed that KSHV reactivation is accompanied by a significant increase in SUMO-2/3 modification around promoter regions, but SUMO-1 enrichment was absent. Expression profiling revealed that the SUMO-2/3 targeted genes are primarily highly transcribed genes that show no expression changes during viral reactivation. Gene ontology analysis further showed that these genes are involved in cellular immune responses and cytokine signaling. High-throughput annotation of SUMO occupancy of transcription factor binding sites (TFBS) pinpointed the presence of three master regulators of immune responses, IRF-1, IRF-2, and IRF-7, as potential SUMO-2/3 targeted transcriptional factors after KSHV reactivation.

CONCLUSION

Our study is the first to identify differential genome-wide SUMO modifications between SUMO paralogues during herpesvirus reactivation. Our findings indicate that SUMO-2/3 modification near protein-coding gene promoters occurs in order to maintain host immune-related gene unaltered during viral reactivation.

Interspecies protein-protein interaction network construction for characterization of host-pathogen interactions: a Candida albicans-zebrafish interaction study

Background

Despite clinical research and development in the last decades, infectious diseases remain a top global problem in public health today, being responsible for millions of morbidities and mortalities each year. Therefore, many studies have sought to investigate host-pathogen interactions from various viewpoints in attempts to understand pathogenic and defensive mechanisms, which could help control pathogenic infections. However, most of these efforts have focused predominately on the host or the pathogen individually rather than on a simultaneous analysis of both interaction partners.

Results

In this study, with the help of simultaneously quantified time-course Candida albicans-zebrafish interaction transcriptomics and other omics data, a computational framework was developed to construct the interspecies protein-protein interaction (PPI) network for C. albicans-zebrafish interactions based on the inference of ortholog-based PPIs and the dynamic modeling of regulatory responses. The identified C. albicans-zebrafish interspecies PPI network highlights the association between C. albicans pathogenesis and the zebrafish redox process, indicating that redox status is critical in the battle between the host and pathogen.

Conclusions

Advancing from the single-species network construction method, the interspecies network construction approach allows further characterization and elucidation of the host-pathogen interactions. With continued accumulation of interspecies transcriptomics data, the proposed method could be used to explore progressive network rewiring over time, which could benefit the development of network medicine for infectious diseases.

Arabidopsis bZIP16 transcription factor integrates light and hormone signaling pathways to regulate early seedling development

Transcriptomic adjustment plays an important role in Arabidopsis thaliana seed germination and deetiolation in response to environmental light signals. The G-box cis-element is commonly present in promoters of genes that respond positively or negatively to the light signal. In pursuing additional transcriptional regulators that modulate light-mediated transcriptome changes, we identified bZIP16, a basic region/Leu zipper motif transcription factor, by G-box DNA affinity chromatography. We confirmed that bZIP16 has G-box-specific binding activity. Analysis of bzip16 mutants revealed that bZIP16 is a negative regulator in light-mediated inhibition of cell elongation but a positive regulator in light-regulated seed germination. Transcriptome analysis supported that bZIP16 is primarily a transcriptional repressor regulating light-, gibberellic acid (GA)-, and abscisic acid (ABA)-responsive genes. Chromatin immunoprecipitation analysis revealed that bZIP16 could directly target ABA-responsive genes and RGA-like2, a DELLA gene in the GA signaling pathway. bZIP16 could also indirectly repress the expression of phytochrome interacting factoR3-like5, which encodes a basic helix-loop-helix protein coordinating hormone responses during seed germination. By repressing the expression of these genes, bZIP16 functions to promote seed germination and hypocotyl elongation during the early stages of Arabidopsis seedling development.

