The functional small RNA interactome reveals targets for the vancomycin-responsive sRNA RsaOI in vancomycin-tolerant Staphylococcus aureus

Small RNAs have been found to control a broad range of bacterial phenotypes including tolerance to antibiotics. Vancomycin tolerance in multidrug resistance Staphylococcus aureus is correlated with dysregulation of small RNAs although their contribution to antibiotic tolerance is poorly understood. RNA-RNA interactome profiling techniques are expanding our understanding of sRNA-mRNA interactions in bacteria; however, determining the function of these interactions for hundreds of sRNA-mRNA pairs is a major challenge. At steady-state, protein and mRNA abundances are often highly correlated and lower than expected protein abundance may indicate translational repression of an mRNA. To identify sRNA-mRNA interactions that regulate mRNA translation, we examined the correlation between gene transcript abundance, ribosome occupancy, and protein levels. We used the machine learning technique self-organizing maps (SOMs) to cluster genes with similar transcription and translation patterns and identified a cluster of mRNAs that appeared to be post-transcriptionally repressed. By integrating our clustering with sRNA-mRNA interactome data generated in vancomycin-tolerant S. aureus by RNase III-CLASH, we identified sRNAs that may be mediating translational repression. We have confirmed sRNA-dependant post-transcriptional repression of several mRNAs in this cluster. Two of these interactions are mediated by RsaOI, a sRNA that is highly upregulated by vancomycin. We demonstrate the regulation of HPr and the cell-wall autolysin Atl. These findings suggest that RsaOI coordinates carbon metabolism and cell wall turnover during vancomycin treatment.

IMPORTANCE

The emergence of multidrug-resistant Staphylococcus aureus (MRSA) is a major public health concern. Current treatment is dependent on the efficacy of last-line antibiotics like vancomycin. The most common cause of vancomycin treatment failure is strains with intermediate resistance or tolerance that arise through the acqusition of a diverse repertoire of point mutations. These strains have been shown to altered small RNA (sRNA) expression in response to antibiotic treatment. Here, we have used a technique termed RNase III-CLASH to capture sRNA interactions with their target mRNAs. To understand the function of these interactions, we have looked at RNA and protein abundance for mRNAs targeted by sRNAs. Messenger RNA and protein levels are generally well correlated and we use deviations from this correlation to infer post-transcriptional regulation and the function of individual sRNA-mRNA interactions. Using this approach we identify mRNA targets of the vancomycin-induced sRNA, RsaOI, that are repressed at the translational level. We find that RsaOI represses the cell wall autolysis Atl and carbon transporter HPr suggestion a link between vancomycin treatment and suppression of cell wall turnover and carbon metabolism.

Profiling the in vivo RNA interactome associated with the endoribonuclease RNase III in Staphylococcus aureus

Regulatory small RNA (sRNA) have been extensively studied in model Gram-negative bacteria, but the functional characterisation of these post-transcriptional gene regulators in Gram-positives remains a major challenge. Our previous work in enterohaemorrhagic E. coli utilised the proximity-dependant ligation technique termed CLASH (UV-crosslinking, ligation, and sequencing of hybrids) for direct high-throughput sequencing of the regulatory sRNA-RNA interactions within the cell. Recently, we adapted the CLASH technique and demonstrated that UV-crosslinking and RNA proximity-dependant ligation can be applied to Staphylococcus aureus, which uncovered the first RNA-RNA interaction network in a Gram-positive bacterium. In this chapter, we describe modifications to the CLASH technique that were developed to capture the RNA interactome associated with the double-stranded endoribonuclease RNase III in two clinical isolates of S. aureus. To briefly summarise our CLASH methodology, regulatory RNA-RNA interactions were first UV-crosslinked in vivo to the RNase III protein and protein-RNA complexes were affinity-purified using the His6-TEV-FLAG tags. Linkers were ligated to RNase III-bound RNA during library preparation and duplexed RNA-RNA species were ligated together to form a single contiguous RNA 'hybrid'. The RNase III-RNA binding sites and RNA-RNA interactions occurring on RNase III (RNA hybrids) were then identified by paired-end sequencing technology. RNase III-CLASH represents a step towards a systems-level understanding of regulatory RNA in Gram-positive bacteria.

Gene-Expression Profiling of Mucinous Ovarian Tumors and Comparison with Upper and Lower Gastrointestinal Tumors Identifies Markers Associated with Adverse Outcomes

PURPOSE

Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primary MOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and gene-expression data were analyzed to identify prognostic and diagnostic features.

EXPERIMENTAL DESIGN

Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors (MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55).

RESULTS

Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio (HR), 2.77; 95% confidence interval (CI), 1.04-7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04-1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01-1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%).

CONCLUSIONS

An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies.

