Cell–cell signaling drives the evolution of complex traits: introduction—lung evo-devo

Physiology integrates biology with the environment through cell–cell interactions at multiple levels. The evolution of the respiratory system has been “deconvoluted” (Torday and Rehan in Am J Respir Cell Mol Biol 31:8–12, 2004) through Gene Regulatory Networks (GRNs) applied to cell–cell communication for all aspects of lung biology development, homeostasis, regeneration, and aging. Using this approach, we have predicted the phenotypic consequences of failed signaling for lung development, homeostasis, and regeneration based on evolutionary principles. This cell–cell communication model predicts other aspects of vertebrate physiology as adaptational responses. For example, the oxygen-induced differentiation of alveolar myocytes into alveolar adipocytes was critical for the evolution of the lung in land dwelling animals adapting to fluctuating Phanarezoic oxygen levels over the past 500 million years. Adipocytes prevent lung injury due to oxygen radicals and facilitate the rise of endothermy. In addition, they produce the class I cytokine leptin, which augments pulmonary surfactant activity and alveolar surface area, increasing selection pressure for both respiratory oxygenation and metabolic demand initially constrained by high-systemic vascular pressure, but subsequently compensated by the evolution of the adrenomedullary beta-adrenergic receptor mechanism. Conserted positive selection for the lung and adrenals created further selection pressure for the heart, which becomes progressively more complex phylogenetically in tandem with the lung. Developmentally, increasing heart complexity and size impinges precociously on the gut mesoderm to induce the liver. That evolutionary-developmental interaction is significant because the liver provides regulated sources of glucose and glycogen to the evolving physiologic system, which is necessary for the evolution of the neocortex. Evolution of neocortical control furthers integration of physiologic systems. Such an evolutionary vertical integration of cell-to-tissue-to-organ-to-physiology of intrinsic cell–cell signaling and extrinsic factors is the reverse of the “top-down” conventional way in which physiologic systems are usually regarded. This novel mechanistic approach, incorporating a “middle-out” cell–cell signaling component, will lead to a readily available algorithm for integrating genes and phenotypes. This symposium surveyed the phylogenetic origins of such vertically integrated mechanisms for the evolution of cell–cell communication as the basis for complex physiologic traits, from sponges to man

Experimental verification of a Jarzynski-related information-theoretic equality using a single trapped ion

Most non-equilibrium processes in thermodynamics are quantified only by inequalities, however the Jarzynski relation presents a remarkably simple and general equality relating non-equilibrium quantities with the equilibrium free energy, and this equality holds in both classical and quantum regimes. We report a single-spin test and confirmation of the Jarzynski relation in quantum regime using a single ultracold $^{40}Ca^{+}$ ion trapped in a harmonic potential, based on a general information-theoretic equality for a temporal evolution of the system sandwiched between two projective measurements. By considering both initially pure and mixed states, respectively, we verify, in an exact and fundamental fashion, the non-equilibrium quantum thermodynamics relevant to the mutual information and Jarzynski equality.Comment: 2 figure

Estimating species relative abundances from museum records

Funding: C.F., U.B. and D.J.R. acknowledge COST Action ‘European Soil-Biology Data Warehouse for Soil Protection’ (EUdaphobase), CA18237, supported by COST (European Cooperation in Science and Technology). AEM thanks the Leverhulme Trust (RPG-2019-401). D.B.B. was supported by an NSF Postdoc Research Fellowship in Biology (NSF 000733206), S.M.R. was supported by an NSERC Discovery Grant Author Contributions, A.V.S. was supported by NSF 1755336, C.S.M was supported by NSF 1398620 and N.J.G was supported by NSF 2019470.1. Dated, geo-referenced museum specimens are a rich data source for reconstructing species' distribution and abundance patterns. However, museum records are potentially biased towards over-representation of rare species, and it is unclear whether museum records can be used to estimate relative abundance in the field. 2. We assembled 17 coupled field and museum datasets to quantitatively compare relative abundance estimates with the Dirichlet distribution. Collectively, these datasets comprise 73,039 museum records and 1,405,316 field observations of 2,240 species. 3. Although museum records of rare species overestimated relative abundance by 1-fold to over 100-fold (median study = 9.0), the relative abundance of species estimated from museum occurrence records was strongly correlated with relative abundance estimated from standardized field surveys (r2 range of 0.10-0.91, median study = 0.43). 4. These analyses provide a justification for estimating species relative abundance with carefully curated museum occurrence records, which may allow for the detection of temporal or spatial shifts in the rank ordering of common and rare species.Publisher PDFPeer reviewe

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN