Using quantitative systems pharmacology for novel drug discovery.

Expert Opin Drug Discov. 2015 Dec;10(12):1315-31

Authors: Pérez-Nueno VI

Abstract
INTRODUCTION: Over the past three decades, the predominant paradigm in drug discovery was designing selective ligands for a specific target to avoid unwanted side effects. However, in the last 5 years, the aim has shifted to take into account the biological network in which they interact. Quantitative and Systems Pharmacology (QSP) is a new paradigm that aims to understand how drugs modulate cellular networks in space and time, in order to predict drug targets and their role in human pathophysiology.
AREAS COVERED: This review discusses existing computational and experimental QSP approaches such as polypharmacology techniques combined with systems biology information and considers the use of new tools and ideas in a wider 'systems-level' context in order to design new drugs with improved efficacy and fewer unwanted off-target effects.
EXPERT OPINION: The use of network biology produces valuable information such as new indications for approved drugs, drug-drug interactions, proteins-drug side effects and pathways-gene associations. However, we are still far from the aim of QSP, both because of the huge effort needed to model precisely biological network models and the limited accuracy that we are able to reach with those. Hence, moving from 'one molecule for one target to give one therapeutic effect' to the 'big systems-based picture' seems obvious moving forward although whether our current tools are sufficient for such a step is still under debate.

PMID: 26328768 [PubMed - indexed for MEDLINE]

Defining bacterial regulons using ChIP-seq.

Methods. 2015 Sep 15;86:80-8

Authors: Myers KS, Park DM, Beauchene NA, Kiley PJ

Abstract
Chromatin immunoprecipitation followed by high-throughput sequencing (ChIP-seq) is a powerful method that identifies protein-DNA binding sites in vivo. Recent studies have illustrated the value of ChIP-seq in studying transcription factor binding in various bacterial species under a variety of growth conditions. These results show that in addition to identifying binding sites, correlation of ChIP-seq data with expression data can reveal important information about bacterial regulons and regulatory networks. In this chapter, we provide an overview of the current state of knowledge about ChIP-seq methodology in bacteria, from sample preparation to raw data analysis. We also describe visualization and various bioinformatic analyses of processed ChIP-seq data.

PMID: 26032817 [PubMed - indexed for MEDLINE]

Systems biology approaches to defining transcription regulatory networks in halophilic archaea.

Methods. 2015 Sep 15;86:102-14

Authors: Darnell CL, Schmid AK

Abstract
To survive complex and changing environmental conditions, microorganisms use gene regulatory networks (GRNs) composed of interacting regulatory transcription factors (TFs) to control the timing and magnitude of gene expression. Genome-wide datasets; such as transcriptomics and protein-DNA interactions; and experiments such as high throughput growth curves; facilitate the construction of GRNs and provide insight into TF interactions occurring under stress. Systems biology approaches integrate these datasets into models of GRN architecture as well as statistical and/or dynamical models to understand the function of networks occurring in cells. Previously, these types of studies have focused on traditional model organisms (e.g. Escherichia coli, yeast). However, recent advances in archaeal genetics and other tools have enabled a systems approach to understanding GRNs in these relatively less studied archaeal model organisms. In this report, we outline a systems biology workflow for generating and integrating data focusing on the TF regulator. We discuss experimental design, outline the process of data collection, and provide the tools required to produce high confidence regulons for the TFs of interest. We provide a case study as an example of this workflow, describing the construction of a GRN centered on multi-TF coordinate control of gene expression governing the oxidative stress response in the hypersaline-adapted archaeon Halobacterium salinarum.

PMID: 25976837 [PubMed - indexed for MEDLINE]

Point process models for localization and interdependence of punctate cellular structures.