RNase III-CLASH of multi-drug resistant Staphylococcus aureus reveals a regulatory mRNA 3'UTR required for intermediate vancomycin resistance

Treatment of methicillin-resistant Staphylococcus aureus infections is dependent on the efficacy of last-line antibiotics including vancomycin. Treatment failure is commonly linked to isolates with intermediate vancomycin resistance (termed VISA). These isolates have accumulated point mutations that collectively reduce vancomycin sensitivity, often by thickening the cell wall. Changes in regulatory small RNA expression have been correlated with antibiotic stress in VISA isolates however the functions of most RNA regulators is unknown. Here we capture RNA-RNA interactions associated with RNase III using CLASH. RNase III-CLASH uncovers hundreds of novel RNA-RNA interactions in vivo allowing functional characterisation of many sRNAs for the first time. Surprisingly, many mRNA-mRNA interactions are recovered and we find that an mRNA encoding a long 3' untranslated region (UTR) (termed vigR 3'UTR) functions as a regulatory 'hub' within the RNA-RNA interaction network. We demonstrate that the vigR 3'UTR promotes expression of folD and the cell wall lytic transglycosylase isaA through direct mRNA-mRNA base-pairing. Deletion of the vigR 3'UTR re-sensitised VISA to glycopeptide treatment and both isaA and vigR 3'UTR deletions impact cell wall thickness. Our results demonstrate the utility of RNase III-CLASH and indicate that S. aureus uses mRNA-mRNA interactions to co-ordinate gene expression more widely than previously appreciated.

HGG-09. TARGETING FACILITATES CHROMATIN TRANSCRIPTION (FACT) AS A NOVEL STRATEGY THAT ENHANCES RESPONSE TO HISTONE DEACETYLASE (HDAC) INHIBITION IN DIPG

DIPG is an aggressive and incurable childhood brain tumour for which new treatments are needed. A high throughput drug screen of 3500 pharmaceutical compounds identified anti-malarials, including quinacrine as having potent activity against DIPG neurospheres. CBL0137, a compound modelled on quinacrine, is a novel anti-cancer compound which targets Facilitates Chromatin Transcription (FACT), a chromatin remodelling complex involved in transcription, replication, and DNA repair. CBL0137 effectively crosses the blood-brain barrier and has recently completed Phase I testing in adult patients. CBL0137 induced apoptosis in DIPG neurospheres and had profound cytotoxic activity against a panel of DIPG cultures. In a DIPG orthotopic model, treatment with CBL0137 significantly improved survival. We found that treatment with CBL0137 up-regulated TP53 and increased histone H3.3 acetylation and tri-methylation in DIPG cells. We therefore examined the interaction between CBL0137 and the histone deacetylase (HDAC) inhibitor panobinostat. In vitro experiments showed that the two agents had profound synergistic activity against DIPG neurospheres in clonogenic assays and enhanced caspase activation and apoptosis. The FACT subunit SSRP1 was found to directly interact with H3.3K27M and treatment with CBL0137 targeted this epigenetic defect, restoring histone H3.3 trimethylation and leading to tumor cell death. Transcriptomic analysis and immunoblotting indicated that combination treatment activated signalling pathways controlled by Retinoblastoma (RB)/E2F1 and subsequently increased phosphorylation and enzymatic activity of enhancer of zeste homolog 2 (EZH2). Consistent with the in vitro results, the combination of CBL0137 and panobinostat significantly prolonged survival in two independent orthotopic models of DIPG, while histological analysis showed restoration of H3K27me3 and decreased Ki67 positive cells. In addition to panobinostat, CBL0137 has been found to combine synergistically in vitro and in vivo with PARP and BET inhibitors. Given these promising results, a paediatric trial of CBL0137 will open through the Children’s Oncology Group with an expansion cohort for DIPG patients.

Dual targeting of the epigenome via FACT complex and histone deacetylase is a potent treatment strategy for DIPG

Diffuse intrinsic pontine glioma (DIPG) is an aggressive and incurable childhood brain tumor for which new treatments are needed. CBL0137 is an anti-cancer compound developed from quinacrine that targets facilitates chromatin transcription (FACT), a chromatin remodeling complex involved in transcription, replication, and DNA repair. We show that CBL0137 displays profound cytotoxic activity against a panel of patient-derived DIPG cultures by restoring tumor suppressor TP53 and Rb activity. Moreover, in an orthotopic model of DIPG, treatment with CBL0137 significantly extends animal survival. The FACT subunit SPT16 is found to directly interact with H3.3K27M, and treatment with CBL0137 restores both histone H3 acetylation and trimethylation. Combined treatment of CBL0137 with the histone deacetylase inhibitor panobinostat leads to inhibition of the Rb/E2F1 pathway and induction of apoptosis. The combination of CBL0137 and panobinostat significantly prolongs the survival of mice bearing DIPG orthografts, suggesting a potential treatment strategy for DIPG.

