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2020-06-03 Depth-dependent mycoplankton glycoside hydrolase gene activity in the open oceanevidence from the Tara Oceans eukaryote metatranscriptomes

Chrismas, N http://hdl.handle.net/10026.1/16031

10.1038/s41396-020-0687-2 The ISME Journal Springer Science and Business Media LLC

All content in PEARL is protected by copyright law. Author manuscripts are made available in accordance with publisher policies. Please cite only the published version using the details provided on the item record or document. In the absence of an open licence (e.g. Creative Commons), permissions for further reuse of content should be sought from the publisher or author. 1 Title: Depth-dependent mycoplankton glycoside hydrolase gene activity in the open ocean –

2 evidence from the Tara Ocean eukaryote metatranscriptomes

3

4 Running title: Fungal glycoside hydrolases in Tara Oceans metatranscriptomes

5

6 Nathan Alexis Mitchell Chrismas1,2 & Michael Cunliffe1,3

7 1Marine Biological Association of the UK, The Laboratory, Citadel Hill, Plymouth, UK

8 2School of Geographical Sciences, University of Bristol, University Road, Bristol, UK

9 3School of Biological and Marine Sciences, University of Plymouth, Plymouth, UK

10

11 Corresponding authors:

12 Nathan Chrismas [email protected]

13 Michael Cunliffe [email protected]

14

1 15 Abstract

16 Mycoplankton are widespread components of marine ecosystems, yet the full extent of their

17 functional roles remain poorly known. Marine mycoplankton are likely functionally analogous

18 to their terrestrial counterparts, including performing saprotrophy and degrading high-

19 molecular weight organic substrates using carbohydrate active enzymes (CAZymes). We

20 investigated the diversity of transcribed oceanic fungal CAZyme genes using the Tara

21 Oceans Metatranscriptomic Occurrences database. We revealed a high diversity of actively

22 transcribed fungal glycoside hydrolases in the open ocean, including a particularly high

23 diversity of enzymes that act upon cellulose in surface waters and the deep chlorophyll

24 maximum (DCM). A variety of other glycoside hydrolases acting on a range of

25 biogeochemically important polysaccharides including β-glucans and chitin were also found.

26 This analysis demonstrates that mycoplankton are active saprotrophs in the open ocean and

27 paves the way for future research into the depth-dependent roles of marine fungi in oceanic

28 carbon cycling, including the biological carbon pump.

29

30

2 31 Even though our understanding of marine fungal diversity is increasing [1, 2], a

32 comprehensive knowledge of their active functional ecology remains limited, especially in

33 the open ocean [1]. Fungal activity has been detected in corals, deep sea and coastal

34 sediments, and associated with phytoplankton blooms, including parasites [1, 2], but the full

35 extent that fungi are functionally active throughout the open ocean water column is yet to be

36 established.

37 Many terrestrial fungi occupy key roles as saprotrophs by decomposing and recycling

38 biogenic matter, making them intrinsic components of healthy functioning ecosystems [3]. In

39 coastal waters there is evidence that planktonic fungi (mycoplankton) degrade and utilise

40 phytoplankton-derived carbohydrate-rich matter in broadly analogous functional modes [4].

41 However, the extent that carbohydrate-based fungal saprotrophy occurs in the open ocean

42 remains largely speculated [1].

43 Glycoside hydrolases (GHs) are a ubiquitous group of carbohydrate-active enzymes

44 (CAZymes) [5] that degrade complex polysaccharides and are categorised into substrate-

45 specific families. In terrestrial fungi, secreted CAZymes are key to the functional potential of

46 saprotrophs and are the primary mode of degradation of high-molecular weight (HMW)

47 polysaccharides (e.g. wood). Coastal saprotrophic mycoplankton also employ secreted GHs

48 to degrade phytoplankton-derived HMW carbohydrate-based substrates [4], but the

49 prevalence and identity of the specific GHs families of active open ocean mycoplankton are

50 unknown.

51 Metagenomes from the Tara Oceans project have been used to assess

52 mycoplankton diversity [6, 7], but the associated metatranscriptomes are yet to be fully

53 explored from a fungal perspective. We interrogated the Marine Atlas of Tara Ocean

54 Unigenes (MATOU) metatranscriptomic occurrences database [8] for transcribed fungal GH

55 genes to explore broad-scale depth-dependent structuring in the oceans. The MATOU

56 database consists of all unique eukaryotic genes assembled from the Tara Oceans

57 metatranscriptomes (Unigenes), their associated taxonomy and occurrence within samples

58 (full methods described in [9]).

3 59 To identify GHs within the MATOU database, reference libraries were created for 61

60 fungal GH families and clustered using CD-Hit [9]. The MATOU Unigenes were searched

61 against these libraries using Diamond v.0.9.22 [10], yielding a database where each positive

62 Unigene match represents a unique GH (similar genes clustered when similarity <95% over

63 90% of the smallest sequence [8]). The database was screened for non-fungal Unigenes

64 using the MATOU taxonomy (Figure 1a, Supplementary Figure 1). After removal of

65 redundant matches (i.e. where multiple GHs matched to a single Unigene), 1,326 unique

66 fungal GH Unigenes were found (~0.001% of the entire Unigene catalogue) that occurred

67 44,386 times in all Tara Oceans samples.

