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Algal Research

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Diversity of monosaccharides in marine macroalgae from the EasternMediterranean Sea

Arthur Robina, Patrick Chavela, Alexander Chemodanova, Alvaro Israelb, Alexander Golberga,⁎

a Porter School of Environmental Studies, Tel Aviv University, Israelb Israel Oceanographic and Limnological Research, Ltd., The National Institute of Oceanography, Israel

A R T I C L E I N F O

Keywords:MacroalgaeBiodiversityMonosaccharidesDiversityBiorefineryUlvaCladophoraGalaxauraNemalionGracilariaPadinaSargassum

A B S T R A C T

Macroalgae are primary producers bearing key roles in the normal functioning of marine environments. Thecritical energy carriers that macroalgae produce are carbohydrates, which support marine ecosystems and areused in biorefineries. In this work, we quantified the monosaccharide content and diversity of macroalgal speciescommon to the Eastern Mediterranean shores representing the three major seaweed divisions, namely,Chlorophyta (Ulva sp. and Cladophora pellucida), Rhodophyta (Nemalion helminthoides, Galaxaura rugosa andGracilaria sp.) and Ochrophyta (Padina pavonica and Sargassum vulgare). We found that the most abundantmonosaccharide was different in 5 out of the 7 investigated species. The monosaccharide diversity profile wasspecific to each taxonomic group, especially in the first two orders of diversity, which correspond to Shannonentropy and Simpson concentration. The content of monosaccharides released by acid hydrolysis varied by 153%between Ulva sp., C. pellucida, G. rugosa, N. helminthoides, Gracilaria sp., P. pavonica, and S. vulgare collected fromthe same site. Ulva sp. collected at different sites at different months showed up to 79% variance in the totalreleased monosaccharides, with up to 270% variance in the content of individual monosaccharides. The culti-vation of Ulva sp. in a photobioreactor under more stable conditions reduced the diversity and the variability ofthe total carbohydrates to only 2%. By comparing amounts and types of monosaccharides derived from mac-roalgae, microalgae and terrestrial plants, it appears that Ulva sp. has the highest economic potential of allphotosynthetic organisms, between $1733 kg−1 and $3140 kg−1 of Ulva biomass.

1. Introduction

Marine macroalgae (seaweeds) are primary producers and along thephotic zone support life and diversity of numerous marine organismssuch as protista, bacteria [1–3], and grazers [4]. In addition, large-sizedseaweeds provide habitat and protection against environmental stres-sors and predators for seaweed-dependent multicellular heterotrophicorganisms [5]. Besides their ecological role in the marine environment,macroalgae provide ecosystem services to numerous coastal commu-nities. Indeed, the demand for seaweeds and seaweed-derived productsdoubled in the last decade and reached approximately 30 million tonsin 2016 [6]. Global seaweed aquaculture accounts for approximately20% of the total world marine aquaculture production by weight, withan annual value of about US $7 billion in 2013 with more than 80%produced in Asia [7]. Wild harvests only account for about 5% of thetotal seaweed production, while cultivated seaweed production hasgrown by about 50% in 10 years [8].

Moreover, macroalgae high biomass productivity [9–11] of poly-saccharides and proteins [12] makes them an exciting feedstock for

emerging biorefineries [13,14]. There is a large and diverse array ofapplications and uses of macroalgae products. Naturally harvested andcultivated macroalgae have many applications, such as in pharmaceu-tical, cosmetic, fertilizers, feed and food processing industries[13,15–17]. Besides the existing products and applications, macroalgaeplay a significant potential role in the emerging low carbon economy byproviding food and biofuels [13,18,19].

Additional ecosystem services from macroalgae include coastalprotection against erosion, carbon sequestration, nursery for fishes,feeding and breeding ground, nutrients cycling, and socio-economicvalues [20]. Furthermore, some species of seaweeds (kelps, fucoids,encrusting corallines, rhodoliths) act as ecosystem engineers by mod-ifying the spatial structure of the environment in which they live andinfluencing associated organisms [21,22]. Moreover, kelp forests andseaweed beds play a significant role in climate change mitigation byproviding CO2 sinks [20].

An important parameter to determine and quantify ecosystem ser-vices is diversity [23–26]. Diversity describes the different states that thesystem under examination takes. In life sciences, diversity describes an

http://dx.doi.org/10.1016/j.algal.2017.10.005Received 10 June 2017; Received in revised form 9 October 2017; Accepted 12 October 2017

⁎ Corresponding author.E-mail address: agolberg@tauex.tau.ac.il (A. Golberg).

Algal Research 28 (2017) 118–127

Available online 06 November 20172211-9264/ © 2017 Elsevier B.V. All rights reserved.

MARK

ecosystem in terms of number and abundance of living species, genes orbiochemicals [27]. Most recently, the true diversity was described as thenumber of equally-common species [27]. In this approach, the diversitycan be described in terms of an equivalent system — one that has thesame value of the diversity index as the system in question, which iscomposed of equally-common system states [27]. Importantly, differ-ently from other diversity indices, useful for system composition com-plexity measurements, diversity is always measured in units of numberof species.

Biodiversity, as the diversity of life at all levels, is scientificallydefined as “the variety of life in a particular habitat or ecosystem, andrelates to genetic and biochemical diversity” [28–31]; referring directly toecosystem services [23,32–34]As different species provide differentservices that affect ecosystems processes [35] impacting the overallsystem function [35]. Specifically in the marine ecosystems, speciesrichness and abundance increases ecosystem function and services [24].Many recent studies show that marine biodiversity improves the ocean'scapacity to provide food, maintain water quality, and recover fromperturbations [36]. In addition, biomass feedstock and the diversity ofpotentially derived products are promising for feedstock availability,accessibility, affordability and economic viability [37,38]. Chemicaldiversity is known to drive ecosystem processes, especially in complexsystem such as forest ponds [39] and coral reefs [40]. Besides complexecosystems, chemical diversity shows special intraspecific variations[30].

Monosaccharides are known to play important metabolic roles suchas energy storage, molecule restructuration and energy transfer fromthe phototrophic to the heterotrophic worlds. Although used for speciescharacterization [41], the diversity of monosaccharides for plants andalgae, defined in terms of number of equally-common species [27], hasnot been determined yet. The question of how monosaccharide di-versity affects functionalities from the organism level to the communityis largely unknown.

We aim to understand the links between biochemical diversity andenergy flows in marine environments and their ecosystem servicesoutputs. In this study, we aimed at determining the diversity ofmonosaccharides in selected macroalgae species collected in the

Eastern Mediterranean Sea, along Israeli shores. Therefore, we devel-oped a methodology for rapid monosaccharide profile determinationwith high pressure ion chromatography (HPIC) and, thereafter, we es-tablished the major monosaccharide diversity profile in the three majorseaweed divisions (Chlorophyta, Rhodophyta and Ochrophyta), in-cluding comparisons of intra-species chemical diversity spatially andseasonally in the green alga Ulva.

We suggest that the chemical diversity profiling of macroalgaespecies based on monosaccharides would provide new insights to themacroalgae ecosystems services and feedstock potential for bior-efineries, altogether contributing to biodiversity conservation, sustain-able development and climate change mitigation. Moreover, we believethat this approach would provide insights into diversity changes,especially community interaction modeling, improving our knowledgeon primary producer diversity, emphasizing the reliance on macroalgaeas primary chemical producers.

