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.

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 CD56dim 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.

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.

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.

Integration of metagenomics-metabolomics reveals specific signatures and functions of airway microbiota in mite-sensitized childhood asthma.

BACKGROUND: Childhood asthma is a multifactorial inflammatory condition of the airways, associated with specific changes in respiratory microbiome and circulating metabolome. METHODS: To explore the functional capacity of asthmatic microbiome and its intricate connection with the host, we performed shotgun sequencing of airway microbiome and untargeted metabolomics profiling of serum samples in a cohort of children with mite-sensitized asthma and non-asthmatic controls. RESULTS: We observed higher gene counts and sample-to-sample dissimilarities in asthmatic microbiomes, indicating a more heterogeneous community structure and functionality among the cases than in controls. Moreover, we identified airway microbial species linked to changes in circulating metabolites and IgE responses of the host, including a positive correlation between Prevotella sp oral taxon 306 and dimethylglycine that were both decreased in patients. Several control-enriched species (Eubacterium sulci, Prevotella pallens, and Prevotella sp oral taxon 306) were inversely correlated with total and allergen-specific IgE levels. Genes related to microbial carbohydrate, amino acid, and lipid metabolism were differentially enriched, suggesting that changes in microbial metabolism may contribute to respiratory health in asthmatics. Pathway modules relevant to allergic responses were differentially abundant in asthmatic microbiome, such as enrichments for biofilm formation by Pseudomonas aeruginosa, membrane trafficking, histidine metabolism, and glycosaminoglycan degradation, and depletions for polycyclic aromatic hydrocarbon degradation. Further, we identified metagenomic and metabolomic markers (eg, Eubacterium sulci) to discriminate cases from the non-asthmatic controls. CONCLUSIONS: Our dual-omics data reveal the connections between respiratory microbes and circulating metabolites perturbed in mite-sensitized pediatric asthma, which may be of etiological and diagnostic implications.

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.

The Arabidopsis O-fucosyltransferase SPINDLY activates nuclear growth repressor DELLA.

Plant development requires coordination among complex signaling networks to enhance the plant's adaptation to changing environments. DELLAs, transcription regulators originally identified as repressors of phytohormone gibberellin signaling, play a central role in integrating multiple signaling activities via direct protein interactions with key transcription factors. Here, we found that DELLA is mono-O-fucosylated by the novel O-fucosyltransferase SPINDLY (SPY) in Arabidopsis thaliana. O-fucosylation activates DELLA by promoting its interaction with key regulators in brassinosteroid- and light-signaling pathways, including BRASSINAZOLE-RESISTANT1 (BZR1), PHYTOCHROME-INTERACTING-FACTOR3 (PIF3) and PIF4. Moreover, spy mutants displayed elevated responses to gibberellin and brassinosteroid, and increased expression of common target genes of DELLAs, BZR1 and PIFs. Our study revealed that SPY-dependent protein O-fucosylation plays a key role in regulating plant development. This finding may have broader importance because SPY orthologs are conserved in prokaryotes and eukaryotes, thus suggesting that intracellular O-fucosylation may regulate a wide range of biological processes in diverse organisms.

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

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.

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.

The role of TGF-ß 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-ß signaling and apoptosis as two of the main functional modules involved in primary and secondary infection. CONCLUSIONS: Our initial in silico analyses pave the way for further investigation into the interesting roles played by the TGF-ß 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.

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.

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.

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 ß-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.

Essential functional modules for pathogenic and defensive mechanisms in Candida albicans infections.

The clinical and biological significance of the study of fungal pathogen Candida albicans (C. albicans) has markedly increased. However, the explicit pathogenic and invasive mechanisms of such host-pathogen interactions have not yet been fully elucidated. Therefore, the essential functional modules involved in C. albicans-zebrafish interactions were investigated in this study. Adopting a systems biology approach, the early-stage and late-stage protein-protein interaction (PPI) networks for both C. albicans and zebrafish were constructed. By comparing PPI networks at the early and late stages of the infection process, several critical functional modules were identified in both pathogenic and defensive mechanisms. Functional modules in C. albicans, like those involved in hyphal morphogenesis, ion and small molecule transport, protein secretion, and shifts in carbon utilization, were seen to play important roles in pathogen invasion and damage caused to host cells. Moreover, the functional modules in zebrafish, such as those involved in immune response, apoptosis mechanisms, ion transport, protein secretion, and hemostasis-related processes, were found to be significant as defensive mechanisms during C. albicans infection. The essential functional modules thus determined could provide insights into the molecular mechanisms of host-pathogen interactions during the infection process and thereby devise potential therapeutic strategies to treat C. albicans infection.

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.