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Host, pathogen, and environment are determinants of the disease triangle, the latter being a key driver of disease outcomes and persistence within a community. The dinoflagellate genus Hematodinium is detrimental to crustaceans globally – considered to suppress the innate defences of hosts, making them more susceptible to co-infections. Evidence supporting immune-suppression is largely anecdotal and sourced from diffuse accounts of compromised decapods. We used a population of shore crabs ( Carcinus maenas ), where Hematodinium sp . is endemic, to determine the extent of collateral infections across two distinct environments (open water, semi-closed dock). Using a multi-resource approach (PCR, histology, haematology, population genetics, eDNA), we identified 162 Hematodinium- positive crabs and size/sex-matched these to 162 Hematodinium- free crabs out of 1,191 analysed. Crabs were interrogated for additional disease-causing agents; haplosporidians, microsporidians, mikrocytids, Vibrio spp., fungi, Sacculina , trematodes, and haemolymph bacterial loads. We found no significant differences in occurrence, severity or composition of collateral infections between Hematodinium -positive and Hematodinium -free crabs at either site, but crucially, we recorded site-restricted blends of pathogens. We found no gross signs of host cell immune reactivity toward Hematodinium in the presence or absence of other pathogens. We contend Hematodinium sp. is an immune-evader rather than immune-suppressor, which suggests an evolutionary drive toward latency in this environmentally plastic host.
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Environment, rather than Hematodinium parasitization, determines
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collateral disease contraction in a crustacean host
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Charlotte E. Davies1,*, Jessica E. Thomas1, Sophie H. Malkin1, Frederico M. Batista1,
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2, Andrew F. Rowley1,, Christopher J. Coates1,*
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1. Department of Biosciences, College of Science, Swansea University, Swansea, SA2 8PP, Wales,
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UK
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2 Current address: Centre for Environment Fisheries and Aquaculture Science (Cefas), Weymouth,
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Dorset, UK
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*Co-corresponding authors:
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CE Davies: c.e.davies@swansea.ac.uk [ORCID; https://orcid.org/0000-0002-5853-1934]
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CJ Coates: c.j.coates@swansea.ac.uk [ORCID; https://orcid.org/0000-0002-4471-4369]
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Running title: Hematodinium sp. is an immune-evader
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Abstract
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Host, pathogen, and environment are determinants of the disease triangle, the latter
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being a key driver of disease outcomes and persistence within a community. The
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dinoflagellate genus Hematodinium is detrimental to crustaceans globally
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considered to suppress the innate defences of hosts, making them more susceptible
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to co-infections. Evidence supporting immune-suppression is largely anecdotal and
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sourced from diffuse accounts of compromised decapods. We used a population of
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shore crabs (Carcinus maenas), where Hematodinium sp. is endemic, to determine
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the extent of collateral infections across two distinct environments (open water, semi-
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closed dock). Using a multi-resource approach (PCR, histology, haematology,
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population genetics, eDNA), we identified 162 Hematodinium-positive crabs and
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size/sex-matched these to 162 Hematodinium-free crabs out of 1,191 analysed.
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Crabs were interrogated for additional disease-causing agents; haplosporidians,
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microsporidians, mikrocytids, Vibrio spp., fungi, Sacculina, trematodes, and
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haemolymph bacterial loads. We found no significant differences in occurrence,
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severity or composition of collateral infections between Hematodinium-positive and
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Hematodinium-free crabs at either site, but crucially, we recorded site-restricted
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blends of pathogens. We found no gross signs of host cell immune reactivity toward
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Hematodinium in the presence or absence of other pathogens. We contend
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Hematodinium sp. is an immune-evader rather than immune-suppressor, which
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suggests an evolutionary drive toward latency in this environmentally plastic host.
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Key words: Endoparasites; disease connectivity; eDNA; aquatic vectors; fisheries;
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co-infections; marine epidemiology
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Introduction
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Host-parasite interactions are intimate and complex the host cannot afford to
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overreact and risk immediate costs such as metabolic derangement (or self-
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reactivity) and longer-term fitness costs, yet must maintain adequate defences to
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fight, and recover from, parasitic insult. Likewise, parasites tend not to be
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hypervirulent as acute damage compromises the host and minimises reproductive
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and transmission potential so there is a broad drive toward immune-evasion for all
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major groups of parasites (sometimes referred to as the immune-evasion hypothesis;
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reviewed by Schmid-Hempel (2009). Dinoflagellates of the genus Hematodinium
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include at least three parasitic species, H. perezi, H. australis and H. sp., which
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target a myriad of crustacean hosts, as far south as Australia (Gornik et al., 2013)
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and as far north as Greenland (Eigemann et al., 2010). Epizootics of Hematodinium
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spp. can devastate localised communities, fishery and aquaculture industries with
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langoustines, shrimp, and blue crabs representing some of the >40 known
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susceptible marine beasties (Albalat et al., 2016, 2012; Davies et al., 2019a; Li et al.,
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2013; Messick and Shields, 2000; Rowley et al., 2015; Shields et al., 2003; Small,
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2012; Small et al., 2012, 2006; Smith et al., 2015; Stentiford et al., 2001; Stentiford
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and Shields, 2005; Wilhelm and Mialhe, 1996). Signs of infection include carapace
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and blood (haemolymph) discolouration from the aggressive proliferation of parasite
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morphotypes within the liquid and solid (hepatopancreas) tissues, and lethargy
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caused by metabolic exhaustion (e.g., hypoproteinaemia). The advanced
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colonisation of the haemolymph leads to a severe decline in the number of
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circulating immune cells (i.e., the haemocytes) and regional tissue necrosis (e.g.,
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muscle) conditions that are likely to be fatal (Rowley et al., 2015). It is the
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conspicuous lack of host reactivity cellular innate immunity that is most intriguing
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about this host-pathogen antibiosis. Little direct evidence supports the reported view
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that Hematodinium spp. suppress the crustacean immune defences, thereby
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enabling the parasite to despoil its host of resources. Furthermore, direct
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suppression of the host’s defences would leave it vulnerable to other infectious or
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opportunistic agents, leading to micro-scale competition with the dinoflagellate.
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Several studies have characterised so-called co-infections of Hematodinium-positive
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crustaceans, including bacterial septicaemia and ciliates in tanner crabs
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(Chionoecetes bairdi; (Love et al., 1993; Meyers et al., 1987)), and yeast-like
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mycosis in edible (Cancer pagurus; (Smith et al., 2013)) and velvet swimming crabs
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(Necora puber; (Stentiford et al., 2003)). These co-infections elicit an immune
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response leading to haemocyte-directed nodulation and melanisation events
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(revealed by haematology and histopathology) but during events, Hematodinium
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are not targeted. Such observations suggest an immune-evasion strategy, rather
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than immune-suppression. Conversely, Li et al. (2015b, 2015a) presented evidence
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for immune activation of the Japanese blue crab (Portunus trituberculatus)
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containing Hematodinium sp., based on measurements of immune gene expression
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(mRNAs) and some enzymatic activities (e.g., phenoloxidase). These data are
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valuable as there are few studies on the interaction between Hematodinium sp. and
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crustacean innate immunity, however, no Hematodinium-derived effectors were
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identified.
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Co-infection, whereby a single individual or species is host to multiple infections
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(microbes or micro/macro-parasites) is commonly observed in both terrestrial and
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aquatic ecosystems. Characterising the drivers of these co-infections is pertinent to
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both the distribution of the parasite population, and in commercially and ecologically
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important species. In both open water fisheries and aquaculture, co-infections may
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be more prevalent due to a large variety of environmental reservoirs and high
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densities, respectively. Recently, we investigated the potential role of non-
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commercial, common shore crabs (Carcinus maenas) as potential reservoirs of
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disease, notably Hematodinium spp. (Davies et al., 2019a), as they are co-located
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with many high value shellfish, e.g., lobsters. During our initial survey, we noted the
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presence of several disease conditions in addition to that caused by Hematodinium
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sp., such as, the parasitic barnacle Sacculina carcini (Rowley et al., 2020).
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Herein, we have investigated the pervasive hypothesis that Hematodinium spp.
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leaves the host immunosuppressed (more susceptible to disease), with broad
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implications to both parasite and host evolutionary ecology. We looked for the
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presence of a diverse selection of known pathogens as agents of co-infections in
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equal numbers of Hematodinium-positive shore crabs and Hematodinium-free
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controls using haematology, histology (gill, hepatopancreas) and molecular
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diagnostics (PCR). Haplosporidians, microsporidians, mikrocytids, Vibrio spp., fungal
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species, S. carcini, paramyxids, trematodes and bacterial counts (CFU) were studied
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in crabs and water across two distinct locations to account for the putative influence
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of environment (e.g., habitat type) on parasite presence/diversity (Davies et al.,
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2020; Davies et al., 2019b). To complement the latter, we probed environmental
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DNA (eDNA) from the surrounding waters of infected crabs to assess the spatial and
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temporal ecology of all agents mentioned above.
