A self-generated Toddler gradient guides mesodermal cell migration

The sculpting of germ layers during gastrulation relies on coordinated migration of progenitor cells, yet the cues controlling these long-range directed movements remain largely unknown. While directional migration often relies on a chemokine gradient generated from a localized source, we find that zebrafish ventrolateral mesoderm is guided by the uniformly expressed and secreted protein Toddler/ELABELA/Apela, acting as a self-generated gradient. We show that the Apelin receptor, which is specifically expressed in mesodermal cells, has a dual role during gastrulation, acting as a scavenger receptor to generate a Toddler gradient, and as a chemokine receptor to sense this guidance cue. Thus, we uncover a single receptor-based self-generated gradient as the enigmatic guidance cue that can robustly steer the directional migration of mesoderm through the complex and continuously changing environment of the gastrulating embryo.

Recurrent high-impact mutations at cognate structural positions in class A G protein-coupled receptors expressed in tumors

G protein-coupled receptors (GPCRs) are the largest family of human proteins. They have a common structure and, signaling through a much smaller set of G proteins, arrestins, and effectors, activate downstream pathways that often modulate hallmark mechanisms of cancer. Because there are many more GPCRs than effectors, mutations in different receptors could perturb signaling similarly so as to favor a tumor. We hypothesized that somatic mutations in tumor samples may not be enriched within a single gene but rather that cognate mutations with similar effects on GPCR function are distributed across many receptors. To test this possibility, we systematically aggregated somatic cancer mutations across class A GPCRs and found a nonrandom distribution of positions with variant amino acid residues. Individual cancer types were enriched for highly impactful, recurrent mutations at selected cognate positions of known functional motifs. We also discovered that no single receptor drives this pattern, but rather multiple receptors contain amino acid substitutions at a few cognate positions. Phenotypic characterization suggests these mutations induce perturbation of G protein activation and/or β-arrestin recruitment. These data suggest that recurrent impactful oncogenic mutations perturb different GPCRs to subvert signaling and promote tumor growth or survival. The possibility that multiple different GPCRs could moonlight as drivers or enablers of a given cancer through mutations located at cognate positions across GPCR paralogs opens a window into cancer mechanisms and potential approaches to therapeutics.

Level of Combined Estrogen and Progesterone Receptor Expression Determines the Eligibility for Adjuvant Endocrine Therapy in Breast Cancer Patients

Hormone receptor (HR)-positive breast cancer has a heterogeneous pattern according to the level of receptor expression. Patients whose breast cancers express low levels of estrogen receptor (ER) or progesterone receptor (PgR) may be eligible for adjuvant endocrine therapy, but limited data are available to support this notion. We aimed to determine whether HR expression level is related to prognosis. Tumors from 6042 patients with breast cancer were retrospectively analyzed for combined HR levels of ER and PgR. Low expression was defined as ER 1–10% and PgR 1–20%. Four HR groups were identified by combining ER and PgR expression levels. Patients whose tumors expressed high levels of a single receptor showed the worst survival outcomes, and their risk continuously increased even after the 10-year follow-up. Endocrine therapy had a significant benefit for patients whose tumors expressed high HR levels and a favorable tendency for patients with tumors expressing low HR levels. We established the possible benefit of endocrine therapy for patients whose breast tumors expressed low HR levels. Thus, HR level was a prognostic factor and might be a determinant of extended therapy, especially for patients with high expression of a single receptor.

Ricardo Miledi. 15 September 1927—18 December 2017

For nearly five decades, Ricardo Miledi was among the foremost researchers in elucidating how nerves transmit signals across synapses. Born in Chihuahua, Mexico, he qualified as a medical doctor, obtained a PhD with Arturo Rosenblueth and then, while in Canberra with John Eccles FRS, was invited by Bernard Katz FRS to join the Biophysics department at University College London, where he stayed from 1958 to 1984. Both independently and with Katz, he demonstrated that influx of calcium into the presynaptic nerve terminal is the essential trigger for the release of the neurotransmitter that carries signals across to the postsynaptic cell. He found that cutting the nerve to a frog's muscle increased the number and distribution of its muscle acetylcholine (ACh) receptors, which he purified and established as membrane proteins. Together with Katz, he introduced the technique of membrane noise analysis to determine the properties of the individual ion channels opened by ACh, providing the first functional characterization of a single receptor with integral ion channel. With Eric Barnard (FRS 1981), he pioneered a new approach facilitating the study of neurotransmitter receptors and ion channels by ‘transplanting’ them from brain and other tissues into large Xenopus oocyte cells by injection of messenger RNA. After moving to the University of California, Irvine, in 1984, he helped to establish the Mexican Institute for Neurobiology at Querétaro. Working in Irvine and Mexico he extended this oocyte expression technique to incorporate transplanted brain membranes, particularly from patients with epilepsy or other neurological disorders. He received many honours for his work, including the Royal Medal (1998), but was happiest working in his lab applying his extraordinary technical skills and imagination to study synaptic transmission and inspiring a generation of neuroscientists.

