An integrative polyomics investigation of bovine mastitis

Bovine mastitis, inflammation of the mammary gland, is one of the most costly and prevalent diseases in the dairy industry. It is commonly caused by bacteria, and Streptococcus uberis is one of the most prevalent causative agents. With advancements in omics technologies, the analysis of system-wide changes in the expression of proteins and metabolites in milk has become possible, and such analyses have broadened the knowledge of molecular changes in bovine mastitis. The work presented in this thesis aims to understand the dynamics of molecular changes in bovine mastitis caused by Streptococcus uberis through system-wide profiling and integrated analysis of milk proteins and metabolites. To this end, archived milk samples collected at specific intervals during the course of an experimentally induced model of Streptococcus uberis mastitis were used. Label-free quantitative proteomics and untargeted metabolomics data were generated from the archived milk samples obtained from six cows at six time-points (0, 36, 42, 57, 81 & 312 hours post-challenge). A total of 570 bovine proteins and 690 putative metabolites were quantified. Hierarchical cluster analysis and principal component analysis showed clustering of samples by the stage of infection, with similarities between pre-infection and resolution stages (0 and 312 hours post-challenge), early infection stages (36 and 42 hours post-challenge) and late infection stages (57 and 81 hours post-challenge). The proteomics and metabolomics data were analysed at both individual omics-layer level and combined inter-layer-level. At individual omics layer-level, the temporal changes identified include changes in the expression of proteins in acute-phase response signalling, FXR/RXR activation, complement system, IL-6 and IL-10 pathways, and changes in the expression of metabolites related to amino acid, carbohydrate, lipid and nucleotide metabolisms. The combined inter-layer-level analyses revealed functional relevance of proteins and metabolites enriched in the co-expression modules. For example, possible immunomodulatory role of bile acids via the FXR/RXR activation pathways could be inferred. Similarly, the actin-binding proteins could be linked to endocytic trafficking of signalling receptors. Overall, the work presented in this thesis provides deeper understanding of molecular changes in mastitis. On a secondary note, it also serves as a case study in the use of integrative polyomics analysis methods in the investigation of host-pathogen interactions

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 1. High abundance proteins, acute phase proteins and peptidomics

A peptidomic investigation of milk from an experimental model of Streptococcus uberis mastitis in dairy cows has incorporated a study of milk high abundance and acute phase (APP) proteins as well as analysis of low molecular weight peptide biomarkers. Intramammary infection (IMI) with S. uberis caused a shift in abundance from caseins, β-lactoglobulin and α-lactalbumin to albumin, lactoferrin and IgG with the increase in lactoferrin occurring last. The APP response of haptoglobin, mammary associated serum amyloid A3 and C-reactive protein occurred between 30–48 hours post challenge with peak concentrations of APPs at 72–96 hours post challenge and declined thereafter at a rate resembling the fall in bacterial count rather than the somatic cell count. A peptide biomarker panel for IMI based on capillary electrophoresis and mass spectrometry was developed. It comprised 77 identified peptides (IMI77) composed mainly of casein derived peptides but also including peptides of glycosylation dependent cell adhesion molecule and serum amyloid A. The panel had a biomarker classification score that increased from 36 hour to 81 hour post challenge, significantly differentiating infected from non-infected milk, thus suggesting potential as a peptide biomarker panel of bovine mastitis and specifically that of S. uberis origin. The use of omic technology has shown a multifactorial cross system reaction in high and low abundance proteins and their peptide derivatives with changes of over a thousand fold in analyte levels in response to S. uberis infection

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics

Mastitis, inflammation of the mammary gland, is the most common and costly disease of dairy cattle in the western world. It is primarily caused by bacteria, with Streptococcus uberis as one of the most prevalent causative agents. To characterize the proteome during Streptococcus uberis mastitis, an experimentally induced model of intramammary infection was used. Milk whey samples obtained from 6 cows at 6 time points were processed using label-free relative quantitative proteomics. This proteomic analysis complements clinical, bacteriological and immunological studies as well as peptidomic and metabolomic analysis of the same challenge model. A total of 2552 non-redundant bovine peptides were identified, and from these, 570 bovine proteins were quantified. Hierarchical cluster analysis and principal component analysis showed clear clustering of results by stage of infection, with similarities between pre-infection and resolution stages (0 and 312 h post challenge), early infection stages (36 and 42 h post challenge) and late infection stages (57 and 81 h post challenge). Ingenuity pathway analysis identified upregulation of acute phase protein pathways over the course of infection, with dominance of different acute phase proteins at different time points based on differential expression analysis. Antimicrobial peptides, notably cathelicidins and peptidoglycan recognition protein, were upregulated at all time points post challenge and peaked at 57 h, which coincided with 10 000-fold decrease in average bacterial counts. The integration of clinical, bacteriological, immunological and quantitative proteomics and other-omic data provides a more detailed systems level view of the host response to mastitis than has been achieved previously

