Toward Interdisciplinary Synergies in Molecular Communications: Perspectives from Synthetic Biology, Nanotechnology, Communications Engineering and Philosophy of Science.

Within many chemical and biological systems, both synthetic and natural, communication via chemical messengers is widely viewed as a key feature. Often known as molecular communication, such communication has been a concern in the fields of synthetic biologists, nanotechnologists, communications engineers, and philosophers of science. However, interactions between these fields are currently limited. Nevertheless, the fact that the same basic phenomenon is studied by all of these fields raises the question of whether there are unexploited interdisciplinary synergies. In this paper, we summarize the perspectives of each field on molecular communications, highlight potential synergies, discuss ongoing challenges to exploit these synergies, and present future perspectives for interdisciplinary efforts in this area.

Molecular Noise in Synaptic Communication.

In synaptic molecular communication (MC), the activation of postsynaptic receptors by neurotransmitter (NTs) is governed by a stochastic reaction-diffusion process. This randomness of synaptic MC contributes to the randomness of the electrochemical downstream signal in the postsynaptic cell, called postsynaptic membrane potential (PSP). Since the randomness of the PSP is relevant for neural computation and learning, characterizing the statistics of the PSP is critical. However, the statistical characterization of the synaptic reaction-diffusion process is difficult because the reversible bi-molecular reaction of NTs with receptors renders the system nonlinear. Consequently, there is currently no model available which characterizes the impact of the statistics of postsynaptic receptor activation on the PSP. In this work, we propose a novel statistical model for the synaptic reaction-diffusion process in terms of the chemical master equation (CME). We further propose a novel numerical method which allows to compute the CME efficiently and we use this method to characterize the statistics of the PSP. Finally, we present results from stochastic particle-based computer simulations which validate the proposed models. We show that the biophysical parameters governing synaptic transmission shape the autocovariance of the receptor activation and, ultimately, the statistics of the PSP. Our results suggest that the processing of the synaptic signal by the postsynaptic cell effectively mitigates synaptic noise while the statistical characteristics of the synaptic signal are preserved. The results presented in this paper contribute to a better understanding of the impact of the randomness of synaptic signal transmission on neuronal information processing.

3D Melanoma Cocultures as Improved Models for Nanoparticle-Mediated Delivery of RNA to Tumors.

Cancer therapy is an emergent application for mRNA therapeutics. While in tumor immunotherapy, mRNA encoding for tumor-associated antigens is delivered to antigen-presenting cells in spleen and lymph nodes, other therapeutic options benefit from immediate delivery of mRNA nanomedicines directly to the tumor. However, tumor targeting of mRNA therapeutics is still a challenge, since, in addition to delivery of the cargo to the tumor, specifics of the targeted cell type as well as its interplay with the tumor microenvironment are crucial for successful intervention. This study investigated lipoplex nanoparticle-mediated mRNA delivery to spheroid cell culture models of melanoma. Insights into cell-type specific targeting, non-cell-autonomous effects, and penetration capacity in tumor and stroma cells of the mRNA lipoplex nanoparticles were obtained. It was shown that both coculture of different cell types as well as three-dimensional cell growth characteristics can modulate distribution and transfection efficiency of mRNA lipoplex formulations. The results demonstrate that three-dimensional coculture spheroids can provide a valuable surplus of information in comparison to adherent cells. Thus, they may represent in vitro models with enhanced predictivity for the in vivo activity of cancer nanotherapeutics.

Saturating Receiver and Receptor Competition in Synaptic DMC: Deterministic and Statistical Signal Models.

Synaptic communication is based on a biological Molecular Communication (MC) system which may serve as a blueprint for the design of synthetic MC systems. However, the physical modeling of synaptic MC is complicated by the possible saturation of the molecular receiver caused by the competition of neurotransmitters (NTs) for postsynaptic receptors. Receiver saturation renders the system behavior nonlinear in the number of released NTs and is commonly neglected in existing analytical models. Furthermore, due to the ligands' competition for receptors (and vice versa), the individual binding events at the molecular receiver are in general not statistically independent and the commonly used binomial model for the statistics of the received signal does not apply. Hence, in this work, we propose a novel deterministic model for receptor saturation in terms of a state-space description based on an eigenfunction expansion of Fick's diffusion equation. The presented solution is numerically stable and computationally efficient. Employing the proposed deterministic model, we show that saturation at the molecular receiver effectively reduces the peak-value of the expected received signal and accelerates the clearance of NTs as compared to the case when receptor occupancy is neglected. We further derive a statistical model for the received signal in terms of the hypergeometric distribution which accounts for the competition of NTs for receptors and the competition of receptors for NTs. The proposed statistical model reveals how the signal statistics are shaped by the number of released NTs, the number of receptors, and the binding kinetics of the receptors, respectively, in the presence of competition. In particular, we show that the impact of these parameters on the signal variance is qualitatively different depending on the relative numbers of NTs and receptors. Finally, the accuracy of the proposed deterministic and statistical models is verified by particle-based computer simulations.