Functional analysis reveals the possible role of the C-terminal sequences and PI motif in the function of lily (Lilium longiflorum) PISTILLATA (PI) orthologues

Two lily (Lilium longiflorum) PISTILLATA (PI) genes, Lily MADS Box Gene 8 and 9 (LMADS8/9), were characterized. LMADS9 lacked 29 C-terminal amino acids including the PI motif that was present in LMADS8. Both LMADS8/9 mRNAs were prevalent in the first and second whorl tepals during all stages of development and were expressed in the stamen only in young flower buds. LMADS8/9 could both form homodimers, but the ability of LMADS8 homodimers to bind to CArG1 was relatively stronger than that of LMADS9 homodimers. 35S:LMADS8 completely, and 35S:LMADS9 only partially, rescued the second whorl petal formation and partially converted the first whorl sepal into a petal-like structure in Arabidopsis pi-1 mutants. Ectopic expression of LMADS8-C (with deletion of the 29 amino acids of the C-terminal sequence) or LMADS8-PI (with only the PI motif deleted) only partially rescued petal formation in pi mutants, which was similar to what was observed in 35S:LMADS9/pi plants. In contrast, 35:LMADS9+L8C (with the addition of the 29 amino acids of the LMADS8 C-terminal sequence) or 35S:LMADS9+L8PI (with the addition of the LMADS8 PI motif) demonstrated an increased ability to rescue petal formation in pi mutants, which was similar to what was observed in 35S:LMADS8/pi plants. Furthermore, ectopic expression of LMADS8-M (with the MADS domain truncated) generated more severe dominant negative phenotypes than those seen in 35S:LMADS9-M flowers. These results revealed that the 29 amino acids including the PI motif in the C-terminal region of the lily PI orthologue are valuable for its function in regulating perianth organ formation.

A novel molecular signature identified by systems genetics approach predicts prognosis in oral squamous cell carcinoma

Molecular methods for predicting prognosis in patients with oral cavity squamous cell carcinoma (OSCC) are urgently needed, considering its high recurrence rate and tendency for metastasis. The present study investigated the genetic basis of variations in gene expression associated with poor prognosis in OSCC using Affymetrix SNP 6.0 and Affymetrix GeneChip Human Gene 1.0 ST arrays. We identified recurrent DNA amplifications scattered from 8q22.2 to 8q24.3 in 112 OSCC specimens. These amplicons demonstrated significant associations with increased incidence of extracapsular spread, development of second primary malignancies, and poor survival. Fluorescence in situ hybridization, in a validation panel consisting of 295 cases, confirmed these associations. Assessment of the effects of copy number variations (CNVs) on genome-wide variations in gene expression identified a total of 85 CNV-associated transcripts enriched in the MYC-centered regulatory network. Twenty-four transcripts associated with increased risk of second primary malignancies, tumor relapse, and poor survival. Besides MYC itself, a novel dysregulated MYC module plays a key role in OSCC carcinogenesis. This study identified a candidate molecular signature associated with poor prognosis in OSCC patients, which may ultimately facilitate patient-tailored selection of therapeutic strategies.

A novel method to identify cooperative functional modules: study of module coordination in the Saccharomyces cerevisiae cell cycle

BACKGROUND

Identifying key components in biological processes and their associations is critical for deciphering cellular functions. Recently, numerous gene expression and molecular interaction experiments have been reported in Saccharomyces cerevisiae, and these have enabled systematic studies. Although a number of approaches have been used to predict gene functions and interactions, tools that analyze the essential coordination of functional components in cellular processes still need to be developed.

RESULTS

In this work, we present a new approach to study the cooperation of functional modules (sets of functionally related genes) in a specific cellular process. A cooperative module pair is defined as two modules that significantly cooperate with certain functional genes in a cellular process. This method identifies cooperative module pairs that significantly influence a cellular process and the correlated genes and interactions that are essential to that process. Using the yeast cell cycle as an example, we identified 101 cooperative module associations among 82 modules, and importantly, we established a cell cycle-specific cooperative module network. Most of the identified module pairs cover cooperative pathways and components essential to the cell cycle. We found that 14, 36, 18, 15, and 20 cooperative module pairs significantly cooperate with genes regulated in early G1, late G1, S, G2, and M phase, respectively. Fifty-nine module pairs that correlate with Cdc28 and other essential regulators were also identified. These results are consistent with previous studies and demonstrate that our methodology is effective for studying cooperative mechanisms in the cell cycle.

CONCLUSIONS

In this work, we propose a new approach to identifying condition-related cooperative interactions, and importantly, we establish a cell cycle-specific cooperation module network. These results provide a global view of the cell cycle and the method can be used to discover the dynamic coordination properties of functional components in other cellular processes.