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Methods
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Sample collection
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The study took place off the South Wales coast, UK at two distinct locations
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described in Davies et al. (2019a). The first location, a semi-closed Prince of Wales
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Dock, Swansea and the second, intertidal Mumbles Pier (referred to forthwith as
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Dock and Pier). For 12 months from November 2017 to October 2018, the shore
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crab population (n = 1,191) and seawater for environmental DNA analysis were
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surveyed at both locations. Laboratory regime, water filtration, histopathology and
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DNA extraction/quantification followed the procedures of Davies et al. (2019a). In
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addition, the present study included quantification of bacterial colony forming units
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(CFUs), which were determined by spreading 200 µL 1:1 haemolymph:sterile 3%
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NaCl solution (w/v) onto tryptone soya agar (TSA) plates supplemented with 2%
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NaCl (two technical replicates were performed per biological replicate). Plates were
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incubated at 25°C for 48 h and CFUs counted. The bacterial load of the haemolymph
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is expressed as CFUs per mL.
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PCR-based approaches and sequencing conditions
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All PCR reactions were carried out in 25 μL total reaction volumes using 2X Master
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Mix (New England Biolabs), oligonucleotide primers synthesized by Eurofins
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(Ebersberg, Germany), 1 μL DNA (ca. 50-200 ng for haemolymph and 3-80 ng for
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water eDNA) and performed on a BioRad T100 PCR thermal cycler. Products
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derived from PCR were visualized on a 2% agarose/TBE gel with GreenSafe
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premium nucleic acid stain (NZYTech, Portugal). For primary diagnostics, general
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Hematodinium primers targeting a highly variable 18S rRNA gene region (Hemat-F-
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1487 and Hemat-R- 1654; Supplementary Table 1) were used to verify the presence
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of any Hematodinium (see Davies et al. (2019a) for full details). Proceeding this, a
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control group of equal number, size and sex of Hematodinium-free crabs were
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chosen, and both groups were subjected to a series of targeted PCRs to determine
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the presence of haplosporidians, microsporidians, mikrocytids, paramyxids, Vibrio
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spp. and fungal species (Supplementary Table 1). Positive amplicons were purified
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using HT ExoSAP-IT™ Fast High-Throughput PCR Product Cleanup (Thermo Fisher
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Scientific, UK) following the manufacturer’s instructions, quantified using the Qubit®
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dsDNA High Sensitivity Kit and Fluorometer (Invitrogen, USA), and sequenced using
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Sanger’s method by Eurofins.
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All sequences have been deposited in the GenBank database under the accession
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numbers MN846355 - MN846359 (from C. maenas haemolymph DNA) and
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MT334463 - MT334513 (seawater eDNA) for haplosporidia (Davies et al., 2020a);
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MN985606 - MN985608 (seawater eDNA) and MN985609 (C. maenas haemolymph
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DNA) for microsporidia, MN985610 - MN985644 (seawater eDNA) for paramyxids,
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MT000071 - MT000098 (seawater eDNA) for mikrocytids and MT000100 -
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MT000103 (C. maenas haemolymph DNA) and MT000104 - MT000107 (seawater
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eDNA) for fungal species. Sequences for Vibrio spp. (<150 bp in length) were
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deposited in the NCBI short read archive (SRA) under accession numbers
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SAMN14133753 to SAMN14133757 (C. maenas haemolymph DNA) and
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SAMN14133758- SAMN14133765 (seawater eDNA; see Supplementary Table 2 for
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complete information).
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Population (genetic) analyses
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The cytochrome c oxidase I (COI) gene was amplified from crab DNA from February
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2018 across both survey sites (n = 100 in total) using oligonucleotides from Roman
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and Palumbi (2004) (Supplementary Table 1). PCR reactions were carried out as
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described above (25 μL total volume, Q5 hot start high fidelity 2X master mix [New
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England Biolabs], oligonucleotide primers synthesized by Eurofins, 1 μL DNA [ca.
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50-200 ng] and visualized on a 2% agarose/TBE gel). Amplicons were purified as
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above and sequenced using Sanger’s method by Source BioScience (Nottingham,
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UK). Chromatograms of the nucleotide sequences were analysed using Bioedit
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version 7.0.9.0 (Hall, 1999). Sequences were aligned and trimmed using Bioedit
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resulting in 93 COI sequences (n = 48 for the Pier location; n = 45 for the Dock
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location) with 481 bp (yielding 37 haplotypes; Genbank accession numbers
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MT547783-MT547812). Additionally, we included in our analyses 227 COI
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sequences of C. maenas from Darling et al. (Darling et al., 2008) (GenBank
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accession numbers FJ159008, FJ159010, FJ159012-13, FJ159015-18, FJ159020-
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21, FJ159023, FJ159025-36, FJ159039-44, FJ159047-52, FJ159057, FJ159059-64,
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FJ159069-80, FJ159084 and FJ159085) across 10 locations (Supplementary Table
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3 for details). ARLEQUIN (version 3.11) was used to calculate the number of
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haplotypes, haplotype diversity and nucleotide diversity (Excoffier et al., 2006;
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Excoffier and Lischer, 2010). Pairwise genetic differentiation (Fst) values using
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10,000 permutations were calculated among the 12 locations using ARLEQUIN. A
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median joining network (Bandelt et al., 1999) using the 293 C. maenas COI
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nucleotide sequences was constructed using PopART version 1.7 (Leigh and Bryant,
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2015). To visualize the genetic similarities between locations, a hierarchical
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clustering analysis based on Fst values with 500 random starts was performed using
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PRIMER v6 (Clarke and Gorley, 2006).
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Hematodinium sp. nucleotide sequences (partial coverage of the ITS1 region) from
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infected crabs (n = 162; GenBank MN057783MN057918) (Davies et al., 2019a)
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representing both the Pier (open) and Dock (semi-closed) locations were reassessed
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for genetic diversity. Sequences were inspected manually, trimmed, aligned, and
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those with undetermined (ambiguous) nucleotides were removed using Bioedit. In
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total, 102 Hematodinium sp. nucleotide sequences between 218 and 229 bp in
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length (n = 49 for the Pier location; n = 53 for the Dock location) were analysed using
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ARLEQUIN (taking into account insertions/deletions) as described above for C.
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maenas COI sequences.
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Tissue histology and microscopy
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Haemolymph preparations from all 324 crabs were assessed for the presence of
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parasites and pathogens, and putative (host) cellular responses (e.g. phagocytosis).
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To accomplish this, haemolymph was rapidly withdrawn, placed on glass slides, and
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examined using phase contrast microscopy. Tissue histology was used as the
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secondary tool after PCR, to screen all 324 crabs to estimate the severity of, and
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potential immune responses to, Hematodinium sp. or any collateral infection (e.g.,
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melanisation reactions, haemocyte aggregation). Histology took place according to
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methods described in Davies et al. (2019a). Briefly, gills and hepatopancreas/gonad
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were excised and fixed in Davidson’s seawater fixative for 24 h prior to their storage
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in 70% ethanol. Samples were processed using a Shandon™ automated tissue
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processor (Thermo Fisher Scientific, Altrincham, UK) prior to wax embedding. Blocks
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were cut at 57 µm thickness using an RM2245 microtome (Leica, Wetzlar,
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Germany) and sections were mounted onto glass slides using albumin-glycerol. All
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slides were stained with Cole’s haematoxylin and eosin prior to inspection using an
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Olympus BX41 microscope.
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Statistical analyses
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Binomial logistic regression models with Logit link functions (following Bernoulli
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distributions) were used (‘MASS’ package) to determine whether specific predictor
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variables had a significant effect on the probability of finding crabs testing positive for
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Hematodinium presence in the crab populations sampled. The information theoretic
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approach was used for model selection and assessment of performance (Richards,
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2005). Initial models are herein referred to as the full models. Once selected, each
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non-significant predictor variable from the full models was sequentially removed
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using the drop1 function to produce final models with increased predictive power,
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herein referred to as the reduced models. The drop1 function compares the initial full
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model with the same model, minus the least significant predictor variable. If the
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reduced model is significantly different from the initial full model (in the case of
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binomial response variables, a Chi-squared test is used to compare the residual sum
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of squares of both models), then the removed predictor variable is kept out of the
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new, reduced model (Table 1). This process continues hierarchically until a final
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reduced model is produced (Zuur et al., 2009). Full models included the input
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variables: Hematodinium (presence of parasite, 0 or 1), location (Dock or Pier),
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season (winter [Dec ’17, Jan ’18, Feb ‘18], spring [Mar ’18, Apr ’18, May ’18],
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summer [Jun ’18, Jul ’18, Aug ’18], autumn [Sept ’18, Oct ’18, Nov ’17]), carapace
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width (continuous number), sex (male or female), carapace colour (green, yellow or
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orange), fouling (presence of epibionts, 0 or 1), and limb loss (0 or 1; for all full
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models, see Supplementary Table 6).
