IL-17A Orchestrates Reactive Oxygen Species/HIF1α-Mediated Metabolic Reprogramming in Psoriasis.

Immune cell-derived IL-17A is one of the key pathogenic cytokines in psoriasis, an immunometabolic disorder. Although IL-17A is an established regulator of cutaneous immune cell biology, its functional and metabolic effects on nonimmune cells of the skin, particularly keratinocytes, have not been comprehensively explored. Using multiomics profiling and systems biology-based approaches, we systematically uncover significant roles for IL-17A in the metabolic reprogramming of human primary keratinocytes (HPKs). High-throughput liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance spectroscopy revealed IL-17A-dependent regulation of multiple HPK proteins and metabolites of carbohydrate and lipid metabolism. Systems-level MitoCore modeling using flux-balance analysis identified IL-17A-mediated increases in HPK glycolysis, glutaminolysis, and lipid uptake, which were validated using biochemical cell-based assays and stable isotope-resolved metabolomics. IL-17A treatment triggered downstream mitochondrial reactive oxygen species and HIF1α expression and resultant HPK proliferation, consistent with the observed elevation of these downstream effectors in the epidermis of patients with psoriasis. Pharmacological inhibition of HIF1α or reactive oxygen species reversed IL-17A-mediated glycolysis, glutaminolysis, lipid uptake, and HPK hyperproliferation. These results identify keratinocytes as important target cells of IL-17A and reveal its involvement in multiple downstream metabolic reprogramming pathways in human skin.

FSHR antagonists can trigger a PCOS-like state.

Over the recent years, FSHR has become an important target for development of fertility regulating agents, as impairment of FSH-FSHR interaction can lead to subfertility or infertility. In our previous study, we identified a 9-mer peptide (FSHß (89-97)) that exhibited FSHR antagonist activity. The histopathological and biochemical observations indicated, in addition to FSHR antagonism, a striking resemblance to a PCOS-like state. These observations led us to hypothesize that use of FSHR antagonists can trigger a PCOS-like state. In the present study, to validate this hypothesis, we performed qRT-PCR validation using ovarian tissue samples from our previous study. Expression of three genes known to be differentially expressed in PCOS was evaluated and found to be similar to the PCOS state. To further test the hypothesis, theoretical simulations were carried out by using the human menstrual cycle model available in the literature. Model simulations for FSHR antagonism were indicative of increased testosterone levels, increased ratio of luteinizing hormone/follicle stimulating hormone, and stockpiling of secondary follicles, which are typical characteristics of PCOS. The findings of this study will be relevant while reviewing the utility of FSHR antagonists for fertility regulation and reproductive medicine.Abbreviations: FSH: Follicle-stimulating hormone; FSHR: Follicle-stimulating hormone receptor; cAMP: Cyclic adenosine 3'5' monophosphate; PKA: Protein kinase A; PI3K: Phosphoinositide 3-kinase; PKB: protein kinase B; ERK1/2: Extracellular signal-regulated protein kinase 1/2; MAPK: Mitogen-activated protein kinases; T: testosterone; E2: estradiol; PCOS: Polycystic ovarian syndrome; LH: luteinizing hormone; Lhcgr: luteinizing hormone/choriogonadotropin receptor; CYP17A1: cytochrome P450 family 17 subfamily A member 1; Inhba: inhibin subunit beta A; qRT-PCR: Real-Time quantitative reverse transcription polymerase chain reaction; FSHß: Follicle-stimulating hormone ß subunit; Ct: Cycle threshold; Rn18s: Rattus norvegicus 18S ribosomal RNA.

A steady-state modeling approach for simulation of antimicrobial peptide-cell membrane interaction.

Antimicrobial Peptides (AMPs) are host defense molecules that initiate microbial death by binding to the membrane. On membrane binding, AMPs undergo changes in conformation and aggregation state to enable killing action. Depending on the AMP and cell membrane characteristics, the nature of binding can be aggregating or non-aggregating, with high/low cooperativity, at single or multiple sites with high/low affinity leading to a unique killing action that needs to be studied individually. In the present study, a steady-state model that simulates AMP-membrane interaction was developed and was used to predict the mechanism of AMP binding. The predictions obtained from the model were validated with experimentally deciphered values available in literature. The model was further used to predict the mechanism for a set of designed AMPs with high sequence similarity to Myeloid Antimicrobial Peptide (MAP) family. Depending on the predicted mechanism, a unique half saturation constant and steepness of response (Hill coefficient) was obtained which was further validated with available data from literature. The model could reliably predict the mechanism, the half saturation constant and the Hill coefficient values. Further based on the analysis, it was observed that aggregation and oligomerization result in drastic killing action in a short range of peptide concentration owing to high Hill coefficient values. Mechanisms such as monomers binding at multiple sites with/without cooperativity result in antimicrobial activity at low half saturation constant though the killing action may not be steep. Thus, the methodology developed here can be used to develop hypothesis for studying AMP-membrane interaction mechanisms.

