New Insights Into Lignification via Network and Multi-Omics Analyses of Arogenate Dehydratase Knock-Out Mutants in Arabidopsis thaliana.

Multiple Arabidopsis arogenate dehydratase (ADT) knock-out (KO) mutants, with phenotypes having variable lignin levels (up to circa 70% reduction), were studied to investigate how differential reductions in ADTs perturb its overall plant systems biology. Integrated "omics" analyses (metabolome, transcriptome, and proteome) of wild type (WT), single and multiple ADT KO lines were conducted. Transcriptome and proteome data were collapsed into gene ortholog (GO) data, with this allowing for enzymatic reaction and metabolome cross-comparisons to uncover dominant or likely metabolic biosynthesis reactions affected. Network analysis of enzymes-highly correlated to stem lignin levels-deduced the involvement of novel putative lignin related proteins or processes. These included those associated with ribosomes, the spliceosome, mRNA transport, aminoacyl tRNA biosynthesis, and phosphorylation. While prior work helped explain lignin biosynthesis regulation at the transcriptional level, our data here provide support for a new hypothesis that there are additional post-transcriptional and translational level processes that need to be considered. These findings are anticipated to lead to development of more accurate depictions of lignin/phenylpropanoid biosynthesis models in situ, with new protein targets identified for further biochemical analysis and/or plant bioengineering. Additionally, using KEGG defined functional categorization of proteomics and transcriptomics analyses, we detected significant changes to glucosinolate, α-linolenic acid, nitrogen, carotenoid, aromatic amino acid, phenylpropanoid, and photosynthesis-related metabolic pathways in ADT KO mutants. Metabolomics results also revealed that putative carotenoid and galactolipid levels were generally increased in amount, whereas many glucosinolates and phenylpropanoids (including flavonoids and lignans) were decreased in the KO mutants.

Ion Mobility Spectrometry and the Omics: Distinguishing Isomers, Molecular Classes and Contaminant Ions in Complex Samples.

Ion mobility spectrometry (IMS) is a widely used analytical technique providing rapid gas phase separations. IMS alone is useful, but its coupling with mass spectrometry (IMS-MS) and various front-end separation techniques has greatly increased the molecular information achievable from different omic analyses. IMS-MS analyses are specifically gaining attention for improving metabolomic, lipidomic, glycomic, proteomic and exposomic analyses by increasing measurement sensitivity (e.g. S/N ratio), reducing the detection limit, and amplifying peak capacity. Numerous studies including national security-related analyses, disease screenings and environmental evaluations are illustrating that IMS-MS is able to extract information not possible with MS alone. Furthermore, IMS-MS has shown great utility in salvaging molecular information for low abundance molecules of interest when high concentration contaminant ions are present in the sample by reducing detector suppression. This review highlights how IMS-MS is currently being used in omic analyses to distinguish structurally similar molecules, isomers, molecular classes and contaminant ions.

Nipah Virus-Like Particle Egress Is Modulated by Cytoskeletal and Vesicular Trafficking Pathways: a Validated Particle Proteomics Analysis.

Classified as a biosafety level 4 (BSL4) select agent, Nipah virus (NiV) is a deadly henipavirus in the Paramyxoviridae family, with a nearly 75% mortality rate in humans, underscoring its global and animal health importance. Elucidating the process of viral particle production in host cells is imperative both for targeted drug design and viral particle-based vaccine development. However, little is understood concerning the functions of cellular machinery in paramyxoviral and henipaviral assembly and budding. Recent studies showed evidence for the involvement of multiple NiV proteins in viral particle formation, in contrast to the mechanisms understood for several paramyxoviruses as being reliant on the matrix (M) protein alone. Further, the levels and purposes of cellular factor incorporation into viral particles are largely unexplored for the paramyxoviruses. To better understand the involvement of cellular machinery and the major structural viral fusion (F), attachment (G), and matrix (M) proteins, we performed proteomics analyses on virus-like particles (VLPs) produced from several combinations of these NiV proteins. Our findings indicate that NiV VLPs incorporate vesicular trafficking and actin cytoskeletal factors. The involvement of these biological processes was validated by experiments indicating that the perturbation of key factors in these cellular processes substantially modulated viral particle formation. These effects were most impacted for NiV-F-modulated viral particle formation either autonomously or in combination with other NiV proteins, indicating that NiV-F budding relies heavily on these cellular processes. These findings indicate a significant involvement of the NiV fusion protein, vesicular trafficking, and actin cytoskeletal processes in efficient viral particle formation.IMPORTANCE Nipah virus is a zoonotic biosafety level 4 agent with high mortality rates in humans. The genus to which Nipah virus belongs, Henipavirus, includes five officially recognized pathogens; however, over 20 species have been identified in multiple continents within the last several years. As there are still no vaccines or treatments for NiV infection, elucidating its process of viral particle production is imperative both for targeted drug design as well as for particle-based vaccine development. Developments in high-throughput technologies make proteomic analysis of isolated viral particles a highly insightful approach to understanding the life cycle of pathogens such as Nipah virus.

