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Blood Pressure Regulation Evolved from Basic Homeostatic Components biomedicines Article Blood Pressure Regulation Evolved from Basic Homeostatic Components Alon Botzer 1, Yoram Finkelstein 2 and Ron Unger 1,* 1 The Mina & Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat Gan 5290002, Israel; [email protected] 2 Neurology and Toxicology Service and Unit, Shaare Zedek Medical Center, Jerusalem 9103102, Israel; yoram.fi[email protected] * Correspondence: [email protected] Abstract: Blood pressure (BP) is determined by several physiological factors that are regulated by a range of complex neural, endocrine, and paracrine mechanisms. This study examined a collection of 198 human genes related to BP regulation, in the biological processes and functional prisms, as well as gene expression in organs and tissues. This was made in conjunction with an orthology analysis performed in 19 target organisms along the phylogenetic tree. We have demonstrated that transport and signaling, as well as homeostasis in general, are the most prevalent biological processes associated with BP gene orthologs across the examined species. We showed that these genes and their orthologs are expressed primarily in the kidney and adrenals of complex organisms (e.g., high order vertebrates) and in the nervous system of low complexity organisms (e.g., flies, nematodes). Furthermore, we have determined that basic functions such as ion transport are ancient and appear in all organisms, while more complex regulatory functions, such as control of extracellular volume emerged in high order organisms. Thus, we conclude that the complex system of BP regulation evolved from simpler components that were utilized to maintain specific homeostatic functions that Citation: Botzer, A.; Finkelstein, Y.; play key roles in existence and survival of organisms. Unger, R. Blood Pressure Regulation Evolved from Basic Homeostatic Keywords: blood pressure; homeostasis; evolution; gene orthologs Components. Biomedicines 2021, 9, 469. https://doi.org/10.3390/ biomedicines9050469 1. Introduction Academic Editor: Juan Sahuquillo The multifactorial nature of BP regulation involves many genes with a widespread distribution across numerous cellular subsystems, posing significant challenges in the Received: 7 March 2021 effort to decipher its complex mechanisms [1]. Here we implement a comparative approach Accepted: 22 April 2021 Published: 25 April 2021 to review the phylogenetic history of the BP system via an analysis of BP associated genes and their orthologs in 19 organisms, enabling us to gain an evolutionary perspective of the Publisher’s Note: MDPI stays neutral development of the system. with regard to jurisdictional claims in Current evidence proposes that the blood vascular system initially emerged in an published maps and institutional affil- ancestor of the tripoblasts over 600 million years ago, as a means to withstand the time- iations. distance constraints of diffusion [2]. This has advanced over the course of evolution and expanded to a more complex “machinery” to support the functional requirements of high order organisms. We suggest that the most fundamental organismal function of this machinery is to preserve the internal milieu, namely, to maintain a stable internal environment concerning Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. temperature, electrolytes and water concentrations, as external conditions perpetually This article is an open access article change. Internal environment, or “milieu intérieur” is a concept formulated by Claude distributed under the terms and Bernard, postulating that “the stability of the internal environment (the milieu intérieur) conditions of the Creative Commons is the condition for the free and independent life”. This is the fundamental principle of Attribution (CC BY) license (https:// homeostasis, a term coined later by Walter Bradford Cannon. creativecommons.org/licenses/by/ Claude Bernard also stated: “The constancy of the environment presupposes a perfec- 4.0/). tion of the organism such that external variations are at every instant compensated and Biomedicines 2021, 9, 469. https://doi.org/10.3390/biomedicines9050469 https://www.mdpi.com/journal/biomedicines Biomedicines 2021, 9, 469 2 of 18 brought into balance. In consequence, far from being indifferent to the external world, the higher animal is on the contrary in a close and wise relation with it, so that its equilibrium results from a continuous and delicate compensation established as if the most sensitive of balances” [3]. This work has utilized bioinformatic tools and data mining techniques to investigate the BP system and elucidate the major homeostatic roles it played in the physiology of the corresponding organisms. In fact, we went back, tracing the evolution of genes that are involved in human BP regulation. 