Cytometry A. 2016 Jun 21;

Authors: Li Y, Majarian TD, Naik AW, Johnson GR, Murphy RF

Abstract
Accurate representations of cellular organization for multiple eukaryotic cell types are required for creating predictive models of dynamic cellular function. To this end, we have previously developed the CellOrganizer platform, an open source system for generative modeling of cellular components from microscopy images. CellOrganizer models capture the inherent heterogeneity in the spatial distribution, size, and quantity of different components among a cell population. Furthermore, CellOrganizer can generate quantitatively realistic synthetic images that reflect the underlying cell population. A current focus of the project is to model the complex, interdependent nature of organelle localization. We built upon previous work on developing multiple non-parametric models of organelles or structures that show punctate patterns. The previous models described the relationships between the subcellular localization of puncta and the positions of cell and nuclear membranes and microtubules. We extend these models to consider the relationship to the endoplasmic reticulum (ER), and to consider the relationship between the positions of different puncta of the same type. Our results do not suggest that the punctate patterns we examined are dependent on ER position or inter- and intra-class proximity. With these results, we built classifiers to update previous assignments of proteins to one of 11 patterns in three distinct cell lines. Our generative models demonstrate the ability to construct statistically accurate representations of puncta localization from simple cellular markers in distinct cell types, capturing the complex phenomena of cellular structure interaction with little human input. This protocol represents a novel approach to vesicular protein annotation, a field that is often neglected in high-throughput microscopy. These results suggest that spatial point process models provide useful insight with respect to the spatial dependence between cellular structures. © 2016 International Society for Advancement of Cytometry.

PMID: 27327612 [PubMed - as supplied by publisher]

Analysis of in vivo single cell behavior by high throughput, human-in-the-loop segmentation of three-dimensional images.

BMC Bioinformatics. 2015;16:397

Authors: Chiang M, Hallman S, Cinquin A, de Mochel NR, Paz A, Kawauchi S, Calof AL, Cho KW, Fowlkes CC, Cinquin O

Abstract
BACKGROUND: Analysis of single cells in their native environment is a powerful method to address key questions in developmental systems biology. Confocal microscopy imaging of intact tissues, followed by automatic image segmentation, provides a means to conduct cytometric studies while at the same time preserving crucial information about the spatial organization of the tissue and morphological features of the cells. This technique is rapidly evolving but is still not in widespread use among research groups that do not specialize in technique development, perhaps in part for lack of tools that automate repetitive tasks while allowing experts to make the best use of their time in injecting their domain-specific knowledge.
RESULTS: Here we focus on a well-established stem cell model system, the C. elegans gonad, as well as on two other model systems widely used to study cell fate specification and morphogenesis: the pre-implantation mouse embryo and the developing mouse olfactory epithelium. We report a pipeline that integrates machine-learning-based cell detection, fast human-in-the-loop curation of these detections, and running of active contours seeded from detections to segment cells. The procedure can be bootstrapped by a small number of manual detections, and outperforms alternative pieces of software we benchmarked on C. elegans gonad datasets. Using cell segmentations to quantify fluorescence contents, we report previously-uncharacterized cell behaviors in the model systems we used. We further show how cell morphological features can be used to identify cell cycle phase; this provides a basis for future tools that will streamline cell cycle experiments by minimizing the need for exogenous cell cycle phase labels.
CONCLUSIONS: High-throughput 3D segmentation makes it possible to extract rich information from images that are routinely acquired by biologists, and provides insights - in particular with respect to the cell cycle - that would be difficult to derive otherwise.

PMID: 26607933 [PubMed - indexed for MEDLINE]

Applications of targeted proteomics in systems biology and translational medicine.

Proteomics. 2015 Sep;15(18):3193-208

Authors: Ebhardt HA, Root A, Sander C, Aebersold R

Abstract
Biological systems are composed of numerous components of which proteins are of particularly high functional significance. Network models are useful abstractions for studying these components in context. Network representations display molecules as nodes and their interactions as edges. Because they are difficult to directly measure, functional edges are frequently inferred from suitably structured datasets consisting of the accurate and consistent quantification of network nodes under a multitude of perturbed conditions. For the precise quantification of a finite list of proteins across a wide range of samples, targeted proteomics exemplified by selected/multiple reaction monitoring (SRM, MRM) mass spectrometry has proven useful and has been applied to a variety of questions in systems biology and clinical studies. Here, we survey the literature of studies using SRM-MS in systems biology and clinical proteomics. Systems biology studies frequently examine fundamental questions in network biology, whereas clinical studies frequently focus on biomarker discovery and validation in a variety of diseases including cardiovascular disease and cancer. Targeted proteomics promises to advance our understanding of biological networks and the phenotypic significance of specific network states and to advance biomarkers into clinical use.