DIPG-27. TARGETING FACILITATES CHROMATIN TRANSCRIPTION (FACT) AS A NOVEL STRATEGY FOR DIFFUSE INTRINSIC PONTINE GLIOMA (DIPG) THAT ENHANCES RESPONSE TO HISTONE DEACETYLASE (HDAC) INHIBITION

Diffuse intrinsic pontine glioma (DIPG) is an aggressive and incurable childhood brain tumour for which new treatments are needed. A high throughput drug screen of 3500 pharmaceutical compounds identified anti-malarials, including quinacrine as having potent activity against DIPG neurospheres. CBL0137, a compound modelled on quinacrine, is an anti-cancer compound which targets Facilitates Chromatin Transcription (FACT), a chromatin remodelling complex involved in transcription, replication, and DNA repair. CBL0137 effectively crosses the blood-brain barrier and is currently in Phase I trials in adult cancer. CBL0137 induced apoptosis in DIPG neurospheres in vitro and had profound cytotoxic activity against a panel of DIPG cultures. In a DIPG orthotopic model, treatment with CBL0137 significantly improved survival. We found that treatment with CBL0137 up-regulated TP53 and increased histone H3.3 acetylation and tri-methylation in DIPG cells. We therefore examined the interaction between CBL0137 and the HDAC inhibitor, panobinostat. In vitro experiments showed that the two agents had profound synergistic activity against DIPG neurospheres in clonogenic assays and enhanced apoptosis. Transcriptomic analysis and immunoblotting indicated that combination treatment activated signalling pathways controlled by Retinoblastoma (RB)/E2F1 and subsequently increased phosphorylation and enzymatic activity of enhancer of zeste homolog 2 (EZH2). Consistent with the in vitro results, the combination of CBL0137 and panobinostat significantly prolonged the survival of two orthotopic models of DIPG, while histological analysis showed increased H3K27me3 and decreased Ki67 positive cells. Given these promising results, a paediatric trial of CBL0137 is planned to open through the Children’s Oncology Group with an expansion cohort for DIPG patients.

DIPG-14. TARGETING POLO-LIKE KINASE 1 IN COMBINATION WITH KEY ONCOGENIC DRIVERS IN DIPG: FROM SINGLE AGENT TO COMBINATION STRATEGIES

Diffuse Intrinsic Pontine Glioma (DIPG) are devastating paediatric brainstem tumours. Loss of function mutations in DIPG decrease genetic stability and impair DNA damage response pathways promoting tumourigenesis. Polo-like Kinase 1 (PLK1) is a pivotal controller of cell growth, regulating key intermediaries of DNA replication, homologous repair, the cell cycle and cell division. We have found DIPG cultures consistently overexpress PLK1 with inhibition resulting in decreased tumour cell growth, heightened cell cycle arrest and apoptosis. Single agent treatment using PLK1 inhibitors unprecedentedly doubled the median survival of animals harbouring DIPG tumours. Through gene expression analysis, we’ve showed PLK1 inhibition affected multiple pathways which control the cell cycle, cell death regulation, microtubule organization and regulation of cell migration. We found these pathways of differentially expressed genes were significantly enriched for known targets of both E2F1 and E2F4. Analysis of gene expression and proteomic studies also revealed PLK1 inhibition decreased the activation and expression of key tumour promoting mediators within multiple phases of the cell cycle, decreased expression of tumour promoters including MYC and the PI3K/mTOR pathway and reactivated tumour suppressors p53 and PTEN. Assessing these changes in the treated transcriptome and proteome, we aim to develop multiple potentially translatable combination treatment strategies for DIPG. We have performed mechanistic studies and identified synergism with PLK1 inhibitors and the epigenetic regulator panobinostat, bet/bromodomain inhibitor JQ1, dual PI3K/mTOR inhibitor bimiralisib and PI3K inhibitor BKM120. Finally, we found PLK1 inhibitors act as potent radiosensitizers, enhancing the therapeutic effects of radiotherapy in vitro and in vivo.

Analytical Guidelines for co-fractionation Mass Spectrometry Obtained through Global Profiling of Gold Standard Saccharomyces cerevisiae Protein Complexes

Co-fractionation MS (CF-MS) is a technique with potential to characterize endogenous and unmanipulated protein complexes on an unprecedented scale. However this potential has been offset by a lack of guidelines for best-practice CF-MS data collection and analysis. To obtain such guidelines, this study thoroughly evaluates novel and published Saccharomyces cerevisiae CF-MS data sets using very high proteome coverage libraries of yeast gold standard complexes. A new method for identifying gold standard complexes in CF-MS data, Reference Complex Profiling, and the Extending 'Guilt-by-Association' by Degree (EGAD) R package are used for these evaluations, which are verified with concurrent analyses of published human data. By evaluating data collection designs, which involve fractionation of cell lysates, it is found that near-maximum recall of complexes can be achieved with fewer samples than published studies. Distributing sample collection across orthogonal fractionation methods, rather than a single high resolution data set, leads to particularly efficient recall. By evaluating 17 different similarity scoring metrics, which are central to CF-MS data analysis, it is found that two metrics rarely used in past CF-MS studies - Spearman and Kendall correlations - and the recently introduced Co-apex metric frequently maximize recall, whereas a popular metric-Euclidean distance-delivers poor recall. The common practice of integrating external genomic data into CF-MS data analysis is also evaluated, revealing that this practice may improve the precision and recall of known complexes but is generally unsuitable for predicting novel complexes in model organisms. If studying nonmodel organisms using orthologous genomic data, it is found that particular subsets of fractionation profiles (e.g. the lowest abundance quartile) should be excluded to minimize false discovery. These assessments are summarized in a series of universally applicable guidelines for precise, sensitive and efficient CF-MS studies of known complexes, and effective predictions of novel complexes for orthogonal experimental validation.

