qFlow Cytometry-Based Receptoromic Screening: A High-Throughput Quantification Approach Informing Biomarker Selection and Nanosensor Development.

Methods Mol Biol. 2017;1570:117-138

Authors: Chen S, Weddell J, Gupta P, Conard G, Parkin J, Imoukhuede PI

Abstract
Nanosensor-based detection of biomarkers can improve medical diagnosis; however, a critical factor in nanosensor development is deciding which biomarker to target, as most diseases present several biomarkers. Biomarker-targeting decisions can be informed via an understanding of biomarker expression. Currently, immunohistochemistry (IHC) is the accepted standard for profiling biomarker expression. While IHC provides a relative mapping of biomarker expression, it does not provide cell-by-cell readouts of biomarker expression or absolute biomarker quantification. Flow cytometry overcomes both these IHC challenges by offering biomarker expression on a cell-by-cell basis, and when combined with calibration standards, providing quantitation of biomarker concentrations: this is known as qFlow cytometry. Here, we outline the key components for applying qFlow cytometry to detect biomarkers within the angiogenic vascular endothelial growth factor receptor family. The key aspects of the qFlow cytometry methodology include: antibody specificity testing, immunofluorescent cell labeling, saturation analysis, fluorescent microsphere calibration, and quantitative analysis of both ensemble and cell-by-cell data. Together, these methods enable high-throughput quantification of biomarker expression.

PMID: 28238133 [PubMed - in process]

Proteome and secretome analysis reveals differential post-transcriptional regulation of Toll-like receptor responses.

Mol Cell Proteomics. 2017 Feb 24;:

Authors: Koppenol-Raab M, Sjoelund VH, Manes NP, Gottschalk RA, Dutta B, Benet ZL, Fraser ID, Nita-Lazar A

Abstract
The innate immune system is the organism's first line of defense against pathogens. Pattern recognition receptors (PRRs) are responsible for sensing the presence of pathogen-associated molecules. The prototypic PRRs, the membrane-bound receptors of the Toll-like receptor (TLR) family, recognize pathogen-associated molecular patterns (PAMPs) and initiate an innate immune response through signaling pathways that depend on the adaptor molecules MyD88 and TRIF. Deciphering the differences in the complex signaling events that lead to pathogen recognition and initiation of the correct response remains challenging. Here we report the discovery of temporal changes in the protein signaling components involved in innate immunity. Using an integrated strategy combining unbiased proteomics, transcriptomics and macrophage stimulations with three different PAMPs, we identified differences in signaling between individual TLRs and revealed specifics of pathway regulation at the protein level.

PMID: 28235783 [PubMed - as supplied by publisher]

Biomarker-driven phenotyping in Parkinson's disease: A translational missing link in disease-modifying clinical trials.

Mov Disord. 2017 Feb 24;:

Authors: Espay AJ, Schwarzschild MA, Tanner CM, Fernandez HH, Simon DK, Leverenz JB, Merola A, Chen-Plotkin A, Brundin P, Kauffman MA, Erro R, Kieburtz K, Woo D, Macklin EA, Standaert DG, Lang AE

Abstract
Past clinical trials of putative neuroprotective therapies have targeted PD as a single pathogenic disease entity. From an Oslerian clinicopathological perspective, the wide complexity of PD converges into Lewy bodies and justifies a reductionist approach to PD: A single-mechanism therapy can affect most of those sharing the classic pathological hallmark. From a systems-biology perspective, PD is a group of disorders that, while related by sharing the feature of nigral dopamine-neuron degeneration, exhibit unique genetic, biological, and molecular abnormalities, which probably respond differentially to a given therapeutic approach, particularly for strategies aimed at neuroprotection. Under this model, only biomarker-defined, homogenous subtypes of PD are likely to respond optimally to therapies proven to affect the biological processes within each subtype. Therefore, we suggest that precision medicine applied to PD requires a reevaluation of the biomarker-discovery effort. This effort is currently centered on correlating biological measures to clinical features of PD and on identifying factors that predict whether various prodromal states will convert into the classical movement disorder. We suggest, instead, that subtyping of PD requires the reverse view, where abnormal biological signals (i.e., biomarkers), rather than clinical definitions, are used to define disease phenotypes. Successful development of disease-modifying strategies will depend on how relevant the specific biological processes addressed by an intervention are to the pathogenetic mechanisms in the subgroup of targeted patients. This precision-medicine approach will likely yield smaller, but well-defined, subsets of PD amenable to successful neuroprotection. © 2017 International Parkinson and Movement Disorder Society.