PMID: 26097198 [PubMed - indexed for MEDLINE]

Molecular mechanism matters: Benefits of mechanistic computational models for drug development.

Pharmacol Res. 2015 Sep;99:149-54

Authors: Clegg LE, Mac Gabhann F

Abstract
Making drug development a more efficient and cost-effective process will have a transformative effect on human health. A key, yet underutilized, tool to aid in this transformation is mechanistic computational modeling. By incorporating decades of hard-won prior knowledge of molecular interactions, cellular signaling, and cellular behavior, mechanistic models can achieve a level of predictiveness that is not feasible using solely empirical characterization of drug pharmacodynamics. These models can integrate diverse types of data from cell culture and animal experiments, including high-throughput systems biology experiments, and translate the results into the context of human disease. This provides a framework for identification of new drug targets, measurable biomarkers for drug action in target tissues, and patient populations for which a drug is likely to be effective or ineffective. Additionally, mechanistic models are valuable in virtual screening of new therapeutic strategies, such as gene or cell therapy and tissue regeneration, identifying the key requirements for these approaches to succeed in a heterogeneous patient population. These capabilities, which are distinct from and complementary to those of existing drug development strategies, demonstrate the opportunity to improve success rates in the drug development pipeline through the use of mechanistic computational models.

PMID: 26093283 [PubMed - indexed for MEDLINE]

Expanding the yeast protein arginine methylome.

Proteomics. 2015 Sep;15(18):3232-43

Authors: Plank M, Fischer R, Geoghegan V, Charles PD, Konietzny R, Acuto O, Pears C, Schofield CJ, Kessler BM

Abstract
Protein arginine methylation is a PTM involved in various cellular processes in eukaryotes. Recent discoveries led to a vast expansion of known sites in higher organisms, indicating that this modification is more widely spread across the proteome than previously assumed. An increased knowledge of sites in lower eukaryotes may facilitate the elucidation of its functions. In this study, we present the discovery of arginine mono-methylation sites in Saccharomyces cerevisiae by a combination of immunoaffinity enrichment and MS/MS. As detection of methylation is prone to yield false positives, we demonstrate the need for stringent measures to avoid elevated false discovery rates. To this end, we employed MethylSILAC in combination with a multistep data analysis strategy. We report 41 unambiguous methylation sites on 13 proteins. Our results indicate that, while substantially less abundant, arginine methylation follows similar patterns as in higher eukaryotes in terms of sequence context and functions of methylated proteins. The majority of sites occur on RNA-binding proteins participating in processes from transcription and splicing to translation and RNA degradation. Additionally, our data suggest a bias for localization of arginine methylation in unstructured regions of proteins, which frequently involves Arg-Gly-Gly motifs or Asn-rich contexts.

PMID: 26046779 [PubMed - indexed for MEDLINE]

Quantitative proteomics and network analysis of SSA1 and SSB1 deletion mutants reveals robustness of chaperone HSP70 network in Saccharomyces cerevisiae.

Proteomics. 2015 Sep;15(18):3126-39

Authors: Jarnuczak AF, Eyers CE, Schwartz JM, Grant CM, Hubbard SJ

Abstract
Molecular chaperones play an important role in protein homeostasis and the cellular response to stress. In particular, the HSP70 chaperones in yeast mediate a large volume of protein folding through transient associations with their substrates. This chaperone interaction network can be disturbed by various perturbations, such as environmental stress or a gene deletion. Here, we consider deletions of two major chaperone proteins, SSA1 and SSB1, from the chaperone network in Sacchromyces cerevisiae. We employ a SILAC-based approach to examine changes in global and local protein abundance and rationalise our results via network analysis and graph theoretical approaches. Although the deletions result in an overall increase in intracellular protein content, correlated with an increase in cell size, this is not matched by substantial changes in individual protein concentrations. Despite the phenotypic robustness to deletion of these major hub proteins, it cannot be simply explained by the presence of paralogues. Instead, network analysis and a theoretical consideration of folding workload suggest that the robustness to perturbation is a product of the overall network structure. This highlights how quantitative proteomics and systems modelling can be used to rationalise emergent network properties, and how the HSP70 system can accommodate the loss of major hubs.