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To explore the effects of Location [Pier or Dock] and Hematodinium [0 or 1] on
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the co-infection assemblage structure (based on abundances of individual
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infections), multivariate analysis of community composition was used. First, those
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crabs which suffered from one or more co-infections were subsampled (n = 78) and
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an unconstrained permutational multivariate analysis of variance (PERMANOVA)
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was run using the ‘adonis’ analysis (‘vegan’ package). This analysis was based on
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Bray-Curtis dissimilarities and 999 permutations. PERMANOVA is non-parametric,
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based on dissimilarities and uses permutation to compute an F-statistic (pseudo-F).
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Non-metric multidimensional scaling (nMDS) using the BrayCurtis measure on a
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square root transformation of the abundance data was also used to visualise
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differences in community composition between groups. This transformation retains
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the quantitative information while down-weighing the importance of the highly
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abundant infections (Clarke, 1993).
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Bacterial colony forming unit numbers and haemocyte counts were log
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transformed [Y=log(y+1)] and following testing for normality, a Mann-Whitney test
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(unpaired) was performed to compare ranks between Hematodinium vs.
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Hematodinium-free crabs, and infections within Hematodinium-positive/free crabs.
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All logistic models and composition analysis were run in RStudio Version 1.2.1335
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(©2009-2019 RStudio, Inc.) using R version 3.6.1. All other statistics (tests of
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normality, transformations and t-tests or non-parametric equivalent) as well as
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graphics, were produced using GraphPad Prism v8 for Windows (GraphPad
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Software, La Jolla California USA).
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Results
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Are there distinct populations of C. maenas at the two study sites?
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Overall, 1,191 crabs were sampled across the year-long survey, 603 from the Dock
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and 588 from the Pier (Davies et al., 2019a). Of these crabs, 13.6% were
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Hematodinium-positive via PCR. The population analysed for the present study is
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comprised of 324 crabs; 162 Hematodinium-positive and 162 size and sex-matched
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Hematodinium-free controls as determined by haematology, hepatopancreas and
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gill histology, and PCR. To determine whether crabs at either site represented
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distinct populations, we assessed the nucleotide diversity of the mitochondrial
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cytochrome c oxidase I submit (COI) gene from 93 crabs (n = 48/Pier; n = 45/Dock)
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using a 588 bp fragment (recommended by Roman and Palumbi (2004)).
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Crabs sampled from the Dock and Pier locations yielded 18 and 19 haplotypes,
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respectively (Genbank accession numbers MT547783-MT547812). In total, 72 COI
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haplotypes were identified among the 320 individual nucleotide sequences (481 bp
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in length) of C. maenas (Figure 1). Eight haplotypes observed in the Dock location
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were unique to this site (i.e. private haplotypes) and 10 private haplotypes were
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observed in the Pier location. Seven haplotypes were shared between Dock and Pier
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locations. Globally, the most common C. maenas haplotype (i.e. haplotype h1 shown
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in yellow in Figure 1) was also the most common haplotype observed in the Dock
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(frequency of 0.33) and Pier (frequency of 0.31) locations. For all locations,
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haplotype diversity (Hd) ranged from 0 to 0.933 and nucleotide diversity (π) from 0 to
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0.0067 (Supplementary Table 3). A similar genetic diversity (i.e. number of
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haplotypes, Hd and π) was observed between Dock and Pier locations
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(Supplementary Table 3). Significant pairwise genetic differentiation (Fst estimates
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between 0.604 and 0.902) was observed between European off-shelf locations
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(located in Iceland and Faroe Islands) and all western/northern locations
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(Supplementary Table 4). Pairwise comparison between sites within the
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western/northern locations revealed low Fst values and the large majority were non-
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significant (P > 0.05). No significant Fst value was observed between Dock and Pier
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locations, indicating that the crabs from two sites were genetically similar
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(Supplementary Table 4).
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Figure 1. Distribution of Carcinus maenas haplotypes observed in the present
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study (DOCK and PIER). At the top-right corner, a median joining haplotype
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network of C. maenas COI sequences is shown. The size of the circles of the
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haplotype network correspond to haplotype frequency and each connection
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represents a single nucleotide difference. The more common haplotypes are shown
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in yellow (h1), brown (h6), grey (h10), dark blue (h13) and light blue (h29). The less
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commons haplotypes are shown in white. At the bottom-right corner, a dendrogram
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of hierarchical clustering based on Fst values is displayed. Additional sequences
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were retrieved from Darling et al. (2008); ICE, Seltjarnarnes Iceland; TOR, Torshavn,
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Faroe Islands; MON, Mongstadt, Norway; OSL, Oslo, Norway; GOT, Goteborg,
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Sweden; NET, Den Helder, the Netherlands; FOW, Fowey, England; BIL, Bilbao,
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Spain; AVE, Aveiro, Portugal; CAD, Cadiz, Spain).
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Are Hematodinium parasites infecting crabs at the two study sites genetically
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distinct?
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No genetic differentiation (Fst= 0.004, P = 0.161) was observed between the two
303
locations. Seventy ITS-1 haplotypes were identified among the 102 individual
304
nucleotide sequences (218-229 bp in length) of Hematodinium sp. (Supplementary
305
Table 5). In total, 31 and 41 haplotypes were observed in the Pier and Dock
306
locations, respectively (Supplementary Figure 1). Only two haplotypes were shared
307
between the two locations and the most common haplotype was present at a
308
frequency of 0.29 in the Pier and 0.23 in the Dock. A high genetic diversity was
309
observed in both locations with a nucleotide diversity of 0.0130 and 0.0274 in the
310
Pier and Dock, respectively.
311
312
Does the presence of Hematodinium leave crabs more susceptible to
313
secondary infection?
314
Across both locations, 24.7% (40/162) of Hematodinium-positive crabs had one or
315
more co-infections (Figures 2 and 3). In terms of Hematodinium-free crabs, 23.5 %
316
(38/162) had one or more infection. In the Dock and Pier locations, 27.6 % (24/87)
317
and 21.3 % (16/75) of Hematodinium-positive crabs were co-infected, with 20.7 %
318
(18/87) and 26.7 % (20/75) of the Hematodinium-free crabs, respectively, testing
319
positive for these notable diseases (Figure 2). There were no significant differences
320
between the number of disease-agents between Hematodinium-positive and
321
Hematodinium-free crabs, regardless of location (P = 0.8967 overall, P = 0.3759
322
Dock, P = 0.5667 Pier, Fisher’s exact test, two-sided, Figures 2a-c). In the Dock
323
location, 3 out of 8 co-infections were observed in crabs (Vibrio spp., microsporidians
324
and Sacculina carcini, Figure 2e; Figure 3) and in the Pier location, 4 out of 8 co-
325
infections were observed (Vibrio spp., Haplosporidium sp., trematode parasites and
326
fungal species, Figure 2f; Figure 3). In terms of eDNA, we were unable to test
327
molecularly for the presence of Sacculina or trematode parasites, but the remaining
328
co-infections (6 out of 6) were all detected in the water (Figure 2g); with 5 out of 6 in
329
the Docks (haplosporidians, microsporidians, mikrocytids, Vibrio spp. and fungal
330
species; Figure 2h; Figure 3) and 5 out of 6 in the Pier; haplosporidians,
331
paramyxids, mikrocytids, Vibrio spp. and fungal species (Figure 2i; Figure 3).
332
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13
333
Figure 2 Percentage of Hematodinium-positive and Hematodinium-free
334
(‘control’) crabs with and without collateral infections in the total population (a),
335
Dock (b) and Pier (c) locations. Also, composition of co-infection from those crabs
336
which had one or more co-infections in Hematodinium positive and control crabs in
337
the total population (d), Dock (e) and Pier (f) locations and composition of infections,
338
including Hematodinium, from seawater eDNA in total (g) Dock (h) and Pier (i)
339
locations from 3 filter membranes per month over 12 months. Note: trematode and
340
Sacculina carcini presence were not tested for in eDNA samples but via histological
341
examination of crab tissues only.
342
343
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14
344
Figure 3 Diseases of shore crabs, Carcinus maenas collected from the two
345
reference locations. (a, b). Dinoflagellate parasite, Hematodinium (arrows) found in
346
the haemolymph (a) and gonadal tissue (b). Scale bars = 10 µm. (c). Co-infected
347
crab with the parasitic barnacle, Sacculina carcini (arrowheads) and Hematodinium
348
(He) in the hepatopancreas. Hepatopancreatic tubule (T). Scale bar = 100 µm. (d).
349
Encysted digenean trematode parasites in the hepatopancreas. Scale bar = 100 µm.
350
(e). Haplosporidium carcini infection showing uninucleate forms (arrows) in the
351
haemolymph. Scale bar = 10 µm. (f). Acute co-infection of crab with yeast like fungus
352
(arrows) and Hematodinium (Ha) in the haemolymph. Scale bar = 10 µm. (g) Colony
353
forming units (CFU) log transformed [Y=log(y+1)] of cultivable bacteria in
354
haemolymph of C. maenas. In the presence and absence of Hematodinium per
355
location. Values represent mean + 95% CI, asterisk denotes significant difference (P
356
0.05).
357
358
359
360
361
362
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15
What factors are associated with collateral infections?