PMID: 28233927 [PubMed - as supplied by publisher]

Perspectives and Challenges of Microbial Application for Crop Improvement.

Front Plant Sci. 2017;8:49

Authors: Timmusk S, Behers L, Muthoni J, Muraya A, Aronsson AC

Abstract
Global population increases and climate change pose a challenge to worldwide crop production. There is a need to intensify agricultural production in a sustainable manner and to find solutions to combat abiotic stress, pathogens, and pests. Plants are associated with complex microbiomes, which have an ability to promote plant growth and stress tolerance, support plant nutrition, and antagonize plant pathogens. The integration of beneficial plant-microbe and microbiome interactions may represent a promising sustainable solution to improve agricultural production. The widespread commercial use of the plant beneficial microorganisms will require a number of issues addressed. Systems approach using microscale information technology for microbiome metabolic reconstruction has potential to advance the microbial reproducible application under natural conditions.

PMID: 28232839 [PubMed - in process]

Principles of Systems Biology, No. 14.

Cell Syst. 2017 Feb 22;4(2):140-143

Authors:

Abstract
This month: sage advice from phage to their offspring; systematic analyses of protein quality control, mitochondrial respiration, and woody biomass; a continental-scale experiment; and engineered protein tools galore.

PMID: 28231445 [PubMed - in process]

Biologically Relevant Heterogeneity: Metrics and Practical Insights.

SLAS Discov. 2017 Mar;22(3):213-237

Authors: Gough A, Stern AM, Maier J, Lezon T, Shun TY, Chennubhotla C, Schurdak ME, Haney SA, Taylor DL

Abstract
Heterogeneity is a fundamental property of biological systems at all scales that must be addressed in a wide range of biomedical applications, including basic biomedical research, drug discovery, diagnostics, and the implementation of precision medicine. There are a number of published approaches to characterizing heterogeneity in cells in vitro and in tissue sections. However, there are no generally accepted approaches for the detection and quantitation of heterogeneity that can be applied in a relatively high-throughput workflow. This review and perspective emphasizes the experimental methods that capture multiplexed cell-level data, as well as the need for standard metrics of the spatial, temporal, and population components of heterogeneity. A recommendation is made for the adoption of a set of three heterogeneity indices that can be implemented in any high-throughput workflow to optimize the decision-making process. In addition, a pairwise mutual information method is suggested as an approach to characterizing the spatial features of heterogeneity, especially in tissue-based imaging. Furthermore, metrics for temporal heterogeneity are in the early stages of development. Example studies indicate that the analysis of functional phenotypic heterogeneity can be exploited to guide decisions in the interpretation of biomedical experiments, drug discovery, diagnostics, and the design of optimal therapeutic strategies for individual patients.

PMID: 28231035 [PubMed - in process]

Conceptual Foundations of Systems Biology Explaining Complex Cardiac Diseases.