PMID: 25689132 [PubMed - indexed for MEDLINE]

Safety and Immunogenicity of the Recombinant BCG Vaccine AERAS-422 in Healthy BCG-naïve Adults: A Randomized, Active-controlled, First-in-human Phase 1 Trial.

EBioMedicine. 2016 May;7:278-286

Authors: Hoft DF, Blazevic A, Selimovic A, Turan A, Tennant J, Abate G, Fulkerson J, Zak DE, Walker R, McClain B, Sadoff J, Scott J, Shepherd B, Ishmukhamedov J, Hokey DA, Dheenadhayalan V, Shankar S, Amon L, Navarro G, Podyminogin R, Aderem A, Barker L, Brennan M, Wallis RS, Gershon AA, Gershon MD, Steinberg S

Abstract
BACKGROUND: We report a first-in-human trial evaluating safety and immunogenicity of a recombinant BCG, AERAS-422, over-expressing TB antigens Ag85A, Ag85B, and Rv3407 and expressing mutant perfringolysin.
METHODS: This was a randomized, double-blind, dose-escalation trial in HIV-negative, healthy adult, BCG-naïve volunteers, negative for prior exposure to Mtb, at one US clinical site. Volunteers were randomized 2:1 at each dose level to receive a single intradermal dose of AERAS-422 (>10(5)-<10(6)CFU=low dose, ≥10(6)-<10(7)CFU=high dose) or non-recombinant Tice BCG (1-8×10(5)CFU). Randomization used an independently prepared randomly generated sequence of treatment assignments. The primary and secondary outcomes were safety and immunogenicity, respectively, assessed in all participants through 182days post-vaccination. ClinicalTrials.gov registration number: NCT01340820.
FINDINGS: Between Nov 2010 and Aug 2011, 24 volunteers were enrolled (AERAS-422 high dose, n=8; AERAS-422 low dose, n=8; Tice BCG, n=8); all were included in the safety and immunogenicity analyses. All 24 subjects had at least one adverse event, primarily expected local reactions. High dose AERAS-422 vaccination induced Ag85A- and Ag85B-specific lymphoproliferative responses and marked anti-mycobacterial activity in a whole blood bactericidal activity culture assay (WBA), but was associated with varicella zoster virus (VZV) reactivation in two vaccinees. These volunteers displayed high BCG-specific IFN-γ responses pre- and post-vaccination possibly predisposing them to autocrine/paracrine negative regulation of immune control of latent VZV. A systems biology transcriptomal approach identified positive correlations between post-vaccination T cell expression modules and WBA, and negative correlations between post-vaccination monocyte expression modules and WBA. The expression of one key macrophage marker (F4/80) was constitutively elevated in the two volunteers with zoster.
INTERPRETATION: The unexpected development of VZV in two of eight healthy adult vaccine recipients resulted in discontinuation of AERAS-422 vaccine development. Immunological and transcriptomal data identified correlations with the development of TB immunity and VZV that require further investigation.
FUNDING: Aeras, FDA, Bill and Melinda Gates Foundation.

PMID: 27322481 [PubMed - as supplied by publisher]

Understanding probiotics' role in allergic children: the clue of gut microbiota profiling.

Curr Opin Allergy Clin Immunol. 2015 Oct;15(5):495-503

Authors: Vernocchi P, Del Chierico F, Fiocchi AG, El Hachem M, Dallapiccola B, Rossi P, Putignani L

Abstract
PURPOSE OF REVIEW: To investigate the functional role of gut microbiota in diet-modulated diseases, evaluating probiotic administration effects by systems biology-driven approaches. Understanding the role of host-gut microbial and gut microbe-microbe interactions in either allergic and healthy children may assist in selecting effective and targeted probiotics for personalized therapies.
RECENT FINDINGS: Food allergy shows a significant increase, especially in Western countries where growing epidemiological data indicate prevalence of small family groups, limited rate of infections in childhood compared with low-income countries, high consumption of sterile foods, hence stimulating a poor trigger of the gut immune system. Therefore, new therapeutic strategies to treat food allergy consist of probiotic administration since early life, thus modulating gut microbiota through immune system stimulation at the mucosal level.
SUMMARY: Currently, new insights for probiotic selection should take into consideration both phenotyping and genotyping bacterial features and host-microbial cross-talk at gut level, by employing multicomponent systems biology approaches to unveil gut ecosystem dynamics in terms of bacteria phylotypes and their metabolic activities. Moreover, new food processes need to be considered to assess the actual performance of probiotic strains administered to allergic patients. The advent of high-performance platforms employing genomic- and mass spectrometry-based techniques has opened new perspectives on the gut microbiota field, and may now serve as advanced tool to dynamically investigate the interplay between probiotics and gut microbiota ecology under allergic conditions.

