An artificial selection procedure enriches for known and suspected chitin degraders from the prokaryotic rare biosphere of multiple marine biotopes

An artificial selection procedure enriches for known and suspected chitin degraders from the prokaryotic rare biosphere of multiple marine biotopes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article An artificial selection procedure enriches for known and suspected chitin degraders from the prokaryotic rare biosphere of multiple marine biotopes Laurence Meunier, Tina Keller-Costa, David Cannella, Jorge Gonçalves, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3456333/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 25 Nov, 2025 Read the published version in BMC Microbiology → Version 1 posted 6 You are reading this latest preprint version Abstract Background Biological chitin degradation is a major process in the ocean, governed primarily by the action of microorganisms. It is now known that the structure and taxonomic profile of chitin-degrading microbial communities change across marine biotopes, but efforts to harness the chitin turnover potential within these communities in the laboratory have seldom been attempted. In this study, we characterized the prokaryotic communities associated with the marine sponge Sarcotragus spinosulus , the octocoral Eunicella labiata , and their surrounding sediment and seawater and applied an artificial selection procedure to enrich bacterial consortia capable of degrading chitin from the abovementioned biotopes. Throughout the procedure, chitin degradation was monitored, and the taxonomic composition of four successive enrichment cultures from each biotope were followed. Results The naturally occurring prokaryotic communities of the two host species were distinct from each other with specific taxa associated with each animal even though they were co-inhabiting the same geographic area. We found that members of the microbial rare biosphere were recruited in the enrichment cultures from all biotopes, while dominant bacterial symbionts likely to play a role in chitin degradation within marine sponges and octocorals remained “unculturable” under the conditions used in this study. Well-known chitin degraders such as Vibrio , Pseudoalteromonas and Aquimarina , as well as other taxa not known or yet poorly known for their role(s) in chitin degradation such as Aureivirga , Halodesulfovibrio , Motilimonas , Muricauda , Psychromonas , Poseidonibacter , Reichenbachiella , and Thalassotalea , among others, were enriched using our artificial selection approach. Distinct chitin-degrading consortia were enriched from each marine biotope, highlighting the feasibility of this approach in fostering the discovery of novel microorganisms and enzymes involved in chitin degradation pathways of relevance in applied biotechnology. Conclusion In this study, distinct bacterial consortia possessing moderate to high efficiencies at degrading chitin were unveiled. They were composed of a mix of known chitin degraders, known chitin utilizers and many taxa poorly or not yet known for their role(s) in chitin degradation such as Aureivirga , Psychromonas, Motilimonas, Reichenbachiella, or Halodesulfovibrio . The latter taxa are potential key players in marine chitin degradation whose study could lead to the discovery of novel enzyme variants able to degrade chitin and its derivatives. prokaryotic communities enrichment cultures chitinase marine sponge octocoral size exclusion chromatography Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1 Introduction Chitin is the most abundant biopolymer in the marine environment, and chitin degradation is a major process dictating the cycling of carbon and nitrogen in the ocean [ 1 ]. Importantly, chitin does not accumulate in the ocean [ 2 ] but undergoes a rapid turnover due to the activity of chitin-degrading microorganisms, leading to the production of small organic molecules such as N-acetylglucosamine (GlcNAc), glucosamine (GlcN), acetate, glucose (Glc) and deacetylated forms of chitin such as chitosan [ 3 , 4 ]. These chitin degradation products can be assimilated by bacteria for cell material synthesis or mineralized into CO 2 and NH 4 + [ 4 ]. Chitin-degrading marine microorganisms may live attached to chitinous exoskeletons or particulate detritus [ 5 ], or in symbiosis with macroeukaryotic hosts such as crustaceans [ 1 , 6 ], marine sponges [ 7 ] and octocorals [ 7 , 8 ]. Microorganisms that directly act on the chitin polymer through the action of endochitinases or deacetylases are usually referred to as “chitin degraders”, whereas microorganisms which consume chitin degradation products such as chitooligosaccharides and chitosan, through the action of exo-chitinases and chitosanases are referred to as “chitin utilizers” or “consumers” [ 4 ]. Endo- and exochitinases degrade chitin through a chitinolytic pathway, meaning that they hydrolyze the glycosidic bonds between the N-acetylglucosamine units of the chitin polymers (endochitinase) or the chitooligosaccharides (COSs) (exochitinases) [ 4 ]. Currently, molecular-based evidence suggests that distinct marine biotopes host taxonomically divergent chitin-degrading communities [ 7 , 9 , 10 ]. This indicates that a multitude of chitin degrading enzymes and accessory proteins (e.g., endochitinases, exochitinases, deacetylases, Lytic Polysaccharides MonoOxygenases (LPMOs), chitin-binding modules) with distinct substrate affinities and physical-chemical optima, produced by diverse chitin-degrading bacteria, remain unexplored and unknown. Current knowledge of the chitin degradation potential within symbiotic communities of sessile marine invertebrates is growing, as recent hypotheses have been raised on the roles of canonical symbionts of octocorals ( Endozoicomonadaceae ) [ 8 ] and marine sponges ( Rhodothermales ) [ 11 ] in the cycling of chitin in benthic ecosystems. However, despite the chitin catalytic potential existing within marine microbial communities, studies designed to harness the metabolism of diverse chitinolytic marine consortia in the laboratory have seldom been attempted [ 12 , 13 ]. Artificial selection (i.e., the making of enrichment cultures from environmental samples) is a powerful technique that allows to select communities efficient at degrading complex compounds such as pollutants or natural polymers like cellulose or chitin [ 13 – 16 ]. It consists of utilizing a natural prokaryotic community as inoculum in a specific medium (e.g., a medium with chitin as the sole source of carbon and nitrogen). Then, successive transfers to new culture media help to progressively select a microbial community specialized in a particular biochemical process or pathway (e.g., chitin degradation). We posit that artificial selection procedures may increase the discoverability of chitin-degrading enzymes and organisms, holding promise for diverse industrial sectors. Notably, chitin degradation products such as chitosan and chitooligosaccharides (COSs) exhibit potential applications in various fields such as agriculture, water treatment, medicine, textiles, and more [ 17 , 18 ]. For instance, chitinolytic enzymes can be used to create natural fungicides and insecticides by inhibiting fungal and harmful insects' growth, which can replace the chemical alternatives [ 17 – 19 ]. Furthermore, chitin-degrading enzymes can be used to generate COSs and chitosan from chitinous waste produced by the seafood industry. At present, industrial processes for the conversion of chitin into chitosan and COSs rely on the use of high amounts of concentrated acids and strong alkali at high temperature [ 20 – 23 ]. Thus, the use of specific enzymes such as chitinases, which act to breakdown the chitin polymer via hydrolysis is more ecofriendly, safe and allows to reduce the molecular weight without altering the chemical structure [ 22 ]. In this context, the first aim of this study was to determine whether prokaryotic community structures of a model High Microbial Abundance sponge ( Sarcotragus spinosulus ) and of a model octocoral ( Eunicella labiata ) species co-inhabiting the same geographic location (Algarve coast, Portugal) are distinct from each other and from those of their environmental surroundings (seawater and sediments). The second goal of this study was to perform an artificial selection procedure to enrich efficient chitin-degrading consortia from the above-mentioned marine biotopes, to answer the question of whether contrasting biotopes lead to taxonomically distinct chitin-degrading communities in the laboratory. During the artificial selection process, chitin degradation was assessed by measuring the change in molecular weight of the chitin polymer by Size Exclusion Chromatography (SEC) instead of using commercial kits that measure a potential degradation activity on short oligomers. The third objective was to determine whether chitin-degrading microorganisms recruited during the artificial selection procedure correspond to so-far unknown microbial lineages taking part in chitin / chitin-derivative degradation processes, and whether they represent dominant or otherwise low-abundant (“rare”) organisms in the original communities. This study highlights putative novel chitinolytic bacteria by artificial selection from multiple marine biotopes. 2 Material and methods 2.1 Sampling Sarcotragus spinosulus (Schmitt, 1862; Porifera, Demospongiae, Keratosa, Irciniidae) (three biological replicates: SP1, SP2, SP3) and Eunicella labiata (Thomson, 1927; Cnidaria, Anthozoa, Octocorallia, Eunicellidae) (three biological replicates: OC1, OC2, OC3) specimens and their surrounding seawater and sediment (three biological replicates each: SW1, SW2 and SW3 for seawater and SD1, SD2, SD3 for sediment) were collected off the Algarve coast, southern Portugal (“Pedra da Greta”: Lat. 36° 58′47.2N, Long. 7° 59′ 20.8W) at a depth of 18–19 m (bottom water pH was 8.13, temperature 19°C, and salinity 36.41 ppt) on the 29th of September 2020 by scuba diving. Pieces of marine sponge and branches of octocoral specimens (about 5 g each) were cut with a sterile scalpel and placed individually with surrounding seawater into Ziploc® bags. Surface sediment was sampled with a sterile spoon ( c. 2 g/ replicate) at c. 1 m distance to the animals and kept in sterile pots. Finally, seawater samples ( c. 2 L/ replicate) were collected c. 1 m above the animals and stored in sterile bottles. Samples were transported to the laboratory in a cooling box (c. 30 min transport time) and sample processing started immediately upon arrival in the laboratory. 2.2 Sample processing In a laminar hood, marine sponges were handled with sterilized tweezers to remove macroscopic epibionts and extracellular endobionts such as mussels, gastropods, worms, and algae. Afterwards, marine sponge specimens were washed with sterile Artificial Seawater (ASW) (ASW: 23.38 g L − 1 NaCl, 2.41 g L − 1 MgSO 4 ∗7H2O, 1.90 gL − 1 MgCl 2 ∗6H 2 O, 1.11 g L − 1 CaCl 2 ∗2H 2 O, 0.75 g L − 1 KCl and 0.17 g L − 1 NaHCO 3 ) and cut into small pieces with a sterile scalpel. The octocoral branches were also checked for epibionts (which, if present, were removed), washed with sterile ASW and the tissue was then scraped off the internal gorgonin skeleton with the help of a sterile scalpel and cut into small pieces. Several replicates of 0.25 g of tissue of each marine sponge and octocoral specimen were stored in sterile 2.0 mL microcentrifuge tubes at -80°C until DNA extraction. Seawater samples (c. 500 mL) were filtered through 0.22 µm pore-size nitrocellulose membranes (Millipore, MERCK) with the help of a vacuum pump. Seawater filters and sediment samples (0.25 g/replicate) were stored in sterile 2.0 mL microcentrifuge tubes at -80°C until DNA extraction. Microbial cell pellets were obtained from marine sponge and octocoral tissue according to the method described by [ 24 ] with minor modifications. Briefly, pieces of marine sponge and octocoral tissue of each specimen (1 g each), prepared as described above, were grinded in 9 mL of sterile Calcium-Magnesium-free-ASW (CMFASW. Composition: 27 g L − 1 NaCl, 1 g L − 1 NaSO 4 , 0.8 g L − 1 KCl and 0.18 g L − 1 NaHCO 3 ) using a sterile mortar and a pestle. The homogenates were then centrifuged at 4°C at 500 g for 2 min to remove the host-derived tissue (pellet). Thereafter, the supernatant was centrifuged at 4°C at 10,000 g for 15 min to recover the microbial cell pellet. To prepare microbial cell pellets from seawater samples, approximately 1 L of seawater was filtered through 0.22 µm pore size membranes (Millipore, MERCK). The seawater membranes were then cut into small pieces with a sterile scissor, mixed with a lab spoon of sterile 2-mm glass beads and with 50 mL of CMFASW. To prepare microbial cell pellets from sediment samples, approximately 1 g of sediment was mixed with a lab spoon of sterile 2 mm glass beads and with 9 mL of CMFASW. Afterwards, the cell suspensions from seawater and sediment were vortexed twice at max. speed for 30–60 sec with a 10 min interval to detach the microbial cells from the filters and sediment, respectively. All suspensions were then centrifuged at 4 ºC at 500 g for 2 min to decant glass beads plus seawater filter pieces or sediment particles. Then, the supernatant was centrifuged at 4 ºC at 10,000 g for 15 min to recover the microbial cell pellet. Each cell pellet (seawater, sediment, marine sponge, and octocoral) was resuspended in 830 µL of sterile ASW and transferred into sterile, 2 mL cryo-vials equipped with 150 µL of sterile 100% glycerol and 20 µL of pure, 100% DMSO. These glycerol stocks were stored at -80°C until further use. 2.3 Artificial selection procedure Glycerol stocks of microbial cell suspensions from the four biotopes (marine sponge, octocoral, sediment and seawater; three biological replicates each) were used as the starting material for artificial selection of microbial communities through successive transfers of enrichment cultures in a chitin-containing culture medium (described below). In total, twelve artificial selection experiments were initiated in this study. The experimental setup for artificially selecting microbial communities is depicted in Fig. 1 . The artificial selection process consisted of one pre-culture (referred to as “enrichment culture PC”) and three successive cultures (so-called “enrichment cultures C1, C2 and C3”). Briefly, 100 µL of each glycerol stock was inoculated into 100 mL of pre-culture medium at 20°C and 85 rpm. After 8 days of incubation, 1 mL of this PC was added to 100 mL of enrichment culture medium. After 7 days of incubation, 1 mL of enrichment culture C1 was transferred to 100 mL of the same fresh enrichment culture medium (C2). This step was repeated once more to generate enrichment culture C3. The culture medium for the preparation of the enrichment cultures (C1, C2 and C3) was composed of 100 mL of autoclaved ASW, 0.15 g of KH 2 PO 4 , 1 g of chitin powder extracted from shrimp shells (C7170 from Sigma-Aldrich/MERCK, Germany) and 160 µL of a solution of trace elements (for details, see Table S1 ). The same medium was amended with 0.01 g of tryptone in the preparation of the pre-culture medium (PC) to boost the growth of bacteria at the beginning of the process (Fig. 1 ). After each incubation period, the viability of the enrichment cultures was directly assessed using the MTT cell viability assay (see below). In addition, the following samples were collected: i) 5 mL for semi-quantitative assessment of chitin degradation (as described below; only for enrichment cultures C2) followed by qualitative characterization of the chitin degradation products by size exclusion chromatography (SEC; only for enrichment culture C2) after storage of the samples at -80°C, and ii) 5 mL for DNA extraction after centrifugation (10,000 g for 10 min) and storage of the pellet at -20°C. 2.4 MTT viability assays This assay was adapted from [ 25 ]. Briefly, 60 µL of MTT (tetrazolium salt; Sigma-Aldrich/Merck, Germany) were added to 200 µL of each enrichment culture (in technical triplicates) in sterile 96-well microplates. The microplates were incubated for 30 min at 37°C. Then, plates were centrifuged at 10,000 g for 7 min and the supernatant was removed. The remaining, reduced formazan cell pellet was dissolved in 200 µL of pure DMSO, the microplates were centrifuged again at 10,000 g for 7 min, and the absorbance at 570 nm (A570) was measured on the supernatant. If the A570 value of a sample was higher than the A570 of the negative control (chitin-based enrichment culture medium incubated under the same conditions as the (pre)cultures but without bacteria), it was interpreted as an indication of bacterial growth. 