Some like it hot: population-specific adaptations in venom production to abiotic stressors in a widely distributed cnidarian

Background: In cnidarians, antagonistic interactions with predators and prey are mediated by their venom, whose synthesis may be metabolically expensive. The potentially high cost of venom production has been hypothesized to drive population-specific variation in venom expression due to differences in abiotic conditions. However, the effects of environmental factors on venom production have been rarely demonstrated in animals. Here, we explore the impact of specific abiotic stresses on venom production of distinct populations of the sea anemone Nematostella vectensis (Actiniaria, Cnidaria) inhabiting estuaries over a broad geographic range where environmental conditions such as temperatures and salinity vary widely. Results: We challenged Nematostella polyps with heat, salinity, UV light stressors, and a combination of all three factors to determine how abiotic stressors impact toxin expression for individuals collected across this species’ range. Transcriptomics and proteomics revealed that the highly abundant toxin Nv1 was the most downregulated gene under heat stress conditions in multiple populations. Physiological measurements demonstrated that venom is metabolically costly to produce. Strikingly, under a range of abiotic stressors, individuals from different geographic locations along this latitudinal cline modulate differently their venom production levels. Conclusions: We demonstrate that abiotic stress results in venom regulation in Nematostella. Together with anecdotal observations from other cnidarian species, our results suggest this might be a universal phenomenon in Cnidaria. The decrease in venom production under stress conditions across species coupled with the evidence for its high metabolic cost in Nematostella suggests downregulation of venom production under certain conditions may be highly advantageous and adaptive. Furthermore, our results point towards local adaptation of this mechanism in Nematostella populations along a latitudinal cline, possibly resulting from distinct genetics and significant environmental differences between their habitats.publishedVersio

Modern venomics--Current insights, novel methods, and future perspectives in biological and applied animal venom research

Venoms have evolved >100 times in all major animal groups, and their components, known as toxins, have been fine-tuned over millions of years into highly effective biochemical weapons. There are many outstanding questions on the evolution of toxin arsenals, such as how venom genes originate, how venom contributes to the fitness of venomous species, and which modifications at the genomic, transcriptomic, and protein level drive their evolution. These questions have received particularly little attention outside of snakes, cone snails, spiders, and scorpions. Venom compounds have further become a source of inspiration for translational research using their diverse bioactivities for various applications. We highlight here recent advances and new strategies in modern venomics and discuss how recent technological innovations and multi-omic methods dramatically improve research on venomous animals. The study of genomes and their modifications through CRISPR and knockdown technologies will increase our understanding of how toxins evolve and which functions they have in the different ontogenetic stages during the development of venomous animals. Mass spectrometry imaging combined with spatial transcriptomics, in situ hybridization techniques, and modern computer tomography gives us further insights into the spatial distribution of toxins in the venom system and the function of the venom apparatus. All these evolutionary and biological insights contribute to more efficiently identify venom compounds, which can then be synthesized or produced in adapted expression systems to test their bioactivity. Finally, we critically discuss recent agrochemical, pharmaceutical, therapeutic, and diagnostic (so-called translational) aspects of venoms from which humans benefit.This work is funded by the European Cooperation in Science and Technology (COST, www.cost.eu) and based upon work from the COST Action CA19144 – European Venom Network (EUVEN, see https://euven-network.eu/). This review is an outcome of EUVEN Working Group 2 (“Best practices and innovative tools in venomics”) led by B.M.v.R. As coordinator of the group Animal Venomics until end 2021 at the Institute for Insectbiotechnology, JLU Giessen, B.M.v.R. acknowledges the Centre for Translational Biodiversity Genomics (LOEWE-TBG) in the programme “LOEWE – Landes-Offensive zur Entwicklung Wissenschaftlich-ökonomischer Exzellenz” of Hesse's Ministry of Higher Education, Research, and the Arts. B.M.v.R. and I.K. further acknowledge funding on venom research by the German Science Foundation to B.M.v.R. (DFG RE3454/6-1). A.C., A.V., and G.Z. were supported by the European Union's Horizon 2020 Research and Innovation program through Marie Sklodowska-Curie Individual Fellowships (grant agreements No. A.C.: 896849, A.V.: 841576, and G.Z.: 845674). M.P.I. is supported by the TALENTO Program by the Regional Madrid Government (2018-T1/BIO-11262). T.H.'s venom research is funded by the DFG projects 271522021 and 413120531. L.E. was supported by grant No. 7017-00288 from the Danish Council for Independent Research (Technology and Production Sciences). N.I. acknowledges funding on venom research by the Research Fund of Nevsehir Haci Bektas Veli University (project Nos. ABAP20F28, BAP18F26). M.I.K. and A.P. acknowledge support from GSRT National Research Infrastructure structural funding project INSPIRED (MIS 5002550). G.A. acknowledges support from the Slovenian Research Agency grants P1-0391, J4-8225, and J4-2547. G.G. acknowledges support from the Institute for Medical Research and Occupational Health, Zagreb, Croatia. E.A.B.U. is supported by a Norwegian Research Council FRIPRO-YRT Fellowship No. 287462