2. Materials and methods

2.1. Algal collections and their taxonomic identification

Fresh macroalgal specimens were collected during the Spring timeof 2016, from the tidal zone at four sites in the Eastern MediterraneanSea: Rosh-Hanikra (33°02′00″ N, 35°06′00″ E), Haifa (32.8355° N,34.9825° E), Mikhmoret, three sites [1–3], (32.4065° N, 34.8716° E),and Tel Aviv (32°07′00″ N 34°49′00″ E). The algal material wastransported as quickly as possible to the lab. The species were identifiedusing morphologically features as verified in Algae Base (http://www.algaebase.org) and published literature for the local marine flora[42–45], as follows (Fig. 1a): two distinct (leaf-shaped and wide fila-ments) morphotypes [46], collectively defined as Ulva sp. (as Ulvaspecies also change their morphology as a function of environment[46], we decided to report the results on the genus level), and Clado-phora pellucida from the division Chlorophyta (green seaweeds), Ga-laxaura rugosa, Nemalion helminthoides and Gracilaria sp. from the di-vision Rhodophyta (red seaweeds) and Padina pavonia and Sargassumvulgare from the division Ochrophyta (brown seaweeds).

Fig. 1. a. Species identified in this study. b–c. Sorting of species with hieratical clustering algorithm. Sorted by b. monosaccharide content and c. diversities profile of monosaccharides.

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2.2. Indoor cultivation of Ulva sp.

Thalli of leaf-shaped Ulva sp. collected from Haifa were cultivatedfor up to 4 months (March–June 2016) in 40 L, 200 μm thick poly-ethylene sleeves (Polytiv, Israel) embedded with anti-UV protection asdescribed in reference [47]. The cultivation was done in nutrient-en-riched seawater under natural illumination. Nutrients were added asammonium nitrate (NH4NO3, Haifa Chemicals Ltd., Israel) and phos-phoric acid (H3PO4, Haifa Chemicals Ltd., IS) to maintain 6.4 g m−3 ofnitrogen and 0.97 g m−3 of phosphorus in the cultivation media. De-pending on specific sleeve location, illumination varied between re-actors in the range of 238–348 μmol photons m−2 s−1. Seawater cir-culated continuously with an exchange rate of 40–80 L h−1 (all waterwas exchanged 1–2 times per hour). Mixing was done using an aircolumn inserted in the sleeves at 2–4 L min−1 air flow rates. Sleeveswere manually cleaned with soap and bleached to remove the con-taminating epiphytes prior to cultivation.

2.3. Acid hydrolysis of algae tissues

The collected biomass was dried at 40 °C until constant weight andcrushed manually to powder in liquid nitrogen using a mortar & pestle.Most chemicals and standards were purchased from Sigma-Aldrich(Israel). Sulfuric acid (2 mL) was added into the tubes and the mix wasvortexed to make the powder evenly distributed in acid.Thermochemical deconstruction [48] (2% sulfuric acid, 1:20 solid tosolvent ratio, 30 min, 121 °C) was conducted in 10 mL centrifuge tubes(Nalgene™ Oak Ridge High-Speed PPCO Centrifuge Tubes (Thermo-Fisher Scientific, CA)) in autoclave (Tuttnauer 2540MLV, Netherlands).Dried samples of biomass (50 mg) were weighed on an analytical bal-ance (Mettler Toledo, Switzerland). Hydrolysates were stored at−20 °C after centrifugation (5 min, 12,000 rpm, using a benchtopcentrifuge (Eppendorf, Germany).

2.4. Determination of monosaccharides in acid hydrolysis by high pressureion chromatography (HPIC)

For monosaccharide analysis, hydrolysates were thawed and analiquot was diluted 50 times in ultrapure water before being filteredthrough a 0.22 μm syringe-filter (Millipore, USA) in HPIC vials (ThermoFischer Scientific, MA, USA). Monosaccharide contents in the hydro-lysates were monitored by HPAEC-PAD (High Pressure Anion-ExchangeChromatography coupled with Pulsed Amperometric Detection) using aDionex ICS-5000 platform (Dionex, Thermo Fischer Scientific, MA,USA) with an analytical column (Aminopack 10) and its correspondingguard column. An electrochemical detector with a AgCl referenceelectrode was used for detection. The analysis was performed using anisocratic flow of 4.8 mM KOH generated by the Eluent Generatortechnology (Dionex, Thermo Fischer Scientific, MA, USA) for 20 min.Then the column was washed with 100 mM KOH between each run andre-equilibrated with 4.8 mM KOH prior to injection. The column tem-perature was kept at 30 °C, and the flow rate was set to 0.25 mL min−1.Calibration curves were produced for each sugar with internal stan-dards. In this work we quantified rhamnose, arabinose, galactose, glu-cose, xylose, glucuronic acid, mannitol, fucose, and mannose.

Glucuronic acid content was monitored by using a program thatinvolved three eluents (NaOH, ultrapure water and sodium acetate) —see Supplementary information Table S3. Two additional small peakswere observed but not analyzed in the area of glucuronic acid peak inall samples that were sensed as aldobiouronic acid and iduronic acid asstated in [49]. Each algal sample was hydrolyzed in duplicate beforeanalysis. All samples were analyzed in duplicate. All data were reportedas weight fraction of the specific monosaccharide biomass (μg ofmonosaccharide mg−1 DW (dry weight) biomass).

2.5. Carbohydrate diversity determination

In this work we denote types as chemicals, monosaccharide, anddataset for the individual macroalgae specimens. Diversity is a quan-titative measure that reflects how many different types (of mono-saccharides, in our case) are in a dataset, taking into account how basicentities are distributed among those types [27]. In recent work [27], afamily function describing the diversity of the biological system wasdescribed, Eq. (1):

∑≡ ⎛

⎝⎜

⎞

⎠⎟

=

−

D p p p p( , , . .)q

i

N

iq

1 2 31

q1

1

(1)

where D is the true system diversity, p is the system state (mono-saccharide fraction from total monosaccharide content in the biomass),N is the number of states in the system (number of chemical species, inthis work limited to the number of different monosaccharides, as thecounter integer, and q is the diversity order [50]. Dq functions, alsocalled “Hill numbers”, possess the doubling properties, expected forbiological systems, and are equal unity when there is only one possiblestate of a system. Interestingly, the definition of true diversity as givenin Eq. (1) combines the widely used diversity indices as richness, D0

(q= 0) Eq. (2); the exponential of Shannon entropy D1 (limit at q= 1),Eq. (3), and inverse Simpson concentration D2 (q= 2) Eq. (4).

∑… ==

D p p p p( , , )i

N

i0

1 2 31

0

(2)

∑… = ⎛

⎝⎜ − ⎞

⎠⎟

=

D p p p p p( , , ) exp lni

N

i i1

1 2 31 (3)

∑… ==

D p p p p( , , ) 1/i

N

i2

1 2 31

2

(4)

In this study we calculated diversities up to q = 7, as after this thechanges between the consequent diversity levels are very small [27].Examples of full calculations of diversities appear in the SupplementaryInformation.

2.6. Analysis of macroalgae market value based on the monosaccharidesprices

We denote the market price for the monosaccharide i as ci ($ kg−1).Then the total price (TPb, $ kg−1) for monosaccharides extracted froma specific biomass would be

∑==

c pTPi

N

i ib1 (5)

The market prices for individual monosaccharides vary according topurity, quantity and manufacturer. For this study, we used the pricecatalog from Sigma Aldrich (http://www.sigmaaldrich.com, 2017 pricelist) with lowest prices per gram of material (Table S4). We made theassumption that monosaccharides released during hydrolysis can beseparated and purified to the level corresponding to the selectedavailable product on Sigma Aldrich catalog (Table S4).

2.7. Statistical analysis

All samples were analyzed with 2 biological replicates and 2 tech-nical repetitions at least. Results were reported as average ± SD.Clustering was operated with hierarchical clustering algorithm, Wardmethod (compact spherical clusters, minimizing variance) implementedin reference [51].