2.5 Chitin degradation assessments Assessments of chitin degradation, described in detail below, were performed on the enrichment cultures C2 of each artificial selection experiment (in triplicates), since chitin was usually observed to be more effectively degraded in C2 cultures, as indicated by preliminary measurements of the amount of decanted chitin left in culture flasks by the end of each enrichment culture C1, C2 and C3. Two approaches were used to assess chitin degradation: the measurement of remaining chitin weight in the cultures and size exclusion chromatography (SEC, detailed below). These techniques were complementary since measuring chitin weight constitutes an easy albeit not extremely precise approach (see Table 1 for standard deviations around triplicate chitin weight measures per sample), being explored in a semi-quantitative fashion in this study, while SEC provides qualitative information on the average size of the chitin polymer in the enrichment cultures (a decrease in polymer size indicates chitin degradation) and the size variations within the cultures (an increase in size variation suggests that the chitin polymer has been degraded into a range of diverse sizes). First, to record the weight of chitin remaining in the enrichment cultures at the end of the C2 incubation period (semi-quantitative assessment), the chitin powder in the liquid culture (5 mL) was first centrifuged at 2,000 g for 5 min and the pellet washed twice with MilliQ water. The chitin pellet was then dried at 70°C in heating blocks (DRB200; Hach, USA) until reaching a constant weight and weighted. The chitin weight loss for each enrichment culture C2 was calculated by subtracting the remaining chitin weight from the initial chitin mass, dividing by the initial mass, and then multiplying by 100. Second, for a detailed assessment of chitin degradation dynamics, SEC was used to determine the molecular mass parameters of the chitin polymers: (i) numbered average molecular weight (Mn), defined as total weight of polymer divided by the total number of molecules; (ii) weight average molecular weight (Mw), which depends on the number of molecules present and on the weight of each molecule; and (iii) polydispersity (PDI), defined as the ratio of the weight average molecular weight to the number average molecular weight, giving a measure of the distribution of the molecular weight within a sample [ 26 ], with three technical replicates conducted for each sample. The molecular mass parameters of the chitin polymers were also determined for the negative control (C-; in triplicate). The SEC protocol was applied to dry chitin pellets obtained from 5 mL of the C2 enrichment cultures, and is described in detail in Supplementary File S1, Methodology SM.1. The polymeric parameters (reported herein as Mn 1 , Mw 1 , and PDI 1 ) were calculated from the signals detected in time slices within a significant region of the whole chromatogram, hereafter termed “region 1”, spanning 70.5 KDa – 1,020 KDa in molecular weight and thus excluding small sized oligomers (Methodology SM.1, Fig. S1 ). For “region 1” of the chromatograms, the numbered average molecular weight Mn 1 was calculated as follows: $$\:Mn=\:\frac{(\sum\:Ni*Mi)}{\sum\:Ni}$$ Where i is a slice (1.666 x 10 − 3 min) of the region, Mi is the molecular weight and Ni is the intensity of the signal. Mw, the weight average molecular weight, was calculated as follows: $$\:Mw=\:\frac{(\sum\:Ni*{Mi}^{2})}{\sum\:Ni*Mi}$$ where i is a slice of the region, Mi is the molecular weight and Ni is the intensity of the signal. Polydispersity PDI is a measure of the broadness of the peak and was calculated as follows: $$\:PDI=\frac{Mn}{Mw}$$ Correlation analyses were thereafter performed to assess the strength of the relationship between chitin degradation parameters assessed in this study. Specifically, Pearson correlations were computed between the estimated Mn 1 values obtained for all C2 enrichment cultures and the corresponding values recorded for weight of remaining chitin in the cultures and PDI 1 using the ggscatter function ( cor.method = “pearson”) from the ggpubr package (v 0.5.0;[ 27 ]) in R. These analyses allowed us to assess hypotheses of a positive correlation between Mn 1 and remaining chitin weight values (the higher the chitin weight remaining in the tube, the higher the molecular mass of the chitin polymer) and a negative correlation between PDI 1 and Mn 1 values (the higher the polydispersity of the chitin peaks, the lower the estimates of chitin molecular weight, suggesting that the large chitin polymer is being broken down into smaller oligos of different sizes). Finally, estimates of chitin weight loss and Mn 1 calculated as described above were integrated to classify the chitin degradation efficiency of samples analyzed in this study as “high” (> 45% weight loss, Mn 1 = [6.93–7.37 + 05], “good” (25–45% weight loss, Mn 1 = [7.65 + 05]), “moderate” (10–25%, Mn 1 = [7.36* − 8.56 + 05]) and “low” (< 10%, Mn 1 = [8.69 + 05]) (Table 1 ). Table 1 Simplified categorization of enrichment cultures into chitin degradation efficiencies based on chitin weight loss. Chitin degradation efficiency Enrichment cultures Weight loss (%) Mn1 range (Da) High SW3, SD1, SD3 > 45% 6.93–7.37 + 05 Good SD2 25–45% 7.65 + 05 Moderate SP1, SP2, SP3, SW1, OC1, OC2, OC3 10–25% 7.36* − 8.56 + 05 Low SW2 < 10% 8.69 + 05 * low Mn 1 values, suggesting high chitin degradation efficiency, were estimated for octocoral samples 2 and 3, which presented, however, moderate estimates of chitin weight loss according to the chitin weight measurement methodology employed in this study. 2.6 Total community DNA extraction and 16S rRNA gene sequencing DNA was directly extracted from 0.25 g of the inner marine sponge tissue, octocoral tissue, sediment and from the seawater filters for the environmental ( in situ ) samples; and from the microbial cell pellets recovered from 5 mL of each enrichment culture (PC, C1, C2 and C3). DNA was extracted using the “DNeasy PowerSoil Pro kit” from Qiagen (ID: 47014) according to the manufacturer’s protocol. The seawater filters were cut into small pieces using sterile scissors prior to DNA extraction. The DNA quantity (ng/µL) and quality (A260/A280 and A260/A230) was estimated with a NanoDrop ND 2000 UV-VIS spectrophotometer (Thermo Fisher Scientific, Waltham, US) and DNA samples were kept at -20°C until further analyses. 16S rRNA gene amplification and sequencing from DNA samples were carried out at StarSeq (Mainz, Germany) using Illumina MiSeq sequencing. The V4 region of the 16S rRNA gene was sequenced following a 2x300 paired-end approach using the primers 515F (5’-GTG YCA GCM GCC GCG GTAA-3’) and 806 Rb (5’-GGA CTA CNV GGG TWT CTA AT-3’) [ 28 , 29 ]. An average of 100,000 paired-end sequences was generated per sample. The library of reads was demultiplexed by StarSeq. 2.7 Processing of the 16S rRNA gene sequencing data All 16S rRNA gene fragment sequences were processed together using the denoising-based pipeline DADA2 (Divisive Amplicon Denoising Algorithm) v.1.8 (in R; [ 30 ]). First, the FilterandTrim function from DADA2 was used to remove the reads with Ns ( maxN = 0 ) using the following settings: trim the end of the forward and reverse reads at a specific base pair position where the quality of the majority of reads dropped under Q = 30 ( truncLen = c(240,150)), filter out the reads belonging to the PhiX bacteriophage ( rm.phix = TRUE ; [ 31 ], select reads with high number of errors ( maxEE = 2 ) and truncate those with high levels of error at the earliest occurrence of a quality score that is equal to or lower than 2 (truncQ = 2; the value 2 is utilized by Illumina as a read end quality indicator). After combining all identical sequence reads into ‘‘unique sequences” (each associated with the number of reads of each sequence), the DADA2 algorithm inferred Amplicon Sequence Variants (ASVs). Paired-end sequences were merged (using the mergeSequenceTables() function from DADA2) and chimeric ASVs were removed (using the DADA2 function removeBimeraDenovo() function) from the ASVs table. Taxonomy (Kingdom, Phylum, Class, Order, Family and Genus) of each ASV was then assigned using the SILVA database version 138.1 [ 32 , 33 ]. The ASVs versus samples and taxonomy profile tables were then imported into R as a phyloseq object using the phyloseq package (v1.38.0; [ 34 ]) to perform diversity and taxonomic composition analyses. The dataset was filtered using the function subset_taxa from the phyloseq R (v1.38.0;[ 34 ]) package to eliminate mitochondria, chloroplast and eukaryote sequences. The final dataset consisted of 60 samples (all sample types included) thoroughly profiled via 16S rRNA gene sequencing. A total of 5,685,383 filtered reads were generated and 5,389 bacterial and 284 archaeal ASVs were found. 2.8 Analysis of 16S rRNA gene fragments Data wrangling and generation of graphics were performed using the R packages phyloseq (v1.38.0; [ 34 ], dplyr (v1.8.6, [ 35 ] and ggplot2 (v 3.4.0; [ 36 ]) for a thorough analysis of the abundance distributions of 16S rRNA gene ASVs across all samples. Briefly, the analytical approach employed in this study involved the generation of stacked bar charts to depict the taxonomic composition of prokaryotic communities of the environmental samples and enrichment cultures at phylum, class and ASV levels, along with assessments of ASV alpha and beta-diversity for all samples and sample groups. Alpha-diversity analyses consisted of documenting observed ASV richness and estimating the Shannon-Wiener diversity index for all samples. Statistical differences in alpha diversity metrics among sample groups were tested using custom analysis of variance (ANOVA) approaches coupled to post-hoc tests depending on the features of each sample group (for details, see Methodology SM.3). Two beta diversity analyses were performed in this study: i) one to determine whether differences in prokaryotic community structure occurred among the environmental samples of each biotope (seawater, sediment, marine sponge and octocoral) and ii) one to determine whether such differences occurred between the enrichment cultures derived from each biotope and from each biotope replicate. For each analysis, the ASV data were first Hellinger-transformed (square root of ASV relative abundances). Then, a Bray-Curtis similarity matrix was calculated using the phyloseq package from R (v1.38.0; [ 34 ]). A Principal Coordinates Analysis (PCoA) was generated for each analysis to ordinate the samples based on the Bray-Curtis matrix. Ordination diagrams were drawn using the ggplot2 package (v 3.4.0;[ 36 ]) in R. To check for significant differences in prokaryotic community structure between environmental samples and/or enrichments cultures, a Permutational Analysis of Variance (PERMANOVA) [ 37 ] or a Welch MANOVA [ 38 ] was performed depending on the homogeneity of variance between groups of samples. For more details on the methodology employed, please see Methodology SM.4. 2.9 Genome-wide inspection of chitin degradation and utilization features among artificially-enriched and poorly-studied bacterial genera We examined chitin degradation and utilization features among genomes of bacterial genera observed to dominate enrichment cultures reported in this study but correspond to so-far poorly known or unknown taxa involved in the metabolism of chitin and its derivatives. Our approach consisted of thorough protein family (Pfam) annotation of all genomes available on DOE JGI’s Integrated Microbial Genomes & Microbiomes (IMG/M) data management system v.7 [ 39 ] for the bacterial taxa under inspection. Specifically, we scanned 102 genomes from ten artificially-selected genera (see Table 2 for details) for the presence of 15 Pfam categories representing protein domains involved in hydrolysis of the large chitin polymer (endo-chitinases of GH families 18 and 19—EC 3.2.1.14, chitin-binding proteins), hydrolysis of chitin non-reducing ends (exo-chitinases, EC 3.2.1.52), chitin deacetylation (polysaccharide deacetylases), and N-acetylglucosamine binding and utilization. The precise Pfam categories used in our in silico prospection for chitin degradation and utilization features are presented in Table 2 . 3 Results 3.1 Prokaryotic community structure in environmental samples The 16S rRNA gene sequencing approach and statistical analyses employed in this study revealed that the here examined biotopes ( S. Spinosulus , E. labiata , seawater and sediment) displayed different prokaryotic taxonomic profiles from one another at the phylum, class, and ASV levels (Figs. S2 and S3). Congruent with earlier microbiome surveys of S. spinosulus and E. labiata specimens from the North Atlantic [ 24 , 40 ], here we observed that these hosts harbour distinct prokaryotic consortia in comparison with those of their environmental vicinities (seawater and sediments). In addition, in this study we found that the prokaryotic communities associated with S. spinosulus and E. labiata were significantly different from each other in terms of structure and taxonomic composition (Figs. S2 and S3). Although all biotopes were dominated by the phyla Pseudomonadota and Bacteroidota , the relative abundance of these phyla changed considerably across biotopes. The same trend was observed for the two most dominant Pseudomonadota classes, Alphaproteobacteria and Gammaproteobacteria , which presented distinct relative abundances across all biotopes. At the ASV level, the prokaryotic communities of the four biotopes were clearly unique and contrasting, thus providing support to the original motivation of this study. Table S3 provides the abundance distributions of all ASVs (n = 5,673) detected across all environmental and enrichment culture samples analyzed in this study (n = 60). 3.2 Artificial selection experiments 3.2.1 Enrichment cultures develop differentially according to their biotope of origin Multivariate analysis of all enrichment cultures showed a clear separation of the cultures according to their source biotope (Fig. 2 ). Moreover, within each biotope, we observed that enrichment cultures also formed distinguishable clusters according to the replicate experiment (Fig. 2 ). The separation of all enrichment cultures according to the source biotope (marine sponge, octocoral, seawater, and sediment) was statistically confirmed by a Welch MANOVA test (p-value = 0.001; pairwise adonis p-value = 0.006 for all pairs of biotopes). Furthermore, separate clustering of enrichment cultures (PC, C1, C2 and C3) derived from the same biotope but from different replicate experiments was confirmed by a PERMANOVA test (p-value = 0.001; pairwise adonis p-value = [0.018–0.042] for each pair of replicates). Moreover, the dispersion among the enrichment cultures PC, C1, C2 and C3 was higher than in their respective environmental samples (see PERMDISP values; Table S4) with one exception (for octocorals, PCs were less dispersed than the environmental samples). 3.2.2 Assessments of chitin polymer molecular weight suggests efficient chitin degradation in some cultures The Mn 1 values of all C2 enrichment cultures, corresponding to the average size of the chitin polymer in these samples, were lower than the Mn 1 value of the negative control, which consisted of chitin medium alone and was estimated at 887 KDa (Fig. 3 ; Tables S2, S5). This indicates that chitin degradation occurred in all enrichment cultures. However, we observed that estimated Mn 1 values ranged from 693 KDa in sample SD1 to 869 KDa in sample SW2, being, overall, positively correlated with chitin weight measures (the lower the Mn 1 estimate, the lower the weight of the remaining chitin) and negatively correlated with polydispersity (the lower the Mn 1 estimate, the higher the polydispersity) (Figs. 3 A and 3 B, Table S5). In summary, the communities that exhibited low chitin weight usually broke down large chitin polymers into smaller molecules of a more diverse size range, resulting in a decrease in average size (Mn 1 ) and an increase in size variation (PDI 1 ) of chitin. The trends above prompted us to establish a semi-quantitative rank of “chitin degradation efficiencies” based on the integration of chitin weight measures and Mn 1 estimates (Table 1 ). According to this scheme, we classified enrichment cultures SD1, SD3 and SW3 as “highly efficient” at degrading chitin, enrichment culture SD2 as “good”, cultures SP1-SP3, OC1-OC3, and SW1 as “moderate”, and culture SW2 as “low efficient” (Table 1 ). It is important to note that the dynamics of chitin degradation across all enrichment cultures could not be fully depicted by the use of one single estimate or index alone. For instance, in spite of the correlations noted above, enrichment cultures OC2 and OC3 presented low Mn 1 estimates, equivalent to that of culture SD3 (a “highly efficient” chitin degrading one) while presenting chitin weight loss of c. 25%, in the range of several “moderately efficient” consortia, being thus classified as “moderate” according to our conservative scheme (Table 1 ). This exemplifies that chitin weight measures alone, for instance, do not fully portray the chitin degradation dynamics in the samples. The assessment of polymeric parameters via SEC holds potential to become an analytical aid in future studies of chitin degradation. 3.2.3 Sharp taxonomy shifts between environmental samples and enrichment cultures were marked by the selection of potentially novel chitin-degrading taxa Figures 4 and 5 display genus-level taxonomic composition, ASV richness and diversity, and activity indicators of enrichment cultures derived from host-associated (Fig. 4 , A-E) and free-living (Fig. 5 , A-E) biotopes. The repeated measure ANOVA tests performed separately on each biotope revealed significant differences in alpha-diversity measures, marked by a decrease in observed ASV richness and Shannon diversity indices, between the environmental samples and their corresponding enrichment cultures (p-value = [7.44 e-10–0.000122] for all samples from every biotope except for one octocoral sample (replicate #1). Post-hoc Tukey tests revealed significant differences in alpha-diversity only between the environmental samples and the PC, C1, C2 and C3 (p-value = [0.00293–3.44e-11]), again for every sample within each biotope except for octocoral replicate sample #1. In contrast, ASV richness and Shannon index did not change significantly further on in the selection process for each biotope, neither between PC and C1, nor between C1 and C2 or between C2 and C3 cultures (Tukey tests p-values = [0.396-1] for observed ASV richness and Tukey tests p-values = [0.479-1] for Shannon index). Furthermore, many of the dominant taxa in the environmental samples were not abundant (< 0.03%) or even undetectable in the enrichment cultures (Fig. 4 A, B; Fig. 5 A, B). Conversely, dominant taxa in the enrichment cultures were poorly represented (< 0.1%) or absent in their corresponding environmental samples (Fig. 4 A, B; Fig. 5 A, B; Table S6). Respiratory activity (low to high) was recorded for all samples (Fig. 4 E, Fig. 5 E, Table S2 ). Vibrio ASV1 was consistently enriched in the cultures from all biotopes (Table S3). Psychromonas ASV26 was enriched in all cultures for which chitin degradation efficiency was classified as “good” or “high” (SD1, SD2, SD3, SW3) (Fig. 5 A, Table S3), and a negative correlation was observed between the relative abundance of ASV26 and remaining chitin weight (Fig. S4). In all sediment cultures, Vibrio ASV13 was enriched. The enrichment cultures from sediment samples SD1 and SD3 were further dominated by Halodesulfovibrio ASV6, Amphritea ASV43, Profundimonas ASV60, Fusibacter ASV113 (in SD1) and ASV140 (in SD3), and Pseudovibrio ASV9. Unclassified Rhodobacteraceae ( Alphaproteobacteria ) ASV91 and Pseudophaeobacter ASV27 were also enriched in SD2 enrichment cultures; Alteromonas ASV29 was enriched in SD3- and Psychrobium ASV72 in SD1- enrichment cultures (Fig. 5 A, Table S3). Regarding the enrichment cultures from seawater SW3, perceived as highly efficient at degrading chitin according to our classification scheme (Table 1 ), C1, C2 and C3 were strongly dominated by Poseidonibacter ASV11. Of note, ASV11 was not enriched in the cultures from the two other seawater samples (SW1 and SW2, Fig. 5 B) where chitin degradation was perceived as “moderate” or “low” (Table S2 ). Other dominant taxa in SW3 enrichment cultures were Vibrio ASV17, Halodesulfovibrio ASV6 and Marinobacterium ASV65. Halarcobacter ASV76 was abundant in the enrichment culture C2 of SW3. In SW1- and SW2- enrichment cultures, other taxa were enriched such as Pseudomonas ASV64, Shewanella ASV14 and Alteromonas ASV29. In the SW1 final enrichment culture, Vibrio ASV40 was also highly enriched and in SW2 enrichment cultures, Pseudoalteromonas ASV10 was highly enriched (Fig. 5 B). All enriched communities from the marine sponge samples were dominated by Pseudophaeobacter ASV27, Vibrio ASV1 (a dominant ASV in sediment and seawater cultures as well) and ASV13, and by Pseudovibrio ASV9 (Fig. 4 A, Table S3). Enrichment cultures of marine sponge samples SP1 and SP2 were also dominated by Shewanella ASV45 (in SP1) and ASV15 (in SP2) (Fig. 4 A). SP2-derived cultures showed high abundance of Vibrio ASV17, and SP3-derived cultures of Enterovibrio ASV16 (Fig. 4 A). Finally, the octocoral-derived enrichment cultures were largely dominated by Aquimarina ASV12 (sample OC2) and by Vibrio ASV1 (sample OC3), while OC1-enriched cultures were co-dominated by many taxa such as Shewanella ASV14, Pseudoalteromonas ASV10, Flavobacteriaceae ASV21 and Motilimonas ASV3 (Fig. 4 B). 