Healthcare (Basel). 2017 Feb 21;5(1):

Authors: Louridas GE, Lourida KG

Abstract
Systems biology is an important concept that connects molecular biology and genomics with computing science, mathematics and engineering. An endeavor is made in this paper to associate basic conceptual ideas of systems biology with clinical medicine. Complex cardiac diseases are clinical phenotypes generated by integration of genetic, molecular and environmental factors. Basic concepts of systems biology like network construction, modular thinking, biological constraints (downward biological direction) and emergence (upward biological direction) could be applied to clinical medicine. Especially, in the field of cardiology, these concepts can be used to explain complex clinical cardiac phenotypes like chronic heart failure and coronary artery disease. Cardiac diseases are biological complex entities which like other biological phenomena can be explained by a systems biology approach. The above powerful biological tools of systems biology can explain robustness growth and stability during disease process from modulation to phenotype. The purpose of the present review paper is to implement systems biology strategy and incorporate some conceptual issues raised by this approach into the clinical field of complex cardiac diseases. Cardiac disease process and progression can be addressed by the holistic realistic approach of systems biology in order to define in better terms earlier diagnosis and more effective therapy.

PMID: 28230815 [PubMed - in process]

Biologically plausible learning in recurrent neural networks reproduces neural dynamics observed during cognitive tasks.

Elife. 2017 Feb 23;6:

Authors: Miconi T

Abstract
Neural activity during cognitive tasks exhibits complex dynamics that flexibly encode task-relevant variables. Chaotic recurrent networks, which spontaneously generate rich dynamics, have been proposed as a model of cortical computation during cognitive tasks. However, existing methods for training these networks are either biologically implausible, and/or require a continuous, real-time error signal to guide learning. Here we show that a biologically plausible learning rule can train such recurrent networks, guided solely by delayed, phasic rewards at the end of each trial. Networks endowed with this learning rule can successfully learn nontrivial tasks requiring flexible (context-dependent) associations, memory maintenance, nonlinear mixed selectivities, and coordination among multiple outputs. The resulting networks replicate complex dynamics previously observed in animal cortex, such as dynamic encoding of task features and selective integration of sensory inputs. We conclude that recurrent neural networks offer a plausible model of cortical dynamics during both learning and performance of flexible behavior.

PMID: 28230528 [PubMed - as supplied by publisher]

Research in Reproduction: Challenges, Needs, and Opportunities.

Front Physiol. 2017;8:46

Authors: Ivell R

PMID: 28228729 [PubMed - in process]

Relationship between salivary/pancreatic amylase and body mass index: a systems biology approach.

BMC Med. 2017 Feb 23;15(1):37

Authors: Bonnefond A, Yengo L, Dechaume A, Canouil M, Castelain M, Roger E, Allegaert F, Caiazzo R, Raverdy V, Pigeyre M, Arredouani A, Borys JM, Lévy-Marchal C, Weill J, Roussel R, Balkau B, Marre M, Pattou F, Brousseau T, Froguel P

Abstract
BACKGROUND: Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach.
METHODS: We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity.
RESULTS: We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation.
CONCLUSIONS: These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.

PMID: 28228143 [PubMed - in process]

Identifying disease network perturbations through regression on gene expression and pathway topology analysis.

Conf Proc IEEE Eng Med Biol Soc. 2016 Aug;2016:5969-5972

Authors: Dimitrakopoulos GN, Balomenos P, Vrahatis AG, Sgarbas K, Bezerianos A, Dimitrakopoulos GN, Balomenos P, Vrahatis AG, Sgarbas K, Bezerianos A, Sgarbas K, Balomenos P, Dimitrakopoulos GN, Bezerianos A, Vrahatis AG

Abstract
In Systems Biology, network-based approaches have been extensively used to effectively study complex diseases. An important challenge is the detection of network perturbations which disrupt regular biological functions as a result of a disease. In this regard, we introduce a network based pathway analysis method which isolates casual interactions with significant regulatory roles within diseased-perturbed pathways. Specifically, we use gene expression data with Random Forest regression models to assess the interactivity strengths of genes within disease-perturbed networks, using KEGG pathway maps as a source of prior-knowledge pertaining to pathway topology. We deliver as output a network with imprinted perturbations corresponding to the biological phenomena arising in a disease-oriented experiment. The efficacy of our approach is demonstrated on a serous papillary ovarian cancer experiment and results highlight the functional roles of high impact interactions and key gene regulators which cause strong perturbations on pathway networks, in accordance with experimentally validated knowledge from recent literature.

PMID: 28227870 [PubMed - in process]

An in silico model of the effects of vitamin D3 on mycobacterium infected macrophage.

Conf Proc IEEE Eng Med Biol Soc. 2016 Aug;2016:1443-1446

Authors: Gough M, May E, Gough M, May E, Gough M, May E

Abstract
Mycobacterium tuberculosis is a global health concern, causing over one million deaths a year. Alveolar macrophages, as the primary host cell of this intracellular bacterium, play an important role in the course of disease. Vitamin D3 is known to have a potent effect on macrophage behavior during infection, modulating the production of pro- and anti-inflammatory cytokines and immune effector molecules. In a vitamin D3 deficient host, the immune systems response to infection is greatly impaired. We used a quantitative systems biology approach to model the intracellular effects of vitamin D3 and compared our simulation output to our in vitro model of mycobacterium infection of macrophages in the presence and absence of Vitamin D3. Our in silico model results agreed with the in vitro assay results of interleukin-10, an anti-inflammatory protein whose production is known to be influenced by vitamin D3. This model will provide a platform for further investigation of the effects of vitamin D3 deficiency on host immune response to infection.

PMID: 28226776 [PubMed - in process]

Bottom-up and top-down computations in word- and face-selective cortex.

Elife. 2017 Feb 22;6:

Authors: Kay KN, Yeatman JD

Abstract
The ability to read a page of text or recognize a person's face depends on category-selective visual regions in ventral temporal cortex (VTC). To understand how these regions mediate word and face recognition, it is necessary to characterize how stimuli are represented and how this representation is used in the execution of a cognitive task. Here, we show that the response of a category-selective region in VTC can be computed as the degree to which the low-level properties of the stimulus match a category template. Moreover, we show that during execution of a task, the bottom-up representation is scaled by the intraparietal sulcus (IPS), and that the level of IPS engagement reflects the cognitive demands of the task. These results provide an account of neural processing in VTC in the form of a model that addresses both bottom-up and top-down effects and quantitatively predicts VTC responses.

PMID: 28226243 [PubMed - as supplied by publisher]

Cynomolgus macaques naturally infected with Trypanosoma cruzi-I exhibit an overall mixed pro-inflammatory/modulated cytokine signature characteristic of human Chagas disease.

PLoS Negl Trop Dis. 2017 Feb;11(2):e0005233

Authors: Vitelli-Avelar DM, Sathler-Avelar R, Mattoso-Barbosa AM, Gouin N, Perdigão-de-Oliveira M, Valério-Dos-Reis L, Costa RP, Elói-Santos SM, Gomes MS, Amaral LR, Teixeira-Carvalho A, Martins-Filho OA, Dick EJ, Hubbard GB, VandeBerg JF, VandeBerg JL

Abstract
BACKGROUND: Non-human primates have been shown to be useful models for Chagas disease. We previously reported that natural T. cruzi infection of cynomolgus macaques triggers clinical features and immunophenotypic changes of peripheral blood leukocytes resembling those observed in human Chagas disease. In the present study, we further characterize the cytokine-mediated microenvironment to provide supportive evidence of the utility of cynomolgus macaques as a model for drug development for human Chagas disease.
METHODS AND FINDINGS: In this cross-sectional study design, flow cytometry and systems biology approaches were used to characterize the ex vivo and in vitro T. cruzi-specific functional cytokine signature of circulating leukocytes from TcI-T. cruzi naturally infected cynomolgus macaques (CH). Results showed that CH presented an overall CD4+-derived IFN-γ pattern regulated by IL-10-derived from CD4+ T-cells and B-cells, contrasting with the baseline profile observed in non-infected hosts (NI). Homologous TcI-T. cruzi-antigen recall in vitro induced a broad pro-inflammatory cytokine response in CH, mediated by TNF from innate/adaptive cells, counterbalanced by monocyte/B-cell-derived IL-10. TcIV-antigen triggered a more selective cytokine signature mediated by NK and T-cell-derived IFN-γ with modest regulation by IL-10 from T-cells. While NI presented a cytokine network comprised of small number of neighborhood connections, CH displayed a complex cross-talk amongst network elements. Noteworthy, was the ability of TcI-antigen to drive a complex global pro-inflammatory network mediated by TNF and IFN-γ from NK-cells, CD4+ and CD8+ T-cells, regulated by IL-10+CD8+ T-cells, in contrast to the TcIV-antigens that trigger a modest network, with moderate connecting edges.
CONCLUSIONS: Altogether, our findings demonstrated that CH present a pro-inflammatory/regulatory cytokine signature similar to that observed in human Chagas disease. These data bring additional insights that further validate these non-human primates as experimental models for Chagas disease.