363
Models were run using Hematodinium sp. as the response variable in order to
364
determine any associations between Hematodinium presence and co-infections
365
(Sacculina, trematodes, haplosporidians, microsporidians, Vibrio spp. and fungal
366
species), however, no co-infection revealed a significant relationship with t
367
Hematodinium sp. in the dataset overall, nor when separated by site
368
(Supplementary Table 6, Models S4-S6). However, the number of bacterial CFUs
369
was significantly higher in the haemolymph of Hematodinium-affected crabs
370
compared to Hematodinium-free crabs, and in the Dock location only (Figure 3g;
371
MannWhitney U = 2899, P = 0.0276 two-tailed).
372
Models were also run using the presence of one or more collateral infections as the
373
response variable against biometric data. Model 1, the reduced model, revealed that
374
size (carapace width; CW) was associated with the presence of one or more co-
375
infections (Table 1, Model 1). Smaller crabs were significantly more likely to display
376
co-infections compared to those that were ‘disease-free’ (P = 0.0137, mean ± SEM:
377
46.26 ± 1.16 vs. 49.80 ± 0.67 mm, respectively; Figure 4a). Hematodinium
378
presence, location, season, sex, crab colour, fouling (presence of epibionts), limb
379
loss and bacterial CFU number did not have a significant effect (Figure 4d, 4g;
380
Supplementary Table 6, Model S1).
381
Model 2, the reduced model using only Hematodinium-positive crabs and the
382
presence of one or more co-infections as the response variable, revealed that size
383
(CW), crab colour and limb loss are all associated with the presence of one or more
384
co-infections in the crabs (Table 1, Model 2). Smaller crabs were significantly more
385
likely to display co-infections (P = 0.0392, mean ± SEM: 46.20 ± 1.66 vs. 49.93 ±
386
0.96 mm, respectively; Figure 4b). Orange crabs were significantly less likely than
387
green or yellow to display co-infections (P = 0.0404; Figure 4e) and those crabs
388
which suffered the loss of one or more limbs were 2.4-fold less likely to present a co-
389
infection than those which had not lost limbs (P = 0.0174, 11.9 vs. 28.57 %
390
respectively; Figure 4h). Location, season, sex, fouling (presence of epibionts) and
391
bacterial CFU number did not have a significant effect on the presence of co-
392
infections in Hematodinium-positive crabs (Supplementary Table 6, Model S2).
393
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Using only control (Hematodinium-free) crabs and the presence of a ‘co-infection’ as
394
the response variable produced no reduced model as the input variables location,
395
season, size (carapace width), sex, crab colour, fouling (presence of epibionts), limb
396
loss and CFU did not have any discernible effect (Figures 4c, 2f, 2i;
397
Supplementary Table 6, Model S3).
398
399
400
Figure 4. Significant factors associated with the presence of one or more co-
401
infections. Carapace width (mm) of C. maenas presenting co-infections and those
402
without in the total population (a), Hematodinium-positive (b) and Hematodinium-free
403
‘controls’ (c). Percentage of C. maenas presenting one or more of the co-infections
404
according to crab colour in the total population (d), Hematodinium-positive (e) and
405
Hematodinium-free controls (f) and percentage of C. maenas presenting loss of one
406
or more limbs in the total population (g), Hematodinium-positive (h) and
407
Hematodinium-free controls (i). Values represent mean + 95% CI, asterisk denotes
408
significant difference (P 0.05).
409
410
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Table 1 Binomial logistic regression models (reduced from the full models,
411
Supplementary Materials: Table S1) testing the effects of biometric and
412
environmental predictor variables on the overall presence of one or more
413
coinfections.
414
Model
Predictor
variable
Estimate
(slope)
P-value
Model 1
CoInfect1 ~ CW + LimbLoss
CW
-0.03368
0.0137 *
Limb loss
-0.53384
0.1070.
df = 320
AIC: 352.13
Model 2
CoInfect1HEMAT ~ CW + Colour
CW
-0.03928
0.0392 *
+ LimbLoss
Colour (orange)
-1.36238
0.0404 *
Colour (yellow)
0.39885
0.3563
df = 157
Limb loss
-1.37492
0.0174 *
AIC: 168.19
*Statistically significant *P ≤ 0.05
415
Abbreviation: SE, standard error
416
417
Does location influence disease profiles in C. maenas?
418
In total, 80 individuals belonging to 6 co-infections were analyzed across 78 hosts
419
(Supplementary Table 7). There was no apparent significant effect of
420
Hematodinium sp. presence (F = 0.6453, P = 0.533) on co-infection number, but a
421
significant effect of location (F = 94.281, P = 0.001) on community structure. The
422
nMDS 2D ordination plots showed great overlap in the parasite community
423
composition of Hematodinium- infected and Hematodinium-free crabs (Figure 5a)
424
but varied greatly according to Dock and Pier locations (Figure 5b). Therefore,
425
whether or not a crab had Hematodinium sp. did not make a difference in the
426
composition of associated infections. Rather, co-infection community structure was
427
determined by location, differing between the Dock and Pier. The differences
428
between Dock and Pier locations were mostly driven by the presence of Sacculina,
429
this being found exclusively in the Docks, as well as trematode parasites,
430
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18
haplosporidians and fungal species, all of which were more abundant in the Pier
431
location.
432
433
Figure 5 nMDS ordinations of parasite (co-infection) community structure. (a).
434
Non-metric multidimensional (nMDS) ordination co-infection/parasite (haplosporidia,
435
microsporidia, Vibrio spp., fungal species, Sacculina carcini and trematodes)
436
community structure in crabs that were Hematodinium sp. positive (orange) and
437
Hematodinium sp. free (black control). (b). Non-metric multidimensional (nMDS)
438
ordination co-infection/parasite (haplosporidia, microsporidia, Vibrio spp., fungal
439
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19
species, Sacculina carcini and trematodes) community structure in crabs from Dock
440
(red) and Pier (blue) locations. Analyses were done using square-root transformation
441
of species’ abundances and Bray-Curtis similarity. Each point denotes an individual
442
crab with one or more co-infections.
443
Does the crab cellular immune system recognise and respond to
444
Hematodinium sp.?
445
We found no evidence of crab haemocyte reactivity toward Hematodinium sp. in the
446
absence or presence of other disease-causing agents (n = 162; Figure 6), either by
447
observing haemolymph freshly withdrawn from the haemocoel using phase contrast
448
microscopy (Figure 6a), or tissue histopathology (e.g., gills and hepatopancreas).
449
Ostensibly, crab haemocytes recognised and responded to other pathogens (Figure
450
6b) and damaged host tissues (Figure 6c), regardless of Hematodinium sp.
451
presence. In fact, even when haemocytes infiltrated tissues in large numbers, the
452
resident Hematodinium sp. were not caught-up in the ensheathment process (Figure
453
6d). These data suggest that Hematodinium sp. evades immune responses, even
454
when the host is responding to other damage- and pathogen-associated molecular
455
patterns.
456
457
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Figure 6 Interaction between Hematodinium and cellular defences of the shore
458
crab, Carcinus maenas. (a). Phase contrast micrograph of living cells including
459
Hematodinium trophonts (He) and host’s haemocytes (H). Note lack of contact and
460
interaction between the trophonts and these immune cells. (b). Host reaction in a
461
crab with co-infection with Hematodinium and the rhizocephalan parasite, Sacculina
462
carcini, with ensheathment by haemocytes (HS) around rootlets of S. carcini (SAC)
463
in the hepatopancreas. Note that the trophonts of Hematodinium (unlabelled arrows)
464
escape incorporation into the sheath around the rhizocephalan. (c). Infiltration and
465
encapsulation of necrotic tissue (NT) in the hepatopancreas of a crab with a severe
466
Hematodinium infection. Note that despite large numbers of this parasite in the
467
tissues they do not become enmeshed within the large haemocyte sheath (HS). (d).
468
Cellular response of haemocyte ensheathment (HS) around unknown debris. Note
469
large numbers of Hematodinium (unlabelled arrows) in the surrounding connective
470
tissue but not within the haemocyte sheath. Scale bars = 50 µm.