3.3. Genome prospection reveals putative novel chitin degraders and consumers in artificially selected consortia Table 2 Pfam-based annotation overview of protein domains involved in chitin degradation found in publicly available genomes of putative novel chitin-degrading/-utilizing genera identified in this study 1 . Class Genus # genomes Endo chitinases Exo chitinases CBP Polysaccharide deacetylases N-acetyl glucosamine Suggested role/coding potential Gammaproteobacteria Motilimonas 4 4 [ 17 – 24 ] 4 [ 3 – 4 ] 4 [ 5 – 11 ] 4 [ 3 – 4 ] 4[ 1 ] Chitin degrader via hydrolysis and deacetylation; COSs degrader via hydrolysis, GlcNAc consumer Alphaproteobacteria Pseudophaeobacter 4 0 0 0 4 [ 2 – 4 ] 4 [ 1 – 2 ] Chitin degrader via deacetylation, GlcNAc consumer Bacteroidia Reichenbachiella 5 5 [ 2 – 3 ] 4 [0–5] 0 5 [ 2 – 4 ] 4 [0–3] Chitin degrader via hydrolysis and deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature), putative GlcNAc consumer (strain-dependent feature) Desulfovibrionia Halodesulfovibrio 5 2 [0–1] 2 [0–1] 2 [0–2] 5 [ 1 – 2 ] 5 [ 1 ] Putative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; GlcNAc consumer Bacteroidia Aureivirga 2 2 [ 2 – 4 ] 0 0 2 [ 1 ] 0 Chitin degrader via hydrolysis and deacetylation Alphaproteobacteria Epibacterium 4 0 2 [0–2] 0 4 [ 4 ] 4 [ 1 ] Chitin degrader via deacetylation; putative COSs consumer (strain-dependent feature); GlcNAc consumer Gammaproteobacteria Psychromonas 18 13 [0–18] 5 [0–10] 5 [0–3] 18 [ 1 – 4 ] 16 [0–2] Putative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); putative GlcNAc consumer (strain-dependent feature) Bacteroidia Muricauda 26 6 [0–4] 25 [0–13] 0 14 [0–2] 26 [ 2 – 6 ] Putative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); GlcNAc consumer Campylobacteria Poseidonibacter 8 0 0 0 8 [ 1 – 3 ] 6 [0–1] Chitin degrader via deacetylation; putative GlcNAc consumer (strain-dependent feature) Alphaproteobacteria Thalassotalea 26 8 [0–3] 19 [0–14] 0 26 [ 1 – 2 ] 26 [ 3 – 9 ] Putative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); GlcNAc consumer 1 Pfam annotations were performed on the IMG/M v.7 system using all genomes available for the examined taxa. Values in cells show the number of genomes within each genus for which a positive score was recorded for the screened function. Values in brackets display the range of variation in the number of protein domains found on the genomes of each genus which scored positive for that function. Pfam categories used to screen for chitin degradation-utilization features across genomes were as follows. Endochitinases: PF00182 (chitinase class I, GH19), PF00704 (GH18), PF08329 (chitinase A N-terminal domain), and PF06483 (chitinase C). Exochitinases: PF03174 and PF13290 (Chitobiase/beta-hexosaminidase C-terminal domains), PF03173 (Chitobiase/beta-hexosaminidase N-terminal domain), PF02838 (GH20, domain 2), PF00728 (GH20, catalytic domain), and PF14845 (beta-acetyl hexosaminidase like). Polysaccharide deacetylases: PF01522 (Polysaccharide deacetylase), PF04748 (divergent polysaccharide deacetylase)]. Chitin-binding proteins (CBP): PF01607 (Chitin binding Peritrophin-A domain, family 14), PF02839 (Carbohydrate-binding module family 5/12). N-acetylglucosamine utilization: PF01182 (Glucosamine-6-phosphate isomerases/6-phosphogluconolactonase)]. Table 2 synthesises Pfam annotation results obtained for 102 genomes across the ten genera examined (for details, see Tables S7A,B). Table S7A presents the full taxonomic string of each genus. We performed a thorough analysis of chitin degradation and chitin-derivative utilization features across 102 publicly available bacterial genomes belonging to the genera Aureivirga , Epibacterium , Halodesulfovibrio , Muricauda , Motilimonas , Pseudophaeobacter , Poseidonibacter , Psychromonas , Reichenbachiella and Thalassotalea (Tables 2 and S7A,B). These genera were targeted because they were detected as dominant taxa in the experiments in which chitin was efficiently degraded (Fig. 3 ) whereas, to the best of our knowledge, current evidence for their roles as chitin degraders or consumers is either non-existent or scarce. Sequences coding for endochitinase domains were detected in the genome of all Motilimonas, Reichenbachiella and Aureivirga strains surveyed, and some Halodesulfovibrio , Psychromonas, Muricauda , and Thalassotalea strains (for details, see Table S7B). Exochitinase protein domains were detected in the genome of all Motilimonas strains and some Reichenbachiella, Epibacterium , Psychromonas , Muricauda and Thalassotalea strains. Sequences coding for polysaccharide deacetylase and N-acetylglucosamine utilization domains were detected in the genomes of the great majority of strains belonging to the different genera. Finally, sequences coding for chitin-binding protein domains were detected in the genomes of all Motilimonas strains and of some Halodesulfovibrio and Psychromonas strains. Compared to the other genomes, those of Motilimonas presented a considerably higher number of targeted sequences: 17 to 24 sequences per genome coding for domains of endochitinases, 3 to 4 for exochitinases, 5 to 11 for CBP and 3 to 4 for polysaccharide deacetylases (Table 2 ). Motilimonas was actually the single genus for which a positive score was recorded for all the searched functions across all genomes surveyed (Table S7B). Interestingly, genomes in the genera Pseudophaeobacter (found to be enriched in samples SD2 and SP2) and Poseidonibacter (sharply enriched in sample SW3, classified as “highly efficient” for chitin degradation) did not possess any endochitinase nor exochitinase coding sequences, but possessed polysaccharide deacetylation and N-acetyl-glucosamine utilization features. Based on these analyses, we proposed putative roles in chitin/chitin-derivative degradation and utilization for the ten bacterial genera examined more thoroughly in this study (Table 2 ). 4 Discussion This study employs artificial selection to enrich chitin-degrading microbial consortia from contrasting marine biotopes. Using metagenomics approaches, Raimundo et al. [ 7 ] found that marine sponges, octocorals, sediments and seawater harbour distinct chitin-degrading communities both in terms of taxonomy and the prevailing metabolic pathways involved in chitin metabolism. Here, we combine taxonomy assignments by 16S rRNA gene sequencing with estimates of chitin degradation to cross-compare the structure and potential metabolism of chitin-degrading consortia selectively enriched from these biotopes in the laboratory. We perform comprehensive alpha and beta-diversity analyses of the source environmental samples from each biotope and their corresponding enrichment cultures. The detailed methodology, results and discussion pertaining to the comparison of the environmental samples collected in situ are presented in Supplementary File S1. In this section, we highlight the recruitment of potential chitin degraders and utilizers from the original communities, placing a focus on the coding potential of enriched bacterial genera so far not described to play fundamental roles in the degradation of chitin and its derivatives. 4.1 Chitin-based artificial selection applied to prokaryotic communities from marine biotopes lead to distinct chitin degrading consortia This study demonstrates that applying a strictly equal artificial selection procedure with chitin as sole organic carbon and nitrogen source to different prokaryotic communities from distinct marine biotopes (i.e., marine sponge, octocoral, sediment, and seawater) leads to different chitin degrading consortia (Fig. 2 , 4 A & 5 A). Moreover, artificial selection was found, in this study, to increase the natural variation among replicate communities observed in the environment. This can be explained by the likely combination of two factors: (1) the fact that natural differences in microbiome assembly (i.e., relative abundance distributions of original community members) might have dictated differential enrichment trajectories in each independent artificial selection experiment, and (2) that such natural variations might have been influenced or augmented by the sampling processing procedures employed (e.g., transportation, handling, conservation of the communities in glycerol), which may have induced biases to the original community composition of replicate samples from the same biotope. This picture aligns with the concept of priority effects on microbiome assembly [ 41 ], whereby the final structure of a given community may rely on the order/timing of arrival of their founding members, which may be considerably influenced by stochastic events yet simultaneously dictate the successional changes underlying the assembly process. Priority effects have been evoked to explain sample-to-sample variability in algal [ 42 ] and fish larvae microbiomes [ 43 , 44 ] and are considered a relevant phenomenon in the assembly of host-associated and free-living microbial communities across marine, freshwater and terrestrial ecosystems [ 41 ]. These outcomes revealed that each experiment was unique to some extent, even though deterministic factors simultaneously shaped the assembly of the enrichment cultures based on their source biotope. It is also reasonable to argue that the source of chitin (in our case, chitin powder from shrimp cells) used in artificial selection experiments likely influences the selected consortium and its degradation efficiency, and needs to be carefully considered during experimental design. To reduce variability among replicate enrichments from the same biotope, future studies may attempt pooling several subsamples (e.g., multiple excisions from the same sponge or coral specimen) to form a composite, representative sample of each replicate. Altogether, our data suggest that applying artificial selection to a range of distinct marine biotopes can increase the discoverability of novel chitin-degrading taxa and consortia, leading to the potential characterization of novel enzymes of marine origin involved in the chitin degradation process. It remains a challenging task to obtain highly resolving estimates of chitin degradation by artificially selected consortia, yet the design of such experiments allows tapping into the chitin degradation capacity of taxa previously unknown to play these roles, which can be further studied by means of both phenotyping and genotyping. 4.2 Artificial selection recruits low-abundance chitin degraders and utilizers The artificial selection procedure employed in this study promotes low-abundance chitin degraders and utilizers within each biotope. Indeed, it was a consistent pattern that dominant taxa in the enrichment cultures were poorly represented or even absent in their corresponding environmental samples (see Table S6 for details). This shows that the culturable bacteria from the marine sponge, octocoral, seawater, and sediment biotopes used in this study likely belong to the microbial rare biosphere within their natural environment. Microbial cultivation bias is a well-known phenomenon previously shown by several studies of free-living [ 45 – 47 ] and host-associated bacterial communities [ 48 – 50 ]. The high diversity of low abundance taxa present in natural microbial communities represents a vast collection of genetic features that contribute to a broad range of both established and potentially undiscovered microbial functions [ 51 , 52 ]. It is also well established that low abundance, “rare” taxa can grow abundant under certain culture conditions [ 53 ] and degrade different pollutants, aromatic hydrocarbons [ 54 – 56 ], as well as complex polymers such as chitin as observed in this study. Enrichment of low abundance, chitin degrading microorganisms might as well occur in the natural environment under certain circumstances. Indeed, it has been recently shown that species in the known chitin degrading genus Aquimarina [ 7 ] usually belong to the rare biosphere of distinct marine biotopes [ 57 ] and may increase in abundance under certain conditions (e.g., in necrotic octocoral tissue [ 8 , 58 ] and on the carapace of injured lobsters [ 59 ]). Hardoim and colleagues suggested that the culturable fraction of bacterial symbionts of the marine sponges Sarcotragus spinosulus and Ircinia variabilis consisted primarily of low abundance species [ 40 ]. Conversely, dominant symbionts belonging to the Rhodothermales order and the Endozoicomonas genus were recently suggested, through genome-resolved metagenomics studies, to play a key role in chitin degradation in marine sponges [ 11 ] and octocorals [ 8 ], respectively. However, although these taxa were abundant in the here examined S. spinosulus ( Rhodothermaceae ASV90; Fig. 3 ) and E. labiata ( Endozoicomonas ASV23; Fig. 3 ) specimens, respectively, they escaped enrichment via artificial selection as attempted in this study. This is likely due to the sampling, transportation and cultivation procedures employed (including the retrieval of microbial cell homogenates from the samples, their conservation, the culture medium, and incubation conditions). Therefore, techniques to domesticate these symbionts in culture need to be implemented to harness their metabolism. These alternative techniques include varying culture conditions (adjusting pH, temperature, and physical-chemical conditions), modifying the composition of the medium (for instance, by incorporating host chemical cues), or adopting gentler sampling processing methods. Another future step could be to express the chitin-degrading enzymes of these symbionts, such as chitinases, without the need for cultivation. This can be achieved through targeted gene cloning and expression for chitinase genes [ 60 , 61 ] or directly by chitinase gene synthesis based on their metagenomic sequences and subsequent cloning and expression. 