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3. Results and discussion

3.1. Diversity of monosaccharides in species collected at the Rosh-HaNikrareef

To study interspecific differences, we quantified content and di-versity of monosaccharides from macroalgae collected from the samelocation at Rosh-HaNikra reef. The quantification of 9 monosaccharidesderived from the macroalgal biomass by acid hydrolysis is reported inFig.2a and Table 1. Interestingly, the monosaccharide with the highestabundance was different in 5 out of the 8 species collected from thissite.

Ulva sp. and C. pellucida had the highest content of glucose(49.18 ± 1.37 and 34.90 ± 2.38 μg mg−1 respectively). However, inthe red algae, the most abundant monosaccharide in G. rugosa wasxylose (103.33 ± 0.01 μg mg−1), in N. helminthoides it was mannose(88.94 ± 9.36 μg mg−1) and in Gracilaria sp. it was galactose(55.49 ± 0.41 μg mg−1). In the brown algae, fucose was observed asmost abundant monosaccharide in P. pavonia(31.30 ± 7.00 μg mg−1), and mannitol in S. vulgare(49.2 ± 6.10 μg mg−1). Even though glucose was the most abundantmonosaccharide in Ulva sp. and C. pellucida, the content of othermonosaccharides differed significantly between the two green algae asrhamnose was noted as the second most abundant monosaccharide inUlva (39.69 ± 1.32 μg mg−1), and observed in much lower con-centration in C. pellucida (4.97 ± 0.60 μg mg−1). Arabinose was thesecond most abundant monosaccharide in C. pellucida(20.95 ± 0.40 μg mg−1), but was observed in very low concentrationin Ulva sp. (1.02 ± 0.04 μg mg−1). In addition, compared to Ulva, C.pellucida showed higher content of galactose (20.41 ± 0.67 μg mg−1

vs 7.74 ± 0.34 μg mg−1); but lower levels of xylose(10.94 ± 0.64 μg mg−1 vs 18.02 ± 0.72 μg mg−1) and glucuronicacid (3.00 ± 0.33 μg mg−1 vs 9.64 ± 1.71 μg mg−1). Mannitol, fu-cose and mannose were completely absent in both Ulva sp. and C. pel-lucida.

The red algae species showed the largest variation in mono-saccharide diversity (Figs. 1b, 2a) and in the total released mono-saccharides content (161.91 ± 9.40 μg mg−1 for N. helminthoides and64.01 ± 0.41 μg mg−1 for Gracilaria sp.). Interestingly, in G. rugosathe most abundant monosaccharide was xylose(103.33 ± 0.01 μg mg−1); while in other tested species (includingChlorophyta and Ochrophyta) hexoses were found as the most abun-dant. In all other tested species, the major released monosaccharideswere hexoses. Xylose content in N. helminthoides was32.43 ± 0.01 μg mg−1, but only 3.66 ± 0.03 μg mg−1 of thismonosaccharide was found in Gracilaria sp. The most abundant

monosaccharide in N. helminthoides was mannose(88.94 ± 9.36 μg mg−1), which showed only 7.83 ± 3.00 μg mg−1

in G. rugosa, and 0.74 ± 0.05 μg mg−1 in Gracilaria sp. In addition,less abundant monosaccharides, but still released by acid hydrolysis inconsiderable amounts, were: galactose for G. rugosa(14.36 ± 2.09 μg mg−1); glucose (20.02 ± 0.01 μg mg−1), and ga-lactose (16.43 ± 0.94 μg mg−1) for N. helminthoides, and finally glu-cose (3.16 ± 0.05 μg mg−1) for Gracilaria sp. Other monosaccharidesoccurred in lower quantities (Fig. 2a, Table 1).

The two species of Ochrophyta showed high diversities (Fig. 2b)with fucose (31.30 ± 7.00 μg mg−1) as the most dominant mono-saccharides in P. pavonia, and mannitol (49.20 ± 6.10 μg mg−1) for S.vulgare. Fucose was the second most abundant monosaccharide for S.vulgare (34.30 ± 3.67 μg mg−1), which was the highest content of thissugar in all tested species. Less abundant, but still released in con-siderable amounts by acid hydrolysis in P. pavonia and S. vulgare, werethe monosaccharides glucose (14.11 ± 0.56 μg mg−1 and13.37 ± 0.55 μg mg−1), and xylose (13.37 ± 0.55 μg mg−1 and8.49 ± 0.94 μg mg−1). Other monosaccharides occurred with lowercontents (Fig. 2a, Table 1).

Interestingly, the analyzed species showed a specific class of di-versity patterns (Fig. 1c), especially at D1 and D2 (corresponding toShannon entropy and Simpson concentration, which are the most in-formative levels of diversity [27]) (Fig. 2b). D0 (number of types ofmonosaccharides) depends on the detection level of the device.Ochrophyta showed the highest first (D1) and second (D2) order di-versities, followed by Chlorophyta and then by Rhodophyta. S. vulgareshowed the highest D1 (5.51), followed by P. pavonia (5.45), C. pellucida(4.67), Ulva sp. (4.01), N. helminthoides (3.55), G. rugosa (2.23) andGracilaria sp. (1.38), (Fig. 2b). P. pavonia showed the highest D2 (4.34),followed by S. vulgare (4.20), C. pellucida (4.06), Ulva sp. (3.33), N.helminthoides (2.72), G. rugosa (1.61) and Gracilaria sp. (1.31) (Fig. 2b).

The monosaccharide diversity plot and its hierarchical clusteringanalysis (Figs. 1b and 2b) showed that C. pellucida and Ulva sp. havesimilar diversity trends, but different from Rhodophyta and Ochro-phyta. Further analysis suggests that although both C. pellucida andUlva sp. shared common taxonomic status (both being within the classUlvophyceae), their structural carbohydrates, cladophoran [52,53] andulvan [54–56] fibers, which include arabinose (cladophoran) andrhamnose/glucuronic acid (ulvan) evolved separately. This suggestionis supported by placement of C. pellucida in the order Cladophorales andUlva to the order Ulvales, a separation that is well established based onmorphology and molecular phylogenetic data [57].

This is also supported by hierarchical clustering analysis of mono-saccharides of all tested algae (Fig. 1b), which showed that C. pellucidais different from Ulva sp. Future evolutionary genetic studies are needed

Fig. 2. Monosaccharide diversity of macroalgae collected from Rosh-HaNikra reef. a. Monosaccharide content released by acid hydrolysis b. Diversity profile of monosaccharides.

A. Robin et al. Algal Research 28 (2017) 118–127

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to further test the hypothesis that genes responsible for carbohydratesbiosynthesis during photosynthesis evolved separately in these algae.Unfortunately, these studies at present are technically not possible dueto the lack of genomes for multicellular C. pellucida.

Despite the variation of the dominant monosaccharides in theanalyzed species, all red macroalgae showed similar diversity ofmonosaccharides, as classified with hierarchical clustering analysis(Figs. 1c and 2b). The results showed that the three species are moresimilar to each other than to Chlorophyta and Phaeophyceae in terms ofdiversity. This finding could be potentially explained by the commonevolution of the Rhodophyta and their divergence from brown andgreen algae. However, comparisons of carbohydrate biosynthesispathways will be required to completely support this explanation.Hierarchical clustering analysis (Fig. 1c) showed that N. helminthoidesand G. rugosa are more closely related to each other than to Gracilariasp. Both N. helminthoides and G. rugosa belongs to the Nemaliales;whereas Gracilaria sp. belongs to the Gracilariales; these two ordersbelong to the Florideophyceae, the largest class of red algae.