PMID: 28225764 [PubMed - in process]

IL-1β induced and p38(MAPK)-dependent activation of the mitogen-activated protein kinase (MAPK)-activated protein kinase (MK) 2 in hepatocytes: signal transduction with robust and concentration-independent signal amplification.

J Biol Chem. 2017 Feb 21;:

Authors: Kulawik A, Engesser R, Ehlting C, Raue A, Albrecht U, Hahn B, Lehmann WD, Gaestel M, Klingmüller U, Häussinger D, Timmer J, Bode JG

Abstract
The Interleukin (IL)-1β induced activation of the p38(MAPK)/MK2 pathway in hepatocytes is important for the control of acute phase response and regulation of liver regeneration. Many aspects of regulatory relevance of this pathway have been investigated in immune cells in the context of inflammation. However, very little is known about concentration-dependent activation kinetics and signal propagation in hepatocytes and the role of MK2. We established a mathematical model for IL-1β induced activation of the p38(MAPK)/MK2 pathway in hepatocytes that was calibrated to quantitative data on time- and IL-1β concentration-dependent phosphorylation of p38(MAPK) and MK2 in primary mouse hepatocytes. This analysis showed that in hepatocytes signal transduction from IL-1β via p38(MAPK) to MK2 is characterized by strong signal amplification. Quantification of p38(MAPK) and MK2 revealed that in hepatocytes at maximum 11.3 % of p38(MAPK) molecules and 36.5 % of MK2 molecules are activated in response to IL-1β. The mathematical model was experimentally validated employing phosphatase inhibitors and the p38(MAPK) inhibitor SB203580. Model simulations predicted an IC50 of 1 μM - 1.2 μM for SB203580 in hepatocytes. In silico analyses and experimental validation demonstrated that kinase activity of p38(MAPK) determines signal amplitude while phosphatase activity affects both signal amplitude and duration. p38(MAPK) and MK2 concentrations and responsiveness towards IL-1β was quantitatively compared between hepatocytes and macrophages. In macrophages the absolute p38(MAPK) and MK2 concentration was significantly higher. Finally, in line with experimental observations the mathematical model predicted a significantly higher EC50 for IL-1β induced pathway activation in macrophages compared to hepatoyces underscoring the importance of cell-type specific differences in pathway regulation.

PMID: 28223354 [PubMed - as supplied by publisher]

Biomechanical aspects of axonal damage in glaucoma: A brief review.

Exp Eye Res. 2017 Feb 18;:

Authors: Stowell C, Burgoyne C, Tamm ER, Ethier CR, Lasker/IRRF Initiative on Astrocytes and Glaucomatous Neurodegeneration Participants