Kernel density weighted loess normalization improves the performance of detection within asymmetrical data

Background

Normalization of gene expression data has been studied for many years and various strategies have been formulated to deal with various types of data. Most normalization algorithms rely on the assumption that the number of up-regulated genes and the number of down-regulated genes are roughly the same. However, the well-known Golden Spike experiment presents a unique situation in which differentially regulated genes are biased toward one direction, thereby challenging the conclusions of previous bench mark studies.

Results

This study proposes two novel approaches, KDL and KDQ, based on kernel density estimation to improve upon the basic idea of invariant set selection. The key concept is to provide various importance scores to data points on the MA plot according to their proximity to the cluster of the null genes under the assumption that null genes are more densely distributed than those that are differentially regulated. The comparison is demonstrated in the Golden Spike experiment as well as with simulation data using the ROC curves and compression rates. KDL and KDQ in combination with GCRMA provided the best performance among all approaches.

Conclusions

This study determined that methods based on invariant sets are better able to resolve the problem of asymmetry. Normalization, either before or after expression summary for probesets, improves performance to a similar degree.

C/D class MADS box genes from two monocots, orchid (Oncidium Gower Ramsey) and lily (Lilium longiflorum), exhibit different effects on floral transition and formation in Arabidopsis thaliana

We have characterized three C/D class MADS box genes from an orchid (Oncidium Gower Ramsey) and a lily (Lilium longiflorum). OMADS4 of orchid and LMADS10 of lily are C class gene orthologs, whereas OMADS2 of orchid is a putative D class gene ortholog. The identity of these three genes is further supported by the presence of conserved motifs in the C-terminal regions of the proteins. The mRNA for these three genes can be detected in flowers and is absent in vegetative leaves. In flowers, OMADS4 and LMADS10 show similar expression patterns, being specifically expressed in the stamens and carpels. The expression of OMADS2 is restricted to the stigmatic cavity and ovary of the carpel. The similarities of the expression patterns of OMADS4/LMADS10 and OMADS2 to those of C and D class genes, respectively, indicate that their transcriptional regulation is highly evolutionarily conserved in these monocot species. Yeast two-hybrid analysis indicates that both OMADS2 and OMADS4 form homodimers and heterodimers with each other. Similar interactions are observed for LMADS2 and LMADS10. Ectopic expression of LMADS10 causes extremely early flowering, terminal flower formation and conversion of the sepals into carpel-like structures, similar to ectopic expression of the lily D class gene LMADS2. In contrast, 35S::OMADS2 and 35S::OMADS4 cause only early or moderately early flowering in transgenic Arabidopsis plants without floral organ conversion. This result indicates that C/D class genes from the lily have stronger effects than those from the orchid in transgenic Arabidopsis, revealing possible functional diversification of C/D class genes from the two monocots in regulating floral transition and formation.

LZF1, a HY5-regulated transcriptional factor, functions in Arabidopsis de-etiolation

We surveyed differential gene expression patterns during early photomorphogenesis in both wild-type and mutant Arabidopsis defective in HY5, an influential positive regulator of the responses of gene expression to a light stimulus, to identify light-responsive genes whose expression was HY5 dependent. These gene-expression data identified light-regulated zinc finger protein 1 (LZF1), a gene encoding a previously uncharacterized C2C2-CO B-box transcriptional regulator. HY5 has positive trans-activating activity toward LZF1 and binding affinity to LZF1 promoter in vivo. HY5 is needed but not sufficient for the induction of LZF1 expression. Anthocyanin content is significantly diminished in lzf1 under far red, which is the most efficient light for the induction of LZF1. The expression of PAP1/MYB75 is elevated in plants overexpressing LZF1, which leads to the hyperaccumulation of anthocyanin in transgenic Arabidopsis. The transition from etioplast to chloroplast and the accumulation of chlorophyll were notably compromised in the lzf1 mutant. We provide molecular evidence that LZF1 influences chloroplast biogenesis and function via regulating genes encoding chloroplast proteins. In the absence of HY5, mutation of LZF1 leads to further reduced light sensitivity for light-regulated inhibition of hypocotyl elongation and anthocyanin and chlorophyll accumulation. Our data indicate that LZF1 is a positive regulator functioning in Arabidopsis de-etiolation.