Recent work on the divergence time and evolution of theFlorideophyceae showed that the Nemaliophycidae (the subclass of theorder Nemaliales) emerged as a separate lineage 597–736 million yearsago [58]. The Gracilariales belong to a different subclass, the Rhody-meniophycidae, which separated 359–477 million year ago [58]. Thus,the difference in monosaccharide diversity profile appears to reflect theevolutionary distance between these taxa. Even in this case, genomicstudies focusing on the genes that control the biosynthesis pathways inthese orders are needed for further investigations.

P. pavonia and S. vulgare showed remarkable similarity in diversityin all tested orders (Fig. 2b): D0 8 and 9; D1 5.45 and 5.51; D2 4.34 and4.20; D3 3.75 and 3.67; D4, 3.41 and 3.40; D5 3.21 and 3.25; and D6

3.08 and 3.14. Both species are from the Ochrophyta division, classPhaeophyceae, with P. pavonia belonging to the order Dictyotales andSargassum sp. to the order Fucales. These species showed high similaritywith the monosaccharide content (Fig. 1b) suggesting that the structureof the monosaccharides is highly conserved in Ochrophyta, as Dictyo-tales and Fucales represent widely separated lineages in the classOchrophyta [59]. Evolutionary genomic comparison between these twospecies will be required to test this suggestion. Based on the compara-tive analysis above, our data suggest that monosaccharide diversityprofile could be a characteristic that is class specific evolving withspecies lineages. This suggestion, however, needs validation withmultiple additional species.

3.2. Monosaccharide content and diversity profile of Ulva sp. in variousgeographic locations

To test the space related changes in monosaccharide content, wesampled Ulva sp. in spring 2016 in 4 different locations spread over a130 km distance. Ulva sp. was chosen because it is probably the mostabundant macroalgae along the Israeli Mediterranean coast. Ulva sp.monosaccharides content released by acid hydrolysis varied by 68%(134.23 ± 3.72 μg mg−1 for algae collected in Mikhmoret and68.10 ± 1.40 μg mg−1 for the specimen collected in Haifa) (Fig. 3aand Table 2). This is a considerable variation for a species that isconsidered an eligible feedstock for biorefineries, especially for fer-mentation [60,61] where the final output depends on the total sugarcontent [62].

The content of individual monosaccharides showed higher variationbetween specimens: 132% for rhamnose (24.30 ± 0.43 μg mg−1 forthe algae collected in Mikhmoret vs 68.10 ± 1.40 μg mg−1 for thespecimen collected in Haifa), 318% for galactose(7.91 ± 0.42 μg mg−1 for the algae collected in Mikhmoret_1 vs1.89 ± 0.03 μg mg−1 for the algae collected in Haifa); 242% for glu-cose (55.47 ± 2.27 μg mg−1 for the algae collected in Mikhmoret_1 vs24.50 ± 0.22 μg mg−1 for the algae collected in Haifa), 219% forxylose (18.02 ± 0.72 μg mg−1 for the algae collected in Rosh-HaNikraTa

ble1

Mon

osacch

arideco

nten

t(based

onbiom

assmeasuredafterdrying

at40

°C)of

macroalga

eco

llected

atRoshHan

ikra

rockyreef.A

verage

conten

tof

rham

nose

(Rha

),arab

inose(A

rb),ga

lactose(G

lc),gluc

ose(G

lu),xy

lose

(Xyl),gluc

uron

icacid

(GluA),man

nitol(M

tol),fuc

ose(Fuc

),man

nose

(Man

),an

dtotal(Tot)show

n±

SD.*

=da

teof

colle

ction.

Species

*Algae

type

Rha

μgmg−

1Arb

μgmg−

1Glc

μgmg−

1Glu

μgmg−

1Xyl

μgmg−

1GluA

μgmg−

1Mtolμg

mg−

1Fu

cμg

mg−

1Man

μgmg−

1To

tμg

mg−

1

Galax

aura

rugosa

1/3

Rho

doph

yta

0.36

±0.08

0.20

±0.03

14.36

±2.09

6.04

±1.18

103.33

±0.01

0.98

±0.41

0.00

0.00

7.83

±3.00

133.12

±3.86

Nem

alionhelm

inthoides

16/5

Rho

doph

yta

1.00

±0.02

0.94

±0.04

16.43

±0.94

20.02

±0.01

32.43

±0.01

0.00

1.08

±0.16

1.06

±0.02

88.94

±9.36

161.91

±9.40

Gracilariasp.

16/5

Rho

doph

yta

0.00

0.00

55.49

±0.41

3.16

±0.05

3.66

±0.03

0.95

±0.01

0.00

0.00

0.74

±0.05

64.01

±0.41

Clado

phorapellu

cida

1/3

Chlorop

hyta

4.97

±0.60

20.95

±0.40

20.41

±0.67

34.90

±2.38

10.94

±0.64

3.00

±0.33

0.00

0.00

0.00

95.17

±2.67

Ulvasp.

1/3

Chlorop

hyta

39.69

±1.32

1.02

±0.04

7.74

±0.34

49.18

±1.37

18.02

±0.72

9.64

±1.71

0.00

0.00

0.00

125.29

±2.68

Padina

pavonia

1/3

Och

roph

yta

2.73

±0.05

0.41

±0.01

7.55

±0.08

14.11

±0.56

13.37

±0.55

4.73

±0.01

5.98

±1.63

31.30

±7.00

0.00

80.18

±7.22

Sargassum

vulgare

1/3

Och

roph

yta

2.78

±0.26

1.73

±0.20

9.92

±0.73

8.78

±0.65

8.49

±0.94

13.22

±3.02

49.2

±6.10

34.30

±3.67

1.89

±0.20

130.33

±7.85

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vs 5.64 ± 0.15 μg mg−1 for the algae collected in Haifa) and 155% forglucuronic acid (24.59 ± 0.16 μg mg−1 for the algae collected in TelBaruh vs 9.64 ± 1.71 μg mg−1 for the algae collected in Rosh-HaNikra). Such variations between macroalgae individual mono-saccharides amounts are considerable, when specific organisms areneeded to convert the numerous non-glucose monosaccharides to fer-mentation products [62]. Each batch of algae requires specific devel-opment adjusting its chemical composition. However, hierarchicalclustering analysis showed that all of the Ulva species collected havesimilar carbohydrate content, unlike with the other species (Fig. 1b).Indeed, diversity profile analysis showed a tiny difference (up to 18%)in D1 between the tested specimens; yet, higher levels of diversity in-creased the difference up to 48% (D6) (Fig. 3b). Hierarchical clusteringanalysis found all tested samples closer to each other than Rhodophytaand Phaeophyceae sub-groups (Fig. 1c).

3.3. Diversity of monosaccharides in Ulva sp. collected at Mikhmoretsampling site

We noticed that monosaccharides content and diversity profile ofUlva sp. changed with time at Mikhmoret sampling site (Fig. 3c, d,

Table 3). We sampled at 3 different sites of Mikhmoret (1 March2016).Total monosaccharide content released with acid hydrolysisvaried by up to 79%, with the highest yields of159.29 ± 8.22 μg mg−1 observed on 15 May 2016, and lowest yield of88.98 ± 1.33 μg mg−1 observed on 5 May 2016. The content of in-dividual monosaccharides varied from 63% for glucose(58.97 ± 5.56 μg mg−1 observed on 15 May 2016 to36.21 ± 0.18 μg mg−1 observed on 5 May 2016) to 270% variationobserved for xylose (21.14 ± 1.60 μg mg−1 observed on 14 April2016 to 5.70 ± 0.18 μg mg−1 observed on 1 March 2016 on site 2).The content of arabinose measured was negligible.