471
472
Discussion
473
Hematodinium-decapod antibiosis
474
Hematodinium spp. outbreaks can wreak havoc on blue crab populations in the USA
475
(Messick, 1994; Messick and Shields, 2000; Shields et al., 2003), cultured decapods
476
in China (Huang et al., 2021; Li et al., 2021) and represent a persistent scourge on
477
langoustine fisheries in Scotland (Albalat et al., 2016, 2012). Although the infectivity
478
and pathobiology of Hematodinium spp. in these hosts are well characterised (Small
479
et al., 2006), outside of commercial settings, their roles as ecological regulators of
480
crustacean populations are largely overlooked. To address this knowledge gap, we
481
examined whether Hematodinium sp. infection is a determinant of co-infection
482
health-related decline in the non-commercial shore crab C. maenas across two sites
483
(semi-closed Dock versus open water Pier). Davies et al. (2019a) recognised a
484
13.6% prevalence of Hematodinium sp. among these crabs using targeted PCR and
485
reported that no significant differences in the spatial or temporal profiles of the
486
disease between the two sites existed. Using these samples, we probed beyond
487
Hematodinium sp. for the presence and diversity of known macro- and micro-
488
parasites among crabs (e.g., S. carcini and haplosporidians, respectively) and the
489
surrounding waters of either location using eDNA. In the host, we identified six out of
490
the eight alternative diseases four via both molecular and histopathology
491
screening, and a further two via the latter technique. Data from crabs and eDNA
492
attributed the variation in collateral infection composition to location, and not to the
493
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21
presence of Hematodinium sp. Strikingly, we found no evidence to suggest that
494
Hematodinium-positive animals were more likely to harbour any one of the disease
495
targets when compared to those diagnosed Hematodinium-free (Figure 2). This
496
outcome is the same across, and within, both sites. When samples were decoupled
497
from Hematodinium sp. data, site-restricted blends of parasites were obvious (Table
498
2; Figure 2). For example, Hematodinium-positive crabs from the Dock contained
499
significantly higher levels of cultivable bacterial CFUs in the haemolymph when
500
compared to Hematodinium-free animals, but this was not the case at the Pier, or
501
when both sites were combined (Figure 3g). The parasitic castrator, Sacculina
502
carcini, was found exclusively in the Dock site and those crabs specifically contained
503
very high levels of CFUs, which we determined previously to be pathognomonic of S.
504
carcini infection (and not Hematodinium sp.) in this species (Rowley et al., 2020).
505
506
Table 2. Detection of pathogens and parasites across sites
507
Pathogen
C. maenas
Seawater eDNA
Dock
Pier
Dock
Pier
Haplosporidia
Microsporidia
Mikrocytids
Paramyxids
Vibrio spp.
Fungal species
Trematode parasites
NA
NA
Sacculina sp.
NA
NA
508
Several articles, including the expansive review by Stentiford and Shields (2005),
509
postulate that Hematodinium spp. suppression of the immune response of their
510
crustacean hosts is the most likely explanation for developing co-occurring
511
secondary/opportunistic infections, including septicaemia and ciliate infections in
512
tanner crabs (Chionoecetes bairdi; (Love et al., 1993; Meyers et al., 1987)) and
513
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22
yeast-like infections in edible crabs (Cancer pagurus), velvet swimming crabs
514
(Necora puber) and shore crabs (C. maenas; (Smith et al., 2013; Stentiford et al.,
515
2003)). Crabs are compromised to a certain extent by the presence of Hematodinium
516
spp., and as the infection progresses, the hosts tissues and resources are replaced
517
with the accumulating dinoflagellate burden, yet there is no evidence to suggest that
518
the parasite is directly suppressing the immune system. Animals can be weakened in
519
the absence of immunosuppression. We contend, based on our evidence, that
520
Hematodinium sp. is an immune-evader in shore crabs, and most likely, in all target
521
hosts. Stentiford et al. (2003) and Stentiford and Shields (2005) do note that there
522
was surprisingly little evidence of host reactivity toward Hematodinium in crabs co-
523
infected with yeast-like microbes. Mycosis is a rare event in the shore crabs studied
524
here (<0.3%; Davies et al., 2020b). Two crabs were harbouring both yeast-like and
525
Hematodinium sp. microbes, but haemocyte-derived nodulation and phagocytosis
526
were restricted to the fungus alone.
527
Phagocytosis and encapsulation/nodule formation (a process where haemocytes
528
wall off would-be colonisers) are the main cellular immune responses in
529
invertebrates (Ratcliffe et al., 1985). Direct observation of live haemocytes revealed
530
that even in cases where there are large numbers of free Hematodinium in
531
circulation, the haemocytes failed to recognise these as foreign. Similarly, nodules
532
and capsules seen histologically in the tissues of Hematodinium-positive crabs did
533
not contain such parasites suggesting an active mechanism to avoid accidental
534
incorporation into these defensive structures, i.e., immune-evasion. Preliminary
535
laboratory-based studies have revealed that C. pagurus with modest Hematodinium
536
infections cleared bacteria with similar dynamics to those free from such infections
537
(Smith and Rowley, 2015), implying that alleged immune-suppression by
538
Hematodinium has no effect on susceptibility to unrelated infections at least in early
539
mid phase. Late infections by Hematodinium cause a marked reduction in
540
defensive cells in circulation (Smith and Rowley, 2015) and these authors ascribed
541
this to a side effect of metabolic exhaustion rather than targeted inhibition of
542
haematopoiesis. Conversely, Li et al. (2015b, 2015a) presented evidence for
543
parasite detection (immune-recognition) and immune suppression in the Japanese
544
blue crab (Portunus trituberculatus) containing Hematodinium sp., based on
545
measurements of candidate immune gene expression (mRNAs) and some
546
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23
enzymatic activities linked to defence (e.g., phenoloxidase). Regarding these
547
studies, it is noteworthy that the selected immune genes were not
548
expressed/suppressed consistently across the 8 day experimental period, there was
549
a lack of correlation between haemograms and enzymic activities (no distinction
550
between active and total phenoloxidase activities), protein levels were not
551
quantitated so it is unclear if increased mRNAs led to more protein, and the mode of
552
crab inoculation itself is likely to induce at least a localised inflammatory response.
553
Subsequently, the authors suggested that P. trituberculatus recognise the presence
554
of Hematodinium sp. and employ oxidising/nitrosative radicals (O2- and NO) and
555
miRNAs to thwart the parasite (Li et al., 2018, 2016). From our data, we cannot rule
556
out the possibility that humoral (soluble)-mediated defences are involved in anti-
557
Hematodinium immunity.
558
Our study showed that the presence of one or more collateral infections overall
559
(regardless of Hematodinium sp. presence or not) was characterised by the size of
560
the animal. We also determined carapace width (size), colouration and limb loss to
561
be significant predictor variables for detecting one or more co-infections in
562
Hematodinium-positive crabs (Table 1, Figure 4), but not in Hematodinium-free
563
crabs. Size alone smaller carapace width was the common predictor variable for
564
co-infection occurrence among all crabs screened. This is to be expected as juvenile
565
crustaceans are known to be at higher risk of contracting disease when compared to
566
their older counterparts (Ashby and Bruns, 2018) . Larger crustaceans have longer
567
moult increments (therefore moult less often) than smaller, younger individuals
568
(Castro and Angell, 2000) giving more time for co-infections to manifest. Indeed, it is
569
postulated that Hematodinium zoospores use the soft cuticle found in newly moulted
570
crabs as a portal of entry to the haemocoel. Injury or breaching of the cuticle can act
571
as a portal of entry for microparasites (Davies et al., 2015).
572
Co-infection incidence or composition did not follow established seasonal patterns
573
associated with Hematodinium dynamics in this host (Supplementary Table 6)
574
high severity and low prevalence in the winter, followed by low severity and high
575
prevalence in the spring (Davies et al., 2019a). No temporal patterns of collateral
576
infection cases were found in either Hematodiniumpositive or Hematodinium-free
577
animals. In addition, we found no evidence of genetic differentiation between crabs
578
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24
and their resident Hematodinium ecotypes sampled from the Dock and Pier, with
579
both locations exhibiting similar genetic heterogeneity (Figure 1; Supplementary
580
Tables 3-5; Supplementary Figure 1). The lack of substantive genetic diversity of
581
host and Hematodinium between the sites is unlikely to account for the different
582
diseases profiles recorded, as such; the evidence listed above implies that disease
583
contraction in shore crabs depends on their environment.
584
Environment-driven contraction of disease
585
Both experimental sites have similar incidence of Hematodinium sp. infections as
586
well as comparable temporal dynamics of the parasite lifecycle (Davies et al.,
587
2019a). The life history of this parasite involves direct transmission of disease
588
resulting from moribund crabs releasing motile zoospores into the water column to
589
infect other susceptible crustaceans (Stentiford and Shields, 2005) and there is no
590
known non-crustacean reservoir of this disease. The Mumbles Pier location
591
supported a higher diversity of disease, in terms of eDNA as well as within the crabs
592
themselves, notably, two new species of Haplosporidia (Davies et al., 2020a).
593
Studies of historical data in Swansea Bay, where the Mumbles Pier location is
594
based, reveal persistence of benthic fauna associations as a heavily modified
595
waterbody bearing the ‘historical scars’ of nearby heavy industry and limited sewage
596
treatment (Callaway, 2016). Despite this, the area surrounding Mumbles Pier
597
showed a significantly higher species richness in benthic fauna than other locations
598
across the Bay (Callaway, 2016). There are few studies on species or biodiversity in
599
the Prince of Wales Dock, but anecdotal observations suggest a sludge-like benthic
600
environment with a large community of C. maenas and mussels, Mytilus edulis,
601
compared with the much more diverse Pier (Callaway, 2016; Powell-Jennings and
602
Callaway, 2018).