68 The top ten GH families containing the greatest number of unique genes were

69 determined by ranking the sum of all Unigene occurrences from all samples for each family

70 (Figure 1b). Overall, the greatest number of unique GHs were involved in cellulose

71 degradation (GH7). Other substrates of the most diverse GH families included β-glucans

72 (GH17 and GH72), β-glycans (GH5, GH16, GH3), α-glucans (GH13), chitin (GH18), N-/O-

73 glycans (GH47) and xylan (GH43). GH diversity was dominated by genes originating from

74 the Ascomycota, except for the abundant GH7s, many of which were unclassified fungal

75 genes (Figure 1c).

76 Transcribed fungal GH genes were recovered from 66 stations (Figure 2). GH7

77 diversity was greatest in the surface and deep chlorophyll maximum (DCM), especially in

78 high productivity areas such as the Mediterranean Sea and the Indian Ocean (Figure 2b). At

79 stations where concomitant samples were available from the surface, DCM and

80 mesopelagic, a distinct drop in GH7 diversity was seen in the mesopelagic. The diversity of

81 other abundant GHs was more heterogeneous between sites (Figure 2c).

82 The high prevalence of unique GH7 transcribed genes in surface waters is likely a

83 response to increased ‘fresh’ phytoplankton-derived matter in the photic zone. Cellulose is a

84 key structural component of many phytoplankton cells [11, 12]. Polysaccharides, such as

85 cellulose, also represent a primary source of particulate organic carbon (POC) [13]. Of the

86 enzymes responsible for cellulose degradation, those within the GH7 family are typically the

4 87 most active, and are important in biomass degradation by terrestrial fungi [14]. The decline

88 in the number of unique GH7 genes below the DCM in the mesopelagic zone in the six sites

89 sampled suggests a shift in mycoplankton functionality due to depletion of readily available

90 phytoplankton-derived carbon sources, and corresponds with the decrease in overall

91 polysaccharide concentrations between surface waters and the mesopelagic zone [15].

92 Amongst the other diverse GH groups, the greatest number of unique genes was in

93 the GH17 family, a group of CAZymes that degrade β-glucans. Cladosporium mycoplankton

94 isolated from coastal waters have been shown to secrete GH17 β-1,3-glucosidase when

95 utilising laminarin [4], which is an algal-derived β-glucan that is a major POC component

96 [16]. Also prevalent were GH18 genes, responsible for degrading chitin, another major

97 polysaccharide and important component of zooplankton and some phytoplankton,

98 suggesting that chitin degradation is a functional role of open ocean mycoplankton, as with

99 fungi in freshwater lake ecosystems [17].

100 While the diversity of transcribed GHs is a strong indicator of active carbohydrate

101 metabolism by mycoplankton, the identity of these fungi remains uncertain. The extent of

102 GH7 genes with unresolved fungal taxonomy opens interesting questions about the

103 phylogeny of these taxa. The majority of the other GHs were affiliated to the Ascomycota, in

104 line with phylogenetic studies that show the phylum dominates open ocean mycoplankton

105 diversity [6]. However, there is a lack of early-diverging taxa (e.g. Chytridiomycota) within the

106 MATOU database. Since Chytridiomycota parasitism of phytoplankton takes place in the

107 open ocean [2] their absence highlights outstanding gaps in our understanding of the

108 functional ecology of marine fungi.

109 The vertical flux of POC in the open ocean is an essential feature of the biological

110 carbon pump (BCP), sustaining the oceans capability to sequester carbon [18].

111 Biogeochemical models of the BCP do not currently consider fungi (e.g. [19]). Given that

112 marine snow is an apparent hotspot for fungi [20], and that here we show differences in

113 fungal GH expression suggesting depth-dependent resource partitioning in relation to POC-

5 114 associated substrates, the recently proposed ‘mycoflux’ [2] should be considered within a

115 contemporary view of the BCP.

116

117 Competing interests

118 The authors declare no conflict of interest.

119

120 Acknowledgments

121 NC is supported by NERC grant NE/N006151/1. MC is supported by NERC grant

122 NE/N006151/1 and ERC grant 772584.

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169

170

171

172

8 173 Figure 1. a) Pipeline describing the steps involved in identifying fungal CAZymes within the

174 Tara Ocean MATOU Unigenes database. A fungal GH protein sequence reference database

175 was created from all the 61 characterised GH subfamilies found in fungi. This was

176 consolidated by clustering sequences at 95 % identity using CD-Hit before Diamond BLAST

177 databases were generated for each subfamily. The MATOU Unigenes were searched

178 against each of these 61 databases using the following thresholds: evalue > 1e-30 , score >

179 1, Subject Cov > 75 %, keeping only the best alignments. Positive matches were then

180 screened using the MATOU taxonomy to discriminate between fungal and non-fungal

181 Unigenes. Occurrences of each Unigene within the Tara Oceans transcriptomes were

182 returned. b) Fungal GH groups found in the MATOU Unigenes database Tara Oceans

183 Metatranscriptomic occurrences ranked by abundance over all Tara Oceans samples. c)

184 Total numbers and taxonomy of unique Fungal Unigenes from the 10 most abundant GH

185 groups.