Results showed 32% variation in the total monosaccharide content(100.88 ± 1.30 μg mg−1 at site 2 to 134.23 ± 3.72 μg mg−1 at site1). The rhamnose content varied by 51%, galactose by 14%, xylose by20% and glucuronic acid by 16% (Fig. 3c, Table 3). These results areimportant for the potential use of Ulva sp. as biorefinery feedstock forsugar production and fermentation substrate, as it shows large varia-tions of critical carbohydrates that affect the final product content[13,63,64].

Similar to the geographic location study, diversity profile analysisshowed a slight difference (up to 18%) in D1, of the tested specimens;

Fig. 3. Spatial and seasonal changes in monosaccharide diversity of Ulva sp. a. Content of monosaccharides in species sampled at 4 different sites about 130 km apart on the EasternMediterranean shores of Israel. Three sites were samples at Mikhmoret. b. Diversity profile of monosaccharides in species sampled at 4 different sites about 130 km apart on the EasternMediterranean shores of Israel. Three sites were samples at Mikhmoret c. Content of monosaccharides in algae sampled at different months at Mikhmoret site. d. Diversity profile ofmonosaccharides of species sampled at different months at Mikhmoret site. Error bars show± standard deviation.

Table 2Monosaccharide content of Ulva sp. collected from various locations along the Israeli Mediterranean cost (spring 2016). Average content of rhamnose (Rha), arabinose (Arb), galactose(Glc), glucose (Glu), xylose (Xyl), glucuronic acid (GluA), mannitol, fucose (Fuc), and mannose (Man), total (Tot) are shown± SD. (Measures are based on biomass dry weight measuredafter drying at 40 °C).

Date of collection 2016 Location Rha μg mg−1 Arb μg mg−1 Glc μg mg−1 Glu μg mg−1 Xyl μg mg−1 GluA μg mg−1 Tot μg mg−1

1/3 Mikhmoret_1 41.58 ± 2.69 0.11 ± 0.10 7.91 ± 0.42 55.47 ± 2.27 17.14 ± 0.91 12.01 ± 0.65 134.23 ± 3.7216/5 Mikhmoret_2 27.53 ± 0.11 0.00 3.34 ± 0.09 50.45 ± 1.28 5.70 ± 0.18 13.85 ± 0.16 100.88 ± 1.3016/5 Mikhmoret_3 31.10 ± 0.45 0.53 ± 0.53 7.19 ± 0.29 49.51 ± 1.93 11.44 ± 1.09 11.89 ± 0.49 111.66 ± 2.341/3 Rosh-HaNikra 39.69 ± 1.32 1.02 ± 0.23 7.74 ± 0.34 49.18 ± 1.37 18.02 ± 0.72 9.64 ± 1.71 125.29 ± 2.685/5 Tel Baruh 56.41 ± 1.26 0.36 ± 0.01 1.79 ± 0.29 16.18 ± 0.38 12.92 ± 0.60 24.59 ± 0.16 112.25 ± 1.4816/3 Haifa 24.30 ± 0.43 0.27 ± 0.01 1.89 ± 0.03 24.50 ± 0.22 5.64 ± 0.15 11.50 ± 1.31 68.10 ± 1.40

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yet, higher levels of diversity increased the variance up to 35% (D6)(Fig. 3d). Hierarchical clustering analysis of diversity profiles clustersall tested Ulva sp. samples closer to each other than to any of theRhodophyta and Phaeophyceae (Fig. 1c).

3.4. Ulva sp. monosaccharide content changes with time during cultivationin the photobioreactor

The algae collected in Haifa were cultivated for 4 months in aphotobioreactor [47] under natural illumination and natural sea waterfortified with nitrogen and phosphors. Total content of mono-saccharides released by acid hydrolysis increased in comparison to thebiomass collected in the field before cultivation in the photobioreactorby 49% (from 68.10 ± 1.40 μg mg−1 to 118.95 ± 7.52 μg mg−1,non-significant improvement (p-value = 0.063)) after 2 months ofcultivation and by 52% after 4 months of cultivation (from68.10 ± 1.40 μg mg−1 to 121.92 ± 5.21 μg mg−1, significant im-provement (p-value = 0.031)) (Fig. 4a). The growth of the mono-saccharides content after 4 months of cultivation showed an increase in

rhamnose (53% from 24.30 ± 0.43 μg mg−1 to37.29 ± 1.43 μg mg−1), glucose (123% from 24.50 ± 0.23 μg mg−1

to 54.84 ± 2.30 μg mg−1) and xylose (61% from5.64 ± 0.15 μg mg−1 to 9.11 ± 0.31 μg mg−1) contents (Fig. 4a).Moreover, the cultivation in the photobioreactor system reduced di-versities in D1 to D6 4 months after cultivation as follows: 5% for D1,10% for D2, 12% reduction for D3, 14% reduction for D4, 15% reductionfor D5 and 17% reduction for D6. We presume that the diversity re-duction indicates that the fixing of the expression levels of specificmonosaccharides is related to the changed environment. These results,added with the differences between seaweed and other plants (terres-trial, micro-algae — see following paragraphs) suggest that plant do-mestication and breeding could reduce chemical diversity; whetherbreeding reduces genetic diversity is still an open question [65–69].

3.5. Monosaccharide diversity profile comparison between macroalgae,microalgae and higher plants

We compared the diversity of the monosaccharides from the testedmacroalgae with the diversity of monosaccharides of some microalgaeand from cell walls of a model plant Arabidopsis thaliana [70] (Fig. 5).The comparison is based on data from the literature [41]. Besides thediatom Phaeodactylum tricornutum, all other tested microalgae speciesshowed lower diversity at all levels in comparison with the testedmacroalgae and Arabidopsis (Table 4). This observation suggests thatdiversity of monosaccharides could be related to the development ofextracellular matrix, as observed in macroalgae and high terrestrialplants.

We noticed that two commercially cultivated species, Dunaliellasalina (microalgae) and Gracilaria sp. (macroalgae), have the lowestdiversity at D1 in comparison with all other species (D1 1.09 and 1.38respectively). Indeed, D. salina showed the lowest monosaccharide di-versity at all ranks. Gracilaria sp. had the lowest diversity of mono-saccharides at all ranks among the analyzed species, with Scenedesmusovalternus and D. salina. These data suggest that our diversity profilemethodology could be used as relevant criteria for screening projects toidentify wild algae species fit for domestication. Nevertheless, we needfurther investigation based on a broader scope of knowledge and widerdatabase comparing larger groups of domesticated algae, grown atdifferent environmental conditions, to assert our suggestion.

Comparison with Arabidopsis carbohydrates cell wall showed a verysimilar diversity between Arabidopsis and Ulva sp. at all levels of di-versity besides D0 (D1 4.89 vs 4.13; D2 3.61 vs 3.5; D3 3.08 vs 3.22; D4

2.82 vs 3.07; D5 2.67 vs 2.98; D6 2.58 vs 2.92). This similarity betweenArabidopsis and C. pellucida at D1 (4.89 vs 4.67) was the largest amongall tested algae. These results could be expected as vascular plantsdescended from green algae that moved to live on land.

3.6. Monosaccharide diversity and economic value

Acid hydrolysis has already been proposed as a method for mono-saccharide production in biorefineries [71–74]. We established thepotential income of macroalgae monosaccharides released by acid hy-drolysis, compared to the potential income of monosaccharides from

Table 3Monosaccharide content (based on biomass dry weight measured after drying at 40 °C) of Ulva sp. collected at Mikhmoret site at various time points. Average content of rhamnose (Rha),arabinose (Arb), galactose (Glc), glucose (Glu), xylose (Xyl), glucuronic acid (GluA), mannitol, fucose (Fuc), and mannose (Man), total (Tot) are shown± SD.