Phylogenetic trees depicting relationships among nucleotide and protein sequences from Fad genes.

<p>(a) Maximum Likelihood tree of Fad nucleotide sequences. Bootstrap values are shown next to nodes, values under 75% not reported. Accession numbers: AtFad KR154727, <i>C</i>. <i>gigas</i> 1 CGI_10016476, <i>C</i>. <i>gigas</i> 2 CGI_10019765, <i>C</i>. <i>gigas</i> 3 XM_011415748, <i>A</i>. <i>californica</i> 1 XM_005096991, <i>A</i>. <i>californica</i> 2 XM_005093125, <i>A</i>. <i>californica</i> 3 XM_005090516, <i>A</i>. <i>californica</i> 4 XM_005090520, <i>L</i>. <i>gigantea</i> 1 XM_009052983, <i>L</i>. <i>gigantea</i> 2 XM_009051720, <i>L</i>. <i>gigantea</i> 3 XM_009046829, <i>C</i>. <i>nobilis</i> (delta-5) KJ598786, <i>H</i>. <i>discus</i> (delta-5) 1 GQ470626, <i>H</i>. <i>discus</i> (delta-5) 2 GQ466197, <i>O</i>. <i>vulgaris</i> (delta-5) JN120258, <i>S</i>. <i>officinalis</i> KP260645. Exon-intron structure for <i>L</i>. <i>gigantea</i> and <i>C</i>. <i>gigas</i> are presented as gene models with exons (red boxes) and introns (red lines) adjacent to the corresponding species. (b) Maximum Likelihood tree of Fad protein sequences. Bootstrap values are shown next to nodes, and values under 75% not reported. Accession numbers: <i>C</i>. <i>gigas</i> 1 EKC33620, <i>C</i>. <i>gigas</i> 2 EKC30965, <i>C</i>. <i>gigas</i> 3 XP_011414050, <i>A</i>. <i>californica</i> 1 XP_005097048, <i>A</i>. <i>californica</i> 2 XP_005093182, <i>A</i>. <i>californica</i> 3 XP_005090573, <i>A</i>. <i>californica</i> 4 XP_005090577, <i>L</i>. <i>gigantea</i> 1 XP_009051231, <i>L</i>. <i>gigantea</i> 2 XP_009049968, <i>L</i>. <i>gigantea</i> 3 XP_009045077, <i>C</i>. <i>nobilis</i> (delta-5) AIC34709, <i>H</i>. <i>discus</i> (delta-5) 1 ADK38580, <i>H</i>. <i>discus</i> (delta-5) 2 ADK12703, <i>O</i>. <i>vulgaris</i> (delta-5) AEK20864, <i>S</i>. <i>officinalis</i> AKE92955.</p

Assembly summary statistics, for <i>C</i>. <i>farreri</i>, <i>A</i>. <i>irradians</i> and <i>C</i>. <i>olivaceus</i> transcriptomes using Trinity <i>de novo</i> assembler.

<p>Assembly summary statistics, for <i>C</i>. <i>farreri</i>, <i>A</i>. <i>irradians</i> and <i>C</i>. <i>olivaceus</i> transcriptomes using Trinity <i>de novo</i> assembler.</p

Maximum Likelihood trees of Elovl nucleotide and protein sequences.