Preparation, Drug Treatment, and Immunohistological Analysis of Tri-Culture Spheroid 3D Melanoma-Like Models.

Most currently available three-dimensional melanoma models have either focused on simplicity or were optimized for physiological relevance. Accordingly, these paradigms have been either composed of malignant cells only or they were sophisticated human skin equivalents featuring multiple cell types and skin-like organization. Here, an intermediate spheroid-based assay system is presented, which uses tri-cultures of human CCD-1137Sk fibroblasts, HaCaT keratinocytes, and SK-MEL-28 melanoma cells. Being made of cell lines, these spheroids can be reliably reproduced without any special equipment using standard culture procedures, and they feature different aspects of skin and early stage melanoma. Therefore, this kind of model can be useful for lead-compound testing or addressing fundamental principles of early melanoma formation.

Monitoring of argatroban and lepirudin anticoagulation in critically ill patients by conventional laboratory parameters and rotational thromboelastometry - a prospectively controlled randomized double-blind clinical trial.

BACKGROUND: Argatroban or lepirudin anticoagulation therapy in patients with heparin induced thrombocytopenia (HIT) or HIT suspect is typically monitored using the activated partial thromboplastin time (aPTT). Although aPTT correlates well with plasma levels of argatroban and lepirudin in healthy volunteers, it might not be the method of choice in critically ill patients. However, in-vivo data is lacking for this patient population. Therefore, we studied in vivo whether ROTEM or global clotting times would provide an alternative for monitoring the anticoagulant intensity effects in critically ill patients. METHODS: This study was part of the double-blind randomized trial "Argatroban versus Lepirudin in critically ill patients (ALicia)", which compared critically ill patients treated with argatroban or lepirudin. Following institutional review board approval and written informed consent, for this sub-study blood of 35 critically ill patients was analysed. Before as well as 12, 24, 48 and 72 h after initiation of argatroban or lepirudin infusion, blood was analysed for aPTT, aPTT ratios, thrombin time (TT), INTEM CT,INTEM CT ratios, EXTEM CT, EXTEM CT ratios and maximum clot firmness (MCF) and correlated with the corresponding plasma concentrations of the direct thrombin inhibitor. RESULTS: To reach a target aPTT of 1.5 to 2 times baseline, median [IQR] plasma concentrations of 0.35 [0.01-1.2] µg/ml argatroban and 0.17 [0.1-0.32] µg/ml lepirudin were required. For both drugs, there was no significant correlation between aPTT and aPTT ratios and plasma concentrations. INTEM CT, INTEM CT ratios, EXTEM CT, EXTEM CT ratios, TT and TT ratios correlated significantly with plasma concentrations of both drugs. Additionally, agreement between argatroban plasma levels and EXTEM CT and EXTEM CT ratios were superior to agreement between argatroban plasma levels and aPTT in the Bland Altman analysis. MCF remained unchanged during therapy with both drugs. CONCLUSION: In critically ill patients, TT and ROTEM parameters may provide better correlation to argatroban and lepirudin plasma concentrations than aPTT. TRIAL REGISTRATION: ClinicalTrials.gov , NCT00798525 , registered on 25 Nov 2008.

Anti-inflammatory Effects of Fungal Metabolites in Mouse Intestine as Revealed by In vitro Models.

Inflammatory bowel diseases (IBD), which include Crohn's disease and ulcerative colitis, are chronic inflammatory disorders that can affect the whole gastrointestinal tract or the colonic mucosal layer. Current therapies aiming to suppress the exaggerated immune response in IBD largely rely on compounds with non-satisfying effects or side-effects. Therefore, new therapeutical options are needed. In the present study, we investigated the anti-inflammatory effects of the fungal metabolites, galiellalactone, and dehydrocurvularin in both an in vitro intestinal inflammation model, as well as in isolated myenteric plexus and enterocyte cells. Administration of a pro-inflammatory cytokine mix through the mesenteric artery of intestinal segments caused an up-regulation of inflammatory marker genes. Treatment of the murine intestinal segments with galiellalactone or dehydrocurvularin by application through the mesenteric artery significantly prevented the expression of pro-inflammatory marker genes on the mRNA and the protein level. Comparable to the results in the perfused intestine model, treatment of primary enteric nervous system (ENS) cells from the murine intestine with the fungal compounds reduced expression of cytokines such as IL-6, TNF-α, IL-1ß, and inflammatory enzymes such as COX-2 and iNOS on mRNA and protein levels. Similar anti-inflammatory effects of the fungal metabolites were observed in the human colorectal adenocarcinoma cell line DLD-1 after stimulation with IFN-γ (10 ng/ml), TNF-α (10 ng/ml), and IL-1ß (5 ng/ml). Our results show that the mesenterially perfused intestine model provides a reliable tool for the screening of new therapeutics with limited amounts of test compounds. Furthermore, we could characterize the anti-inflammatory effects of two novel active compounds, galiellalactone, and dehydrocurvularin which are interesting candidates for studies with chronic animal models of IBD.