4.3 Cross-feeding may promote co-existence of chitin degraders and utilizers in enrichment cultures In the enrichment cultures derived from octocorals and marine sponges, chitin degradation was classified as moderate according to chitin weight loss and Mn 1 estimates, while bacterial activity (low to high) was recorded in these cultures. Moreover, many well-known chitin degraders were enriched in these cultures from their corresponding natural biotopes, such as Vibrio [ 7 , 62 ], Shewanella [ 7 , 63 ], Pseudoalteromonas [ 7 , 64 ], Pseudomonas [ 65 , 66 ], Aquimarina [ 7 , 67 ], Alteromonas [ 68 ], and Enterovibrio [ 7 ]. Our results suggest that in the conditions of our experiments the degradation dynamics occurring in the enrichment cultures from the marine sponge and the octocoral biotopes could not be thoroughly captured by the techniques we used to assess chitin hydrolysis (chitin weight loss or SEC). It might also be that these taxa grew using smaller soluble oligomers originally present in the chitin powder whose degradation dynamics and shifts in molecular weight are rather challenging to monitor and interpret. In this study, we observed four bacterial consortia from sediment and seawater samples which were classified as “highly efficient” (SD1, SD3 and SW3) and “good” (SD2), at degrading chitin. Among these four selected communities, some of the enriched taxa were already known to be chitin degraders such as Vibrio [ 7 , 62 ], Alteromonas [ 68 ] and Pseudoalteromonas [ 7 , 64 ]. Some others are known to be chitin utilizers such as representatives of the Rhodobacteraceae ( Alphaproteobacteria ) family [ 7 , 8 ] and of the genus Pseudovibrio in the Stappiaceae family [ 7 ]. This suggests the co-existence of chitin degraders and utilizers through hypothesized cross-feeding mechanisms. Indeed, chitin degraders might make excess chitin degradation products available (COSs, chitosan, GlcNAc) which are used by other chitinolytic bacteria (i.e., chitin utilizers). This process, although difficult to demonstrate experimentally, was already suggested in previous studies [ 4 , 7 , 8 , 69 – 71 ]. Moreover, to the best of our knowledge, many other taxa enriched in cultures classified as possessing “moderate” (all host-associated cultures), “good” or “high” chitin degradation efficiencies are so far unknown or understudied for their role as chitin degraders and/or utilizers. This includes genera such as Amphritea , Aureivirga , Epibacterium , Fusibacter , Halarcobacter, Halodesulfovibrio, Marinobacterium , Motilimonas , Muricauda , Poseidonibacter , Profundimonas, Pseudophaeobacter , Psychrobium , Psychromonas , Reichenbachiella , and Thalassotalea (Fig. 3 , Table S6). Using dedicated functional annotation of dozens of genomes available for ten representative genera (Tables 1 and S7), we suggest that Motilimonas, Reichenbachiella, Halodesulfovibrio, Aureivirga and Psychromonas are potential chitin degraders by means of hydrolysis (Tables 1 and S7). Epibacterium may have a role in chitin utilization/COSs degradation via hydrolysis. Pseudophaeobacter and Poseidonibacter may have a role in chitin degradation via deacetylation and in GlcNAc consumption. Moreover, all genera examined, except Aureivirga , are classified as potential GlcNAc utilisers. Wright and colleagues [ 13 ] applied an artificial selection process on microbial communities from bulk marine debris (Devon, UK) using varying incubation times (e.g., 9 days and 4 days) over several transfers, observing a few enriched taxa in common with our study. These include well-known chitin degraders such as Vibrio , Alteromonas and Pseudoalteromonas and other taxa less known for their role in chitin degradation such as Muricauda and Thalassotalea . Genomes available for these two taxa were found, in our study, to possess endochitinase genes which is suggestive of a potential role for these organisms as chitin degraders by means of hydrolysis in multiple biotopes. These trends suggest that performing the artificial selection procedure on several marine biotopes, as it was done in this study, increases the chance of obtaining different taxa involved in chitin degradation. Moreover, Wright et al. (2019) suggested that successive transfers over short time periods (e.g., 4 days) favours the selection of chitin-degrading bacteria in the Gammaproteobacteria class while reducing the abundance of chitin utilizers / “grazers” of COSs, such as representative members of the Alphaproteobacteria class. The seven-day incubation period employed in our study led to the promotion of relatively stable communities most likely composed by a mix of chitin degraders and utilizers over the course of the experiment (29 days from the pre-culture to culture C3). Taken together, our results suggest that a versatile and functionally convergent coding potential for chitin metabolism, involving the breakdown of chitin and COSs via endo and exochitinase-mediated hydrolysis, deacetylation into chitosan, and N-acetylglucosamine utilization features, was assembled in enrichment cultures via artificial selection from multiple marine biotopes. This indicates that cross-feeding among artificially-selected bacteria can act as a possible mechanism underlying the diversity of chitin degraders and utilizers in the enrichment cultures, as observed experimentally for combinations of specific, marine bacterial isolates [ 71 ]. Enrichment cultures from sediments were regarded and “good” or “efficient” chitin degraders, while those derived from host-associated (sponges and octocorals) communities classified as “moderate” and seawater-derived cultures varying considerably from “low” to “efficient”, with the taxonomic composition within the enrichment cultures being influenced by the source biotope, in spite of observed sample-to-sample variability. 5 Conclusion In this study, distinct bacterial consortia efficient at degrading chitin composed by known chitin degraders, known chitin utilizers and many taxa not yet known or only poorly studied for their role(s) in chitin degradation were selected from several marine biotopes. The latter taxa (e.g., Motilimonas , Muricauda , Halodesulfovibrio , Psychromonas , Reichenbachiella , among others) are potential key players in marine chitin degradation revealed in this study by means of artificial selection. Building upon these enriched prokaryotic communities, future investigation can employ both top-down and bottom-up approaches. Top-down methods may involve isolating strains from the communities, studying the chitin degradation abilities of these isolated strains through commercially available chitinase assays and/or chitin degradation activity screenings on colloidal chitin agar plates, and reconstructing even simpler communities. In addition, bottom-up techniques may include diluting the communities to specifically select the most active chitin degraders and utilizers. These combined approaches hold potential to find optimal blends of bacteria successful at degrading chitin. Recently, DNA-Stable Isotope Probing (DNA-SIP) has been implemented to monitor the incorporation of 13 C labelled chitin by natural microbial communities [ 72 ]. Such an approach holds promise in unveiling chitin degraders, utilizers and scavengers (those not directly acting on chitin or COSs but feeding on metabolic by-products of chitin degraders and utilizers – see e.g., [ 71 ]) in future artificial selection experiments, possibly strengthening cross-feeding hypotheses often raised to explain the co-existence of chitin-transforming microorganisms in natural and artificial settings. As an outlook, efforts are being made in our laboratory to i) isolate the prevailing taxa enriched from the different enriched cultures, ii) test for their ability to degrade chitin and iii) sequence their genomes and search for genes involved in chitin degradation to more specifically determine their chitin degradation and/or utilization capacities. In parallel, metagenomic sequencing of the chitin-degrading consortia is also being performed by our team to investigate the role(s) of each taxon in the consortia and to discover novel chitinolytic enzymes from the marine environment. Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Competing Interests The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding This work was supported by a PhD grant to L. Meunier from the Fonds de la recherche dans l’Industrie et l’Agriculture (FRIA) at the Fonds de la Recherche Scientifique (FRS-FNRS). This work was also supported by the Portuguese Foundation for Science and Technology (FCT), through the research project EXPL/BIA-MIC/0286/2021 and projects UIDB/04565/2020 and UIDP/04565/2020 of iBB and LA/P/0140/2020 of i4HB. TKC is the recipient of an investigator contract (CEECIND/00788/2017) conceded by the FCT. MM acknowledges a doctoral grant (SFRH/BD/151376/2021) from the MIT Portugal program, financed through FCT. Acknowledgments We are grateful to Adela Belackova and the 'Fisheries, Biodiversity and Conservation' team from the Center of Marine Sciences (CCMAR), University of Algarve, for their precious help during sampling. Availability of data and materials The amplicon data (Table S8) are available in the Sequence Read Archives (SRA) under the project accession number PRJNA999598, sample accession numbers SAMN36737297 to SAMN36737311, SAMN36737334 to SAMN36737348, SAMN36743901 to SAMN367433915 and SAMN36744262 to SAMN36744262 to SAMN36744276; run accession numbers from SRR25451171 to SRR25451185, SRR25451141 to SRR25451155, SRR25451652 to SRR25451666 and SRR25451336 to SRR25451350. 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Ecology and exploration of the rare biosphere. Nat Rev Microbiol. 2015;13:217–29. Shade A, Jones SE, Caporaso JG, Handelsman J, Knight R, Fierer N, et al. Conditionally Rare Taxa Disproportionately Contribute to Temporal Changes in Microbial Diversity. mBio. 2014;5. 10.1128/mbio.01371-14 . Sauret C, Séverin T, Vétion G, Guigue C, Goutx M, Pujo-Pay M, et al. Rare biosphere’ bacteria as key phenanthrene degraders in coastal seawaters. Environ Pollut. 2014;194:246–53. Fuentes S, Barra B, Caporaso JG, Seeger M. From Rare to Dominant: a Fine-Tuned Soil Bacterial Bloom during Petroleum Hydrocarbon Bioremediation. Appl Environ Microbiol. 2016;82:888–96. Wang Y, Hatt JK, Tsementzi D, Rodriguez -RLM, Ruiz-Pérez CA, Weigand MR, et al. Quantifying the Importance of the Rare Biosphere for Microbial Community Response to Organic Pollutants in a Freshwater Ecosystem. Appl Environ Microbiol. 2017;83:e03321–16. Silva SG, Paula P, Da Silva JP, Mil-Homens D, Teixeira MC, Fialho AM, et al. Insights into the Antimicrobial Activities and Metabolomes of Aquimarina ( Flavobacteriaceae, Bacteroidetes ) Species from the Rare Marine Biosphere. Mar Drugs. 2022;20:423. Keller-Costa T. Metagenomic insights into the taxonomy, function, and dysbiosis of prokaryotic communities in octocorals. 2021;:21. Ooi MC, Goulden EF, Trotter AJ, Smith GG, Bridle AR. Aquimarina sp. Associated With a Cuticular Disease of Cultured Larval Palinurid and Scyllarid Lobsters. Front Microbiol. 2020;11:573588. Gan Z, Yang J, Tao N, Yu Z, Zhang K-Q. Cloning and expression analysis of a chitinase gene Crchi1 from the mycoparasitic fungus Clonostachys rosea (syn. Gliocladium roseum ). J Microbiol. 2007;45:422–30. Wang S, Fang X, Liang K, Li S, Han S, Zhu T. Cloning, expression and antifungal effect of the recombinant chitinase from Streptomyces sampsonii KJ40. Cienc Rural. 2023;53:e20210663. Svitil AL, Chadhain S, Moore JA, Kirchman DL. Chitin Degradation Proteins Produced by the Marine Bacterium Vibrio harveyi Growing on Different Forms of Chitin. Appl Environ Microbiol. 1997;63:408–13. Laribi-Habchi H, Bouacem K, Allala F, Jabeur F, Selama O, Mechri S et al. Characterization of chitinase from Shewanella inventionis HE3 with bio-insecticidal effect against granary weevil, Sitophilus granarius Linnaeus ( Coleoptera : Curculionidae ). Process Biochemistry. 2020;97:222–33. Techkarnjanaruk S, Goodman AE. Multiple genes involved in chitin degradation from the marine bacterium Pseudoalteromonas sp. strain S91. Microbiology. 1999;145:925–34. Folders J, Algra J, Roelofs MS, van Loon LC, Tommassen J, Bitter W. Characterization of Pseudomonas aeruginosa Chitinase, a Gradually Secreted Protein. J Bacteriol. 2001;183:7044–52. Chen L, Jiang H, Cheng Q, Chen J, Wu G, Kumar A, et al. Enhanced nematicidal potential of the chitinase pachi from Pseudomonas aeruginosa in association with Cry21Aa. Sci Rep. 2015;5:14395. Nedashkovskaya O, Kim S-G, Stenkova A, Kukhlevskiy A, Zhukova N, Mikhailov V. Aquimarina algiphila sp. nov., a chitin degrading bacterium isolated from the red alga Tichocarpus crinitus . Int J Syst Evol MicroBiol. 2018;68. Tsujibo H, Fujimoto K, Kimura Y, Miyamoto K, Imada C, Okami Y et al. Purification and characterization of beta-N-acetylglucosaminidase from Alteromonas sp. strain O-7. Bioscience, biotechnology, and biochemistry. 1995;59:1135–6. Daniels M, Stubbusch AKM, Held NA, Schubert OT, Ackermann M. Effects of interspecies interactions on marine community ecosystem function. preprint. Microbiology; 2022. Daniels M, van Vliet S, Ackermann M. Changes in interactions over ecological time scales influence single-cell growth dynamics in a metabolically coupled marine microbial community. ISME J. 2023;17:406–16. Pontrelli S, Szabo R, Pollak S, Schwartzman J, Ledezma-Tejeida D, Cordero OX, et al. Metabolic cross-feeding structures the assembly of polysaccharide degrading communities. Sci Adv. 2022;8:eabk3076. Martinović T, Mašínová T, López-Mondéjar R, Jansa J, Štursová M, Starke R, et al. Microbial utilization of simple and complex carbon compounds in a temperate forest soil. Soil Biol Biochem. 2022;173:108786. Additional Declarations No competing interests reported. Supplementary Files SupplementaryFileS1revisedv4finalIG.docx SupplementarytablesMeunieretalBMCfinal.xlsx Cite Share Download PDF Status: Published Journal Publication published 25 Nov, 2025 Read the published version in BMC Microbiology → Version 1 posted Editorial decision: Revision requested 07 Feb, 2025 Reviews received at journal 20 Dec, 2024 Reviewers agreed at journal 13 Nov, 2024 Reviewers invited by journal 18 Sep, 2024 Submission checks completed at journal 08 Aug, 2024 First submitted to journal 05 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3456333","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":412750433,"identity":"93473abd-0855-4ec0-a0aa-58402eccb08d","order_by":0,"name":"Laurence Meunier","email":"","orcid":"","institution":"Université Libre de Bruxelles","correspondingAuthor":false,"prefix":"","firstName":"Laurence","middleName":"","lastName":"Meunier","suffix":""},{"id":412750434,"identity":"84d5a94f-9c27-48ea-91c1-b79ad46c5d58","order_by":1,"name":"Tina Keller-Costa","email":"","orcid":"","institution":"University of Lisbon","correspondingAuthor":false,"prefix":"","firstName":"Tina","middleName":"","lastName":"Keller-Costa","suffix":""},{"id":412750435,"identity":"7a4315f7-2110-4c5a-b26e-42c9c2f577c7","order_by":2,"name":"David Cannella","email":"","orcid":"","institution":"Université Libre de Bruxelles","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Cannella","suffix":""},{"id":412750436,"identity":"a6ca8ba8-d6d5-4310-97ef-f843118ed8e7","order_by":3,"name":"Jorge Gonçalves","email":"","orcid":"","institution":"Universidade do Algarve (UALG)","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Gonçalves","suffix":""},{"id":412750437,"identity":"cc997a1c-834a-4909-9a14-df25aaf10c9b","order_by":4,"name":"Etienne Dechamps","email":"","orcid":"","institution":"Université Libre de Bruxelles","correspondingAuthor":false,"prefix":"","firstName":"Etienne","middleName":"","lastName":"Dechamps","suffix":""},{"id":412750438,"identity":"31454d68-a62d-4328-b808-890b09737466","order_by":5,"name":"Matilde Marques","email":"","orcid":"","institution":"University of Lisbon","correspondingAuthor":false,"prefix":"","firstName":"Matilde","middleName":"","lastName":"Marques","suffix":""},{"id":412750439,"identity":"01e089c6-0d02-49ca-af72-a293393c9c60","order_by":6,"name":"Rodrigo Costa","email":"data:image/png;base64,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","orcid":"","institution":"University of Lisbon","correspondingAuthor":true,"prefix":"","firstName":"Rodrigo","middleName":"","lastName":"Costa","suffix":""},{"id":412750440,"identity":"bdecacf3-995a-4496-a244-657a3494565b","order_by":7,"name":"Isabelle F. George","email":"","orcid":"","institution":"Université Libre de Bruxelles","correspondingAuthor":false,"prefix":"","firstName":"Isabelle","middleName":"F.","lastName":"George","suffix":""}],"badges":[],"createdAt":"2023-10-17 07:59:38","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3456333/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3456333/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12866-025-04218-7","type":"published","date":"2025-11-25T15:56:51+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":76631442,"identity":"23c70bd0-b95a-45bd-bf86-92797a2e9303","added_by":"auto","created_at":"2025-02-19 06:42:01","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":1331337,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eExperimental design of the artificial selection process. SEC, Size Exclusion Chromatography. Image created with BioRender.com\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/6fd4d540d7249a7ad84abfbe.jpeg"},{"id":76630342,"identity":"130a7d88-e3bf-4ed0-9803-c8fdaa2baf6d","added_by":"auto","created_at":"2025-02-19 06:34:01","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":263772,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003ePcoA of prokaryotic communities from enrichment cultures performed on a Bray-Curtis distance matrix after Hellinger transformation of the ASV relative abundances. The different colors represent the biotope from which the prokaryotic communities were obtained. PC = preculture, C1 = enrichment culture 1, C2 = enrichment culture 2 and C3 = enrichment culture 3 during the artificial selection experiment. The ellipses were drawn manually.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/4098bee7e66385766e391771.jpg"},{"id":76631715,"identity":"2b298e49-e732-440d-9bf9-645db9d11720","added_by":"auto","created_at":"2025-02-19 06:50:01","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":300007,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelations between parameters of chitin degradation in the enrichment culture C2 of all experiments. A) Correlation between the numbered Average molecular weight of the first region (70.5 - 1,020 KDa)(Mn\u003csub\u003e1\u003c/sub\u003e) of the SEC chromatogram and the chitin weight (mg); B) Correlation between Mn\u003csub\u003e1\u003c/sub\u003e and the polydispersity of the first region of the SEC chromatogram (PDI\u003csub\u003e1\u003c/sub\u003e). R and p values refer respectively to Pearson’s correlation coefficient and associated p-value. The light grey zone indicates a 95% confidence interval. Examples of chromatograms are depicted in Fig. S1.\u003c/p\u003e","description":"","filename":"Fig3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/18b152ed41f61ae50577f01b.jpg"},{"id":76631449,"identity":"0d4d16dc-aafc-41d9-af05-cb973473f92e","added_by":"auto","created_at":"2025-02-19 06:42:02","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":859190,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic composition, alpha diversity and respiratory activity indicators of prokaryotic communities from marine sponges and octocorals during the artificial selection experiments. A) and B) Genus-level taxonomic composition of prokaryotic communities in environmental marine sponge and octocoral samples (ES) and their corresponding enrichment cultures (PC, C1, C2, and C3). In each of the six sub-datasets (one for each experiment), genera whose relative abundance was below 0.03 % were merged into the category “Others”. C) Observed ASV richness and D) corresponding Shannon diversity index of prokaryotic communities from environmental samples and their corresponding enrichment cultures. E) Microbial activity assessments based on MTT assay results (Absorbance at 570 nm). Absorbance values of negative controls were subtracted from the values shown on the Y-axis.