Unified feature association networks through integration of transcriptomic and proteomic data.

High-throughput multi-omics studies and corresponding network analyses of multi-omic data have rapidly expanded their impact over the last 10 years. As biological features of different types (e.g. transcripts, proteins, metabolites) interact within cellular systems, the greatest amount of knowledge can be gained from networks that incorporate multiple types of -omic data. However, biological and technical sources of variation diminish the ability to detect cross-type associations, yielding networks dominated by communities comprised of nodes of the same type. We describe here network building methods that can maximize edges between nodes of different data types leading to integrated networks, networks that have a large number of edges that link nodes of different-omic types (transcripts, proteins, lipids etc). We systematically rank several network inference methods and demonstrate that, in many cases, using a random forest method, GENIE3, produces the most integrated networks. This increase in integration does not come at the cost of accuracy as GENIE3 produces networks of approximately the same quality as the other network inference methods tested here. Using GENIE3, we also infer networks representing antibody-mediated Dengue virus cell invasion and receptor-mediated Dengue virus invasion. A number of functional pathways showed centrality differences between the two networks including genes responding to both GM-CSF and IL-4, which had a higher centrality value in an antibody-mediated vs. receptor-mediated Dengue network. Because a biological system involves the interplay of many different types of molecules, incorporating multiple data types into networks will improve their use as models of biological systems. The methods explored here are some of the first to specifically highlight and address the challenges associated with how such multi-omic networks can be assembled and how the greatest number of interactions can be inferred from different data types. The resulting networks can lead to the discovery of new host response patterns and interactions during viral infection, generate new hypotheses of pathogenic mechanisms and confirm mechanisms of disease.

Functional Comparison of Blood-Stage Plasmodium falciparum Malaria Vaccine Candidate Antigens.

The malaria genome encodes over 5,000 proteins and many of these have also been proposed to be potential vaccine candidates, although few of these have been tested clinically. RH5 is one of the leading blood-stage Plasmodium falciparum malaria vaccine antigens and Phase I/II clinical trials of vaccines containing this antigen are currently underway. Its likely mechanism of action is to elicit antibodies that can neutralize merozoites by blocking their invasion of red blood cells (RBC). However, many other antigens could also elicit neutralizing antibodies against the merozoite, and most of these have never been compared directly to RH5. The objective of this study was to compare a range of blood-stage antigens to RH5, to identify any antigens that outperform or synergize with anti-RH5 antibodies. We selected 55 gene products, covering 15 candidate antigens that have been described in the literature and 40 genes selected on the basis of bioinformatics functional prediction. We were able to make 20 protein-in-adjuvant vaccines from the original selection. Of these, S-antigen and CyRPA robustly elicited antibodies with neutralizing properties. Anti-CyRPA IgG generally showed additive GIA with anti-RH5 IgG, although high levels of anti-CyRPA-specific rabbit polyclonal IgG were required to achieve 50% GIA. Our data suggest that further vaccine antigen screening efforts are required to identify a second merozoite target with similar antibody-susceptibility to RH5.

Application of multiplexed ion mobility spectrometry towards the identification of host protein signatures of treatment effect in pulmonary tuberculosis.