186

187 Figure 2. a) Global map indicating Tara Oceans stations searched for fungal GH Unigenes

188 in the surface, deep chlorophyll maximum (DCM) and mesopelagic. b) Mean unique

189 unigenes/station for each of the major oceanic regions sampled. c) Depth dependent

190 partitioning of fungal GH Unigenes in the Surface (SUR), DCM and mesopelagic (MES).

9 database Total unique unigene

occurrences 10000 8000 2000 4000 6000

(a) (b) 0 Fungal GH MATOU CAZymes Sequences GH7 GH17 GH5 CD-Hit GH72 GH16 Build GH13 GH3 GH47 GH18 DIAMONDBLAST BLAST Databases GH43 GH12 GH37 GH32 GH Unigenes GH31 GH11 GH135 GH45 MATOU Filter Taxonomy GH38 GH10 GH20 GH1 GH62 GH30 GH28 Fungal Non-fungal GH51 Unigenes Unigenes GH55 GH63 GH152 GH78 Fungal MATOU Non-fungal MATOU GH93 Metatranscriptomic Metatranscriptomic GH79 Occurrences Occurrences GH81 (c) GH2 250 GH27 GH133 GH71 Ascomycota 200 GH128 Basidiomycota Unassigned Fungal GH65 GH115 150 GH35 GH132 GH75 100 GH36 GH53 GH6 50 GH29 Numbers of unique unigenes GH67 GH84 0 GH49 GH3 GH5 GH7 GH13 GH16 GH17 GH18 GH43 GH47 GH72 GH25 (a) (b) Surface 100% n=12 n=10 n=12 n=9 n=9 n=4 n=10

TARA_152 90% TARA_145 TARA_11TARA_23TARA_25 TARA_146 TARA_144 TARA_4 TARA_9TARA_22 TARA_26 80% TARA_132 TARA_143 TARA_150 TARA_30 TARA_142 TARA_151 70% TARA_131 TARA_135 TARA_148 TARA_20 TARA_36 TARA_38 TARA_137TARA_139 TARA_7 TARA_18 TARA_136 TARA_149 TARA_39 60% TARA_138 TARA_147 TARA_128 TARA_109 TARA_41 TARA_40 TARA_110 TARA_102 50% TARA_125 TARA_123 TARA_72 TARA_47 TARA_46 TARA_100 TARA_52 TARA_124 TARA_122 TARA_76 TARA_70 TARA_48 TARA_111 40% TARA_78TARA_68TARA_67 TARA_51 TARA_98 TARA_92 TARA_64 30% TARA_93 TARA_80 TARA_66 TARA_65 TARA_82 TARA_81 20% TARA_83 TARA_84 TARA_85 10% 0% [IO] [MS] [NAO][NPO] [SAO] [SO] [SPO] DCM 100% n=9 n=7 n=5 n=7 n=7 n=2 n=6 90% TARA_23 TARA_22 80% TARA_151TARA_9 TARA_25 TARA_132 TARA_135 TARA_143 TARA_36 TARA_150 TARA_7TARA_30 70% TARA_142 TARA_4 TARA_38 TARA_131TARA_137 TARA_18 60% TARA_41TARA_39 TARA_128 TARA_109 TARA_138 TARA_110 50% TARA_72 TARA_47 TARA_100 TARA_102 TARA_76 TARA_52 TARA_111 TARA_51 40% TARA_93 TARA_78 TARA_68 TARA_98 TARA_64 TARA_80 30% TARA_66 TARA_65 TARA_82 TARA_81 20% TARA_85 10% 0% [IO] [MS] [NAO][NPO] [SAO] [SO] [SPO] n=1 n=3 n=1 n=2 Mesopelagic 100% 90% 80% TARA_149 70% TARA_135 60% TARA_138

TARA_109 50%

TARA_100 40% TARA_68 TARA_98 30% 20% 10% 0% Key to Regions: [NPO] North Pacific Ocean [NAO][NPO] [SAO] [SPO] [IO] Indian Ocean [SAO] South Atlantic Ocean Key to GH Groups: [MS] Mediterranean Sea [SO] Southern Ocean GH7 GH17 GH5 GH72 GH16 [NAO] North Atlantic Ocean [SPO] South Pacific Ocean GH13 GH3 GH47 GH43 GH18

(c) TARA_100 TARA_109 TARA_135 SUR

DCM

MES

TARA_68

Depth TARA_138 TARA_98 SUR

DCM

MES

0 30 60 90 0 30 60 90 0 30 60 90 Total Unique unigenes/station