\u003c/p\u003e","description":"","filename":"Fig4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/85d0512914275b031ed19e5f.jpg"},{"id":76630358,"identity":"08c58a77-4b68-45e2-aaeb-fe7f09fbc5fd","added_by":"auto","created_at":"2025-02-19 06:34:02","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3077895,"visible":true,"origin":"","legend":"\u003cp\u003eTaxonomic composition, alpha diversity, and bioactivity indicators of prokaryotic communities from seawater and sediments during the artificial selection experiments. A) and B) Genus-level taxonomic composition of prokaryotic communities in environmental sediment and seawater samples (ES) and their corresponding enrichment cultures (PC, C1, C2, and C3). In each of the six sub-datasets (one for each experiment), genera whose relative abundance was below 0.03 % were merged into the category “Others”. C) observed ASV richness and D) corresponding Shannon diversity index of prokaryotic communities from environmental samples and their corresponding enrichment cultures. E) Microbial activity assessments based on MTT assay results (Absorbance at 570 nm). Absorbance values values of negative controls were subtracted from the values shown on the Y-axis.\u003c/p\u003e","description":"","filename":"Fig5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/01926730ff8514afd5c90aae.jpg"},{"id":97178025,"identity":"3af6f9e8-cf72-4eb3-a66a-8091e5dbe660","added_by":"auto","created_at":"2025-12-01 15:59:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7406566,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/a3a4222f-332d-46c1-85a3-c9c72b4f8f07.pdf"},{"id":76630351,"identity":"b31cb15c-61b3-413a-af50-f2df1adf50a6","added_by":"auto","created_at":"2025-02-19 06:34:01","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1412370,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFileS1revisedv4finalIG.docx","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/6942e9c2abbbdc85cdcd49b3.docx"},{"id":76630344,"identity":"cbfd3e33-a9d3-4b9b-a7a1-cac0ee5a19fc","added_by":"auto","created_at":"2025-02-19 06:34:01","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":1507170,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarytablesMeunieretalBMCfinal.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3456333/v1/79966691fbc05cee3a957460.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"An artificial selection procedure enriches for known and suspected chitin degraders from the prokaryotic rare biosphere of multiple marine biotopes","fulltext":[{"header":"1 Introduction","content":"\u003cp\u003eChitin is the most abundant biopolymer in the marine environment, and chitin degradation is a major process dictating the cycling of carbon and nitrogen in the ocean [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Importantly, chitin does not accumulate in the ocean [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e] but undergoes a rapid turnover due to the activity of chitin-degrading microorganisms, leading to the production of small organic molecules such as N-acetylglucosamine (GlcNAc), glucosamine (GlcN), acetate, glucose (Glc) and deacetylated forms of chitin such as chitosan [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These chitin degradation products can be assimilated by bacteria for cell material synthesis or mineralized into CO\u003csub\u003e2\u003c/sub\u003e and NH\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Chitin-degrading marine microorganisms may live attached to chitinous exoskeletons or particulate detritus [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], or in symbiosis with macroeukaryotic hosts such as crustaceans [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], marine sponges [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and octocorals [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Microorganisms that directly act on the chitin polymer through the action of endochitinases or deacetylases are usually referred to as \u0026ldquo;chitin degraders\u0026rdquo;, whereas microorganisms which consume chitin degradation products such as chitooligosaccharides and chitosan, through the action of exo-chitinases and chitosanases are referred to as \u0026ldquo;chitin utilizers\u0026rdquo; or \u0026ldquo;consumers\u0026rdquo; [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Endo- and exochitinases degrade chitin through a chitinolytic pathway, meaning that they hydrolyze the glycosidic bonds between the N-acetylglucosamine units of the chitin polymers (endochitinase) or the chitooligosaccharides (COSs) (exochitinases) [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrently, molecular-based evidence suggests that distinct marine biotopes host taxonomically divergent chitin-degrading communities [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. This indicates that a multitude of chitin degrading enzymes and accessory proteins (e.g., endochitinases, exochitinases, deacetylases, Lytic Polysaccharides MonoOxygenases (LPMOs), chitin-binding modules) with distinct substrate affinities and physical-chemical optima, produced by diverse chitin-degrading bacteria, remain unexplored and unknown. Current knowledge of the chitin degradation potential within symbiotic communities of sessile marine invertebrates is growing, as recent hypotheses have been raised on the roles of canonical symbionts of octocorals (\u003cem\u003eEndozoicomonadaceae\u003c/em\u003e) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and marine sponges (\u003cem\u003eRhodothermales\u003c/em\u003e) [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] in the cycling of chitin in benthic ecosystems. However, despite the chitin catalytic potential existing within marine microbial communities, studies designed to harness the metabolism of diverse chitinolytic marine consortia in the laboratory have seldom been attempted [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Artificial selection (i.e., the making of enrichment cultures from environmental samples) is a powerful technique that allows to select communities efficient at degrading complex compounds such as pollutants or natural polymers like cellulose or chitin [\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. It consists of utilizing a natural prokaryotic community as inoculum in a specific medium (e.g., a medium with chitin as the sole source of carbon and nitrogen). Then, successive transfers to new culture media help to progressively select a microbial community specialized in a particular biochemical process or pathway (e.g., chitin degradation). We posit that artificial selection procedures may increase the discoverability of chitin-degrading enzymes and organisms, holding promise for diverse industrial sectors. Notably, chitin degradation products such as chitosan and chitooligosaccharides (COSs) exhibit potential applications in various fields such as agriculture, water treatment, medicine, textiles, and more [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. For instance, chitinolytic enzymes can be used to create natural fungicides and insecticides by inhibiting fungal and harmful insects' growth, which can replace the chemical alternatives [\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Furthermore, chitin-degrading enzymes can be used to generate COSs and chitosan from chitinous waste produced by the seafood industry. At present, industrial processes for the conversion of chitin into chitosan and COSs rely on the use of high amounts of concentrated acids and strong alkali at high temperature [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Thus, the use of specific enzymes such as chitinases, which act to breakdown the chitin polymer via hydrolysis is more ecofriendly, safe and allows to reduce the molecular weight without altering the chemical structure [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this context, the first aim of this study was to determine whether prokaryotic community structures of a model High Microbial Abundance sponge (\u003cem\u003eSarcotragus spinosulus\u003c/em\u003e) and of a model octocoral (\u003cem\u003eEunicella labiata\u003c/em\u003e) species co-inhabiting the same geographic location (Algarve coast, Portugal) are distinct from each other and from those of their environmental surroundings (seawater and sediments). The second goal of this study was to perform an artificial selection procedure to enrich efficient chitin-degrading consortia from the above-mentioned marine biotopes, to answer the question of whether contrasting biotopes lead to taxonomically distinct chitin-degrading communities in the laboratory. During the artificial selection process, chitin degradation was assessed by measuring the change in molecular weight of the chitin polymer by Size Exclusion Chromatography (SEC) instead of using commercial kits that measure a potential degradation activity on short oligomers. The third objective was to determine whether chitin-degrading microorganisms recruited during the artificial selection procedure correspond to so-far unknown microbial lineages taking part in chitin / chitin-derivative degradation processes, and whether they represent dominant or otherwise low-abundant (\u0026ldquo;rare\u0026rdquo;) organisms in the original communities. This study highlights putative novel chitinolytic bacteria by artificial selection from multiple marine biotopes.\u003c/p\u003e"},{"header":"2 Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e2.1 Sampling\u003c/h2\u003e\n \u003cp\u003e\u003cem\u003eSarcotragus spinosulus\u003c/em\u003e (Schmitt, 1862; Porifera, Demospongiae, Keratosa, Irciniidae) (three biological replicates: SP1, SP2, SP3) and \u003cem\u003eEunicella labiata\u003c/em\u003e (Thomson, 1927; Cnidaria, Anthozoa, Octocorallia, Eunicellidae) (three biological replicates: OC1, OC2, OC3) specimens and their surrounding seawater and sediment (three biological replicates each: SW1, SW2 and SW3 for seawater and SD1, SD2, SD3 for sediment) were collected off the Algarve coast, southern Portugal (\u0026ldquo;Pedra da Greta\u0026rdquo;: Lat. 36\u0026deg; 58\u0026prime;47.2N, Long. 7\u0026deg; 59\u0026prime; 20.8W) at a depth of 18\u0026ndash;19 m (bottom water pH was 8.13, temperature 19\u0026deg;C, and salinity 36.41 ppt) on the 29th of September 2020 by scuba diving. Pieces of marine sponge and branches of octocoral specimens (about 5 g each) were cut with a sterile scalpel and placed individually with surrounding seawater into Ziploc\u0026reg; bags. Surface sediment was sampled with a sterile spoon (\u003cem\u003ec.\u003c/em\u003e 2 g/ replicate) at \u003cem\u003ec.\u003c/em\u003e 1 m distance to the animals and kept in sterile pots. Finally, seawater samples (\u003cem\u003ec.\u003c/em\u003e 2 L/ replicate) were collected \u003cem\u003ec.\u003c/em\u003e 1 m above the animals and stored in sterile bottles. Samples were transported to the laboratory in a cooling box (c. 30 min transport time) and sample processing started immediately upon arrival in the laboratory.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\n \u003ch2\u003e2.2 Sample processing\u003c/h2\u003e\n \u003cp\u003eIn a laminar hood, marine sponges were handled with sterilized tweezers to remove macroscopic epibionts and extracellular endobionts such as mussels, gastropods, worms, and algae. Afterwards, marine sponge specimens were washed with sterile Artificial Seawater (ASW) (ASW: 23.38 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 NaCl, 2.41 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 MgSO\u003csub\u003e4\u003c/sub\u003e\u0026lowast;7H2O, 1.90 gL\u0026thinsp;\u0026minus;\u0026thinsp;1 MgCl\u003csub\u003e2\u003c/sub\u003e\u0026lowast;6H\u003csub\u003e2\u003c/sub\u003eO, 1.11 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 CaCl\u003csub\u003e2\u003c/sub\u003e\u0026lowast;2H\u003csub\u003e2\u003c/sub\u003eO, 0.75 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 KCl and 0.17 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 NaHCO\u003csub\u003e3\u003c/sub\u003e) and cut into small pieces with a sterile scalpel. The octocoral branches were also checked for epibionts (which, if present, were removed), washed with sterile ASW and the tissue was then scraped off the internal gorgonin skeleton with the help of a sterile scalpel and cut into small pieces. Several replicates of 0.25 g of tissue of each marine sponge and octocoral specimen were stored in sterile 2.0 mL microcentrifuge tubes at -80\u0026deg;C until DNA extraction. Seawater samples (c. 500 mL) were filtered through 0.22 \u0026micro;m pore-size nitrocellulose membranes (Millipore, MERCK) with the help of a vacuum pump. Seawater filters and sediment samples (0.25 g/replicate) were stored in sterile 2.0 mL microcentrifuge tubes at -80\u0026deg;C until DNA extraction.\u003c/p\u003e\n \u003cp\u003eMicrobial cell pellets were obtained from marine sponge and octocoral tissue according to the method described by [\u003cspan class=\"CitationRef\"\u003e24\u003c/span\u003e] with minor modifications. Briefly, pieces of marine sponge and octocoral tissue of each specimen (1 g each), prepared as described above, were grinded in 9 mL of sterile Calcium-Magnesium-free-ASW (CMFASW. Composition: 27 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 NaCl, 1 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 NaSO\u003csub\u003e4\u003c/sub\u003e, 0.8 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 KCl and 0.18 g L\u0026thinsp;\u0026minus;\u0026thinsp;1 NaHCO\u003csub\u003e3\u003c/sub\u003e) using a sterile mortar and a pestle. The homogenates were then centrifuged at 4\u0026deg;C at 500 g for 2 min to remove the host-derived tissue (pellet). Thereafter, the supernatant was centrifuged at 4\u0026deg;C at 10,000 g for 15 min to recover the microbial cell pellet. To prepare microbial cell pellets from seawater samples, approximately 1 L of seawater was filtered through 0.22 \u0026micro;m pore size membranes (Millipore, MERCK). The seawater membranes were then cut into small pieces with a sterile scissor, mixed with a lab spoon of sterile 2-mm glass beads and with 50 mL of CMFASW. To prepare microbial cell pellets from sediment samples, approximately 1 g of sediment was mixed with a lab spoon of sterile 2 mm glass beads and with 9 mL of CMFASW. Afterwards, the cell suspensions from seawater and sediment were vortexed twice at max. speed for 30\u0026ndash;60 sec with a 10 min interval to detach the microbial cells from the filters and sediment, respectively. All suspensions were then centrifuged at 4 \u0026ordm;C at 500 g for 2 min to decant glass beads plus seawater filter pieces or sediment particles. Then, the supernatant was centrifuged at 4 \u0026ordm;C at 10,000 g for 15 min to recover the microbial cell pellet. Each cell pellet (seawater, sediment, marine sponge, and octocoral) was resuspended in 830 \u0026micro;L of sterile ASW and transferred into sterile, 2 mL cryo-vials equipped with 150 \u0026micro;L of sterile 100% glycerol and 20 \u0026micro;L of pure, 100% DMSO. These glycerol stocks were stored at -80\u0026deg;C until further use.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\n \u003ch2\u003e2.3 Artificial selection procedure\u003c/h2\u003e\n \u003cp\u003eGlycerol stocks of microbial cell suspensions from the four biotopes (marine sponge, octocoral, sediment and seawater; three biological replicates each) were used as the starting material for artificial selection of microbial communities through successive transfers of enrichment cultures in a chitin-containing culture medium (described below). In total, twelve artificial selection experiments were initiated in this study.\u003c/p\u003e\n \u003cp\u003eThe experimental setup for artificially selecting microbial communities is depicted in Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e. The artificial selection process consisted of one pre-culture (referred to as \u0026ldquo;enrichment culture PC\u0026rdquo;) and three successive cultures (so-called \u0026ldquo;enrichment cultures C1, C2 and C3\u0026rdquo;). Briefly, 100 \u0026micro;L of each glycerol stock was inoculated into 100 mL of pre-culture medium at 20\u0026deg;C and 85 rpm. After 8 days of incubation, 1 mL of this PC was added to 100 mL of enrichment culture medium. After 7 days of incubation, 1 mL of enrichment culture C1 was transferred to 100 mL of the same fresh enrichment culture medium (C2). This step was repeated once more to generate enrichment culture C3. The culture medium for the preparation of the enrichment cultures (C1, C2 and C3) was composed of 100 mL of autoclaved ASW, 0.15 g of KH\u003csub\u003e2\u003c/sub\u003ePO\u003csub\u003e4\u003c/sub\u003e, 1 g of chitin powder extracted from shrimp shells (C7170 from Sigma-Aldrich/MERCK, Germany) and 160 \u0026micro;L of a solution of trace elements (for details, see Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). The same medium was amended with 0.01 g of tryptone in the preparation of the pre-culture medium (PC) to boost the growth of bacteria at the beginning of the process (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cp\u003eAfter each incubation period, the viability of the enrichment cultures was directly assessed using the MTT cell viability assay (see below). In addition, the following samples were collected: i) 5 mL for semi-quantitative assessment of chitin degradation (as described below; only for enrichment cultures C2) followed by qualitative characterization of the chitin degradation products by size exclusion chromatography (SEC; only for enrichment culture C2) after storage of the samples at -80\u0026deg;C, and ii) 5 mL for DNA extraction after centrifugation (10,000 g for 10 min) and storage of the pellet at -20\u0026deg;C.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\n \u003ch2\u003e2.4 MTT viability assays\u003c/h2\u003e\n \u003cp\u003eThis assay was adapted from [\u003cspan class=\"CitationRef\"\u003e25\u003c/span\u003e]. Briefly, 60 \u0026micro;L of MTT (tetrazolium salt; Sigma-Aldrich/Merck, Germany) were added to 200 \u0026micro;L of each enrichment culture (in technical triplicates) in sterile 96-well microplates. The microplates were incubated for 30 min at 37\u0026deg;C. Then, plates were centrifuged at 10,000 g for 7 min and the supernatant was removed. The remaining, reduced formazan cell pellet was dissolved in 200 \u0026micro;L of pure DMSO, the microplates were centrifuged again at 10,000 g for 7 min, and the absorbance at 570 nm (A570) was measured on the supernatant. If the A570 value of a sample was higher than the A570 of the negative control (chitin-based enrichment culture medium incubated under the same conditions as the (pre)cultures but without bacteria), it was interpreted as an indication of bacterial growth.