PMID: 26258924 [PubMed - indexed for MEDLINE]

Malaria vaccine clinical trials: what's on the horizon.

Curr Opin Immunol. 2015 Aug;35:98-106

Authors: Moreno A, Joyner C

Abstract
Significant progress toward a malaria vaccine, specifically for Plasmodium falciparum, has been made in the past few years with the completion of numerous clinical trials. Each trial has utilized a unique combination of antigens, delivery platforms, and adjuvants, which has provided the research community with a wealth of critical information to apply towards the development of next generation malaria vaccines. Despite the progress toward a P. falciparum vaccine, P. vivax vaccine research requires more momentum and additional investigations to identify novel vaccine candidates. In this review, recently completed and ongoing malaria vaccine clinical trials as well as vaccine candidates that are in the development pipeline are reviewed. Perspectives for future research using post-genomic mining, nonhuman primate models, and systems biology are also discussed.

PMID: 26172291 [PubMed - indexed for MEDLINE]

Evolutionary trends and functional anatomy of the human expanded autophagy network.

Autophagy. 2015;11(9):1652-67

Authors: Till A, Saito R, Merkurjev D, Liu JJ, Syed GH, Kolnik M, Siddiqui A, Glas M, Scheffler B, Ideker T, Subramani S

Abstract
All eukaryotic cells utilize autophagy for protein and organelle turnover, thus assuring subcellular quality control, homeostasis, and survival. In order to address recent advances in identification of human autophagy associated genes, and to describe autophagy on a system-wide level, we established an autophagy-centered gene interaction network by merging various primary data sets and by retrieving respective interaction data. The resulting network ('AXAN') was analyzed with respect to subnetworks, e.g. the prime gene subnetwork (including the core machinery, signaling pathways and autophagy receptors) and the transcription subnetwork. To describe aspects of evolution within this network, we assessed the presence of protein orthologs across 99 eukaryotic model organisms. We visualized evolutionary trends for prime gene categories and evolutionary tracks for selected AXAN genes. This analysis confirms the eukaryotic origin of autophagy core genes while it points to a diverse evolutionary history of autophagy receptors. Next, we used module identification to describe the functional anatomy of the network at the level of pathway modules. In addition to obvious pathways (e.g., lysosomal degradation, insulin signaling) our data unveil the existence of context-related modules such as Rho GTPase signaling. Last, we used a tripartite, image-based RNAi - screen to test candidate genes predicted to play a role in regulation of autophagy. We verified the Rho GTPase, CDC42, as a novel regulator of autophagy-related signaling. This study emphasizes the applicability of system-wide approaches to gain novel insights into a complex biological process and to describe the human autophagy pathway at a hitherto unprecedented level of detail.

PMID: 26103419 [PubMed - indexed for MEDLINE]

Analysis of Wnt signalling dynamics during colon crypt development in 3D culture.

Sci Rep. 2015;5:11036

Authors: Tan CW, Hirokawa Y, Burgess AW

Abstract
Many systems biology studies lack context-relevant data and as a consequence the predictive capabilities can be limited in developing targeted cancer therapeutics. Production of colon crypt in vitro is ideal for studying colon systems biology. This report presents the first production of, to our knowledge, physiologically-shaped, functional colon crypts in vitro (i.e. single crypts with cells expressing Mucin 2 and Chromogranin A). Time-lapsed monitoring of crypt formation revealed an increased frequency of single-crypt formation in the absence of noggin. Using quantitative 3D immunofluorescence of β-catenin and E-cadherin, spatial-temporal dynamics of these proteins in normal colon crypt cells stimulated with Wnt3A or inhibited by cycloheximide has been measured. Colon adenoma cultures established from APC(min/+) mouse have developmental differences and β-catenin spatial localization compared to normal crypts. Quantitative data describing the effects of signalling pathways and proteins dynamics for both normal and adenomatous colon crypts is now within reach to inform a systems approach to colon crypt biology.