Designing Antibacterial Peptides with Enhanced Killing Kinetics.

Antimicrobial peptides (AMPs) are gaining attention as substitutes for antibiotics in order to combat the risk posed by multi-drug resistant pathogens. Several research groups are engaged in design of potent anti-infective agents using natural AMPs as templates. In this study, a library of peptides with high sequence similarity to Myeloid Antimicrobial Peptide (MAP) family were screened using popular online prediction algorithms. These peptide variants were designed in a manner to retain the conserved residues within the MAP family. The prediction algorithms were found to effectively classify peptides based on their antimicrobial nature. In order to improve the activity of the identified peptides, molecular dynamics (MD) simulations, using bilayer and micellar systems could be used to design and predict effect of residue substitution on membranes of microbial and mammalian cells. The inference from MD simulation studies well corroborated with the wet-lab observations indicating that MD-guided rational design could lead to discovery of potent AMPs. The effect of the residue substitution on membrane activity was studied in greater detail using killing kinetic analysis. Killing kinetics studies on Gram-positive, negative and human erythrocytes indicated that a single residue change has a drastic effect on the potency of AMPs. An interesting outcome was a switch from monophasic to biphasic death rate constant of Staphylococcus aureus due to a single residue mutation in the peptide.

Constraints based analysis of extended cybernetic models.

The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms.

Stochastic galactokinase expression underlies GAL gene induction in a GAL3 mutant of Saccharomyces cerevisiae.

GAL1 and GAL3 are paralogous signal transducers that functionally inactivate Gal80p to activate the Gal4p-dependent transcriptional activation of GAL genes in Saccharomyces cerevisiae in response to galactose. Unlike a wild-type strain, the gal3∆ strain shows delayed growth kinetics as a result of the signaling function of GAL1. The mechanism ensuring that GAL1 is eventually expressed to turn on the GAL switch in the gal3∆ strain remains a paradox. Using galactose and histidine growth complementation assays, we demonstrate that 0.3% of the gal3∆ cell population responds to galactose. This is corroborated by flow cytometry and microscopic analysis. The galactose responders and nonresponders isolated from the galactose-adapted population attain the original bimodal state and this phenotype is found to be as hard wired as a genetic trait. Computational analysis suggests that the log-normal distribution in GAL4 synthesis can lead to bimodal expression of GAL80, resulting in the bimodal expression of GAL genes. Heterozygosity at the GAL80 but not at the GAL1, GAL2 or GAL4 locus alters the extent of bimodality of the gal3∆ cell population. We suggest that the asymmetric expression pattern between GAL1 and GAL3 results in the ability of S. cerevisiae to activate the GAL pathway by conferring nongenetic heterogeneity.

GAL regulon of Saccharomyces cerevisiae performs optimally to maximize growth on galactose.

The GAL regulon in Saccharomyces cerevisiae is a well-characterized genetic network that is utilized for the metabolism of galactose as an energy source. The network contains a transcriptional activator, Gal4p, which binds to its cognate-binding site to express GAL genes. Further, Gal80p and Gal3p are the repressor and galactose sensor, respectively, which are also under the regulation of GAL regulon. It is shown that the wild-type strain produces only about 80% of the maximum expression feasible from the regulon, which is observed in a mutant strain lacking Gal80p. This raises a fundamental question regarding the optimality of expression from the GAL regulon in S. cerevisiae. To address this issue, we evaluated the burden on growth due to the synthesis of GAL proteins in S. cerevisiae. The analysis demonstrated that both the media type and the extent of enzyme synthesized play a role in determining the burden on growth. We show that the burden can be quantified by relating to a parameter, ß, the ratio of enzyme activity to the initial substrate concentration. The analysis demonstrated that the GAL regulon of the wild-type strain performed effectively to optimize growth on galactose.

Effect on ß-galactosidase synthesis and burden on growth of osmotic stress in Escherichia coli.