Date of collection 2016 Rha μg mg−1 Arb μg mg−1 Glc μg mg−1 Glu μg mg−1 Xyl μg mg−1 GluA μg mg−1 Tot μg mg−1

1/3 41.58 ± 2.69 0.11 ± 0.10 7.91 ± 0.42 55.47 ± 2.27 17.14 ± 0.91 12.01 ± 0.65 134.23 ± 3.721/3 27.53 ± 0.11 0.00 3.34 ± 0.09 50.45 ± 1.28 5.70 ± 0.18 13.85 ± 0.16 100.88 ± 1.301/3 31.10 ± 0.45 0.53 ± 0.53 7.19 ± 0.29 49.51 ± 1.93 11.44 ± 1.09 11.89 ± 0.49 111.66 ± 2.3414/4 50.86 ± 0.77 0.40 ± 0.01 6.21 ± 0.27 54.09 ± 3.45 21.14 ± 1.60 20.26 ± 3.18 152.97 ± 5.025/5 29.41 ± 0.33 0.21 ± 0.04 4.57 ± 0.03 36.21 ± 0.18 6.64 ± 0.38 11.95 ± 1.22 88.98 ± 1.3315/5 64.74 ± 5.56 0.00 2.74 ± 0.09 58.97 ± 5.56 16.27 ± 1.67 16.57 ± 1.71 159.29 ± 8.22

Fig. 4. Monosaccharide diversity of Ulva sp. cultivated in the photobioreactor. a. Majormonosaccharide content. b. Diversity profile. Error bars show± standard deviation.

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microalgae and terrestrial plants used for biofuel production. Totalincome for each biomass has been calculated on the basis of purifiedmonosaccharide market price (all content, separated and recovered,appears in Fig. 6). Our preliminary model of monosaccharides pricing ismainly based on Sigma Aldrich supplier.

Our preliminary model shows the highest potential for Ulva sp.($1733 kg−1–$3140 kg−1), followed by N. helminthoides ($779 kg−1),C. pellucida ($721 kg−1), P. pavonia ($503 kg−1), Gracilaria sp.($355 kg−1) and G. rugosa ($223 kg−1) (Fig. 6a). In comparison, thehighest potential income from the monosaccharides recovered from themicroalgae biomass hydrolysis was for P. tricornutum ($1210 kg−1),followed by D. salina ($394 kg−1), C. vulgaris ($311 kg−1), P. pur-pureum ($163 kg−1), and S. ovalternus ($142 kg−1) (Fig. 6b). Forcomparison, we have to take into account that the analysis of the fourmore common sources of biomass for sugars and bioenergy productionwith the highest potential income from monosaccharides comes fromMonterey pine RM 8493 ($291 kg−1), followed by Wheat straw RM8494 ($187 kg−1), Eastern cottonwood RM 8492 ($171 kg−1) andSugarcane bagasse RM 8491 ($132 kg−1) (Fig. 6c).

These results suggest that marine macroalgae are a potential valu-able source of monosaccharides. The variation of potential income(Ulva sp.) depends highly on the biomass composition. Therefore, weassert that controlled cultivation could mitigate these fluctuations,suggesting that this method is likely preferable to in situ sampling,especially for downstream processing (Fig. 4).

4. Conclusions

In this work, we quantified the content and the diversity of sig-nificant monosaccharides released by acid hydrolysis from varioustypes of macroalgae collected along the Israeli Mediterranean Seashore. Five of the seven investigated macroalgae species showed dif-ferent monosaccharides with the highest comparable content. Theanalyzed species showed specific patterns of monosaccharide diversityprofile, especially at D1, which corresponds to Shannon entropy and D2,which corresponds to Simpson concentration. Ulva sp. showed up to 79%variance in the total monosaccharide content released by acid hydro-lysis, with up to 270% variance in the content of individual mono-saccharides. Ulva sp. cultivation in the photobioreactor took up to4 months, reducing the variance in the total carbohydrate content to2%, and the variance in the individual monosaccharide content to 51%,as well. In addition, cultivation in the photobioreactor reduced thediversities 4 months after cultivation by 5% for D1 to 17% reduction forD6. This significant reduction of diversity profile indicates the fixing ofspecific monosaccharide content. The economic potential of mono-saccharides, derived from tested macroalgae, microalgae and terrestrialplants species, are significant. Our work shows that Ulva sp. has thehighest economic potential from investigated species with potentialincome of $1733 kg−1–$3140 kg−1 based on extractable and purifiedmonosaccharides prices. However, new technologies are needed forfaster separation and purification of multiple monosaccharides at thesame time.

Author contributions

AR performed experiments, data analysis and drafted the manu-script, PC did ecosystem service and economic analysis and drafted themanuscript, AC collected and cultivated the algae, AI identified thespecies and edited the manuscript, and AG conceived the study, diddata analysis and wrote the manuscript.

Fig. 5. Monosaccharide diversity profiles comparisons between macroalgae, microalgae and model high plant Arabidopsis.

Table 4Monosaccharide diversity of macroalgae, microalgae and plant cell wall. Source of ori-ginal content of monosaccharides for microalgae [41] is based on plant cell wall [70].

D0 D1 D2 D3 D4 D5 D6

Phaeodactylum tricornutum [41] 8.00 5.59 4.32 3.75 3.46 3.29 3.17Pennisetum purpureum [41] 4.00 2.36 1.85 1.66 1.58 1.54 1.51Chlorella vulgaris [41] 8.00 2.50 1.66 1.49 1.43 1.40 1.38Dunaliella salina [41] 3.00 1.09 1.03 1.02 1.02 1.02 1.02Scenedesmus ovalternus [41] 5.00 1.55 1.22 1.17 1.15 1.14 1.13Padina pavonia Rosh-HaNikra

1.3.20168.00 5.46 4.34 3.75 3.42 3.21 3.08

Sargassum vulgare Rosh-HaNikra1.3.2016

9.00 5.52 4.21 3.67 3.41 3.25 3.15

Galaxaura rugosa Rosh-HaNikra1.3.2017

7.00 2.24 1.61 1.46 1.40 1.37 1.36

Nemalion helminthoides Rosh-HaNikra 1.3.2017

8.00 3.56 2.72 2.38 2.21 2.11 2.05

Gracilaria sp. Rosh-HaNikra16.5.2016

3.00 1.38 1.32 1.24 1.21 1.20 1.19

Cladophora pellucida Rosh-HaNikra1.3.2016

6.00 4.68 4.07 3.74 3.53 3.38 3.28

Ulva sp. Rosh-HaNikra 1.3.2016 6.00 4.13 3.51 3.23 3.08 2.99 2.92Arabidopsis cell wall extract[70] 9.00 4.90 3.61 3.08 2.82 2.67 2.58

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Conflict of interest

The authors declare no conflict of interest.

Acknowledgements

The authors thank Israel Ministry of Science and Technology (Grant# 3-13572) and Israel Ministry of Infrastructures, Energy and WaterResources (Grant # 215-11-051) and TAU Center for Innovation inTransportation for financial support of this work. The authors ac-knowledge anonymous Editor and Reviewer 1 who made a very sub-stantial contribution in shaping the manuscript.

Statement of informed consent, human/animal rights

No conflicts, informed consent, human or animal rights applicable.

Appendix A. Supplementary data

Supplementary data to this article can be found online at https://doi.org/10.1016/j.algal.2017.10.005.

References

[1] C.M.M. Gachon, T. Sime-Ngando, M. Strittmatter, A. Chambouvet, G.H. Kim, Algaldiseases: spotlight on a black box, Trends Plant Sci. 15 (2010) 633–640.

[2] F. Goecke, A. Labes, J. Wiese, J. Imhoff, Chemical interactions between marinemacroalgae and bacteria, Mar. Ecol. Prog. Ser. 409 (2010) 267–299.