PMID: 26087250 [PubMed - indexed for MEDLINE]

Metabolic Profiling and Phenotyping of Central Nervous System Diseases: Metabolites Bring Insights into Brain Dysfunctions.

J Neuroimmune Pharmacol. 2015 Sep;10(3):402-24

Authors: Dumas ME, Davidovic L

Abstract
Metabolic phenotyping corresponds to the large-scale quantitative and qualitative analysis of the metabolome i.e., the low-molecular weight <1 KDa fraction in biological samples, and provides a key opportunity to advance neurosciences. Proton nuclear magnetic resonance and mass spectrometry are the main analytical platforms used for metabolic profiling, enabling detection and quantitation of a wide range of compounds of particular neuro-pharmacological and physiological relevance, including neurotransmitters, secondary messengers, structural lipids, as well as their precursors, intermediates and degradation products. Metabolic profiling is therefore particularly indicated for the study of central nervous system by probing metabolic and neurochemical profiles of the healthy or diseased brain, in preclinical models or in human samples. In this review, we introduce the analytical and statistical requirements for metabolic profiling. Then, we focus on key studies in the field of metabolic profiling applied to the characterization of animal models and human samples of central nervous system disorders. We highlight the potential of metabolic profiling for pharmacological and physiological evaluation, diagnosis and drug therapy monitoring of patients affected by brain disorders. Finally, we discuss the current challenges in the field, including the development of systems biology and pharmacology strategies improving our understanding of metabolic signatures and mechanisms of central nervous system diseases.

PMID: 25616565 [PubMed - indexed for MEDLINE]

Integrated Genomic and Network-Based Analyses of Complex Diseases and Human Disease Network.

J Genet Genomics. 2015 Dec 15;

Authors: Al-Harazi O, Al Insaif S, Al-Ajlan MA, Kaya N, Dzimiri N, Colak D

Abstract
A disease phenotype generally reflects various pathobiological processes that interact in a complex network. The highly interconnected nature of the human protein interaction network (interactome) indicates that, at the molecular level, it is difficult to consider diseases as being independent of one another. Recently, genome-wide molecular measurements, data mining and bioinformatics approaches have provided the means to explore human diseases from a molecular basis. The exploration of diseases and a system of disease relationships based on the integration of genome-wide molecular data with the human interactome could offer a powerful perspective for understanding the molecular architecture of diseases. Recently, subnetwork markers have proven to be more robust and reliable than individual biomarker genes selected based on gene expression profiles alone, and achieve higher accuracy in disease classification. We have applied one of these methodologies to idiopathic dilated cardiomyopathy (IDCM) data that we have generated using a microarray and identified significant subnetworks associated with the disease. In this paper, we review the recent endeavours in this direction, and summarize the existing methodologies and computational tools for network-based analysis of complex diseases and molecular relationships among apparently different disorders and human disease network. We also discuss the future research trends and topics of this promising field.

PMID: 27318646 [PubMed - as supplied by publisher]

Genetic heterogeneity in autism: From single gene to a pathway perspective.

Neurosci Biobehav Rev. 2016 Jun 15;

Authors: An JY, Claudianos C

Abstract
The extreme genetic heterogeneity of autism spectrum disorder (ASD) represents a major challenge. Recent advances in genetic screening and systems biology approaches have extended our knowledge of the genetic etiology of ASD. In this review, we discuss the paradigm shift from a single gene causation model to pathway perturbation model as a guide to better understand the pathophysiology of ASD. We discuss recent genetic findings obtained through next-generation sequencing (NGS) and examine various integrative analyses using systems biology and complex networks approaches that identify convergent patterns of genetic elements associated with ASD.

PMID: 27317861 [PubMed - as supplied by publisher]

Label-free Quantification of Proteins in Single Embryonic Cells with Neural Fate in the Cleavage-Stage Frog (Xenopus laevis) Embryo using CE-ESI-HRMS.

