Synthetic molecular communication (MC) is a new communication engineering paradigm which is expected to enable revolutionary applications such as smart drug delivery and real-time health monitoring. The design and implementation of synthetic MC systems (MCSs) at nano-and microscale is very challenging. This is particularly true for synthetic MCSs employing biological components as transmitters and receivers or as interfaces with natural biological MCSs. Nevertheless, since such biological components have been optimized by nature over billions of years, using them in synthetic MCSs is highly promising. This paper provides a survey of biological components that can potentially serve as the main building blocks, i.e., transmitter, receiver, and signaling particles, for the design and implementation of synthetic MCSs. Nature uses a large variety of signaling particles of different sizes and with vastly different properties for communication among biological entities. Here, we focus on three important classes of signaling particles: cations (specifically protons and calcium ions), neurotransmitters (specifically acetylcholine, dopamine, and serotonin), and phosphopeptides. These three classes have unique and distinct features such as their large diffusion coefficients, their specificity, and/or their uniqueness of signaling that make them suitable candidates for signaling particles in synthetic MCSs. For each of these candidate signaling particles, we present several specific transmitter and receiver structures mainly built upon proteins that are capable of performing the distinct physiological functionalities required from the transmitters and receivers of MCSs. Moreover, we present options for both microscale implementation of MCSs as well as the micro-to-macroscale interfaces needed for experimental evaluation of MCSs. One of the main advantages of employing proteins for signal emission and detection is that they can be modified with tools from synthetic biology and be tailored to a wide range of application needs. We discuss the properties, limitations, and applications of the proposed biological building blocks for synthetic MCSs in detail. Furthermore, we outline new research directions for the implementation and the theoretical design and analysis of the proposed transmitter and receiver architectures.

Early-onset epileptic encephalopathy (EE) and combined developmental and epileptic encephalopathies (DEE) are clinically and genetically heterogeneous severely devastating conditions. Recent studies emphasized de novo variants as major underlying cause suggesting a generally low-recurrence risk. In order to better understand the full genetic landscape of EE and DEE, we performed high-resolution chromosomal microarray analysis in combination with whole-exome sequencing in 63 deeply phenotyped independent patients. After bioinformatic filtering for rare variants, diagnostic yield was improved for recessive disorders by manual data curation as well as molecular modeling of missense variants and untargeted plasma-metabolomics in selected patients. In total, we yielded a diagnosis in ∼42% of cases with causative copy number variants in 6 patients (∼10%) and causative sequence variants in 16 established disease genes in 20 patients (∼32%), including compound heterozygosity for causative sequence and copy number variants in one patient. In total, 38% of diagnosed cases were caused by recessive genes, of which two cases escaped automatic calling due to one allele occurring de novo. Notably, we found the recessive gene SPATA5 causative in as much as 3% of our cohort, indicating that it may have been underdiagnosed in previous studies. We further support candidacy for neurodevelopmental disorders of four previously described genes (PIK3AP1, GTF3C3, UFC1, and WRAP53), three of which also followed a recessive inheritance pattern. Our results therefore confirm the importance of de novo causative gene variants in EE/DEE, but additionally illustrate the major role of mostly compound heterozygous or hemizygous recessive inheritance and consequently high-recurrence risk.

Dendritic cells (DCs) are major regulators of innate and adaptive immune responses. DCs can be classified into plasmacytoid DCs and conventional DCs (cDCs) type 1 and 2. Murine and human cDC1 share the mRNA expression of XCR1. Murine studies indicated a specific role of the XCR1–XCL1 axis in the induction of immune responses. Here, we describe that human cDC1 can be distinguished into XCR1 ⁻ and XCR1 ⁺ cDC1 in lymphoid as well as nonlymphoid tissues. Steady-state XCR1 ⁺ cDC1 display a preactivated phenotype compared to XCR1 ⁻ cDC1. Upon stimulation, XCR1 ⁺ cDC1, but not XCR1 ⁻ cDC1, secreted high levels of inflammatory cytokines as well as chemokines. This was associated with enhanced activation of NK cells mediated by XCR1 ⁺ cDC1. Moreover, XCR1 ⁺ cDC1 excelled in inhibiting replication of Influenza A virus. Further, under DC differentiation conditions, XCR1 ⁻ cDC1 developed into XCR1 ⁺ cDC1. After acquisition of XCR1 expression, XCR1 ⁻ cDC1 secreted comparable level of inflammatory cytokines. Thus, XCR1 is a marker of terminally differentiated cDC1 that licenses the antiviral effector functions of human cDC1, while XCR1 ⁻ cDC1 seem to represent a late immediate precursor of cDC1.

SARS-CoV-2, the virus causing the COVID-19 pandemic, changes frequently through the appearance of mutations constantly leading to new variants. However, only few variants evolve as dominating and will be considered as “Variants of Concern” (VOCs) by the world health organization (WHO). At the end of 2020 the alpha (B.1.1.7) variant appeared in the United Kingdom and dominated the pandemic situation until mid of 2021 when it was substituted by the delta variant (B.1.617.2) that first appeared in India as predominant. At the end of 2021, SARS-CoV-2 omicron (B.1.1.529) evolved as the dominating variant. Here, we use in silico modeling and molecular dynamics (MD) simulations of the receptor-binding domain of the viral spike protein and the host cell surface receptor ACE2 to analyze and compare the interaction pattern between the wild type, delta and omicron variants. We identified residue 493 in delta (glutamine) and omicron (arginine) with altered binding properties towards ACE2.

Heat shock protein 47 (HSP47) is an endoplasmic reticulum (ER)-resident collagen-specific chaperone and essential for proper formation of the characteristic collagen triple helix. It preferentially binds to the folded conformation of its clients and accompanies them from the ER to the Golgi compartment, where it releases them and is recycled back to the ER. Unlike other chaperones, the binding and release cycles are not governed by nucleotide exchange and hydrolysis, but presumably the dissociation of the HSP47-procollagen complex is triggered by the lower pH in the Golgi (pH 6.3) compared with the ER (pH 7.4). Histidine residues have been suggested as triggers due to their approximate textbook pK_a value of 6.1 for their side chains. We present here an extensive theoretical and experimental study of the 14 histidine residues present in canine HSP47, where we have mutated all histidine residues in the collagen binding interface and additionally all of those that were predicted to undergo a significant change in protonation state between pH 7 and 6. These mutants were characterized by biolayer interferometry for their pH-dependent binding to a collagen model. One mutant (H238N) loses binding, which can be explained by a rearrangement of the Arg²²² and Asp³⁸⁵ residues, which are crucial for specific collagen recognition. Most of the other mutants were remarkably silent, but a double mutant with His²⁷³ and His²⁷⁴ exchanged for asparagines exhibits a much less pronounced pH dependence of collagen binding. This effect is mainly caused by a lower k_off at the low pH values.