<p>(a) Phylogenetic tree of Elovl nucleotide sequences. Bootstrap values are shown next to nodes, and values under 75% not reported. Accession numbers: NmElovla KR154728, NmElovlb KR154729, <i>C</i>. <i>gigas</i> 1 CGI_10028198, <i>C</i>. <i>gigas</i> 2 CGI_10008431, <i>C</i>. <i>gigas</i> 3 CGI_10020977, <i>C</i>. <i>gigas</i> 4 CGI_10012627 <i>C</i>. <i>gigas</i> 5 CGI_10007566, <i>C</i>. <i>gigas</i> 6 XM_011452473, <i>C</i>. <i>gigas</i> 7 XM_011452475, <i>A</i>. <i>californica</i> 1 XM_005098245, <i>A</i>. <i>californica</i> 2 XM_005095626, <i>A</i>. <i>californica</i> 3 XM_005106603, <i>L</i>. <i>gigantea</i> 1 XM_009047472, <i>L</i>. <i>gigantea</i> 2 XM_009052848, <i>C</i>. <i>nobilis</i> (<i>Elovl2/5</i>) KF245423, <i>O</i>. <i>vulgaris</i> (<i>Elovl4</i>) KJ590963, <i>O</i>. <i>vulgaris</i> (<i>Elovl2/5</i>) JX020803, <i>S</i>. <i>officinalis KP260646</i>. Exon-intron structure for <i>L</i>. <i>gigantea</i> and <i>C</i>. <i>gigas</i> are presented as gene models with exons (red boxes) and introns (red lines) adjacent to the corresponding species. (b) Phylogenetic tree of Elovl protein sequences. Bootstrap values shown next to nodes, and values under 75% not reported. Accession numbers: <i>C</i>. <i>gigas</i> 1 CGI_10028198, <i>C</i>. <i>gigas</i> 2 EKC41251, <i>C</i>. <i>gigas</i> 3 EKC25061, <i>C</i>. <i>gigas</i> 4 EKC39214, <i>C</i>. <i>gigas</i> 5 EKC19804, <i>C</i>. <i>gigas</i> 6 XP_011450775, <i>C</i>. <i>gigas</i> 7 XP_011450777, <i>A</i>. <i>californica</i> 1 XP_005098302, <i>A</i>. <i>californica</i> 2 XP_005095683, <i>A</i>. <i>californica</i> 3 XP_005106660, <i>L</i>. <i>gigantea</i> 1 XP_009045720, <i>L</i>. <i>gigantea</i> 2 XP_009051096, <i>C</i>. <i>nobilis</i> (Elovl2/5) AGW22128, <i>O</i>. <i>vulgaris</i> (Elovl4) AIA58679, <i>O</i>. <i>vulgaris</i> (Elovl2/5) AFM93779, <i>S</i>. <i>officinalis</i> AKE92956.</p

Alignment of Elovl protein sequences showing conserved and variable regions.

<p>The histidine box (HXXHH) is indicated with a black rectangular outline. Highly conserved aa residues (K, E, DT, L, HH, N, H, MY, YY, T, LF, F) are designated with the symbol ★.</p

List of candidate genes that encode putative Fad and Elovl proteins identified from <i>L</i>. <i>pealeii</i> and <i>C</i>. <i>farreri</i> transcriptome assemblies.

<p>List of candidate genes that encode putative Fad and Elovl proteins identified from <i>L</i>. <i>pealeii</i> and <i>C</i>. <i>farreri</i> transcriptome assemblies.</p

List of mollusc Fad and Elovl genes, currently available in NCBI NR protein and UNIPROT databases.

<p>List of mollusc Fad and Elovl genes, currently available in NCBI NR protein and UNIPROT databases.</p

Alignment of Fad protein sequences showing conserved and variable regions.

<p>The haeme binding domain (HPGG) and the three histidine boxes (HXXXH, HXXHH and QXXHH) are indicated with a black rectangular outline.</p

Fad and Elovl genes extracted from the currently available complete mollusc genomes of <i>C</i>. <i>gigas</i>, <i>A</i>. <i>californica</i> and <i>L</i>. <i>gigantea</i>.

<p>Fad and Elovl genes extracted from the currently available complete mollusc genomes of <i>C</i>. <i>gigas</i>, <i>A</i>. <i>californica</i> and <i>L</i>. <i>gigantea</i>.</p