603
The profile of other microbes/parasites differed between the two sites notably with
604
S. carcini in the Dock and trematode infestations at the Pier. A possible explanation
605
of the differences in these diseases between the open water site (Pier at Mumbles
606
Head) and semi-enclosed dock site relates to the presence of reservoirs and/or
607
alternate hosts of disease as well as physical properties. For example, the
608
unidentified digenean trematode parasites seen in the hepatopancreas of crabs take
609
the form of encysted metacercarial stages (Figure 3d). Trematodes have multi-host
610
.CC-BY 4.0 International licensemade available under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted May 27, 2021. ; https://doi.org/10.1101/2021.05.26.445743doi: bioRxiv preprint
25
life cycles and predation of infected crabs by sea birds results in this definitive host
611
becoming infected subsequently releasing infective stages in their faeces that infect
612
various littorinid molluscs as the first intermediate host (Blakeslee et al., 2015).
613
Presumably, the putative absence of grazing littorinids in the semi-enclosed Dock
614
breaks the infection cycle despite the presence of both shore crabs and sea birds in
615
this site. The limited water flow in the Dock site probably favours the transmission of
616
S. carcini while the tidal flow at Mumbles reduces the chance of infectious stages
617
making contact with uninfected crabs.
618
Concluding remarks
619
Species of the parasitic dinoflagellate genus Hematodinium represent a substantive
620
threat to populations of commercially important crustaceans globally. Our work
621
described herein presents two major steps forward in our understanding of crab-
622
Hematodinium antibiosis:
623
1) Pre-existing Hematodinium sp. infection is not a determinant for collateral
624
disease contraction in shore crabs. No significant differences detected with
625
respect to ‘co-infection’ levels between Hematodinium-positive versus
626
Hematodinium-free crabs overall, or at either geographically close site. Clear
627
site-specific blends of parasites were found in the hosts, regardless of
628
Hematodinium presence/absence, and in the surrounding waters. Binomial
629
logistic regression models revealed carapace width (small) as a significant
630
predictor variable of co-infections overall. This is in contrast to seasonality and
631
sex as key predictor variables of Hematodinium sp. in crabs reported by Davies
632
et al. (2019a). If Hematodinium was a determinant for co-infections, we should
633
see a seasonal pattern, or sex bias, but we do not. Therefore, we contest that
634
co-infection occurrence is decoupled from Hematodinium sp.
635
2) Hematodinium sp. is most likely an immune-evader of the crustacean cellular
636
defences, and not an immune-suppressor. The mechanism employed to avoid
637
the attention of the host’s immune response does not influence susceptibility to
638
other infections. If Hematodinium sp. was supressing the immune system of
639
crabs, then we would expect to see more alternative opportunistic infections (we
640
do not), and/or, a reduced capacity of the host to react to other agents (we do
641
.CC-BY 4.0 International licensemade available under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted May 27, 2021. ; https://doi.org/10.1101/2021.05.26.445743doi: bioRxiv preprint
26
not). Haemocyte-driven responses remain intact in early infections, but never
642
target Hematodinium sp.
643
644
Overall, we resolve that Hematodinium spp. specifically evade the cellular immune
645
systems of the 40+ species of susceptible crustaceans rather than suppress it, and,
646
co-infection community structure is determined by location, i.e. habitat or
647
surrounding biodiversity (e.g. Davies et al., 2020; Davies et al., 2019b). The putative
648
mechanisms of such evasion remain unclear but may reside in molecular mimicry of
649
host by these parasites.
650
651
Acknowledgements: This study was part-funded by the European Regional
652
Development fund through the Ireland Wales Cooperation Programme, BLUEFISH,
653
awarded to CJC and AFR. AFR is also part-funded by the BBSRC/NERC ARCH UK
654
Aquaculture Initiative (BB/P017215/1), and start-up funds from Swansea University
655
assigned to CJC were used to supplement this study. The authors should like to
656
thank Mr. Peter Crocombe, Ms. Charlotte Bryan, Ms. Jenna Haslam and Ms. Emma
657
Quinn, and boat skippers, Mr. Keith Naylor, Mr. Max Robinson and Mr. Barry
658
Thomas, for assistance in the laboratory and field, respectively.
659
660
Author contributions.
661
Conceptualization, CC. Data curation, CD, SM, FB, AR, CC. Formal analysis, CD,
662
FB, AR, CC. Funding acquisition, AR, CC. Investigation, CD, JB, SM, FB, AR, CC.
663
Methodology, CD, SM, FB, AR, CC. Project administration, SM, AR, CC. Resources,
664
AR, CC. Software, CD, FB, AR, CC. Supervision, AR, CC. Validation, CD, CC.
665
Visualisation, CD, FB, AR, CC. Writing original draft presentation, review and
666
editing, CD, AR, CC.
667
668
Competing interests. The authors declare that they have no competing interests,
669
financial or otherwise.
670
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted May 27, 2021. ; https://doi.org/10.1101/2021.05.26.445743doi: bioRxiv preprint
27
671
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877
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Supplementary Table 1. Forward (Fwd) and reverse (Rev) primer sequences used for the amplification of pathogens from
879
Carcinus maenas and host DNA, by PCR. Each PCR run included initial denaturation and final extension steps, according to the
880
first and final temperatures, respectively, noted in the thermocycler settings.
881
Target
pathogen
Primers
Thermocycler settings
Amplicon
size (bp)
References
Dir.
Name
Sequence (5'3')
Final conc
(µM)
Temp
(°C)
Time
No. of
cycles
Hematodinium
Fwd
HematF1487
CCTGGCTCGATAGAGTTG
0.5
94
10 min
30
187
(Gruebl et
al., 2002)
sp.
Rev
HematR1654
GGCTGCCGTCCGAATTATTCAC
94
15 s
54
15 s
72
30 s
72
10 min
Fungi
Fwd
ITS1F
CTTGGTCATTTAGAGGAAGTAA
0.4
95
2 min
30
320
(Gardes
and Bruns,
1993; White
et al., 1990)
Rev
ITS2
GCTGCGTTCTTCATCGATGC
95
30 s
55
30 s
72
1 min
72
10 min
Haplosporidia
Fwd
C5fHap
GTAGTCCCARCYATAACBATGTC
1
95
5 min
30
NA
(Hartikainen
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et al.,
2014a)
spp (round 1)
Rev
Sb1n
GATCCHTCYGCAGGTTCACCTACG
95
30 s
65
45 s
72
1 min
72
10 min
Haplosporidia
Fwd
V5fHapl
GGACTCRGGGGGAAGTATGCT
1
95
5 min
30
650
(Hartikainen
et al.,
2014a)
sp (round 2)
Rev
Sb2nHap
CCTTGTTACGACTTBTYCTTCCTC
95
30 s
65
45 s
72
1 min
72
10 min
Mikrocytids
Fwd
mik451F
GCCGAGAYGGTTAAWGAGCCTCCT
0.5
95
5 min
30
967
(Hartikainen
et al.,
2014b)
(round 1)
Rev
mik1511R
CCTATTCAGCGCGCTCTGTTGAGA
95
30 s
64
45 s
72
1 min
72
10 min
Mikrocytids
Fwd
mik868F
GGACTACCAGWGGCGAAAGCGCCT
0.5
95
5 min
30
481
(Hartikainen
et al.,
2014b)
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(round 2)
Rev
mik1340R
TGCATCACGGACCTACCTTWGACC
95
30 s
62
45 s
72
1 min
72
10 min
Vibrio spp.
Fwd
567F
GGCGTAAAGCGCATGCAGGT
0.5
94
10 min
30
113
(Thompson
et al., 2004;
Vezzulli et
al., 2012)
Rev
680R
GAAATTCTACCCCCCTCTACAG
94
30 s
58
30 s
72
1 min
72
10 min
Microsporidia
Fwd
CTMicrosp-G
CACCAGGTTGATTCTGCCTGAC
0.5
94
5 min
35
1100-
(Fedorko et
al., 1995;
Stentiford et
al., 2018)
Rev
Microsp1342r
ACGGGCGGTGTGTACAAAGAACAG
94
30 s
1300
63
30 s
72
90 s
72
10 min
Paramyxid
Fwd
Para1+fN
GCGAGGGGTAAAATCTGAT
1
95
3 min
42
NA
(Ward et al.,
2016)
(round 1)
Rev
ParaGENrDBn
GTGTACAAAGGACAGGGACT
95
30 s
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67
1 min
72
1 min
72
5 min
Paramyxid
Fwd
Para3+fN
GGCTTCTGGGAGATTACGG
1
95
3 min
42
450
(Ward et al.,
2016)
(round 2)
Rev
Para2+rN
TCGATCCCRACTGRGCC
95
30 s
62
1 min
72
1 min
72
5 min
Cytochrome c
Fwd
Cm_F
GCTTGAGCTGGCATAGTAGG
0.5
94
2 min
30
588
(Roman
and
Palumbi,
2004)
oxidase I (COI)
Rev
Cm_R
GAATGAGGTGTTTAGATTTCG
94
1 min
gene
50
1 min
72
1 min
72
10 min
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Supplementary Table 2. Blast results and accession numbers of positive samples obtained in this study and used for phylogenetic
882
analyses.