Cross-linking Mass Spectrometry Analysis of the Yeast Nucleus Reveals Extensive Protein-Protein Interactions Not Detected by Systematic Two-Hybrid or Affinity Purification-Mass Spectrometry

Saccharomyces cerevisiae has the most comprehensively characterized protein-protein interaction network, or interactome, of any eukaryote. This has predominantly been generated through multiple, systematic studies of protein-protein interactions by two-hybrid techniques and of affinity-purified protein complexes. A pressing question is to understand how large-scale cross-linking mass spectrometry (XL-MS) can confirm and extend this interactome. Here, intact yeast nuclei were subject to cross-linking with disuccinimidyl sulfoxide (DSSO) and analyzed using hybrid MS2-MS3 methods. XlinkX identified a total of 2,052 unique residue pair cross-links at 1% FDR. Intraprotein cross-links were found to provide extensive structural constraint data, with almost all intralinks that mapped to known structures and slightly fewer of those mapping to homology models being within 30 Å. Intralinks provided structural information for a further 366 proteins. A method for optimizing interprotein cross-link score cut-offs was developed, through use of extensive known yeast interactions. Its application led to a high confidence, yeast nuclear interactome. Strikingly, almost half of the interactions were not previously detected by two-hybrid or AP-MS techniques. Multiple lines of evidence existed for many such interactions, whether through literature or ortholog interaction data, through multiple unique interlinks between proteins, and/or through replicates. We conclude that XL-MS is a powerful means to measure interactions, that complements two-hybrid and affinity-purification techniques.

Different Pathways Mediate Amphotericin-Lactoferrin Drug Synergy in Cryptococcus and Saccharomyces

Fungal infections are an increasing cause of morbidity and mortality. Current antifungal drugs are limited in spectrum, few new drugs are in development, and resistance is an increasing issue. Drug synergy can enhance available drugs and extend their lifetime, however, few synergistic combinations are in clinical use and mechanistic data on how combinations work is lacking. The multifunctional glycoprotein lactoferrin (LF) acts synergistically with amphotericin B (AMB) in a range of fungal species. Whole LF binds and sequesters iron, and LF can also be digested enzymatically to produce cationic peptides with distinct antimicrobial functions. To understand how LF synergizes AMB, we previously undertook a transcriptomic analysis in Saccharomyces and found a paradoxical down-regulation of iron and stress response, suggesting stress pathway interference was dysregulating an appropriate response, resulting in cell death. To extend this to a fungal pathogen, we here perform the same analysis in Cryptococcus neoformans. While both fungi responded to AMB in a similar way, the addition of LF produced remarkably contrasting results, with the Cryptococcus transcriptome enriched for processes relating to cellular stress, up-regulation of endoplasmic-reticulum-associated protein degradation (ERAD), stress granule disassembly and protein folding, endoplasmic reticulum-Golgi-vacuole trafficking and autophagy, suggesting an overall disruption of protein and lipid biosynthesis. These studies demonstrate that the mechanism of LF-mediated synergy is species-specific, possibly due to differences in the way LF peptides are generated, bind to and enter cells and act on intracellular targets, illustrating how very different cellular processes can underlie what appears to be a similar phenotypic response.

Higher abundance of enterovirus A species in the gut of children with islet autoimmunity

Enteroviruses (EVs) are prime candidate environmental triggers of islet autoimmunity (IA), with potential as vaccine targets for type 1 diabetes prevention. However, the use of targeted virus detection methods and the selective focus on EVs by most studies increases the risk for substantial investigation bias and an overestimated association between EV and type 1 diabetes. Here we performed comprehensive virome-capture sequencing to examine all known vertebrate-infecting viruses without bias in 182 specimens (faeces and plasma) collected before or at seroconversion from 45 case children with IA and 48 matched controls. From >2.6 billion reads, 28 genera of viruses were detected and 62% of children (58/93) were positive for ≥1 vertebrate-infecting virus. We identified 129 viruses as differentially abundant between the gut of cases and controls, including 5 EV-A types significantly more abundant in the cases. Our findings further support EV’s hypothesised contribution to IA and corroborate the proposal that viral load may be an important parameter in disease pathogenesis. Furthermore, our data indicate a previously unrecognised association of IA with higher EV-A abundance in the gut of children and provide a catalog of viruses to be interrogated further to determine a causal link between virus infection and type 1 diabetes.