Osmotic Shock is known to negatively affect growth rate along with an extended lag phase. The reduction in growth rate can be characterized as burden due to the osmotic stress. Studies have shown that production of unnecessary protein also burdens cellular growth. This has been demonstrated by growing Escherichia coli on glycerol in the presence of Isopropyl-ß-D-1-thiogalactopyranoside (IPTG) to induce ß-galactosidase synthesis which does not offer any benefit towards growth. The trade off between osmotic stress and burden on growth due to unnecessary gene expression has not been enumerated. The influence of osmotic stress on ß-galactosidase synthesis and activity is not clearly understood. Here, we study the effect of salt concentration on ß-galactosidase activity and burden on growth due to unnecessary gene expression in E.coli. We characterize the burden on growth in presence of varying concentrations of salt in the presence of IPTG using three strains, namely wild type, ∆lacI and ∆lacIlacZ mutant strains. We demonstrate that the salt concentrations, sensitively inhibits enzyme synthesis thereby influencing the burden on growth. In a wild type strain, addition of lactose into the medium demonstrated growth benefit at low salt concentration but not at higher concentrations. The extent of burden due to osmotic shock was higher in a lactose M9 medium than in a glycerol M9 medium. A linear relationship was observed between enzyme activity and burden on growth in various media types studied.

Optical control demonstrates switch-like PIP3 dynamics underlying the initiation of immune cell migration.

There is a dearth of approaches to experimentally direct cell migration by continuously varying signal input to a single cell, evoking all possible migratory responses and quantitatively monitoring the cellular and molecular response dynamics. Here we used a visual blue opsin to recruit the endogenous G-protein network that mediates immune cell migration. Specific optical inputs to this optical trigger of signaling helped steer migration in all possible directions with precision. Spectrally selective imaging was used to monitor cell-wide phosphatidylinositol (3,4,5)-triphosphate (PIP3), cytoskeletal, and cellular dynamics. A switch-like PIP3 increase at the cell front and a decrease at the back were identified, underlying the decisive migratory response. Migration was initiated at the rapidly increasing switch stage of PIP3 dynamics. This result explains how a migratory cell filters background fluctuations in the intensity of an extracellular signal but responds by initiating directionally sensitive migration to a persistent signal gradient across the cell. A two-compartment computational model incorporating a localized activator that is antagonistic to a diffusible inhibitor was able to simulate the switch-like PIP3 response. It was also able simulate the slow dissipation of PIP3 on signal termination. The ability to independently apply similar signaling inputs to single cells detected two cell populations with distinct thresholds for migration initiation. Overall the optical approach here can be applied to understand G-protein-coupled receptor network control of other cell behaviors.

Experimental and steady-state analysis of the GAL regulatory system in Kluyveromyces lactis.

The galactose uptake mechanism in yeast is a well-studied regulatory network. The regulatory players in the galactose regulatory mechanism (GAL system) are conserved in Saccharomyces cerevisiae and Kluyveromyces lactis, but the molecular mechanisms that occur as a result of the molecular interactions between them are different. The key differences in the GAL system of K. lactis relative to that of S. cerevisiae are: (a) the autoregulation of KlGAL4; (b) the dual role of KlGal1p as a metabolizing enzyme as well as a galactose-sensing protein; (c) the shuttling of KlGal1p between nucleus and cytoplasm; and (d) the nuclear confinement of KlGal80p. A steady-state model was used to elucidate the roles of these molecular mechanisms in the transcriptional response of the GAL system. The steady-state results were validated experimentally using measurements of beta-galactosidase to represent the expression for genes having two binding sites. The results showed that the autoregulation of the synthesis of activator KlGal4p is responsible for the leaky expression of GAL genes, even at high glucose concentrations. Furthermore, GAL gene expression in K. lactis shows low expression levels because of the limiting function of the bifunctional protein KlGal1p towards the induction process in order to cope with the need for the metabolism of lactose/galactose. The steady-state model of the GAL system of K. lactis provides an opportunity to compare with the design prevailing in S. cerevisiae. The comparison indicates that the existence of a protein, Gal3p, dedicated to the sensing of galactose in S. cerevisiae as a result of genome duplication has resulted in a system which metabolizes galactose efficiently.

Mathematical modeling and experimental validation of chemotaxis under controlled gradients of methyl-aspartate in Escherichia coli.