Mixture modeling of transcript abundance classes in natural populations

Expression profiling of Drosophila melanogaster adult female heads for 108 nearly isogenic lines from two different populations, and of CEPH lymphoblastoid lines, shows that differential expression of transcripts among individuals is due to a complex interplay of cis- and trans-acting factors.

Background

Populations diverge in genotype and phenotype under the influence of such evolutionary processes as genetic drift, mutation accumulation, and natural selection. Because genotype maps onto phenotype by way of transcription, it is of interest to evaluate how these evolutionary factors influence the structure of variation at the level of transcription. Here, we explore the distributions of cis-acting and trans-acting factors and their relative contributions to expression of transcripts that exhibit two or more classes of abundance among individuals within populations.

Results

Expression profiling using cDNA microarrays was conducted in Drosophila melanogaster adult female heads for 58 nearly isogenic lines from a North Carolina population and 50 from a California population. Using a mixture modeling approach, transcripts were identified that exhibit more than one mode of transcript abundance across the samples. Power studies indicate that sample sizes of 50 individuals will generally be sufficient to detect divergent transcript abundance classes. The distribution of transcript abundance classes is skewed toward low frequency minor classes, which is reminiscent of the typical skew in genotype frequencies. Similar results are observed in reported data on gene expression in human lymphoblast cell lines, in which analysis of association with linked polymorphisms implies that cis-acting single nucleotide polymorphisms make only a modest contribution to bimodal distributions of transcript abundance.

Conclusion

Population surveys of gene expression may complement genetical genomics as a general approach to quantifying sources of transcriptional variation. Differential expression of transcripts among individuals is due to a complex interplay of cis-acting and trans-acting factors.

Quantitative trait transcripts for nicotine resistance in Drosophila melanogaster

Although most genetic association studies are performed with the intention of detecting nucleotide polymorphisms that are correlated with a complex trait, transcript abundance should also be expected to associate with diseases or phenotypes. We performed a scan for such quantitative trait transcripts in adult female heads of the fruit fly (Drosophila melanogaster) that might explain variation for nicotine resistance. The strongest association was seen for abundance of ornithine aminotransferase transcripts, implicating detoxification and neurotransmitter biosynthesis as mediators of the quantitative response to the drug. Subsequently, genetic analysis and metabolite profiling confirmed a complex role for ornithine and GABA levels in modification of survival time upon chronic nicotine exposure. Differences between populations from North Carolina and California suggest that the resistance mechanism may be an evolved response to environmental exposure.

Mixed-Model Reanalysis of Primate Data Suggests Tissue and Species Biases in Oligonucleotide-Based Gene Expression Profiles

An emerging issue in evolutionary genetics is whether it is possible to use gene expression profiling to identify genes that are associated with morphological, physiological, or behavioral divergence between species and whether these genes have undergone positive selection. Some of these questions were addressed in a recent study (Enard  et al. 2002) of the difference in gene expression among human, chimp, and orangutan, which suggested an accelerated rate of divergence in gene expression in the human brain relative to liver. Reanalysis of the Affymetrix data set using analysis of variance methods to quantify the contributions of individuals and species to variation in expression of 12,600 genes indicates that as much as one-quarter of the genome shows divergent expression between primate species at the 5% level. The magnitude of fold change ranges from 1.2-fold up to 8-fold. Similar conclusions apply to reanalysis of Enard  et al.'s (2002) parallel murine data set. However, biases inherent to short oligonucleotide microarray technology may account for some of the tissue and species effects. At high significance levels, more differences were observed in the liver than in the brain in each of the pairwise species comparisons, so it is not clear that expression divergence is accelerated in the human brain. Further, there is an apparent bias toward upregulation of gene expression in the brain in both primates and mice, whereas genes are equally likely to be up- or downregulated in the liver when these species diverge. A small subset of genes that are candidates for adaptive divergence may be identified on the basis of a high ratio of interspecific to intraspecific divergence.