Visualizing Post-Translational Modifications in Protein Interaction Networks Using PTMOracle

Post-translational modifications (PTMs) of proteins act as key regulators of protein activity, including the regulation of protein-protein interactions (PPIs). However, exploring functional links between PTMs and PPIs can be difficult. PTMOracle is a Cytoscape app that facilitates the co-visualization and co-analysis of PTMs in the context of PPI networks. PTMOracle also allows extensive data to be integrated and co-analyzed, allowing the role of domains, motifs, and disordered regions to be considered. Here, we describe several PTMOracle protocols investigating complex PTM-associated relationships and their role in PPIs. This is assisted by OraclePainter for coloring proteins by the modifications present and visualizing these in the context of networks, by OracleTools for cross-matching PTMs with sequence feature for all nodes in the network, and by OracleResults for exploring specific proteins and visualizing their PTMs in the context of protein sequences. This unit aims to demonstrate how PTMOracle can be used to systematically explore network visualizations and generate testable hypotheses regarding the functional role of PTMs in PPIs, and how the results can be analyzed to better understand the regulatory role of PTMs in PPIs. © 2019 by John Wiley & Sons, Inc.

Knockout of the Hmt1p Arginine Methyltransferase in Saccharomyces cerevisiae Leads to the Dysregulation of Phosphate-associated Genes and Processes

Hmt1p is the predominant arginine methyltransferase in Saccharomyces cerevisiae Its substrate proteins are involved in transcription, transcriptional regulation, nucleocytoplasmic transport and RNA splicing. Hmt1p-catalyzed methylation can also modulate protein-protein interactions. Hmt1p is conserved from unicellular eukaryotes through to mammals where its ortholog, PRMT1, is lethal upon knockout. In yeast, however, the effect of knockout on the transcriptome and proteome has not been described. Transcriptome analysis revealed downregulation of phosphate-responsive genes in hmt1Δ, including acid phosphatases PHO5, PHO11, and PHO12, phosphate transporters PHO84 and PHO89 and the vacuolar transporter chaperone VTC3 Analysis of the hmt1Δ proteome revealed decreased abundance of phosphate-associated proteins including phosphate transporter Pho84p, vacuolar alkaline phosphatase Pho8p, acid phosphatase Pho3p and subunits of the vacuolar transporter chaperone complex Vtc1p, Vtc3p and Vtc4p. Consistent with this, phosphate homeostasis was dysregulated in hmt1Δ cells, showing decreased extracellular phosphatase levels and decreased total P_i in phosphate-depleted medium. In vitro, we showed that transcription factor Pho4p can be methylated at Arg-241, which could explain phosphate dysregulation in hmt1Δ if interplay exists with phosphorylation at Ser-242 or Ser-243, or if Arg-241 methylation affects the capacity of Pho4p to homodimerize or interact with Pho2p. However, the Arg-241 methylation site was not validated in vivo and the localization of a Pho4p-GFP fusion in hmt1Δ was not different from wild type. To our knowledge, this is the first study to reveal an association between Hmt1p and phosphate homeostasis and one which suggests a regulatory link between S-adenosyl methionine and intracellular phosphate.

PTMOracle: A Cytoscape App for Covisualizing and Coanalyzing Post-Translational Modifications in Protein Interaction Networks

Post-translational modifications of proteins (PTMs) act as key regulators of protein activity and of protein-protein interactions (PPIs). To date, it has been difficult to comprehensively explore functional links between PTMs and PPIs. To address this, we developed PTMOracle, a Cytoscape app for coanalyzing PTMs within PPI networks. PTMOracle also allows extensive data to be integrated and coanalyzed with PPI networks, allowing the role of domains, motifs, and disordered regions to be considered. For proteins of interest, or a whole proteome, PTMOracle can generate network visualizations to reveal complex PTM-associated relationships. This is assisted by OraclePainter for coloring proteins by modifications, OracleTools for network analytics, and OracleResults for exploring tabulated findings. To illustrate the use of PTMOracle, we investigate PTM-associated relationships and their role in PPIs in four case studies. In the yeast interactome and its rich set of PTMs, we construct and explore histone-associated and domain-domain interaction networks and show how integrative approaches can predict kinases involved in phosphodegrons. In the human interactome, a phosphotyrosine-associated network is analyzed but highlights the sparse nature of human PPI networks and lack of PTM-associated data. PTMOracle is open source and available at the Cytoscape app store: http://apps.cytoscape.org/apps/ptmoracle .