Escherichia coli has evolved an intracellular pathway to regulate its motion termed as chemotaxis so as to move towards a favorable environment such as regions with higher concentration of nutrients. Chemotaxis is a response to temporal and spatial variation of extracellular ligand concentration and randomness in motion induced by collisions with solvent molecules. Previous studies have reported average drift velocities for a given gradient and do not measure drift velocities as a function of time and space. To address this issue, a novel experimental technique was developed to quantify the motion of E. coli cells to varying concentrations and gradients of methyl-aspartate so as to capture the spatial and temporal variation of the drift velocity. A two-state receptor model accounting for the intracellular signaling pathway predicted the experimentally observed increase in drift velocity with gradient and the subsequent adaptation. Our study revealed that the rotational diffusivity induced by the extracellular environment is crucial in determining the drift velocity of E. coli. The model predictions matched with experimental observations only when the response of the intracellular pathway was highly ultra-sensitive to overcome the extracellular randomness. The parametric sensitivity of the pathway indicated that the dissociation constant for the binding of the ligand and the rate constants of the methylation/demethylation of the receptor are key to predict the performance of the chemotactic behavior. The study also indicates a possible role of oxygen in the chemotaxis response and that the response to a ligand may have to account for effects of oxygen.

A steady state model for the transcriptional regulation of filamentous growth in Saccharomyces cerevisiae.

Occurrence of multiple upstream activation sites (UASs) is a structural motif that is observed within the promoter of eukaryotic genes for coordinating gene expression. Transcriptional activation depends on the ability of transcriptional activators to bind to its specific UASs, which are kept inaccessible due to the nucleosomal organization of the chromatin. Targeting of chromatin remodeling complexes by a sequence specific transcriptional activator is shown to be detrimental for transcriptional initiation. Here, we analyze such a regulatory structure involving ordered recruitment of transcriptional activators and chromatin remodeling complexes with respect to activation of a flocculin gene, FLO11 involved in the filamentous growth to gain insights into its regulation. We develop a steady state model for the transcriptional regulation of FLO11 by primary transcriptional activators Flo8p, Ste12p, Tec1p and Mss11p, which are under a complex network comprising of cAMP and MAPK pathways. Our analysis predicts that the FLO11 promoter should undergo varying chromatin remodeling activity from partial to complete disassembly depending upon the concentration of Ste12p. This variation should be sensitive and sharply shift to saturate with Ste12p concentration. Overexpression of Ste12p can increase the overall chromatin remodeling activity by increasing the local concentration of remodeling complex through active recruitment. Further, we demonstrate that the chromatin remodeling activity brings about amplification of cAMP and MAPK signal and in absence of either of the signals, the input signal required for the other increases. We also discuss the results obtained from our steady state analysis in respect to other eukaryotic genes.

Elementary mode analysis to study the preculturing effect on the metabolic state of Lactobacillus rhamnosus during growth on mixed substrates.

Quantification of metabolism through elementary modes offers insights into the working of a metabolic network. We have determined the fluxes of elementary modes through linear optimization using the stoichiometry of the elementary modes as a constraint. We apply this methodology to obtain insights into the effect of preculturing on growth of Lactobacillus rhamnosus on medium containing mixed substrates. L. rhamnosus, a microaerophilic organism, produces flavor compounds such as diacetyl and acetoin during growth on glucose and citrate. The uptake of citrate has been shown to be sensitive to preculturing states of the cells. Elementary modes demonstrated that citrate was utilized by the organism as a sole carbon source. Further, both glucose and citrate was catabolized by this organism through aerobic and anaerobic routes. The flux analysis indicated that only 21 elementary modes were operational during growth of L. rhamnosus on glucose and citrate. Glucose specifically accounted for 6 elementary modes, while the remaining 15 involved citrate as substrate. The modes associated with glucose were mainly operational when cells were precultured on glucose. It was observed that all the 21 modes contributed to the fluxes when the cells were precultured on citrate. The NADH recycling through lactate formation and oxygen uptake were dependent on the preculturing state. The analysis also demonstrated that preculturing on citrate yielded better productivity of diacetyl and acetoin.

An optimal model for representing the kinetics of growth and product formation by Lactobacillus rhamnosus on multiple substrates.

A comprehensive model was developed to simulate Lactobacillus rhamnosus growth on a medium containing multiple limiting carbon sources. The strategy of optimizing specific growth rate to predict growth on multiple substrates was demonstrated. The model predictions were based on parameters obtained from L. rhamnosus growth on individual substrates. The model was able to simulate the growth, substrate consumption, product formation and specific growth rate profiles of L. rhamnosus accurately. The model prediction that co-metabolism of glucose and pyruvate enhances growth rate of and flavor production by the bacterium was experimentally verified.