Optimal ligand discrimination by asymmetric dimerization and turnover of interferon receptors

In multicellular organisms, antiviral defense mechanisms evoke a reliable collective immune response despite the noisy nature of biochemical communication between tissue cells. A molecular hub of this response, the interferon I receptor (IFNAR), discriminates between ligand types by their affinity regardless of concentration. To understand how ligand type can be decoded robustly by a single receptor, we frame ligand discrimination as an information-theoretic problem and systematically compare the major classes of receptor architectures: allosteric, homodimerizing, and heterodimerizing. We demonstrate that asymmetric heterodimers achieve the best discrimination power over the entire physiological range of local ligand concentrations. This design enables sensing of ligand presence and type, and it buffers against moderate concentration fluctuations. In addition, receptor turnover, which drives the receptor system out of thermodynamic equilibrium, allows alignment of activation points for ligands of different affinities and thereby makes ligand discrimination practically independent of concentration. IFNAR exhibits this optimal architecture, and our findings thus suggest that this specialized receptor can robustly decode digital messages carried by its different ligands.

Bacterial Toxins Active against Mosquitoes: Mode of Action and Resistance

Larvicides based on the bacteria Bacillus thuringiensis svar. israelensis (Bti) and Lysinibacillus sphaericus are effective and environmentally safe compounds for the control of dipteran insects of medical importance. They produce crystals that display specific and potent insecticidal activity against larvae. Bti crystals are composed of multiple protoxins: three from the three-domain Cry type family, which bind to different cell receptors in the midgut, and one cytolytic (Cyt1Aa) protoxin that can insert itself into the cell membrane and act as surrogate receptor of the Cry toxins. Together, those toxins display a complex mode of action that shows a low risk of resistance selection. L. sphaericus crystals contain one major binary toxin that display an outstanding persistence in field conditions, which is superior to Bti. However, the action of the Bin toxin based on its interaction with a single receptor is vulnerable for resistance selection in insects. In this review we present the most recent data on the mode of action and synergism of these toxins, resistance issues, and examples of their use worldwide. Data reported in recent years improved our understanding of the mechanism of action of these toxins, showed that their combined use can enhance their activity and counteract resistance, and reinforced their relevance for mosquito control programs in the future years.

Universal nomenclature for oxytocin–vasotocin ligand and receptor families

Oxytocin (OXT; hereafter OT) and arginine vasopressin or vasotocin (AVP or VT; hereafter VT) are neurotransmitter ligands that function through specific receptors to control diverse functions1,2. Here we performed genomic analyses on 35 species that span all major vertebrate lineages, including newly generated high-contiguity assemblies from the Vertebrate Genomes Project3,4. Our findings support the claim5 that OT (also known as OXT) and VT (also known as AVP) are adjacent paralogous genes that have resulted from a local duplication, which we infer was through DNA transposable elements near the origin of vertebrates and in which VT retained more of the parental sequence. We identified six major oxytocin–vasotocin receptors among vertebrates. We propose that all six of these receptors arose from a single receptor that was shared with the common ancestor of invertebrates, through a combination of whole-genome and large segmental duplications. We propose a universal nomenclature based on evolutionary relationships for the genes that encode these receptors, in which the genes are given the same orthologous names across vertebrates and paralogous names relative to each other. This nomenclature avoids confusion due to differential naming in the pre-genomic era and incomplete genome assemblies, furthers our understanding of the evolution of these genes, aids in the translation of findings across species and serves as a model for other gene families.

Evolving the Olfactory System with Machine Learning

The convergent evolution of the fly and mouse olfactory system led us to ask whether the anatomic connectivity and functional logic in vivo would evolve in artificial neural networks constructed to perform olfactory tasks. Artificial networks trained to classify odor identity recapitulate the connectivity inherent in the olfactory system. Input units are driven by a single receptor type, and units driven by the same receptor converge to form a glomerulus. Glomeruli exhibit sparse, unstructured connectivity to a larger, expansion layer. When trained to both classify odor and impart innate valence on odors, the network develops independent pathways for innate output and odor classification. Thus, artificial networks evolve even without the biological mechanisms necessary to build these systems in vivo, providing a rationale for the convergent evolution of olfactory circuits.