Transcriptome and network analyses in Saccharomyces cerevisiae reveal that amphotericin B and lactoferrin synergy disrupt metal homeostasis and stress response

Invasive fungal infections are difficult to treat. The few available antifungal drugs have problems with toxicity or efficacy, and resistance is increasing. To overcome these challenges, existing therapies may be enhanced by synergistic combination with another agent. Previously, we found amphotericin B (AMB) and the iron chelator, lactoferrin (LF), were synergistic against a range of different fungal pathogens. This study investigates the mechanism of AMB-LF synergy, using RNA-seq and network analyses. AMB treatment resulted in increased expression of genes involved in iron homeostasis and ATP synthesis. Unexpectedly, AMB-LF treatment did not lead to increased expression of iron and zinc homeostasis genes. However, genes involved in adaptive response to zinc deficiency and oxidative stress had decreased expression. The clustering of co-expressed genes and network analysis revealed that many iron and zinc homeostasis genes are targets of transcription factors Aft1p and Zap1p. The aft1Δ and zap1Δ mutants were hypersensitive to AMB and H₂O₂, suggesting they are key regulators of the drug response. Mechanistically, AMB-LF synergy could involve AMB affecting the integrity of the cell wall and membrane, permitting LF to disrupt intracellular processes. We suggest that Zap1p- and Aft1p-binding molecules could be combined with existing antifungals to serve as synergistic treatments.

Synergy and antagonism between iron chelators and antifungal drugs in Cryptococcus

Fungal infections remain very difficult to treat, and developing new antifungal drugs is difficult and expensive. Recent approaches therefore seek to augment existing antifungals with synergistic agents that can lower the therapeutic dose, increase efficacy and prevent resistance from developing. Iron limitation can inhibit microbial growth, and iron chelators have been employed to treat fungal infections. In this study, chequerboard testing was used to explore combinations of iron chelators with antifungal agents against pathogenic Cryptococcus spp. with the aim of determining how disruption to iron homeostasis affects antifungal susceptibility. The iron chelators ethylenediaminetetraacetic acid (EDTA), deferoxamine (DFO), deferiprone (DFP), deferasirox (DSX), ciclopirox olamine and lactoferrin (LF) were paired with the antifungal agents amphotericin B (AmB), fluconazole, itraconazole, voriconazole and caspofungin. All chelators except for DFO increased the efficacy of AmB, and significant synergy was seen between AmB and LF for all Cryptococcus strains. Addition of exogenous iron rescued cells from the antifungal effect of LF alone but could not prevent inhibition by AmB + LF, indicating that synergy was not due primarily to iron chelation but to other properties of LF that were potentiated in the presence of AmB. Significant synergy was not seen consistently for other antifungal-chelator combinations, and EDTA, DSX and DFP antagonised the activity of azole drugs in strains of Cryptococcus neoformans var. grubii. This study highlights the range of interactions that can be induced by chelators and indicates that most antifungal drugs are not enhanced by iron limitation in Cryptococcus.

Proteomic Validation of Transcript Isoforms, Including Those Assembled from RNA-Seq Data

Human proteome analysis now requires an understanding of protein isoforms. We recently published the PG Nexus pipeline, which facilitates high confidence validation of exons and splice junctions by integrating genomics and proteomics data. Here we comprehensively explore how RNA-seq transcriptomics data, and proteomic analysis of the same sample, can identify protein isoforms. RNA-seq data from human mesenchymal (hMSC) stem cells were analyzed with our new TranscriptCoder tool to generate a database of protein isoform sequences. MS/MS data from matching hMSC samples were then matched against the TranscriptCoder-derived database, along with Ensembl and the neXtProt database. Querying the TranscriptCoder-derived or Ensembl database could unambiguously identify ∼450 protein isoforms, with isoform-specific proteotypic peptides, including candidate hMSC-specific isoforms for the genes DPYSL2 and FXR1. Where isoform-specific peptides did not exist, groups of nonisoform-specific proteotypic peptides could specifically identify many isoforms. In both the above cases, isoforms will be detectable with targeted MS/MS assays. Unfortunately, our analysis also revealed that some isoforms will be difficult to identify unambiguously as they do not have peptides that are sufficiently distinguishing. We covisualize mRNA isoforms and peptides in a genome browser to illustrate the above situations. Mass spectrometry data is available via ProteomeXchange (PXD001449).

Tools to covisualize and coanalyze proteomic data with genomes and transcriptomes: validation of genes and alternative mRNA splicing

Direct links between proteomic and genomic/transcriptomic data are not frequently made, partly because of lack of appropriate bioinformatics tools. To help address this, we have developed the PG Nexus pipeline. The PG Nexus allows users to covisualize peptides in the context of genomes or genomic contigs, along with RNA-seq reads. This is done in the Integrated Genome Viewer (IGV). A Results Analyzer reports the precise base position where LC-MS/MS-derived peptides cover genes or gene isoforms, on the chromosomes or contigs where this occurs. In prokaryotes, the PG Nexus pipeline facilitates the validation of genes, where annotation or gene prediction is available, or the discovery of genes using a "virtual protein"-based unbiased approach. We illustrate this with a comprehensive proteogenomics analysis of two strains of Campylobacter concisus . For higher eukaryotes, the PG Nexus facilitates gene validation and supports the identification of mRNA splice junction boundaries and splice variants that are protein-coding. This is illustrated with an analysis of splice junctions covered by human phosphopeptides, and other examples of relevance to the Chromosome-Centric Human Proteome Project. The PG Nexus is open-source and available from https://github.com/IntersectAustralia/ap11_Samifier. It has been integrated into Galaxy and made available in the Galaxy tool shed.