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003e2.5 Chitin degradation assessments\u003c/h2\u003e\n \u003cp\u003eAssessments of chitin degradation, described in detail below, were performed on the enrichment cultures C2 of each artificial selection experiment (in triplicates), since chitin was usually observed to be more effectively degraded in C2 cultures, as indicated by preliminary measurements of the amount of decanted chitin left in culture flasks by the end of each enrichment culture C1, C2 and C3.\u003c/p\u003e\n \u003cp\u003eTwo approaches were used to assess chitin degradation: the measurement of remaining chitin weight in the cultures and size exclusion chromatography (SEC, detailed below). These techniques were complementary since measuring chitin weight constitutes an easy albeit not extremely precise approach (see Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e for standard deviations around triplicate chitin weight measures per sample), being explored in a semi-quantitative fashion in this study, while SEC provides qualitative information on the average size of the chitin polymer in the enrichment cultures (a decrease in polymer size indicates chitin degradation) and the size variations within the cultures (an increase in size variation suggests that the chitin polymer has been degraded into a range of diverse sizes).\u003c/p\u003e\n \u003cp\u003eFirst, to record the weight of chitin remaining in the enrichment cultures at the end of the C2 incubation period (semi-quantitative assessment), the chitin powder in the liquid culture (5 mL) was first centrifuged at 2,000 g for 5 min and the pellet washed twice with MilliQ water. The chitin pellet was then dried at 70\u0026deg;C in heating blocks (DRB200; Hach, USA) until reaching a constant weight and weighted. The chitin weight loss for each enrichment culture C2 was calculated by subtracting the remaining chitin weight from the initial chitin mass, dividing by the initial mass, and then multiplying by 100.\u003c/p\u003e\n \u003cp\u003eSecond, for a detailed assessment of chitin degradation dynamics, SEC was used to determine the molecular mass parameters of the chitin polymers: (i) numbered average molecular weight (Mn), defined as total weight of polymer divided by the total number of molecules; (ii) weight average molecular weight (Mw), which depends on the number of molecules present and on the weight of each molecule; and (iii) polydispersity (PDI), defined as the ratio of the weight average molecular weight to the number average molecular weight, giving a measure of the distribution of the molecular weight within a sample [\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e], with three technical replicates conducted for each sample. The molecular mass parameters of the chitin polymers were also determined for the negative control (C-; in triplicate). The SEC protocol was applied to dry chitin pellets obtained from 5 mL of the C2 enrichment cultures, and is described in detail in Supplementary File S1, Methodology SM.1.\u003c/p\u003e\n \u003cp\u003eThe polymeric parameters (reported herein as Mn\u003csub\u003e1\u003c/sub\u003e, Mw\u003csub\u003e1\u003c/sub\u003e, and PDI\u003csub\u003e1\u003c/sub\u003e) were calculated from the signals detected in time slices within a significant region of the whole chromatogram, hereafter termed \u0026ldquo;region 1\u0026rdquo;, spanning 70.5 KDa \u0026ndash; 1,020 KDa in molecular weight and thus excluding small sized oligomers (Methodology SM.1, Fig. \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e). For \u0026ldquo;region 1\u0026rdquo; of the chromatograms, the numbered average molecular weight Mn\u003csub\u003e1\u003c/sub\u003e was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equa\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equa\" name=\"EquationSource\"\u003e$$\\:Mn=\\:\\frac{(\\sum\\:Ni*Mi)}{\\sum\\:Ni}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eWhere \u003cem\u003ei\u003c/em\u003e is a slice (1.666 x 10\u003csup\u003e\u0026minus;\u0026thinsp;3\u003c/sup\u003e min) of the region, \u003cem\u003eMi\u003c/em\u003e is the molecular weight and \u003cem\u003eNi\u003c/em\u003e is the intensity of the signal.\u003c/p\u003e\n \u003cp\u003eMw, the weight average molecular weight, was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equb\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equb\" name=\"EquationSource\"\u003e$$\\:Mw=\\:\\frac{(\\sum\\:Ni*{Mi}^{2})}{\\sum\\:Ni*Mi}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003ewhere \u003cem\u003ei\u003c/em\u003e is a slice of the region, \u003cem\u003eMi\u003c/em\u003e is the molecular weight and \u003cem\u003eNi\u003c/em\u003e is the intensity of the signal.\u003c/p\u003e\n \u003cp\u003ePolydispersity PDI is a measure of the broadness of the peak and was calculated as follows:\u003c/p\u003e\n \u003cdiv id=\"Equc\" class=\"Equation\"\u003e\n \u003cdiv class=\"mathdisplay\" id=\"FileID_Equc\" name=\"EquationSource\"\u003e$$\\:PDI=\\frac{Mn}{Mw}$$\u003c/div\u003e\n \u003c/div\u003e\n \u003cp\u003eCorrelation analyses were thereafter performed to assess the strength of the relationship between chitin degradation parameters assessed in this study. Specifically, Pearson correlations were computed between the estimated Mn\u003csub\u003e1\u003c/sub\u003e values obtained for all C2 enrichment cultures and the corresponding values recorded for weight of remaining chitin in the cultures and PDI\u003csub\u003e1\u003c/sub\u003e using the \u003cem\u003eggscatter\u003c/em\u003e function (\u003cem\u003ecor.method\u003c/em\u003e= \u0026ldquo;pearson\u0026rdquo;) from the ggpubr package (v 0.5.0;[\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e]) in R. These analyses allowed us to assess hypotheses of a positive correlation between Mn\u003csub\u003e1\u003c/sub\u003e and remaining chitin weight values (the higher the chitin weight remaining in the tube, the higher the molecular mass of the chitin polymer) and a negative correlation between PDI\u003csub\u003e1\u003c/sub\u003e and Mn\u003csub\u003e1\u003c/sub\u003e values (the higher the polydispersity of the chitin peaks, the lower the estimates of chitin molecular weight, suggesting that the large chitin polymer is being broken down into smaller oligos of different sizes).\u003c/p\u003e\n \u003cp\u003eFinally, estimates of chitin weight loss and Mn\u003csub\u003e1\u003c/sub\u003e calculated as described above were integrated to classify the chitin degradation efficiency of samples analyzed in this study as \u0026ldquo;high\u0026rdquo; (\u0026gt;\u0026thinsp;45% weight loss, Mn\u003csub\u003e1\u003c/sub\u003e = [6.93\u0026ndash;7.37\u0026thinsp;+\u0026thinsp;05], \u0026ldquo;good\u0026rdquo; (25\u0026ndash;45% weight loss, Mn\u003csub\u003e1\u003c/sub\u003e = [7.65\u0026thinsp;+\u0026thinsp;05]), \u0026ldquo;moderate\u0026rdquo; (10\u0026ndash;25%, Mn\u003csub\u003e1\u003c/sub\u003e = [7.36* \u0026minus;\u0026thinsp;8.56\u0026thinsp;+\u0026thinsp;05]) and \u0026ldquo;low\u0026rdquo; (\u0026lt;\u0026thinsp;10%, Mn\u003csub\u003e1\u003c/sub\u003e = [8.69\u0026thinsp;+\u0026thinsp;05]) (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSimplified categorization of enrichment cultures into chitin degradation efficiencies based on chitin weight loss.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eChitin degradation efficiency\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eEnrichment cultures\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eWeight loss (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMn1 range (Da)\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSW3, SD1, SD3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6.93\u0026ndash;7.37\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGood\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSD2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e25\u0026ndash;45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.65\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSP1, SP2, SP3, SW1, OC1, OC2, OC3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10\u0026ndash;25%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7.36* \u0026minus;\u0026thinsp;8.56\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSW2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;10%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8.69\u0026thinsp;+\u0026thinsp;05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cem\u003e* low Mn\u003c/em\u003e \u003csub\u003e\u0026nbsp;\u003cem\u003e1\u003c/em\u003e\u0026nbsp;\u003c/sub\u003e \u003cem\u003evalues, suggesting high chitin degradation efficiency, were estimated for octocoral samples 2 and 3, which presented, however, moderate estimates of chitin weight loss according to the chitin weight measurement methodology employed in this study.\u003c/em\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003e2.6 Total community DNA extraction and 16S rRNA gene sequencing\u003c/h2\u003e\n \u003cdiv class=\"BlockQuote\"\u003e\n \u003cp\u003eDNA was directly extracted from 0.25 g of the inner marine sponge tissue, octocoral tissue, sediment and from the seawater filters for the environmental (\u003cem\u003ein situ\u003c/em\u003e) samples; and from the microbial cell pellets recovered from 5 mL of each enrichment culture (PC, C1, C2 and C3). DNA was extracted using the \u0026ldquo;DNeasy PowerSoil Pro kit\u0026rdquo; from Qiagen (ID: 47014) according to the manufacturer\u0026rsquo;s protocol. The seawater filters were cut into small pieces using sterile scissors prior to DNA extraction. The DNA quantity (ng/\u0026micro;L) and quality (A260/A280 and A260/A230) was estimated with a NanoDrop ND 2000 UV-VIS spectrophotometer (Thermo Fisher Scientific, Waltham, US) and DNA samples were kept at -20\u0026deg;C until further analyses. 16S rRNA gene amplification and sequencing from DNA samples were carried out at StarSeq (Mainz, Germany) using Illumina MiSeq sequencing. The V4 region of the 16S rRNA gene was sequenced following a 2x300 paired-end approach using the primers 515F (5\u0026rsquo;-GTG YCA GCM GCC GCG GTAA-3\u0026rsquo;) and 806 Rb (5\u0026rsquo;-GGA CTA CNV GGG TWT CTA AT-3\u0026rsquo;) [\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e]. An average of 100,000 paired-end sequences was generated per sample. The library of reads was demultiplexed by StarSeq.\u003c/p\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\n \u003ch2\u003e2.7 Processing of the 16S rRNA gene sequencing data\u003c/h2\u003e\n \u003cp\u003eAll 16S rRNA gene fragment sequences were processed together using the denoising-based pipeline DADA2 (Divisive Amplicon Denoising Algorithm) v.1.8 (in R; [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e]). First, the \u003cem\u003eFilterandTrim\u003c/em\u003e function from DADA2 was used to remove the reads with Ns (\u003cem\u003emaxN\u0026thinsp;=\u0026thinsp;0\u003c/em\u003e) using the following settings: trim the end of the forward and reverse reads at a specific base pair position where the quality of the majority of reads dropped under Q\u0026thinsp;=\u0026thinsp;30 (\u003cem\u003etruncLen\u003c/em\u003e\u0026thinsp;=\u0026thinsp;c(240,150)), filter out the reads belonging to the PhiX bacteriophage (\u003cem\u003erm.phix\u0026thinsp;=\u0026thinsp;TRUE\u003c/em\u003e; [\u003cspan class=\"CitationRef\"\u003e31\u003c/span\u003e], select reads with high number of errors (\u003cem\u003emaxEE\u0026thinsp;=\u0026thinsp;2\u003c/em\u003e) and truncate those with high levels of error at the earliest occurrence of a quality score that is equal to or lower than 2 (truncQ\u0026thinsp;=\u0026thinsp;2; the value 2 is utilized by Illumina as a read end quality indicator). After combining all identical sequence reads into \u0026lsquo;\u0026lsquo;unique sequences\u0026rdquo; (each associated with the number of reads of each sequence), the DADA2 algorithm inferred Amplicon Sequence Variants (ASVs). Paired-end sequences were merged (using the \u003cem\u003emergeSequenceTables()\u003c/em\u003e function from DADA2) and chimeric ASVs were removed (using the DADA2 function \u003cem\u003eremoveBimeraDenovo()\u003c/em\u003e function) from the ASVs table. Taxonomy (Kingdom, Phylum, Class, Order, Family and Genus) of each ASV was then assigned using the SILVA database version 138.1 [\u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e\n \u003cp\u003eThe ASVs versus samples and taxonomy profile tables were then imported into R as a phyloseq object using the phyloseq package (v1.38.0; [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]) to perform diversity and taxonomic composition analyses. The dataset was filtered using the function \u003cem\u003esubset_taxa\u003c/em\u003e from the phyloseq R (v1.38.0;[\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]) package to eliminate mitochondria, chloroplast and eukaryote sequences. The final dataset consisted of 60 samples (all sample types included) thoroughly profiled via 16S rRNA gene sequencing. A total of 5,685,383 filtered reads were generated and 5,389 bacterial and 284 archaeal ASVs were found.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\n \u003ch2\u003e2.8 Analysis of 16S rRNA gene fragments\u003c/h2\u003e\n \u003cp\u003eData wrangling and generation of graphics were performed using the R packages phyloseq (v1.38.0; [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e], dplyr (v1.8.6, [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e] and ggplot2 (v 3.4.0; [\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]) for a thorough analysis of the abundance distributions of 16S rRNA gene ASVs across all samples. Briefly, the analytical approach employed in this study involved the generation of stacked bar charts to depict the taxonomic composition of prokaryotic communities of the environmental samples and enrichment cultures at phylum, class and ASV levels, along with assessments of ASV alpha and beta-diversity for all samples and sample groups.\u003c/p\u003e\n \u003cp\u003eAlpha-diversity analyses consisted of documenting observed ASV richness and estimating the Shannon-Wiener diversity index for all samples. Statistical differences in alpha diversity metrics among sample groups were tested using custom analysis of variance (ANOVA) approaches coupled to post-hoc tests depending on the features of each sample group (for details, see Methodology SM.3).\u003c/p\u003e\n \u003cp\u003eTwo beta diversity analyses were performed in this study: i) one to determine whether differences in prokaryotic community structure occurred among the environmental samples of each biotope (seawater, sediment, marine sponge and octocoral) and ii) one to determine whether such differences occurred between the enrichment cultures derived from each biotope and from each biotope replicate. For each analysis, the ASV data were first Hellinger-transformed (square root of ASV relative abundances). Then, a Bray-Curtis similarity matrix was calculated using the phyloseq package from R (v1.38.0; [\u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]). A Principal Coordinates Analysis (PCoA) was generated for each analysis to ordinate the samples based on the Bray-Curtis matrix. Ordination diagrams were drawn using the ggplot2 package (v 3.4.0;[\u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]) in R.\u003c/p\u003e\n \u003cp\u003eTo check for significant differences in prokaryotic community structure between environmental samples and/or enrichments cultures, a Permutational Analysis of Variance (PERMANOVA) [\u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e] or a Welch MANOVA [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e] was performed depending on the homogeneity of variance between groups of samples. For more details on the methodology employed, please see Methodology SM.4.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\n \u003ch2\u003e2.9 Genome-wide inspection of chitin degradation and utilization features among artificially-enriched and poorly-studied bacterial genera\u003c/h2\u003e\n \u003cp\u003eWe examined chitin degradation and utilization features among genomes of bacterial genera observed to dominate enrichment cultures reported in this study but correspond to so-far poorly known or unknown taxa involved in the metabolism of chitin and its derivatives. Our approach consisted of thorough protein family (Pfam) annotation of all genomes available on DOE JGI\u0026rsquo;s Integrated Microbial Genomes \u0026amp; Microbiomes (IMG/M) data management system v.7 [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e] for the bacterial taxa under inspection. Specifically, we scanned 102 genomes from ten artificially-selected genera (see Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e for details) for the presence of 15 Pfam categories representing protein domains involved in hydrolysis of the large chitin polymer (endo-chitinases of GH families 18 and 19\u0026mdash;EC 3.2.1.14, chitin-binding proteins), hydrolysis of chitin non-reducing ends (exo-chitinases, EC 3.2.1.52), chitin deacetylation (polysaccharide deacetylases), and N-acetylglucosamine binding and utilization. The precise Pfam categories used in our \u003cem\u003ein silico\u003c/em\u003e prospection for chitin degradation and utilization features are presented in Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3 Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Prokaryotic community structure in environmental samples\u003c/h2\u003e \u003cp\u003eThe 16S rRNA gene sequencing approach and statistical analyses employed in this study revealed that the here examined biotopes (\u003cem\u003eS. Spinosulus\u003c/em\u003e, \u003cem\u003eE. labiata\u003c/em\u003e, seawater and sediment) displayed different prokaryotic taxonomic profiles from one another at the phylum, class, and ASV levels (Figs. S2 and S3). Congruent with earlier microbiome surveys of \u003cem\u003eS. spinosulus\u003c/em\u003e and \u003cem\u003eE. labiata\u003c/em\u003e specimens from the North Atlantic [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], here we observed that these hosts harbour distinct prokaryotic consortia in comparison with those of their environmental vicinities (seawater and sediments). In addition, in this study we found that the prokaryotic communities associated with \u003cem\u003eS. spinosulus\u003c/em\u003e and \u003cem\u003eE. labiata\u003c/em\u003e were significantly different from each other in terms of structure and taxonomic composition (Figs. S2 and S3). Although all biotopes were dominated by the phyla \u003cem\u003ePseudomonadota\u003c/em\u003e and \u003cem\u003eBacteroidota\u003c/em\u003e, the relative abundance of these phyla changed considerably across biotopes. The same trend was observed for the two most dominant \u003cem\u003ePseudomonadota\u003c/em\u003e classes, \u003cem\u003eAlphaproteobacteria\u003c/em\u003e and \u003cem\u003eGammaproteobacteria\u003c/em\u003e, which presented distinct relative abundances across all biotopes. At the ASV level, the prokaryotic communities of the four biotopes were clearly unique and contrasting, thus providing support to the original motivation of this study. Table S3 provides the abundance distributions of all ASVs (n\u0026thinsp;=\u0026thinsp;5,673) detected across all environmental and enrichment culture samples analyzed in this study (n\u0026thinsp;=\u0026thinsp;60).