2. Materials and Methods 2.1. BP Genes, Orthologous Proteins and Target Organism Selection This study investigated a set of 198 genes associated with the BP regulation system. These genes were obtained and identified by means of bioinformatic analyses performed previously by Botzer et al. [4]. A set of orthologous proteins pertaining to these genes, from 19 organisms (see Figure1) were obtained from two different sources—STRING and InParanoid. STRING—Search Tool for the Retrieval of Interacting Genes/Proteins, (http://string- db.org/ (accessed on May 2017)) is a meta-resource that aggregates most of the available information on protein–protein associations and includes both direct physical interactions and protein interactions derived from literature. Since version 9.1, it contains pre-computed orthology relations imported from the eggNOG database [5]. eggnog—evolutionary geneal- ogy of genes: Non-supervised Orthologous Groups, (http://eggnogdb.embl.de (accessed on May 2017)) is a public resource that provides Orthologous Groups (OG’s) of proteins at different taxonomic levels. It provides pairwise orthology relationships within OG’s based on analysis of phylogenetic trees. Protein sequences from the selected organisms were extracted and used to compute an all-against-all pair-wise similarity matrix. The comparison uses Smith-Waterman alignments and computational adjustments of the scores, as in BLAST, to prevent spurious hits between low-complexity sequence regions [6]. In- Paranoid (http://InParanoid.sbc.su.se (accessed on February 2018))—gathers proteomes of completely sequenced eukaryotic species and calculates pairwise ortholog relationships among them. This tool implements a two-pass BLAST approach that makes use of high- precision compositional score matrix adjustment, but avoids the alignment truncation that sometimes follows [7]. Both tools demonstrated similar results, but we decided to pursue analyses with data retrieved from STRING, which included a more comprehensive and updated coverage. We then composed an organism-to-protein similarity map, consisting of similarity scores between the 198 human BP protein sequences and their ortholog proteins in the 19 target organisms, as obtained from STRING. This map was produced by calculation of pairwise sequence alignment, using EMBOSS Needle Global Alignment tool (https: //www.ebi.ac.uk/Tools/psa/emboss_needle/ (accessed on February 2018)). This tool creates an optimal global alignment of two sequences using the Needleman-Wunsch algorithm, returning a value representing the percent of similarity between sequences, enabling homology to be inferred and the evolutionary relationship between the sequences studied [8]. Target organism selection was made with the intention to create a span of a wide vari- ety of complexities—starting with the multicellular organism T. adhaerens as the simplest, going through flies, nematodes, fish, amphibians and eventually complex organisms as pri- mates and other mammals (see Figure1 for a complete list of organisms). We gave emphasis to well-researched model organisms, displaying sufficient and reliable orthology data, as well as extended annotations derived from established biological and genetic knowledge. Biomedicines 2021, 9, x FOR PEER REVIEW 3 of 19 Biomedicines 2021, 9, 469 3 of 18 Figure 1. Cont. Biomedicines 2021, 9, x FOR PEER REVIEW 4 of 19 Biomedicines 2021, 9, 469 4 of 18 CACNA2D1 99.9 67.4 94.1 96.2 95.3 79.3 83.8 94.2 77 84.5 81.8 75 28.3 45.7 43 44.5 42.4 38.9 41.1 KCNK2 100 57.5 97.7 98.8 99.5 96 99.5 95.5 95.1 93.9 89 84.6 39.6 35.9 35.8 17.1 39.2 40.5 31.4 NR3C2 99.7 67.7 91.4 95.3 96.2 94.8 97.8 94 93 88.8 76.1 63.2 20.5 26 16.1 25.3 21.1 17.2 5.8 LPL 100 88.3 96.2 95.6 94.8 96.2 95.6 90 88 81 83.3 71.8 18.8 46 32.4 39.6 40.4 0 42.4 PTGS2 99.7 98.5 93 93.2 95 94.2 94.7 91.9 92.5 90.9 86.8 85.2 57.9 62.7 6.4 17.1 33.8 15.4 31 PTGS1 94.7 93.7 92.9 94 94 94.8 95.3 88.1 79.5 84.2 84.4 79.1 58.1 55.1 25.5 32.2 33.1 14.2 30.4 NR3C1 99.9 97.4 47.9 92.3 95.9 96.3 95.6 89.7 88.9 84.9 75.8 63.4 24.4 29.5 23.3 29.1 25.5 22.7 19.8 ADRA1B 97.9 99 54 96.9 87.5 97.7 74.8 85.6 81.7 63 64.2 60.7 44.2 34.9 40.8 33.8 37.4 33 30.1 SCNN1G 90 93 92.9 91.9 92.2 91.4 93.6 86.6 87.1 80.4 74.5 33.4 38.7 32 39 33.9 28.9 34.7 35.1 SCNN1B 87.9 98.8 90.8 90.9 94.1 91.3 93.9 87.3 87.4 76 75 32.9 38.4 33 38.3 33.7 29.4 33.1 38.6 EDNRB 99.4 96.1 77.3 77.5 77.3 76.4 80.7 72 61.3 67.3 60.9 61 36.1 29.8 32.9 33.6 35.7 30.4 27.2 DRD5 99 97.1 87.2 87.2 91.2 89 80.9 81.5 47.6 77 73.7 64 45.6 34.6 43.7 39 42.3 36.7 35.1 F2R 99.8 98.4 81.2 87.9 88.6 87.4 91.6 82.4 43.6 71 70.2 65.4 35.5 33.7 37.1 29.9 33.8 32.8 38.6 WNK4 99.5 89 52.4 88.8 53.4 90.1 83.7 80.9 31.9 53.3 37.3 39 17.5 14.8 22.8 23.2 14.7 32.3
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