RATIONALE: The monitoring of TB treatments in clinical practice and clinical trials relies on traditional sputum-based culture status indicators at specific time points. Accurate, predictive, blood-based protein markers would provide a simpler and more informative view of patient health and response to treatment. OBJECTIVE: We utilized sensitive, high throughput multiplexed ion mobility-mass spectrometry (IM-MS) to characterize the serum proteome of TB patients at the start of and at 8 weeks of rifamycin-based treatment. We sought to identify treatment specific signatures within patients as well as correlate the proteome signatures to various clinical markers of treatment efficacy. METHODS: Serum samples were collected from 289 subjects enrolled in CDC TB Trials Consortium Study 29 at time of enrollment and at the end of the intensive phase (after 40 doses of TB treatment). Serum proteins were immunoaffinity-depleted of high abundant components, digested to peptides and analyzed for data acquisition utilizing a unique liquid chromatography IM-MS platform (LC-IM-MS). Linear mixed models were utilized to identify serum protein changes in the host response to antibiotic treatment as well as correlations with culture status end points. RESULTS: A total of 10,137 peptides corresponding to 872 proteins were identified, quantified, and used for statistical analysis across the longitudinal patient cohort. In response to TB treatment, 244 proteins were significantly altered. Pathway/network comparisons helped visualize the interconnected proteins, identifying up regulated (lipid transport, coagulation cascade, endopeptidase activity) and down regulated (acute phase) processes and pathways in addition to other cross regulated networks (inflammation, cell adhesion, extracellular matrix). Detection of possible lung injury serum proteins such as HPSE, significantly downregulated upon treatment. Analyses of microbiologic data over time identified a core set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2) which change in response to treatment and also strongly correlate with culture status. A similar set of proteins at baseline were found to be predictive of week 6 and 8 culture status. CONCLUSION: A comprehensive host serum protein dataset reflective of TB treatment effect is defined. A repeating set of serum proteins (TTHY, AFAM, CRP, RET4, SAA1, PGRP2, among others) were found to change significantly in response to treatment, to strongly correlate with culture status, and at baseline to be predictive of future culture conversion. If validated in cohorts with long term follow-up to capture failure and relapse of TB, these protein markers could be developed for monitoring of treatment in clinical trials and in patient care.

Multi-platform 'Omics Analysis of Human Ebola Virus Disease Pathogenesis.

The pathogenesis of human Ebola virus disease (EVD) is complex. EVD is characterized by high levels of virus replication and dissemination, dysregulated immune responses, extensive virus- and host-mediated tissue damage, and disordered coagulation. To clarify how host responses contribute to EVD pathophysiology, we performed multi-platform 'omics analysis of peripheral blood mononuclear cells and plasma from EVD patients. Our results indicate that EVD molecular signatures overlap with those of sepsis, imply that pancreatic enzymes contribute to tissue damage in fatal EVD, and suggest that Ebola virus infection may induce aberrant neutrophils whose activity could explain hallmarks of fatal EVD. Moreover, integrated biomarker prediction identified putative biomarkers from different data platforms that differentiated survivors and fatalities early after infection. This work reveals insight into EVD pathogenesis, suggests an effective approach for biomarker identification, and provides an important community resource for further analysis of human EVD severity.

The landscape of viral proteomics and its potential to impact human health.

INTRODUCTION: Advances in mass spectrometry-based proteomic technologies are enhancing studies of viral pathogenesis. Identification and quantification of host and viral proteins and modifications in cells and extracellular fluids during infection provides useful information about pathogenesis, and will be critical for directing clinical interventions and diagnostics. AREAS COVERED: Herein we review and discuss a broad range of global proteomic studies conducted during viral infection, including those of cellular responses, protein modifications, virion packaging, and serum proteomics. We focus on viruses that impact human health and focus on experimental designs that reveal disease processes and surrogate markers. Expert commentary: Global proteomics is an important component of systems-level studies that aim to define how the interaction of humans and viruses leads to disease. Viral-community resource centers and strategies from other fields (e.g., cancer) will facilitate data sharing and platform-integration for systems-level analyses, and should provide recommended standards and assays for experimental designs and validation.

A genome wide association study of Plasmodium falciparum susceptibility to 22 antimalarial drugs in Kenya.

BACKGROUND: Drug resistance remains a chief concern for malaria control. In order to determine the genetic markers of drug resistant parasites, we tested the genome-wide associations (GWA) of sequence-based genotypes from 35 Kenyan P. falciparum parasites with the activities of 22 antimalarial drugs. METHODS AND PRINCIPAL FINDINGS: Parasites isolated from children with acute febrile malaria were adapted to culture, and sensitivity was determined by in vitro growth in the presence of anti-malarial drugs. Parasites were genotyped using whole genome sequencing techniques. Associations between 6250 single nucleotide polymorphisms (SNPs) and resistance to individual anti-malarial agents were determined, with false discovery rate adjustment for multiple hypothesis testing. We identified expected associations in the pfcrt region with chloroquine (CQ) activity, and other novel loci associated with amodiaquine, quinazoline, and quinine activities. Signals for CQ and primaquine (PQ) overlap in and around pfcrt, and interestingly the phenotypes are inversely related for these two drugs. We catalog the variation in dhfr, dhps, mdr1, nhe, and crt, including novel SNPs, and confirm the presence of a dhfr-164L quadruple mutant in coastal Kenya. Mutations implicated in sulfadoxine-pyrimethamine resistance are at or near fixation in this sample set. CONCLUSIONS/SIGNIFICANCE: Sequence-based GWA studies are powerful tools for phenotypic association tests. Using this approach on falciparum parasites from coastal Kenya we identified known and previously unreported genes associated with phenotypic resistance to anti-malarial drugs, and observe in high-resolution haplotype visualizations a possible signature of an inverse selective relationship between CQ and PQ.

Six genes are preferentially transcribed by the circulating and sequestered forms of Plasmodium falciparum parasites that infect pregnant women.

In areas of stable malaria transmission, susceptibility to Plasmodium falciparum malaria increases during first pregnancy. Women become resistant to pregnancy malaria over successive pregnancies as they acquire antibodies against the parasite forms that sequester in the placenta, suggesting that a vaccine is feasible. Placental parasites are antigenically distinct and bind receptors, like chondroitin sulfate A (CSA), that are not commonly bound by other parasites. We used whole-genome-expression analysis to find transcripts that distinguish parasites of pregnant women from other parasites and employed a novel approach to define and adjust for cell cycle timing of parasites. Transcription of six genes was substantially higher in both placental parasites and peripheral parasites from pregnant women, and each gene encodes a protein with a putative export sequence and/or transmembrane domain. This cohort of genes includes var2csa, a member of the variant PfEMP1 gene family previously implicated in pregnancy malaria, as well as five conserved genes of unknown functions. Women in East Africa acquire antibodies over successive pregnancies against a protein encoded by one of these genes, PFD1140w, and this protein shows seroreactivity similar to that of VAR2CSA domains. These findings suggest that a suite of genes may be important for the genesis of the placental binding phenotype of P. falciparum and may provide novel targets for therapeutic intervention.

Gene set coregulated by the Saccharomyces cerevisiae nonsense-mediated mRNA decay pathway.

The nonsense-mediated mRNA decay (NMD) pathway has historically been thought of as an RNA surveillance system that degrades mRNAs with premature translation termination codons, but the NMD pathway of Saccharomyces cerevisiae has a second role regulating the decay of some wild-type mRNAs. In S. cerevisiae, a significant number of wild-type mRNAs are affected when NMD is inactivated. These mRNAs are either wild-type NMD substrates or mRNAs whose abundance increases as an indirect consequence of NMD. A current challenge is to sort the mRNAs that accumulate when NMD is inactivated into direct and indirect targets. We have developed a bioinformatics-based approach to address this challenge. Our approach involves using existing genomic and function databases to identify transcription factors whose mRNAs are elevated in NMD-deficient cells and the genes that they regulate. Using this strategy, we have investigated a coregulated set of genes. We have shown that NMD regulates accumulation of ADR1 and GAL4 mRNAs, which encode transcription activators, and that Adr1 is probably a transcription activator of ATS1. This regulation is physiologically significant because overexpression of ADR1 causes a respiratory defect that mimics the defect seen in strains with an inactive NMD pathway. This strategy is significant because it allows us to classify the genes regulated by NMD into functionally related sets, an important step toward understanding the role NMD plays in the normal functioning of yeast cells.

Mass spectrometric analysis of Plasmodium falciparum erythrocyte membrane protein-1 variants expressed by placental malaria parasites.

Surface proteins from Plasmodium falciparum are important malaria vaccine targets. However, the surface proteins previously identified are highly variant and difficult to study. We used tandem mass spectrometry to characterize the variant antigens (Plasmodium falciparum erythrocyte membrane protein 1 (PfEMP1)) expressed on the surface of malaria-infected erythrocytes that bind to chondroitin sulfate A (CSA) in the placenta. Whereas PfEMP1 variants previously implicated as CSA ligands were detected, in unselected parasites four novel variants were detected in CSA-binding or placental parasites but not in unselected parasites. These novel PfEMP1 variants require further study to confirm whether they play a role in placental malaria.