A multidimensional matrix for systems biology research and its application to interaction networks

A multidimensional matrix containing 76 parameters from 21 transcriptomics, proteomics, interactomics, phenotypic and sequence-based data sets, in which each data set covered most of the Saccharomyces cerevisiae proteome, was compiled for systems biology research. The maximal information coefficient (MIC) was used to measure correlations between every pair of parameters. Out of 2850 possible comparisons, 340 pairs of variables (12%) showed statistically significant MIC scores. There were 321 relationships that were expected; these included relationships within physicochemical parameters of proteins, between abundance levels of genes/proteins and expression noise, and between different types of intracellular networks. We found 19 potentially novel relationships between different types of "-omics" data. The strongest of these involved genetic interaction networks, which were correlated with pleiotropy and cell-to-cell variability in protein expression. Protein disorder also showed a number of significant relationships with protein abundance, signaling and regulatory networks. Significant cross-talk was seen between the signaling and kinase interaction networks. Investigation of this revealed densely connected kinase clusters and significant signaling between them, along with signaling centers that act as integrators or broadcasters of intracellular information. These centers may allow for redundancy and a means of dampening noise in networks under a variety of genetic or environmental perturbations.

Children with islet autoimmunity and enterovirus infection demonstrate a distinct cytokine profile

Cytokines are upregulated in prediabetes, but their relationship with Enterovirus (EV) infection and development of islet autoimmunity is unknown. Cytokines (n = 65) were measured using Luminex xMAP technology in a nested case-control study of 67 children with a first-degree relative with type 1 diabetes: 27 with islet autoantibodies (Ab(+)) and 40 age-matched persistently autoantibody negative (Ab(-)) control subjects. Of 74 samples, 37 (50%) were EV-PCR(+) in plasma and/or stool (EV(+)) and the remainder were negative for EV and other viruses (EV(-)). Fifteen cytokines, chemokines, and growth factors were elevated (P ≤ 0.01) in Ab(+) versus Ab(-) children (interleukin [IL]-1β, IL-5, IL-7, IL-12(p70), IL-16, IL-17, IL-20, IL-21, IL-28A, tumor necrosis factor-α, chemokine C-C motif ligand [CCL]13, CCL26, chemokine C-X-C motif ligand 5, granulocyte-macrophage colony-stimulating factor, and thrombopoietin); most have proinflammatory effects. In EV(+) versus EV(-) children, IL-10 was higher (P = 0.005), while IL-21 was lower (P = 0.008). Cytokine levels did not differ between Ab(+)EV(+) and Ab(+)EV(-) children. Heat maps demonstrated clustering of some proinflammatory cytokines in Ab(+) children, suggesting they are coordinately regulated. In conclusion, children with islet autoimmunity demonstrate higher levels of multiple cytokines, consistent with an active inflammatory process in the prediabetic state, which is unrelated to coincident EV infection. Apart from differences in IL-10 and IL-21, EV infection was not associated with a specific cytokine profile.

The Interactorium: visualising proteins, complexes and interaction networks in a virtual 3-D cell

Here, we describe the Interactorium, a tool in which a Virtual Cell is used as the context for the seamless visualisation of the yeast protein interaction network, protein complexes and protein 3-D structures. The tool has been designed to display very complex networks of up to 40 000 proteins or 6000 multiprotein complexes and has a series of toolboxes and menus to allow real-time data manipulation and control the manner in which data are displayed. It incorporates new algorithms that reduce the complexity of the visualisation by the generation of putative new complexes from existing data and by the reduction of edges through the use of protein "twins" when they occur in multiple locations. Since the Interactorium permits multi-level viewing of the molecular biology of the cell, it is a considerable advance over existing approaches. We illustrate its use for Saccharomyces cerevisiae but note that it will also be useful for the analysis of data from simpler prokaryotes and higher eukaryotes, including humans. The Interactorium is available for download at http://www.interactorium.net.

Identification of arginine- and lysine-methylation in the proteome of Saccharomyces cerevisiae and its functional implications

Background

The methylation of eukaryotic proteins has been proposed to be widespread, but this has not been conclusively shown to date. In this study, we examined 36,854 previously generated peptide mass spectra from 2,607 Saccharomyces cerevisiae proteins for the presence of arginine and lysine methylation. This was done using the FindMod tool and 5 filters that took advantage of the high number of replicate analysis per protein and the presence of overlapping peptides.

