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.

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.

Controlling the Controllers: Regulation of Histone Methylation by Phosphosignalling.

Histone methylation is central to the regulation of eukaryotic transcription. Here, we review how the histone methylation system itself is regulated. There is substantial evidence that mammalian histone methyltransferases and demethylases are phosphorylated and regulated by upstream signalling pathways. Functional studies of specific phosphosites are revealing which kinases and pathways signal to the histone methylation system and are discovering the diverse effects of phosphorylation on enzyme function. Nevertheless, the majority of phosphosites have no known kinase or function and our understanding of how histone methylation is regulated is fragmentary. Improved approaches are needed to establish and study the key regulatory phosphorylation sites on histone methyltransferases and demethylases, to avoid focus on constitutive sites which may have little regulatory purpose.

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 Pi 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.

Systems-based approaches enable identification of gene targets which improve the flavour profile of low-ethanol wine yeast strains.

Metabolic engineering has been vital to the development of industrial microbes such as the yeast Saccharomyces cerevisiae. However, sequential rounds of modification are often needed to achieve particular industrial design targets. Systems biology approaches can aid in identifying genetic targets for modification through providing an integrated view of cellular physiology. Recently, research into the generation of commercial yeasts that can produce reduced-ethanol wines has resulted in metabolically-engineered strains of S. cerevisiae that are less efficient at producing ethanol from sugar. However, these modifications led to the concomitant production of off-flavour by-products. A combination of transcriptomics, proteomics and metabolomics was therefore used to investigate the physiological changes occurring in an engineered low-ethanol yeast strain during alcoholic fermentation. Integration of 'omics data identified several metabolic reactions, including those related to the pyruvate node and redox homeostasis, as being significantly affected by the low-ethanol engineering methodology, and highlighted acetaldehyde and 2,4,5-trimethyl-1,3-dioxolane as the main off-flavour compounds. Gene remediation strategies were then successfully applied to decrease the formation of these by-products, while maintaining the 'low-alcohol' phenotype. The data generated from this comprehensive systems-based study will inform wine yeast strain development programmes, which, in turn, could potentially play an important role in assisting winemakers in their endeavour to produce low-alcohol wines with desirable flavour profiles.

Does the primary site really matter? Profiling mucinous ovarian cancers of uncertain primary origin (MO-CUP) to personalise treatment and inform the design of clinical trials.

OBJECTIVE: Advanced stage mucinous ovarian cancers are diagnostically and therapeutically challenging. Histotype specific trials have failed due to low recruitment after excluding non-ovarian primaries. Mucinous ovarian cancers are commonly metastatic from other sites however lack definitive diagnostic markers. We suggest a classification of mucinous ovarian cancers of uncertain primary origin 'MO-CUPs' in clinical trials. This study aims to identify drug targets to guide treatment and future trials. METHODS: We analyzed a large de-identified, multi-platform tumor profiling dataset of MO-CUPs enriched for advanced stage and recurrent cases submitted to Caris Life Sciences. Available data included a 45-gene next-generation sequencing (NGS) panel, gene amplification of HER2 and cMET and 18 immunohistochemical (IHC) markers of drug sensitivity/resistance. RESULTS: Mucinous tumors from 333 patients were analyzed, including 38 borderline tumors and 295 invasive cancers. The most common mutations in a subset (n = 128) of invasive cancers were KRAS (60%), TP53 (38%), PIK3CA (13%) and PTEN (9%). Borderline tumors had higher rates of BRAF mutations, and PGP and TOP2A overexpression than invasive cases. KRAS mutant invasive cancers had lower expression of thymidylate synthase (p = 0.01) and higher expression of TUBB3 (p = 0.01) than KRAS wildtype tumors. CONCLUSIONS: To our knowledge, this is the largest series profiling mucinous ovarian cancers and almost certainly includes cases of ovarian and non-ovarian origin. Given the difficulty recruiting patients to histotype-specific trials in rare subsets of ovarian cancer, it may be more important to focus on identifying potential treatment targets and to personalise treatment and design clinical trials in MO-CUPS agnostic of primary site to overcome these issues.

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.