Common and unique transcriptional responses to dietary restriction and loss of insulin receptor substrate 1 (IRS1) in mice

Dietary restriction (DR) is the most widely studied non-genetic intervention capable of extending lifespan across multiple taxa. Modulation of genes, primarily within the insulin/insulin-like growth factor signalling (IIS) and the mechanistic target of rapamycin (mTOR) signalling pathways also act to extend lifespan in model organisms. For example, mice lacking insulin receptor substrate-1 (IRS1) are long-lived and protected against several age-associated pathologies. However, it remains unclear how these particular interventions act mechanistically to produce their beneficial effects. Here, we investigated transcriptional responses in wild-type and IRS1 null mice fed an ad libitum diet (WTAL and KOAL) or fed a 30% DR diet (WTDR or KODR). Using an RNAseq approach we noted a high correlation coefficient of differentially expressed genes existed within the same tissue across WTDR and KOAL mice and many metabolic features were shared between these mice. Overall, we report that significant overlap exists in the tissue-specific transcriptional response between long-lived DR mice and IRS1 null mice. However, there was evidence of disconnect between transcriptional signatures and certain phenotypic measures between KOAL and KODR, in that additive effects on body mass were observed but at the transcriptional level DR induced a unique set of genes in these already long-lived mice

Elevated O-GlcNAc levels activate epigenetically repressed genes and delay mouse ES cell differentiation without affecting naive to primed cell transition

The differentiation of mouse embryonic stem (ES) cells is controlled by the interaction of multiple signaling pathways, typically mediated by post-translational protein modifications. The addition of O-linked N-acetylglucosamine (O-GlcNAc) to serine and threonine residues of nuclear and cytoplasmic proteins is one such modification (O-GlcNAcylation), whose function in ES cells is only now beginning to be elucidated. Here we demonstrate that the specific inhibition of O-GlcNAc hydrolase (Oga) causes increased levels of protein O-GlcNAcylation and impairs differentiation of mouse ES cells both in serum-free monolayer and in embryoid bodies (EBs). Use of reporter cell lines demonstrates that Oga inhibition leads to a reduction in the number of Sox1-expressing neural progenitors generated following induction of neural differentiation, as well as maintained expression of the ES cell marker Oct4 (Pou5f1). In EBs expression of mesodermal and endodermal markers is also delayed. However, the transition of naïve cells to primed pluripotency indicated by Rex1 (Zfp42), Nanog, Esrrb and Dppa3 downregulation and Fgf5 upregulation remains unchanged. Finally, we demonstrate that increased O-GlcNAcylation results in upregulation of genes normally epigenetically silenced in ES cells, supporting the emerging role for this protein modification in the regulation of histone modifications and DNA methylation. Stem Cells 2014

Changes in plasma itaconate elevation in early rheumatoid arthritis patients elucidates disease activity associated macrophage activation

Objective. To characterize changes in the plasma metabolic profile in newly diagnosed rheumatoid arthritis (RA) patients upon commencement of conventional disease modifying anti-rheumatic drug (cDMARD) therapy. Methods. Plasma samples collected in an early RA randomized strategy study (NCT00920478) that compared clinical (DAS) disease activity assessment with musculoskeletal ultrasound assessment (MSUS) to drive treatment decisions were subjected to untargeted metabolomic analysis. Metabolic profiles were collected at pre- and 3 months post commencement of non-biologic cDMARD. Metabolites that changed in association with changes in the DAS44 score were identified at the 3 month timepoint. Results. A total of ten metabolites exhibited a clear correlation with reduction in DAS44 score following cDMARD commencement, particularly itaconate, its derived anhydride and a derivative of itaconate coA. Increasing itaconate correlated with improved DAS44 score and decreasing levels of CRP. Conclusion. cDMARD treatment effects invoke consistent changes in plasma detectable metabolites, that in turn implicate clinical disease activity with macrophages. Such changes inform RA pathogenesis and reveal for the first time a link between itaconate production and resolution of an inflammatory disease in humans. Quantitative metabolic biomarker based tests of clinical change in state are feasible and should be developed around the itaconate pathway

Fibroblast growth factor signalling in multiple sclerosis: inhibition of myelination and induction of pro-inflammatory environment by FGF9