Abstract
The biomechanical environment within the optic nerve head (ONH) is complex and is likely directly involved in the loss of retinal ganglion cells (RGCs) in glaucoma. Unfortunately, our understanding of this process is poor. Here we describe factors that influence ONH biomechanics, including ONH connective tissue microarchitecture and anatomy; intraocular pressure (IOP); and cerebrospinal fluid pressure (CSFp). We note that connective tissue factors can vary significantly from one individual to the next, as well as regionally within an eye, and that the understanding of ONH biomechanics is hindered by anatomical differences between small-animal models of glaucoma (rats and mice) and humans. Other challenges of using animal models of glaucoma to study the role of biomechanics include the complexity of assessing the degree of glaucomatous progression; and inadequate tools for monitoring and consistently elevating IOP in animal models. We conclude with a consideration of important open research questions/challenges in this area, including: (i) Creating a systems biology description of the ONH; (ii) addressing the role of astrocyte connective tissue remodeling and reactivity in glaucoma; (iii) providing a better characterization of ONH astrocytes and non-astrocytic constituent cells; (iv) better understanding the role of ONH astrocyte phagocytosis, proliferation and death; (v) collecting gene expression and phenotype data on a larger, more coordinated scale; and (vi) developing an implantable IOP sensor.

PMID: 28223180 [PubMed - as supplied by publisher]

Systems biology of oxygen homeostasis.

Wiley Interdiscip Rev Syst Biol Med. 2017 Feb 21;:

Authors: Samanta D, Prabhakar NR, Semenza GL

Abstract
Metazoan species maintain oxygen homeostasis through the activity of hypoxia-inducible factors, which are transcriptional activators that regulate the expression of hundreds of genes to match O2 supply and demand. Here, we review the involvement of hypoxia-inducible factors in the molecular physiology and pathophysiology of cellular O2 sensing, O2 delivery, O2 utilization, and systemic O2 sensing. For further resources related to this article, please visit the WIREs website.

PMID: 28221004 [PubMed - as supplied by publisher]

Network Reconstitution for Quantitative Subnetwork Interaction Analysis.

Methods Mol Biol. 2017;1578:223-231

Authors: Katagiri F

Abstract
A fundamental task in systems biology is to quantify the contributions of the systems' parts and their interactions. Here I describe a powerful concept and tool for this purpose: network reconstitution. Genotypes of an organism that represent all possible combinations of the subnetworks in question will be quantitatively phenotyped. The quantitative phenotype data is analyzed using an R script to obtain estimates for single subnetwork contributions and their interactions.

PMID: 28220428 [PubMed - in process]

Where Sepsis and Antimicrobial Resistance Countermeasures Converge.

Front Public Health. 2017;5:6

Authors: Inglis TJ, Urosevic N

Abstract
The United Nations General Assembly debate on antimicrobial resistance (AMR) recognizes the global significance of AMR. Much work needs to be done on technology capability and capacity to convert the strategic intent of the debate into operational plans and tangible outcomes. Enhancement of the biomedical science-clinician interface requires better exploitation of systems biology tools for in-laboratory and point of care methods that detect sepsis and characterize AMR. These need to link sepsis and AMR data with responsive, real-time surveillance. We propose an AMR sepsis register, similar in concept to a cancer registry, to aid coordination of AMR countermeasures.

PMID: 28220145 [PubMed - in process]

Systems Biology-Derived Discoveries of Intrinsic Clocks.

Front Neurol. 2017;8:25

Authors: Millius A, Ueda HR

Abstract
A systems approach to studying biology uses a variety of mathematical, computational, and engineering tools to holistically understand and model properties of cells, tissues, and organisms. Building from early biochemical, genetic, and physiological studies, systems biology became established through the development of genome-wide methods, high-throughput procedures, modern computational processing power, and bioinformatics. Here, we highlight a variety of systems approaches to the study of biological rhythms that occur with a 24-h period-circadian rhythms. We review how systems methods have helped to elucidate complex behaviors of the circadian clock including temperature compensation, rhythmicity, and robustness. Finally, we explain the contribution of systems biology to the transcription-translation feedback loop and posttranslational oscillator models of circadian rhythms and describe new technologies and "-omics" approaches to understand circadian timekeeping and neurophysiology.

PMID: 28220104 [PubMed - in process]