Mol Cell Proteomics. 2016 Jun 17;

Authors: Lombard-Banek C, Reddy S, Moody SA, Nemes P

Abstract
Quantification of protein expression in single cells promises to advance a systems-level understanding of normal development. Using a bottom-up proteomic workflow and multiplexing quantification by tandem mass tags, we recently demonstrated relative quantification between single embryonic cells (blastomeres) in the frog (Xenopus laevis) embryo. In this study, we minimize derivatization steps to enhance analytical sensitivity and use label-free quantification (LFQ) for single Xenopus cells. The technology builds on a custom-designed capillary electrophoresis microflow-electrospray ionization high-resolution mass spectrometry platform and LFQ by MaxLFQ (MaxQuant). By judiciously tailoring performance to peptide separation, ionization, and data-dependent acquisition, we demonstrate an ~75-amol (~11 nM) lower limit of detection and quantification for proteins in complex cell digests. The platform enabled the identification of 438 non-redundant protein groups by measuring 16 ng of protein digest, or <0.2% of the total protein contained in a blastomere in the 16-cell embryo. LFQ intensity was validated as a quantitative proxy for protein abundance. Correlation analysis was performed to compare protein quantities between the embryo and n = 3 different single D11 blastomeres, which are fated to develop into the nervous system. A total of 335 non-redundant protein groups were quantified in union between the single D11 cells spanning a 4 log-order concentration range. LFQ and correlation analysis detected expected proteomic differences between the whole embryo and blastomeres, and also found translational differences between individual D11 cells. LFQ on single cells raises exciting possibilities to study gene expression in other cells and models to help better understand cell processes on a systems biology level.

PMID: 27317400 [PubMed - as supplied by publisher]

Airway remodeling: Systems biology approach, from bench to bedside.

Technol Health Care. 2016 Jun 10;

Authors: Najafi A, Ghanei M, Jamalkandi SA

Abstract
Airway Remodeling, a patho-physiologic process, is considered as a key feature of chronic airway diseases. In recent years, our understanding of the complex diseases has increased significantly by the use of combined approaches, including systems biology, which may contribute to the development of personalized and predictive medicine approaches. Integrative analysis, along with the cooperation of clinicians, computer scientists, research scientists, and bench scientists, has become an important part of the experimental design and therapeutic strategies in the era of omics. The airway remodeling process is the result of the dysregulation of several signaling pathways that modulate the airway regeneration; therefore, high-throughput experiments and systems biology approach can help to understand this process better. The study reviews related literature and is consistent with the existing clinical evidence.

PMID: 27315153 [PubMed - as supplied by publisher]

Differential RNA-seq, Multi-Network Analysis and Metabolic Regulation Analysis of Kluyveromyces marxianus Reveals a Compartmentalised Response to Xylose.

PLoS One. 2016;11(6):e0156242

Authors: Schabort DT, Letebele PK, Steyn L, Kilian SG, du Preez JC

Abstract
We investigated the transcriptomic response of a new strain of the yeast Kluyveromyces marxianus, in glucose and xylose media using RNA-seq. The data were explored in a number of innovative ways using a variety of networks types, pathway maps, enrichment statistics, reporter metabolites and a flux simulation model, revealing different aspects of the genome-scale response in an integrative systems biology manner. The importance of the subcellular localisation in the transcriptomic response is emphasised here, revealing new insights. As was previously reported by others using a rich medium, we show that peroxisomal fatty acid catabolism was dramatically up-regulated in a defined xylose mineral medium without fatty acids, along with mechanisms to activate fatty acids and transfer products of β-oxidation to the mitochondria. Notably, we observed a strong up-regulation of the 2-methylcitrate pathway, supporting capacity for odd-chain fatty acid catabolism. Next we asked which pathways would respond to the additional requirement for NADPH for xylose utilisation, and rationalised the unexpected results using simulations with Flux Balance Analysis. On a fundamental level, we investigated the contribution of the hierarchical and metabolic regulation levels to the regulation of metabolic fluxes. Metabolic regulation analysis suggested that genetic level regulation plays a major role in regulating metabolic fluxes in adaptation to xylose, even for the high capacity reactions, which is unexpected. In addition, isozyme switching may play an important role in re-routing of metabolic fluxes in subcellular compartments in K. marxianus.

PMID: 27315089 [PubMed - as supplied by publisher]