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Artificial selection experiments\u003c/h2\u003e \u003cdiv id=\"Sec15\" class=\"Section3\"\u003e \u003ch2\u003e3.2.1 Enrichment cultures develop differentially according to their biotope of origin\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMultivariate analysis of all enrichment cultures showed a clear separation of the cultures according to their source biotope (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Moreover, within each biotope, we observed that enrichment cultures also formed distinguishable clusters according to the replicate experiment (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The separation of all enrichment cultures according to the source biotope (marine sponge, octocoral, seawater, and sediment) was statistically confirmed by a Welch MANOVA test (p-value\u0026thinsp;=\u0026thinsp;0.001; pairwise adonis p-value\u0026thinsp;=\u0026thinsp;0.006 for all pairs of biotopes). Furthermore, separate clustering of enrichment cultures (PC, C1, C2 and C3) derived from the same biotope but from different replicate experiments was confirmed by a PERMANOVA test (p-value\u0026thinsp;=\u0026thinsp;0.001; pairwise adonis p-value = [0.018\u0026ndash;0.042] for each pair of replicates). Moreover, the dispersion among the enrichment cultures PC, C1, C2 and C3 was higher than in their respective environmental samples (see PERMDISP values; Table S4) with one exception (for octocorals, PCs were less dispersed than the environmental samples).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section3\"\u003e \u003ch2\u003e3.2.2 Assessments of chitin polymer molecular weight suggests efficient chitin degradation in some cultures\u003c/h2\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe Mn\u003csub\u003e1\u003c/sub\u003e values of all C2 enrichment cultures, corresponding to the average size of the chitin polymer in these samples, were lower than the Mn\u003csub\u003e1\u003c/sub\u003e value of the negative control, which consisted of chitin medium alone and was estimated at 887 KDa (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Tables S2, S5). This indicates that chitin degradation occurred in all enrichment cultures. However, we observed that estimated Mn\u003csub\u003e1\u003c/sub\u003e values ranged from 693 KDa in sample SD1 to 869 KDa in sample SW2, being, overall, positively correlated with chitin weight measures (the lower the Mn\u003csub\u003e1\u003c/sub\u003e estimate, the lower the weight of the remaining chitin) and negatively correlated with polydispersity (the lower the Mn\u003csub\u003e1\u003c/sub\u003e estimate, the higher the polydispersity) (Figs.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB, Table S5). In summary, the communities that exhibited low chitin weight usually broke down large chitin polymers into smaller molecules of a more diverse size range, resulting in a decrease in average size (Mn\u003csub\u003e1\u003c/sub\u003e) and an increase in size variation (PDI\u003csub\u003e1\u003c/sub\u003e) of chitin.\u003c/p\u003e \u003cp\u003eThe trends above prompted us to establish a semi-quantitative rank of \u0026ldquo;chitin degradation efficiencies\u0026rdquo; based on the integration of chitin weight measures and Mn\u003csub\u003e1\u003c/sub\u003e estimates (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). According to this scheme, we classified enrichment cultures SD1, SD3 and SW3 as \u0026ldquo;highly efficient\u0026rdquo; at degrading chitin, enrichment culture SD2 as \u0026ldquo;good\u0026rdquo;, cultures SP1-SP3, OC1-OC3, and SW1 as \u0026ldquo;moderate\u0026rdquo;, and culture SW2 as \u0026ldquo;low efficient\u0026rdquo; (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). It is important to note that the dynamics of chitin degradation across all enrichment cultures could not be fully depicted by the use of one single estimate or index alone. For instance, in spite of the correlations noted above, enrichment cultures OC2 and OC3 presented low Mn\u003csub\u003e1\u003c/sub\u003e estimates, equivalent to that of culture SD3 (a \u0026ldquo;highly efficient\u0026rdquo; chitin degrading one) while presenting chitin weight loss of c. 25%, in the range of several \u0026ldquo;moderately efficient\u0026rdquo; consortia, being thus classified as \u0026ldquo;moderate\u0026rdquo; according to our conservative scheme (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This exemplifies that chitin weight measures alone, for instance, do not fully portray the chitin degradation dynamics in the samples. The assessment of polymeric parameters via SEC holds potential to become an analytical aid in future studies of chitin degradation.\u003c/p\u003e \u003cp\u003e \u003cb\u003e3.2.3 Sharp taxonomy shifts between environmental samples and enrichment cultures were marked by the selection of potentially novel chitin-degrading taxa\u003c/b\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigures \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e display genus-level taxonomic composition, ASV richness and diversity, and activity indicators of enrichment cultures derived from host-associated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, A-E) and free-living (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, A-E) biotopes. The repeated measure ANOVA tests performed separately on each biotope revealed significant differences in alpha-diversity measures, marked by a decrease in observed ASV richness and Shannon diversity indices, between the environmental samples and their corresponding enrichment cultures (p-value = [7.44 e-10\u0026ndash;0.000122] for all samples from every biotope except for one octocoral sample (replicate #1). Post-hoc Tukey tests revealed significant differences in alpha-diversity only between the environmental samples and the PC, C1, C2 and C3 (p-value = [0.00293\u0026ndash;3.44e-11]), again for every sample within each biotope except for octocoral replicate sample #1. In contrast, ASV richness and Shannon index did not change significantly further on in the selection process for each biotope, neither between PC and C1, nor between C1 and C2 or between C2 and C3 cultures (Tukey tests p-values = [0.396-1] for observed ASV richness and Tukey tests p-values = [0.479-1] for Shannon index). Furthermore, many of the dominant taxa in the environmental samples were not abundant (\u0026lt;\u0026thinsp;0.03%) or even undetectable in the enrichment cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B). Conversely, dominant taxa in the enrichment cultures were poorly represented (\u0026lt;\u0026thinsp;0.1%) or absent in their corresponding environmental samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, B; Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, B; Table S6).\u003c/p\u003e \u003cp\u003eRespiratory activity (low to high) was recorded for all samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eE, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eE, Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). \u003cem\u003eVibrio\u003c/em\u003e ASV1 was consistently enriched in the cultures from all biotopes (Table S3). \u003cem\u003ePsychromonas\u003c/em\u003e ASV26 was enriched in all cultures for which chitin degradation efficiency was classified as \u0026ldquo;good\u0026rdquo; or \u0026ldquo;high\u0026rdquo; (SD1, SD2, SD3, SW3) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, Table S3), and a negative correlation was observed between the relative abundance of ASV26 and remaining chitin weight (Fig. S4). In all sediment cultures, \u003cem\u003eVibrio\u003c/em\u003e ASV13 was enriched. The enrichment cultures from sediment samples SD1 and SD3 were further dominated by \u003cem\u003eHalodesulfovibrio\u003c/em\u003e ASV6, \u003cem\u003eAmphritea\u003c/em\u003e ASV43, \u003cem\u003eProfundimonas\u003c/em\u003e ASV60, \u003cem\u003eFusibacter\u003c/em\u003e ASV113 (in SD1) and ASV140 (in SD3), and \u003cem\u003ePseudovibrio\u003c/em\u003e ASV9. Unclassified \u003cem\u003eRhodobacteraceae\u003c/em\u003e (\u003cem\u003eAlphaproteobacteria\u003c/em\u003e) ASV91 and \u003cem\u003ePseudophaeobacter\u003c/em\u003e ASV27 were also enriched in SD2 enrichment cultures; \u003cem\u003eAlteromonas\u003c/em\u003e ASV29 was enriched in SD3- and \u003cem\u003ePsychrobium\u003c/em\u003e ASV72 in SD1- enrichment cultures (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA, Table S3).\u003c/p\u003e \u003cp\u003eRegarding the enrichment cultures from seawater SW3, perceived as highly efficient at degrading chitin according to our classification scheme (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e), C1, C2 and C3 were strongly dominated by \u003cem\u003ePoseidonibacter\u003c/em\u003e ASV11. Of note, ASV11 was not enriched in the cultures from the two other seawater samples (SW1 and SW2, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB) where chitin degradation was perceived as \u0026ldquo;moderate\u0026rdquo; or \u0026ldquo;low\u0026rdquo; (Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e). Other dominant taxa in SW3 enrichment cultures were \u003cem\u003eVibrio\u003c/em\u003e ASV17, \u003cem\u003eHalodesulfovibrio\u003c/em\u003e ASV6 and \u003cem\u003eMarinobacterium\u003c/em\u003e ASV65. \u003cem\u003eHalarcobacter\u003c/em\u003e ASV76 was abundant in the enrichment culture C2 of SW3. In SW1- and SW2- enrichment cultures, other taxa were enriched such as \u003cem\u003ePseudomonas\u003c/em\u003e ASV64, \u003cem\u003eShewanella\u003c/em\u003e ASV14 and \u003cem\u003eAlteromonas\u003c/em\u003e ASV29. In the SW1 final enrichment culture, \u003cem\u003eVibrio\u003c/em\u003e ASV40 was also highly enriched and in SW2 enrichment cultures, \u003cem\u003ePseudoalteromonas\u003c/em\u003e ASV10 was highly enriched (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). All enriched communities from the marine sponge samples were dominated by \u003cem\u003ePseudophaeobacter\u003c/em\u003e ASV27, \u003cem\u003eVibrio\u003c/em\u003e ASV1 (a dominant ASV in sediment and seawater cultures as well) and ASV13, and by \u003cem\u003ePseudovibrio\u003c/em\u003e ASV9 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA, Table S3). Enrichment cultures of marine sponge samples SP1 and SP2 were also dominated by \u003cem\u003eShewanella\u003c/em\u003e ASV45 (in SP1) and ASV15 (in SP2) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). SP2-derived cultures showed high abundance of \u003cem\u003eVibrio\u003c/em\u003e ASV17, and SP3-derived cultures of \u003cem\u003eEnterovibrio\u003c/em\u003e ASV16 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Finally, the octocoral-derived enrichment cultures were largely dominated by \u003cem\u003eAquimarina\u003c/em\u003e ASV12 (sample OC2) and by \u003cem\u003eVibrio\u003c/em\u003e ASV1 (sample OC3), while OC1-enriched cultures were co-dominated by many taxa such as \u003cem\u003eShewanella\u003c/em\u003e ASV14, \u003cem\u003ePseudoalteromonas\u003c/em\u003e ASV10, \u003cem\u003eFlavobacteriaceae\u003c/em\u003e ASV21 and \u003cem\u003eMotilimonas\u003c/em\u003e ASV3 (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.3. Genome prospection reveals putative novel chitin degraders and consumers in artificially selected consortia\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePfam-based annotation overview of protein domains involved in chitin degradation found in publicly available genomes of putative novel chitin-degrading/-utilizing genera identified in this study\u003csup\u003e1\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e# genomes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eEndo\u003c/p\u003e \u003cp\u003echitinases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eExo\u003c/p\u003e \u003cp\u003echitinases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCBP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePolysaccharide deacetylases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eN-acetyl\u003c/p\u003e \u003cp\u003eglucosamine\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eSuggested role/coding potential\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGammaproteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMotilimonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 [\u003cspan additionalcitationids=\"CR18 CR19 CR20 CR21 CR22 CR23\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4 [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via hydrolysis and deacetylation; COSs degrader via hydrolysis, GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlphaproteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePseudophaeobacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via deacetylation, GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacteroidia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eReichenbachiella\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 [0\u0026ndash;5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 [0\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via hydrolysis and deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature), putative GlcNAc consumer\u0026nbsp;(strain-dependent feature)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eDesulfovibrionia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eHalodesulfovibrio\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 [0\u0026ndash;1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 [0\u0026ndash;1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2 [0\u0026ndash;2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e5 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePutative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacteroidia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAureivirga\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via hydrolysis and deacetylation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlphaproteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEpibacterium\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 [0\u0026ndash;2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e4 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via deacetylation; putative COSs consumer (strain-dependent feature); GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eGammaproteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePsychromonas\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 [0\u0026ndash;18]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 [0\u0026ndash;10]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5 [0\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18 [\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e16 [0\u0026ndash;2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePutative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); putative GlcNAc consumer\u0026nbsp;(strain-dependent feature)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eBacteroidia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMuricauda\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 [0\u0026ndash;4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 [0\u0026ndash;13]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e14 [0\u0026ndash;2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 [\u003cspan additionalcitationids=\"CR3 CR4 CR5\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePutative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCampylobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003ePoseidonibacter\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8 [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6 [0\u0026ndash;1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eChitin degrader via deacetylation; putative GlcNAc consumer (strain-dependent feature)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAlphaproteobacteria\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eThalassotalea\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 [0\u0026ndash;3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19 [0\u0026ndash;14]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e26 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e26 [\u003cspan additionalcitationids=\"CR4 CR5 CR6 CR7 CR8\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePutative chitin degrader via hydrolysis (strain-dependent feature); chitin degrader via deacetylation; putative COSs degrader via hydrolysis (strain-dependent feature); GlcNAc consumer\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003csup\u003e \u003cem\u003e1\u003c/em\u003e \u003c/sup\u003e \u003cem\u003ePfam annotations were performed on the IMG/M v.7 system using all genomes available for the examined taxa. Values in cells show the number of genomes within each genus for which a positive score was recorded for the screened function. Values in brackets display the range of variation in the number of protein domains found on the genomes of each genus which scored positive for that function. Pfam categories used to screen for chitin degradation-utilization features across genomes were as follows. Endochitinases: PF00182 (chitinase class I, GH19), PF00704 (GH18), PF08329 (chitinase A N-terminal domain), and PF06483 (chitinase C). Exochitinases: PF03174 and PF13290 (Chitobiase/beta-hexosaminidase C-terminal domains), PF03173 (Chitobiase/beta-hexosaminidase N-terminal domain), PF02838 (GH20, domain 2), PF00728 (GH20, catalytic domain), and PF14845 (beta-acetyl hexosaminidase like). Polysaccharide deacetylases: PF01522 (Polysaccharide deacetylase), PF04748 (divergent polysaccharide deacetylase)]. Chitin-binding proteins (CBP): PF01607 (Chitin binding Peritrophin-A domain, family 14), PF02839 (Carbohydrate-binding module family 5/12). N-acetylglucosamine utilization: PF01182 (Glucosamine-6-phosphate isomerases/6-phosphogluconolactonase)].