[3] F. Goecke, V. Thiel, J. Wiese, A. Labes, J.F. Imhoff, Algae as an important en-vironment for bacteria-phylogenetic relationships among new bacterial speciesisolated from algae, Phycologia 52 (2013) 14–24.

[4] M. Wahl, Marine epibiosis. I. Fouling and antifouling: some basic aspects, Mar. Ecol.Prog. Ser. 58 (1989) 175–189.

[5] E. Cacabelos, C. Olabarria, M. Incera, J.S. Troncoso, Estuarine, coastal and shelfscience effects of habitat structure and tidal height on epifaunal assemblages as-sociated with macroalgae, Estuar. Coast. Shelf Sci. 89 (2010) 43–52.

[6] E.J. Cottier-Cook, et al., Safeguarding the Future of the Global SeaweedAquaculture Industry, 12 (2016) (ISBN 978-92-808-6080-1).

[7] J.K. Kim, C. Yarish, E.K. Hwang, M. Park, Y. Kim, Seaweed aquaculture: cultivationtechnologies, challenges and its ecosystem services, Algae 32 (2017) 1–13.

[8] FAO, The State of World Fisheries and Aquaculture, Available from: http://www.

fao.org/fishery/en, .[9] D.J.A. McHugh, Guide to the seaweed industry, FAO Fish. Tech. Pap. (2003).

[10] S. Kraan, Mass-cultivation of carbohydrate rich macroalgae, a possible solution forsustainable biofuel production, Mitig. Adapt. Strateg. Glob. Chang. 18 (2013)27–46.

[11] A. Chemodanov, et al., Net primary productivity, biofuel production and CO2

emissions reduction potential of Ulva sp. (Chlorophyta) biomass in a coastal area ofthe Eastern Mediterranean, Energy Convers. Manag. 148 (2017) 1497–1507.

[12] A.D. Hughes, M.S. Kelly, K.D. Black, M.S. Stanley, Biogas from macroalgae: is ittime to revisit the idea? Biotechnol. Biofuels 5 (2012) 86.

[13] Y. Lehahn, K.N. Ingle, A. Golberg, Global potential of offshore and shallow watersmacroalgal biorefineries to provide for food, chemicals and energy: feasibility andsustainability, Algal Res. 17 (2016) 150–160.

[14] M. Polikovsky, et al., Towards marine biorefineries: selective proteins extractionsfrom marine macroalgae Ulva with pulsed electric fields, Innovative Food Sci.Emerg. Technol. (2016), http://dx.doi.org/10.1016/j.ifset.2016.03.013.

[15] N. Wei, J. Quarterman, Y.-S. Jin, Marine macroalgae: an untapped resource forproducing fuels and chemicals, Trends Biotechnol. 31 (2013) 70–77.

[16] A.J. Smit, Medicinal and pharmaceutical uses of seaweed natural products: a re-view, J. Appl. Phycol. 16 (2004) 245–262.

[17] M.S. Kelly, S. Dworjanyn, The Potential for Marine Biomass for Anaerobic BiogasProduction, The Crown Estate, 2008.

[18] R. Jiang, K.N. Ingle, A. Golberg, Macroalgae (seaweed) for liquid transportationbiofuel production: what is next? Algal Res. 14 (2016) 48–57.

[19] A. Golberg, et al., Proposed design of distributed macroalgal biorefineries: ther-modynamics, bioconversion technology, and sustainability implications for devel-oping economies, Biofuels, Bioprod. Biorefin. 8 (2014) 67–82.

[20] I.K. Chung, et al., Installing kelp forests/seaweed beds for mitigation and adapta-tion against global warming: Korean project overview, ICES J. Mar. Sci. 70 (2013)1038–1044.

[21] C.A. Watt, R.A. Scrosati, Seaweeds as ecosystems engineers, Bull. Ecol. Soc. Am. 95(2014) 250–251.

[22] D. Basso, L. Babbini, S. Kaleb, V.A. Bracchi, A. Falace, Monitoring deepMediterranean rhodolith beds, Aquat. Conserv. Mar. Freshwat. Ecosyst. 26 (2016)549–561.

[23] F. Isbell, et al., High plant diversity is needed to maintain ecosystem services,Nature 477 (2011) 199–202.

[24] K.A. Engelhardt, M.E. Ritchie, Effects of macrophyte species richness on wetlandecosystem functioning and services, Nature 411 (2001) 687–689.

[25] D.U. Hooper, et al., Effects of biodiversity on ecosystem functioning: a consensus ofcurrent knowledge, Ecol. Monogr. 75 (2005) 3–35.

[26] G.W. Luck, G.C. Daily, P.R. Ehrlich, Population diversity and ecosystem services,Trends Ecol. Evol. 18 (2003) 331–336.

[27] L. Jost, Entropy and diversity, Oikos 113 (2006) 363–375.[28] D.R. Bellwood, T.P. Hughes, C. Folke, M. Nyström, Confronting the coral reef crisis,

Nature 429 (2004) 827–833.[29] C.L. Meier, W.D. Bowman, Links between plant litter chemistry, species diversity,

and below-ground ecosystem function, Proc. Natl. Acad. Sci. U. S. A. 105 (2008)19780–19785.

Fig. 6. Economic value assessment of monosaccharidebiorefinery from a. green, red and brown macroalgae; b.representative green, red and brown microalgae; c. re-presentative lignocellulose energy crops. The price catalogfrom Sigma Aldrich (http://www.sigmaaldrich.com, 2017price list) with lowest prices per g of material was used.(For interpretation of the references to colour in this figurelegend, the reader is referred to the web version of thisarticle.)

A. Robin et al. Algal Research 28 (2017) 118–127

126

[30] C. Noyer, O.P. Thomas, M.A. Becerro, Patterns of chemical diversity in theMediterranean sponge Spongia lamella, PLoS One 6 (2011) e20844.

[31] J.W. Fahey, A.T. Zalcmann, P. Talalay, The chemical diversity and distribution ofglucosinolates and isothiocyanates amoung plants, Phytochemistry 56 (2001) 5–51.

[32] F. Isbell, D. Tilman, S. Polasky, M. Loreau, The biodiversity-dependent ecosystemservice debt, Ecol. Lett. 18 (2015) 119–134.

[33] P. Balvanera, et al., Linking biodiversity and ecosystem services: current un-certainties and the necessary next steps, Bioscience 64 (2014) 49–57.

[34] G.M. Mace, K. Norris, A.H. Fitter, Biodiversity and ecosystem services: a multi-layered relationship, Trends Ecol. Evol. 27 (2012) 19–25.

[35] A. Hector, R. Bagchi, Biodiversity and ecosystem multifunctionality, Nature 448(2007) 188–190.

[36] B. Worm, et al., Impacts of biodiversity loss on ocean ecosystem services, Science314 (2006) 787–790.

[37] J. Yuan, X. Wang, C. Stewart, Biomass feedstock: diversity as a solution, Biofuels 2(2011) 491–493.

[38] P. Kumari, A.J. Bijo, V.A. Mantri, C.R.K. Reddy, B. Jha, Fatty acid profiling oftropical marine macroalgae: an analysis from chemotaxonomic and nutritionalperspectives, Phytochemistry 86 (2013) 44–56.

[39] A.B. Stoler, D.J. Burke, R.A. Relyea, Litter chemistry and chemical diversity driveecosystem processes in forest ponds, Ecology 97 (2016) 1783–1795.

[40] K. Sharp, et al., Phylogenetic and chemical diversity of three chemotypes of bloom-forming Lyngbya species (Cyanobacteria: Oscillatoriales) from reefs of southeasternFlorida, Appl. Environ. Microbiol. 75 (2009) 2879–2888.