883
884
GenBank ID
Sample
Target
Primers
Sample type
Top blast
Qu
ery
cov
er
% ID
MN846355
P2_Dec
Haplosporidia
V5fHapl /Sb2nHap
Carcinus maenas haemolymph
DNA
MN537839.1
93
97.12
MN846356
P30_Feb
Haplosporidia
V5fHapl /Sb2nHap
Carcinus maenas haemolymph
DNA
MN537839.1
93
97.62
MN846357
P24_Jun
Haplosporidia
V5fHapl /Sb2nHap
Carcinus maenas haemolymph
DNA
MN537839.1
93
97.28
MN846358
P49_Sept
Haplosporidia
V5fHapl /Sb2nHap
Carcinus maenas haemolymph
DNA
MN537839.1
93
97.12
MN846359
P24_Oct
Haplosporidia
V5fHapl /Sb2nHap
Carcinus maenas haemolymph
DNA
MN537839.1
93
97.62
MT334463
Water_P1A_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
MT334464
Water_P1B_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.84
MT334465
Water_P2A_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
MT334466
Water_P2B_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.68
MT334467
Water_P3A_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
MT334468
Water_P1A_Dec
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208581.1
100
86.67
MT334469
Water_P1B_Dec
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.84
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MT334470
Water_P2A_Dec
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
88
95.34
MT334471
Water_P3A_Dec
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
MT334472
Water_P1A_Jan
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
88
95.65
MT334473
Water_P1B_Jan
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
88
95.34
MT334474
Water_M2Pool_Ja
n
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.39
MT334475
Water_P3A_Jan
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208603.1
100
98.88
MT334476
Water_P3B_Jan
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.14
MT334477
Water_P2B_Feb
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208603.1
100
99.52
MT334478
Water_P3Pool_Fe
b
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208603.1
100
90.27
MT334479
Water_P1B_Mar
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
MT311214.1
100
99.5
MT334480
Water_P3B_Mar
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.39
MT334481
Water_P2B_Apr
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.64
MT334482
Water_P3A_Apr
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.65
MT334483
Water_P2Pool_Ma
y
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
86
95.11
MT334484
Water_P3A_May
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.37
MT334485
Water_P3B_May
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.65
MT334486
Water_P2A_Jun
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
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MT334487
Water_P2B_Jun
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.91
MT334488
Water_P3A_Jun
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208596.1
100
88.53
MT334489
Water_P2B_Jul
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.36
MT334490
Water_P3B_Jul
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.36
MT334491
Water_P1A_Aug
_band1
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208596.1
100
88.53
MT334492
Water_P1A_Aug
_band2
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
100
MT334493
Water_P1A_Aug
_band3
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
99
99.64
MT334494
Water_P3A_Aug
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
97
99.54
MT334495
Water_P3B_Aug
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.65
MT334496
Water_P1A_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
JN368430.1
92
93.75
MT334497
Water_P1B_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.2
MT334498
Water_P2A_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
MK070859.1
100
93.15
MT334499
Water_P2B_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.84
MT334500
Water_P3A_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.65
MT334501
Water_P3B_Sept
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208596.1
95
85.52
MT334502
Water_P1A_Oct
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208603.1
100
90.91
MT334503
Water_P2B_Oct
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.14
MT334504
Water_P3A_Oct
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208580.1
89
95.65
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MT334505
Water_P3B_Oct
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KY522823.1
100
99.84
MT334506
Water_P3A_Jul
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208603.1
100
99.04
MT334507
Water_D3B_Nov
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
MK070858.1
100
99.03
MT334508
Water_D1B_Jan
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
GU385680.1
99
93.88
MT334509
Water_D1A_Feb
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
KF208570.1
100
99.52
MT334510
Water_D2B_Feb
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
GU385680.1
97
89.93
MT334511
Water_D2A_Mar
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
GU385680.1
97
93.18
MT334512
Water_D1B_Apr
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
DQ103863.1
100
99.81
MT334513
Water_D2B_May
Haplosporidia
V5fHapl /Sb2nHap
Seawater filter (eDNA)
MK070858.1
100
99.68
MN985606
Water_D1B_Jun
Microsporidia
CTMicrosp-G /
Microsp1342r
Seawater filter (eDNA)
KR303710.1
99
96.95
MN985607
Water_D2B_Jun
Microsporidia
CTMicrosp-G /
Microsp1342r
Seawater filter (eDNA)
FJ756177.1
98
98.84
MN985608
Water_D3B_Jun
Microsporidia
CTMicrosp-G /
Microsp1342r
Seawater filter (eDNA)
FJ756177.1
98
99.49
MN985609
Crab_D16_Aug
Microsporidia
CTMicrosp-G /
Microsp1342r
Carcinus maenas haemolymph
DNA
MG241440.1
100
83.73
MN985610
Water_P2A_Nov
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.5
MN985611
Water_P3A_Nov
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
100
MN985612
Water_P3B_Nov
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
87
91.19
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MN985613
Water_P2A_Dec
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985614
Water_P1A_Jan
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.75
MN985615
Water_P1B_Jan
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259323.1
99
88.91
MN985616
Water_P1B_Feb
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.53
MN985617
Water_P2B_Mar
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.74
MN985618
Water_P1A_Apr
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.52
MN985619
Water_P1B_Apr
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.5
MN985620
Water_P2A_Apr
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.75
MN985621
Water_P2B_Apr
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
100
MN985622
Water_P3B_Apr
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985623
Water_P2A_May
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.05
MN985624
Water_P2B_May
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
100
MN985625
Water_P2B_May(2
)
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.5
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MN985626
Water_P3A_May
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
100
MN985627
Water_P1B_Jun
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259327.1
100
93.36
MN985628
Water_P2B_Jun
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259327.1
99
100
MN985629
Water_P3B_Jun
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985630
Water_P1A_Jul
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985631
Water_P1B_Jul
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
94
96.37
MN985632
Water_P1B_Jul(2)
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
100
99.07
MN985633
Water_P1A_Aug
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.48
MN985634
Water_P2B_Aug
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.48
MN985635
Water_P3A_Aug
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985636
Water_P1B_Sept_
1
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
99.75
MN985637
Water_P1B_Sept_
2
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
100
99.3
MN985638
Water_P2B_Sept
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
100
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MN985639
Water_P3A_Sept
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
99
100
MN985640
Water_P3B_Sept
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
KX259324.1
100
99.5
MN985641
Water_P1A_Oct_1
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
94
91.96
MN985642
Water_P1A_Oct_2
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
100
98.84
MN985643
Water_P1B_Oct
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
100
99.07
MN985644
Water_P3A_Oct
Paramyxid
Para3+fN /
Para2+rN
Seawater filter (eDNA)
MH304633.1
91
91.63
MT000071
Water_D3A_Nov
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000072
Water_P2A_Nov
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KJ150292.1
100
99.56
MT000073
Water_P3A_Nov
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
83
82.89
MT000074
Water_P1A_Dec
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.53
MT000075
Water_D1A_Jan
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000076
Water_P3B_Jan
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.76
MT000077
Water_D1A_Feb
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
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MT000078
Water_D2A_Feb
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000079
Water_P3A_Feb
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.73
MT000080
Water_D1B_Jun
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
99.58
MT000081
Water_D2B_Jun
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000082
Water_D3B_Jun
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
99.57
MT000083
Water_D1A_Jul
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
98.72
MT000084
Water_D2A_Jul
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000085
Water_D3A_Jul
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000086
Water_D3B_Jul
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000087
Water_P3A_Aug
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.73
MT000088
Water_P1A_Sep
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.73
MT000089
Water_P2A_Sep
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.73
MT000090
Water_P3A_Sep
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.53
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MT000091
Water_D1A_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
99.79
MT000092
Water_D3A_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
100
MT000093
Water_P1A_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF548050.1
100
87.73
MT000094
Water_P2A_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KP164508.1
94
88.14
MT000095
Water_P3A_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KJ150292.1
100
98.91
MT000096
Water_P1B_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KJ150292.1
100
99.56
MT000097
Water_P3B_Oct
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KJ150292.1
93
92.31
MT000098
Water_D1B_Nov
Mikrocytid
mik868F /
mik1340R
Seawater filter (eDNA)
KF297353.1
100
99.15
MT000100
Crab_P5_Dec
Fungal
species
ITS1F / ITS2
Carcinus maenas haemolymph
DNA
HM119586.1
100
88.55
MT000101
Crab_P50_May
Fungal
species
ITS1F / ITS2
Carcinus maenas haemolymph
DNA
HM119586.1
100
87.88
MT000102
Crab_P21_Aug
Fungal
species
ITS1F / ITS2
Carcinus maenas haemolymph
DNA
HM119586.1
100
87.88
MT000103
Crab_P28_Nov
Fungal
species
ITS1F / ITS2
Carcinus maenas haemolymph
DNA
JQ038334.1
100
86.18
MT000104
Water_D3A_Mar
Fungal
species
ITS1F / ITS2
Seawater filter (eDNA)
KY115002.1
28
96.25
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MT000105
Water_D1A_Apr
Fungal
species
ITS1F / ITS2
Seawater filter (eDNA)
MH625678.1
22
95.59
MT000106
Water_D1A_May
Fungal
species
ITS1F / ITS2
Seawater filter (eDNA)
KY115002.1
32
89.13
MT000107
Water_D2A_Aug
Fungal
species
ITS1F / ITS2
Seawater filter (eDNA)
MH625594.1
100
76.65
SAMN14133753
Crab_D15_Jul
Vibrio sp.