Results

A total of 83 high-confidence lysine and arginine methylation sites were found in 66 proteins. Motif analysis revealed many methylated sites were associated with MK, RGG/RXG/RGX or WXXXR motifs. Functionally, methylated proteins were significantly enriched for protein translation, ribosomal biogenesis and assembly and organellar organisation and were predominantly found in the cytoplasm and ribosome. Intriguingly, methylated proteins were seen to have significantly longer half-life than proteins for which no methylation was found. Some 43% of methylated lysine sites were predicted to be amenable to ubiquitination, suggesting methyl-lysine might block the action of ubiquitin ligase.

Conclusions

This study suggests protein methylation to be quite widespread, albeit associated with specific functions. Large-scale tandem mass spectroscopy analyses will help to further confirm the modifications reported here.

High throughput protein-protein interaction data: clues for the architecture of protein complexes

Background

High-throughput techniques are becoming widely used to study protein-protein interactions and protein complexes on a proteome-wide scale. Here we have explored the potential of these techniques to accurately determine the constituent proteins of complexes and their architecture within the complex.

Results

Two-dimensional representations of the 19S and 20S proteasome, mediator, and SAGA complexes were generated and overlaid with high quality pairwise interaction data, core-module-attachment classifications from affinity purifications of complexes and predicted domain-domain interactions. Pairwise interaction data could accurately determine the members of each complex, but was unexpectedly poor at deciphering the topology of proteins in complexes. Core and module data from affinity purification studies were less useful for accurately defining the member proteins of these complexes. However, these data gave strong information on the spatial proximity of many proteins. Predicted domain-domain interactions provided some insight into the topology of proteins within complexes, but was affected by a lack of available structural data for the co-activator complexes and the presence of shared domains in paralogous proteins.

Conclusion

The constituent proteins of complexes are likely to be determined with accuracy by combining data from high-throughput techniques. The topology of some proteins in the complexes will be able to be clearly inferred. We finally suggest strategies that can be employed to use high throughput interaction data to define the membership and understand the architecture of proteins in novel complexes.

Are protein complexes made of cores, modules and attachments?

It has recently been proposed by Gavin et al. (Nature 2006, 440, 631-636) that protein complexes in the cell exist in different forms. The proteins within each complex were proposed to exist as three different classes, being core, module or attachment proteins. This study investigates whether the core-module-attachment classification of proteins within each complex is supported by other high-throughput protein data. Core proteins were found to have lower abundance, and shorter half-life as compared to attachment proteins, whilst the abundance and half-life of core and module proteins were similar. When the cell was perturbed, core proteins had smaller changes in abundance as compared to module and attachment proteins. Comparisons between six different pairwise interaction types of core, module and attachment proteins within a complex showed interaction types involving core or module proteins were more likely to be mediated by domain-domain interactions (DDIs) than interaction types involving attachment proteins. Interaction types that involve attachment proteins had a relatively higher ratio of abundance and ratio of half-life. So we conclude that, the core, module and attachment model of protein complexes is supported by data from these proteomic scale datasets, and describe a model for a typical protein complex that considers the above results.

Protein-protein interactions and disease: use of S. cerevisiae as a model system

Disease-causing mutations are increasingly being studied to see if they cause the loss or gain of protein-protein interactions. Because the interaction network of humans is poorly understood and difficult to investigate, here we propose the use of Saccharomyces cerevisiae as a model system for understanding the impact of disease-causing mutations on protein-protein interactions. Alignments of human disease-associated proteins and 379 yeast orthologs showed that 124 of these proteins have >40% sequence identity, with some orthologs having up to 89% identity. A total of 1826 amino acid mutations associated with human disease were found to map to invariant amino acids in yeast. These mutations were proportionately more likely to be non-conservative than non-disease associated polymorphisms for the same proteins (p=0.016). Importantly, 73 of the mutations mapped to protein-protein interaction domains, implying a direct link between mutation and changes in protein interactivity. In the manuscript, all alignment information and tables that map mutations and diseases to yeast orthologs are given. This will help researchers experimentally test the impact of mutations on protein-protein interactions in S. cerevisiae and, by homology, explore the role of such mutations in the genesis of human disease.

Surface accessibility of protein post-translational modifications

Protein post-translational modifications are crucial to the function of many proteins. In this study, we have investigated the structural environment of 8378 incidences of 44 types of post-translational modifications with 19 different approaches. We show that modified amino acids likely to be involved in protein-protein interactions, such as ester-linked phosphorylation, methylarginine, acetyllysine, sulfotyrosine, hydroxyproline, and hydroxylysine, are clearly surface associated. Other modifications, including O-GlcNAc, phosphohistidine, 4-aspartylphosphate, methyllysine, and ADP-ribosylarginine, are either not surface associated or are in a protein's core. Artifactual modifications were found to be randomly distributed throughout the protein. We discuss how the surface accessibility of post-translational modifications can be important for protein-protein interactivity.