[41] J.G. Ortiz-Tena, B. Rühmann, D. Schieder, V. Sieber, Revealing the diversity of algalmonosaccharides: fast carbohydrate fingerprinting of microalgae using crude bio-mass and showcasing sugar distribution in Chlorella vulgaris by biomass fractiona-tion, Algal Res. 17 (2016) 227–235.

[42] A. Israel, R. Einav, Alien seaweeds from the Levant basin (Eastern MediterraneanSea), with emphasis to the Israeli shores, Isr. J. Plant Sci. 9978 (2017) 1–12.

[43] R. Einav, A. Israel, Checklist of seaweeds from the Israeli Mediterranean: tax-onomical and ecological approaches, Isr. J. Plant Sci. 56 (2008) 127–191.

[44] R. Hoffman, A. Israel, Y. Lipkin, Z. Dubinsky, D. Iluz, First record of two seaweedsfrom the Israeli Mediterranean: Galaxaura rugosa (J. Ellis and Solander) J. V.Lamouroux (Rhodophyta) and Codium adhaerens C. Agardh (Chloropyta), Isr. J.Plant Sci. 56 (2008) 123–127.

[45] R. Einav, Seaweeds of Eastern Mediterranean Coast, A.R.G. Gantner Verlag K. G.Press, Dehradun, 2007.

[46] G. Gao, Z. Zhong, X. Zhou, J. Xu, Changes in morphological plasticity of Ulvaprolifera under different environmental conditions: a laboratory experiment,Harmful Algae 59 (2016) 51–58.

[47] A. Chemodanov, A. Robin, A. Golberg, Design of marine macroalgae photo-bioreactor integrated into building to support seagriculture for biorefinery andbioeconomy, Bioresour. Technol. 241 (2017) 1084–1093.

[48] R. Jiang, et al., Thermochemical hydrolysis of macroalgae Ulva for biorefinery:Taguchi robust design method, Sci Rep 6 (2016).

[49] B. Quemener, M. Lahaye, C. Bobin-Dubigeon, Sugar determination in ulvans by achemical-enzymatic method coupled to high performance anion exchange chro-matography, J. Appl. Phycol. 9 (1997) 179–188.

[50] M.O. Hill, Diversity and Evenness: A Unifying Notation and Its Consequences,Wiley, 2017 (on behalf of the Ecological Society of America Stable URL: http://www.jstor.org/stable/1934352 JSTOR is a not-for-profit service that helps. 54,427–432).

[51] P. Wessa, Hierarchical Clustering (v1.0.3) in Free Statistics Software (v1.1.23-r7),Office for Research Development and Education, 2012, http://www.wessa.net/rwasp_hierarchicalclustering.wasp/.

[52] E. Hirst, W. Mackie, E. Percival, The water-soluble polysaccharides of Cladophorarupestris and of Chaetomorpha spp. Part II. The site of ester sulphate groups and the

linkage between the galactose residues, J. Chem. Soc. 2958 (1965), http://dx.doi.org/10.1039/jr9650002958.

[53] E.J. Bourne, P.G. Johnson, E. Percival, The water-soluble polysaccharides ofCladophora rupestris. Part IV. Autohydrolysis, methylation of the partly desulphatedmaterial, and correlation with the results from smith degradation, J. Chem. Soc. C(1970) 1561–1569.

[54] P. Nyvall Collén, J.-F. Sassi, H. Rogniaux, H. Marfaing, W. Helbert, Ulvan lyasesisolated from the Flavobacteria persicivirga ulvanivorans are the first members of anew polysaccharide lyase family, J. Biol. Chem. 286 (2011) 42063–42071.

[55] G. Paradossi, F. Cavalieri, E. Chiessi, A conformational study on the algal poly-saccharide ulvan, Macromolecules 35 (2002) 6404–6411.

[56] M. Lahaye, A. Robic, Structure and function properties of Ulvan, a polysaccharidefrom green seaweeds, Biomacromolecules 8 (2007) 1765–1774.

[57] F. Leliaert, et al., Phylogeny and molecular evolution of the green algae, CRC Crit.Rev. Plant Sci. 31 (2012) 1–46.

[58] E.C. Yang, et al., Divergence time estimates and the evolution of major lineages inthe florideophyte red algae, Sci Rep 6 (2016) 21361.

[59] T. Silberfeld, et al., A multi-locus time-calibrated phylogeny of the brown algae(Heterokonta, Ochrophyta, Phaeophyceae): investigating the evolutionary nature ofthe ‘brown algal crown radiation, Mol. Phylogenet. Evol. 56 (2010) 659–674.

[60] N. Trivedi, C.R.K. Reddy, R. Radulovich, B. Jha, Solid state fermentation (SSF)-derived cellulase for saccharification of the green seaweed Ulva for bioethanolproduction, Algal Res. 9 (2015) 48–54.

[61] L. Korzen, et al., An economic analysis of bioethanol production from the marinemacroalga Ulva (Chlorophyta), Technology 3 (2015) 114–118.

[62] E. Vitkin, A. Golberg, Z. Yakhini, BioLEGO — a web-based application for bior-efinery design and evaluation of serial biomass fermentation, Technology (2015)1–10, http://dx.doi.org/10.1142/S2339547815400038.

[63] N. Trivedi, et al., An integrated process for the extraction of fuel and chemicals frommarine macroalgal biomass, Sci Rep 6 (2016) 30728.

[64] H. van der Wal, et al., Production of acetone, butanol, and ethanol from biomass ofthe green seaweed Ulva lactuca, Bioresour. Technol. 128 (2013) 431–437.

[65] Y. Jiao, et al., Genome-wide genetic changes during modern breeding of maize, Nat.Genet. 44 (2012) 812–815.

[66] Y.B. Fu, Understanding crop genetic diversity under modern plant breeding, Theor.Appl. Genet. 128 (2015) 2131–2142.

[67] D. Zamir, Improving plant breeding with exotic genetic libraries, Nat. Rev. Genet. 2(2001) 983–989.

[68] X.Q. Huang, et al., Did modern plant breeding lead to genetic erosion in Europeanwinter wheat varieties? Crop Sci. 47 (2007) 343–349.

[69] J.C. Glaszmann, B. Kilian, H.D. Upadhyaya, R.K. Varshney, Accessing genetic di-versity for crop improvement, Curr. Opin. Plant Biol. 13 (2010) 167–173.

[70] J. Fang, G. Qin, J. Ma, Y.-M. She, Quantification of plant cell wall monosaccharidesby reversed-phase liquid chromatography with 2-aminobenzamide pre-column de-rivatization and a non-toxic reducing reagent 2-picoline borane, J. Chromatogr. A1414 (2015) 122–128.

[71] C. Fehér, et al., Investigation of selective arabinose release from corn fibre by acidhydrolysis under mild conditions, J. Chem. Technol. Biotechnol. 90 (2015)896–906.

[72] P. Mäki-Arvela, T. Salmi, B. Holmbom, S. Willför, D.Y. Murzin, Synthesis of sugarsby hydrolysis of hemicelluloses—a review, Chem. Rev. 111 (2011) 5638–5666.

[73] B.P. Lavarack, G.J. Griffin, D. Rodman, The acid hydrolysis of sugarcane bagassehemicellulose to produce xylose, arabinose, glucose and other products, BiomassBioenergy 23 (2002) 367–380.

[74] T. Sainio, M. Kallioinen, O. Nakari, M. Mänttäri, Production and recovery ofmonosaccharides from lignocellulose hot water extracts in a pulp mill biorefinery,Bioresour. Technol. 135 (2013) 730–737.

A. Robin et al. Algal Research 28 (2017) 118–127

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