567F / 680R
Carcinus maenas haemolymph
DNA
MT510186.1
100
100
SAMN14133754
Crab_P6_Sept
Vibrio sp.
567F / 680R
Carcinus maenas haemolymph
DNA
MT510186.1
100
98.63
SAMN14133755
Crab_D49_Oct
Vibrio sp.
567F / 680R
Carcinus maenas haemolymph
DNA
NONE
SAMN14133756
Crab_D18_Aug
Vibrio sp.
567F / 680R
Carcinus maenas haemolymph
DNA
MT634723.1
95
100
SAMN14133757
Crab_D16_Aug
Vibrio sp.
567F / 680R
Carcinus maenas haemolymph
DNA
MT634723.1
70
97.96
SAMN14133758
Water_P1B_Jul
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
KF941973.1
98
94.52
SAMN14133759
Water_P1B_Aug
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
MT510186.1
100
98.63
SAMN14133760
Water_P1B_Sept
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
LN871542.1
88
97.01
SAMN14133761
Water_P1B_Oct
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
HE584789.1
96
89.23
SAMN14133762
Water_D1B_Jul
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
MN023424.1
100
97.3
SAMN14133763
Water_D1B_Aug
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
MT510186.1
100
98.63
SAMN14133764
Water_D1B_Sept
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
KY282191.1
72
100
SAMN14133765
Water_D1B_Oct
Vibrio sp.
567F / 680R
Seawater filter (eDNA)
KF994032.1
98
94.44
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Supplementary Table 3. Genetic diversity indices of C. maenas COI sequences
885
(481 bp).
886
Location
Code
n
h
P
Hd (SD)
π (SD)
Seltjarnarnes, Iceland*
ICE
18
1
0
0
0
Torshavn, Faroe Islands*
TOR
19
2
1
0.515 (0.052)
0.0032 (0.0022)
Mongstad, Norway*
MON
22
12
5
0.853 (0.065)
0.0044 (0.0028)
Oslo, Norway
OSL
9
5
1
0.806 (0.120)
0.0067 (0.0043)
Goteborg, Sweden*
GOT
15
10
3
0.933 (0.045)
0.0067 (0.0041)
Den Helder, the Netherlands*
NET
45
17
7
0.784 (0.059)
0.0043 (0.0027)
Dock, Swansea, UK
DOCK
45
18
8
0.855 (0.038)
0.0042 (0.0027)
Mumbles Pier, UK
PIER
48
19
10
0.823 (0.041)
0.0039 (0.0025)
Fowey, England*
FOW
14
8
3
0.890 (0.060)
0.0047 (0.0031)
Bilbao, Spain*
BIL
15
6
3
0.648 (0.134)
0.0031 (0.0022)
Aveiro, Portugal*
AVE
23
9
3
0.795 (0.065)
0.0037 (0.0025)
Cadiz, Spain*
CAD
47
21
12
0.864 (0.042)
0.0039 (0.002524
n, number of individuals analysed; h, number of haplotypes; P, private haplotypes; Hd (SD), haplotype
887
diversity (standard deviation); π (SD), nucleotide diversity (standard deviation).
888
889
890
891
Supplementary Table 4. Pairwise genetic differentiation (Fst) of Carcinus maenas
892
samples estimated using COI sequence data.
893
1
ICE
2
TOR
3
MON
4
OSL
5
GOT
6
NET
7
DOC
K
8
PIER
9
FOW
10
BIL
11
AVE
12
CAD
2
0.381
0.000
3
0.839
0.688
0.000
4
0.859
0.670
0.022
0.000
5
0.789
0.604
0.013
-0.024
0.000
6.
0.802
0.678
0.019
0.064
0.038
0.000
7
0.797
0.666
0.028
0.083
0.016
0.001
0.000
8
0.805
0.675
0.070
0.123
0.045
0.010
-0.006
0.000
9
0.857
0.675
-0.016
0.015
-0.018
-0.019
-0.012
0.003
0.000
10
0.902
0.730
0.054
0.118
0.067
-0.018
0.006
0.007
0.012
0.000
11
0.859
0.710
-0.006
0.068
0.040
-0.013
0.001
0.027
-0.011
-0.012
0.000
12
0.821
0.710
0.032
0.108
0.103
0.005
0.042
0.057
0.016
-0.009
-0.006
0.000
Values in bold are statistically significant (p < 0.05).
894
895
896
897
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Supplementary Table 5. Genetic diversity indices of Hematodinium sp. ITS-1
898
sequences from infected Carcinus maenas collected in Swansea Dock and in the
899
Mumbles Pier during winter, spring, summer, and autumn.
900
Location
Season
n
h
Hd (SD)
π (SD)
Pier
Winter
8
3
0.464 (0.200)
0.0305 (0.0182)
Spring
20
15
0.958 (0.033)
0.0180 (0.0105)
Summer
13
11
0.961 (0.050)
0.0201 (0.0123)
Autumn
8
8
1.000 (0.0625)
0.0191 (0.0120)
Total
49
31
0.917 (0.0343)
0.0199 (0.0109)
Dock
Winter
13
9
0.872 (0.091)
0.0322 (0.0181)
Spring
14
11
0.934 (0.061)
0.0261 (0.0149)
Summer
15
15
1.000 (0.024)
0.0289 (0.0162)
Autumn
11
10
0.982 (0.046)
0.0274 (0.0159)
Total
53
41
0.951 (0.025)
0.0274 (0.0146)
Both sites
Overall
102
70
0.935 (0.021)
0.0228 (0.0122)
n, number of individuals analysed; h, number of haplotypes; P, private haplotypes; Hd (SD),
901
haplotype diversity (standard deviation); π (SD), nucleotide diversity (standard deviation).
902
903
904
Supplementary Figure 1. Haplotype network of partial ITS region (252 bp) from
905
Hematodinium species infecting shore crabs. In total, 102 Hematodinium sequences
906
from two sites (n = 49/Pier; n = 53/Dock) were analysed. The size of each circle depicted is
907
proportional to the frequency of a haplotype within the dataset. The network was visualized
908
using POPART (Leigh and Bryant, 2015).
909
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Supplementary Table 6. Full model used in order to predict response variable of
910
presence of one or more coinfections before reduction. Asterisk denotes significance
911
(P ≤ 0.05).
912
Model
Predictor variable
Estimate
(slope)
SE
P-value
Model S1
CoInfect1 ~ Hemat +
Hemat
0.07426
0.27317
0.78575
Location + Season +
CW +
Location (pier)
-0.35599
0.31114
0.25256
Sex + Colour +
LimbLoss
Season (Spring)
-0.15239
0.41978
0.71659
+ Fouling
Season (Summer)
-0.03200
0.42583
0.94010
Season (Winter)
-0.49015
0.46174
0.28845
df = 312
CW
-0.04199
0.01542
0.00646 **
AIC: 352.76
Sex (male)
0.38302
0.33016
0.24601
Colour (orange)
0.01962
0.39744
0.96062
Colour (yellow)
0.31485
0.34121
0.35614
Limb loss
-0.56282
0.34125
0.09909
Fouling
-0.62346
0.43881
0.15538
Model S2
CoInfect1HEMAT ~
Location (pier)
-0.63614
0.46889
0.1749
Location + Season +
CW +
Season (Spring)
-0.23071
0.66875
0.7301
Sex + Colour +
LimbLoss
Season (Summer)
-1.02654
0.67776
0.1299
+ Fouling
Season (Winter)
-0.91081
0.71682
0.2039
CW
-0.04612
0.02204
0.0364 *
df = 154
Sex (male)
-0.09198
0.48664
0.8501
AIC: 170.73
Colour (orange)
-1.22687
0.76605
0.1093
Colour (yellow)
0.42058
0.51301
0.4123
Limb loss
-1.42522
0.59542
0.0167 *
Fouling
-0.96667
0.70577
0.1708
Model S3
CoInfect1CONTROL ~
Location (pier)
0.03996
0.45151
0.929
Location + Season +
CW +
Season (Spring)
-0.21535
0.65644
0.743
Sex + Colour +
LimbLoss
Season (Summer)
0.57898
0.62695
0.356
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+ Fouling
Season (Winter)
-0.41023
0.70226
0.559
CW
-0.03354
0.02244
0.135
df = 157
Sex (male)
0.80267
0.48811
0.100
AIC: 183.17
Colour (orange)
0.67402
0.52790
0.202
Colour (yellow)
0.13042
0.54066
0.809
Limbloss
-0.04315
0.46013
0.925
Fouling
-0.63988
0.62217
0.304
Model S4