The failure of remyelination in multiple sclerosis is largely unexplained. Lindner et al. report that glial cells in demyelinating lesions show increased expression of fibroblast growth factor 9 (FGF9). This induces astrocyte-dependent responses that inhibit remyelination and stimulate expression of pro-inflammatory chemokines, supporting a feedback loop that amplifies disease activit

Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis:3. Untargeted metabolomics

Intramammary infection leading to bovine mastitis is the leading disease problem affecting dairy cows and has marked effects on the milk produced by infected udder quarters. An experimental model of Streptococcus uberis mastitis has previously been investigated for clinical, immunological and pathophysiological alteration in milk, and has been the subject of peptidomic and quantitative proteomic investigation. The same sample set has now been investigated with a metabolomics approach using liquid chromatography and mass spectrometry. The analysis revealed over 3000 chromatographic peaks, of which 690 were putatively annotated with a metabolite. Hierarchical clustering analysis and principal component analysis demonstrated that metabolite changes due to S. uberis infection were maximal at 81 hours post challenge with metabolites in the milk from the resolution phase at 312 hours post challenge being closest to the pre-challenge samples. Metabolic pathway analysis revealed that the majority of the metabolites mapped to carbohydrate and nucleotide metabolism show a decreasing trend in concentration up to 81 hours post-challenge whereas an increasing trend was found in lipid metabolites and di-, tri- and tetra-peptides up to the same time point. The increase in these peptides coincides with an increase in larger peptides found in the previous peptidomic analysis and is likely to be due to protease degradation of milk proteins. Components of bile acid metabolism, linked to the FXR pathway regulating inflammation, were also increased. Metabolomic analysis of the response in milk during mastitis provides an essential component to the full understanding of the mammary gland’s response to infection

Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology

Non-negative matrix factorization is a useful tool for reducing the dimension of large datasets. This work considers simultaneous non-negative matrix factorization of multiple sources of data. In particular, we perform the first study that involves more than two datasets. We discuss the algorithmic issues required to convert the approach into a practical computational tool and apply the technique to new gene expression data quantifying the molecular changes in four tissue types due to different dosages of an experimental panPPAR agonist in mouse. This study is of interest in toxicology because, whilst PPARs form potential therapeutic targets for diabetes, it is known that they can induce serious side-effects. Our results show that the practical simultaneous non-negative matrix factorization developed here can add value to the data analysis. In particular, we find that factorizing the data as a single object allows us to distinguish between the four tissue types, but does not correctly reproduce the known dosage level groups. Applying our new approach, which treats the four tissue types as providing distinct, but related, datasets, we find that the dosage level groups are respected. The new algorithm then provides separate gene list orderings that can be studied for each tissue type, and compared with the ordering arising from the single factorization. We find that many of our conclusions can be corroborated with known biological behaviour, and others offer new insights into the toxicological effects. Overall, the algorithm shows promise for early detection of toxicity in the drug discovery process

Fibroblast growth factor signalling in multiple sclerosis:inhibition of myelination and induction of pro-inflammatory environment by FGF9

Remyelination failure plays an important role in the pathophysiology of multiple sclerosis, but the underlying cellular and molecular mechanisms remain poorly understood. We now report actively demyelinating lesions in patients with multiple sclerosis are associated with increased glial expression of fibroblast growth factor 9 (FGF9), which we demonstrate inhibits myelination and remyelination in vitro. This inhibitory activity is associated with the appearance of multi-branched ‘pre-myelinating’ MBP+/PLP+ oligodendrocytes that interact with axons but fail to assemble myelin sheaths; an oligodendrocyte phenotype described previously in chronically demyelinated multiple sclerosis lesions. This inhibitory activity is not due to a direct effect of FGF9 on cells of the oligodendrocyte lineage but is mediated by factors secreted by astrocytes. Transcriptional profiling and functional validation studies demonstrate that these include effects dependent on increased expression of tissue inhibitor of metalloproteinase-sensitive proteases, enzymes more commonly associated with extracellular matrix remodelling. Further, we found that FGF9 induces expression of Ccl2 and Ccl7, two pro-inflammatory chemokines that contribute to recruitment of microglia and macrophages into multiple sclerosis lesions. These data indicate glial expression of FGF9 can initiate a complex astrocyte-dependent response that contributes to two distinct pathogenic pathways involved in the development of multiple sclerosis lesions. Namely, induction of a pro-inflammatory environment and failure of remyelination; a combination of effects predicted to exacerbate axonal injury and loss in patients