\u003c/em\u003e Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e \u003cem\u003esynthesises Pfam annotation results obtained for 102 genomes across the ten genera examined (for details, see Tables S7A,B). Table S7A presents the full taxonomic string of each genus.\u003c/em\u003e\u003c/p\u003e \u003cp\u003eWe performed a thorough analysis of chitin degradation and chitin-derivative utilization features across 102 publicly available bacterial genomes belonging to the genera \u003cem\u003eAureivirga\u003c/em\u003e, \u003cem\u003eEpibacterium\u003c/em\u003e, \u003cem\u003eHalodesulfovibrio\u003c/em\u003e, \u003cem\u003eMuricauda\u003c/em\u003e, \u003cem\u003eMotilimonas\u003c/em\u003e, \u003cem\u003ePseudophaeobacter\u003c/em\u003e, \u003cem\u003ePoseidonibacter\u003c/em\u003e, \u003cem\u003ePsychromonas\u003c/em\u003e, \u003cem\u003eReichenbachiella\u003c/em\u003e and \u003cem\u003eThalassotalea\u003c/em\u003e (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e and S7A,B). These genera were targeted because they were detected as dominant taxa in the experiments in which chitin was efficiently degraded (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) whereas, to the best of our knowledge, current evidence for their roles as chitin degraders or consumers is either non-existent or scarce. Sequences coding for endochitinase domains were detected in the genome of all \u003cem\u003eMotilimonas, Reichenbachiella\u003c/em\u003e and \u003cem\u003eAureivirga\u003c/em\u003e strains surveyed, and some \u003cem\u003eHalodesulfovibrio\u003c/em\u003e, \u003cem\u003ePsychromonas, Muricauda\u003c/em\u003e, and \u003cem\u003eThalassotalea\u003c/em\u003e strains (for details, see Table S7B). Exochitinase protein domains were detected in the genome of all \u003cem\u003eMotilimonas\u003c/em\u003e strains and some \u003cem\u003eReichenbachiella, Epibacterium\u003c/em\u003e, \u003cem\u003ePsychromonas\u003c/em\u003e, \u003cem\u003eMuricauda\u003c/em\u003e and \u003cem\u003eThalassotalea\u003c/em\u003e strains. Sequences coding for polysaccharide deacetylase and N-acetylglucosamine utilization domains were detected in the genomes of the great majority of strains belonging to the different genera. Finally, sequences coding for chitin-binding protein domains were detected in the genomes of all \u003cem\u003eMotilimonas\u003c/em\u003e strains and of some \u003cem\u003eHalodesulfovibrio\u003c/em\u003e and \u003cem\u003ePsychromonas\u003c/em\u003e strains. Compared to the other genomes, those of \u003cem\u003eMotilimonas\u003c/em\u003e presented a considerably higher number of targeted sequences: 17 to 24 sequences per genome coding for domains of endochitinases, 3 to 4 for exochitinases, 5 to 11 for CBP and 3 to 4 for polysaccharide deacetylases (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). \u003cem\u003eMotilimonas\u003c/em\u003e was actually the single genus for which a positive score was recorded for all the searched functions across all genomes surveyed (Table S7B). Interestingly, genomes in the genera \u003cem\u003ePseudophaeobacter\u003c/em\u003e (found to be enriched in samples SD2 and SP2) and \u003cem\u003ePoseidonibacter\u003c/em\u003e (sharply enriched in sample SW3, classified as \u0026ldquo;highly efficient\u0026rdquo; for chitin degradation) did not possess any endochitinase nor exochitinase coding sequences, but possessed polysaccharide deacetylation and N-acetyl-glucosamine utilization features. Based on these analyses, we proposed putative roles in chitin/chitin-derivative degradation and utilization for the ten bacterial genera examined more thoroughly in this study (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"4 Discussion","content":"\u003cp\u003eThis study employs artificial selection to enrich chitin-degrading microbial consortia from contrasting marine biotopes. Using metagenomics approaches, Raimundo \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] found that marine sponges, octocorals, sediments and seawater harbour distinct chitin-degrading communities both in terms of taxonomy and the prevailing metabolic pathways involved in chitin metabolism. Here, we combine taxonomy assignments by 16S rRNA gene sequencing with estimates of chitin degradation to cross-compare the structure and potential metabolism of chitin-degrading consortia selectively enriched from these biotopes in the laboratory. We perform comprehensive alpha and beta-diversity analyses of the source environmental samples from each biotope and their corresponding enrichment cultures. The detailed methodology, results and discussion pertaining to the comparison of the environmental samples collected \u003cem\u003ein situ\u003c/em\u003e are presented in Supplementary File S1. In this section, we highlight the recruitment of potential chitin degraders and utilizers from the original communities, placing a focus on the coding potential of enriched bacterial genera so far not described to play fundamental roles in the degradation of chitin and its derivatives.\u003c/p\u003e \u003cp\u003e \u003cb\u003e4.1 Chitin-based artificial selection applied to prokaryotic communities from marine biotopes lead to distinct chitin degrading consortia\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThis study demonstrates that applying a strictly equal artificial selection procedure with chitin as sole organic carbon and nitrogen source to different prokaryotic communities from distinct marine biotopes (i.e., marine sponge, octocoral, sediment, and seawater) leads to different chitin degrading consortia (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eA \u0026amp; \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). Moreover, artificial selection was found, in this study, to increase the natural variation among replicate communities observed in the environment. This can be explained by the likely combination of two factors: (1) the fact that natural differences in microbiome assembly (i.e., relative abundance distributions of original community members) might have dictated differential enrichment trajectories in each independent artificial selection experiment, and (2) that such natural variations might have been influenced or augmented by the sampling processing procedures employed (e.g., transportation, handling, conservation of the communities in glycerol), which may have induced biases to the original community composition of replicate samples from the same biotope. This picture aligns with the concept of priority effects on microbiome assembly [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], whereby the final structure of a given community may rely on the order/timing of arrival of their founding members, which may be considerably influenced by stochastic events yet simultaneously dictate the successional changes underlying the assembly process. Priority effects have been evoked to explain sample-to-sample variability in algal [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] and fish larvae microbiomes [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] and are considered a relevant phenomenon in the assembly of host-associated and free-living microbial communities across marine, freshwater and terrestrial ecosystems [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. These outcomes revealed that each experiment was unique to some extent, even though deterministic factors simultaneously shaped the assembly of the enrichment cultures based on their source biotope. It is also reasonable to argue that the source of chitin (in our case, chitin powder from shrimp cells) used in artificial selection experiments likely influences the selected consortium and its degradation efficiency, and needs to be carefully considered during experimental design. To reduce variability among replicate enrichments from the same biotope, future studies may attempt pooling several subsamples (e.g., multiple excisions from the same sponge or coral specimen) to form a composite, representative sample of each replicate. Altogether, our data suggest that applying artificial selection to a range of distinct marine biotopes can increase the discoverability of novel chitin-degrading taxa and consortia, leading to the potential characterization of novel enzymes of marine origin involved in the chitin degradation process. It remains a challenging task to obtain highly resolving estimates of chitin degradation by artificially selected consortia, yet the design of such experiments allows tapping into the chitin degradation capacity of taxa previously unknown to play these roles, which can be further studied by means of both phenotyping and genotyping.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Artificial selection recruits low-abundance chitin degraders and utilizers\u003c/h2\u003e \u003cp\u003eThe artificial selection procedure employed in this study promotes low-abundance chitin degraders and utilizers within each biotope. Indeed, it was a consistent pattern that dominant taxa in the enrichment cultures were poorly represented or even absent in their corresponding environmental samples (see Table S6 for details). This shows that the culturable bacteria from the marine sponge, octocoral, seawater, and sediment biotopes used in this study likely belong to the microbial rare biosphere within their natural environment. Microbial cultivation bias is a well-known phenomenon previously shown by several studies of free-living [\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] and host-associated bacterial communities [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. The high diversity of low abundance taxa present in natural microbial communities represents a vast collection of genetic features that contribute to a broad range of both established and potentially undiscovered microbial functions [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]. It is also well established that low abundance, \u0026ldquo;rare\u0026rdquo; taxa can grow abundant under certain culture conditions [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] and degrade different pollutants, aromatic hydrocarbons [\u003cspan additionalcitationids=\"CR55\" citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], as well as complex polymers such as chitin as observed in this study. Enrichment of low abundance, chitin degrading microorganisms might as well occur in the natural environment under certain circumstances. Indeed, it has been recently shown that species in the known chitin degrading genus \u003cem\u003eAquimarina\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] usually belong to the rare biosphere of distinct marine biotopes [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] and may increase in abundance under certain conditions (e.g., in necrotic octocoral tissue [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] and on the carapace of injured lobsters [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]).\u003c/p\u003e \u003cp\u003eHardoim and colleagues suggested that the culturable fraction of bacterial symbionts of the marine sponges \u003cem\u003eSarcotragus spinosulus\u003c/em\u003e and \u003cem\u003eIrcinia variabilis\u003c/em\u003e consisted primarily of low abundance species [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Conversely, dominant symbionts belonging to the \u003cem\u003eRhodothermales\u003c/em\u003e order and the \u003cem\u003eEndozoicomonas\u003c/em\u003e genus were recently suggested, through genome-resolved metagenomics studies, to play a key role in chitin degradation in marine sponges [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and octocorals [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], respectively. However, although these taxa were abundant in the here examined \u003cem\u003eS. spinosulus\u003c/em\u003e (\u003cem\u003eRhodothermaceae\u003c/em\u003e ASV90; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and \u003cem\u003eE. labiata\u003c/em\u003e (\u003cem\u003eEndozoicomonas\u003c/em\u003e ASV23; Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) specimens, respectively, they escaped enrichment via artificial selection as attempted in this study. This is likely due to the sampling, transportation and cultivation procedures employed (including the retrieval of microbial cell homogenates from the samples, their conservation, the culture medium, and incubation conditions). Therefore, techniques to domesticate these symbionts in culture need to be implemented to harness their metabolism. These alternative techniques include varying culture conditions (adjusting pH, temperature, and physical-chemical conditions), modifying the composition of the medium (for instance, by incorporating host chemical cues), or adopting gentler sampling processing methods. Another future step could be to express the chitin-degrading enzymes of these symbionts, such as chitinases, without the need for cultivation. This can be achieved through targeted gene cloning and expression for chitinase genes [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e, \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] or directly by chitinase gene synthesis based on their metagenomic sequences and subsequent cloning and expression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Cross-feeding may promote co-existence of chitin degraders and utilizers in enrichment cultures\u003c/h2\u003e \u003cp\u003eIn the enrichment cultures derived from octocorals and marine sponges, chitin degradation was classified as moderate according to chitin weight loss and Mn\u003csub\u003e1\u003c/sub\u003e estimates, while bacterial activity (low to high) was recorded in these cultures. Moreover, many well-known chitin degraders were enriched in these cultures from their corresponding natural biotopes, such as \u003cem\u003eVibrio\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], \u003cem\u003eShewanella\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e], \u003cem\u003ePseudoalteromonas\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e], \u003cem\u003ePseudomonas\u003c/em\u003e [\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e], \u003cem\u003eAquimarina\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], \u003cem\u003eAlteromonas\u003c/em\u003e [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e], and \u003cem\u003eEnterovibrio\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Our results suggest that in the conditions of our experiments the degradation dynamics occurring in the enrichment cultures from the marine sponge and the octocoral biotopes could not be thoroughly captured by the techniques we used to assess chitin hydrolysis (chitin weight loss or SEC). It might also be that these taxa grew using smaller soluble oligomers originally present in the chitin powder whose degradation dynamics and shifts in molecular weight are rather challenging to monitor and interpret. In this study, we observed four bacterial consortia from sediment and seawater samples which were classified as \u0026ldquo;highly efficient\u0026rdquo; (SD1, SD3 and SW3) and \u0026ldquo;good\u0026rdquo; (SD2), at degrading chitin. Among these four selected communities, some of the enriched taxa were already known to be chitin degraders such as \u003cem\u003eVibrio\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e], \u003cem\u003eAlteromonas\u003c/em\u003e [\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e] and \u003cem\u003ePseudoalteromonas\u003c/em\u003e [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]. Some others are known to be chitin utilizers such as representatives of the \u003cem\u003eRhodobacteraceae\u003c/em\u003e (\u003cem\u003eAlphaproteobacteria\u003c/em\u003e) family [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and of the genus \u003cem\u003ePseudovibrio\u003c/em\u003e in the \u003cem\u003eStappiaceae\u003c/em\u003e family [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This suggests the co-existence of chitin degraders and utilizers through hypothesized cross-feeding mechanisms. Indeed, chitin degraders might make excess chitin degradation products available (COSs, chitosan, GlcNAc) which are used by other chitinolytic bacteria (i.e., chitin utilizers). This process, although difficult to demonstrate experimentally, was already suggested in previous studies [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan additionalcitationids=\"CR70\" citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. Moreover, to the best of our knowledge, many other taxa enriched in cultures classified as possessing \u0026ldquo;moderate\u0026rdquo; (all host-associated cultures), \u0026ldquo;good\u0026rdquo; or \u0026ldquo;high\u0026rdquo; chitin degradation efficiencies are so far unknown or understudied for their role as chitin degraders and/or utilizers. This includes genera such as \u003cem\u003eAmphritea\u003c/em\u003e, \u003cem\u003eAureivirga\u003c/em\u003e, \u003cem\u003eEpibacterium\u003c/em\u003e, \u003cem\u003eFusibacter\u003c/em\u003e, \u003cem\u003eHalarcobacter, Halodesulfovibrio, Marinobacterium\u003c/em\u003e, \u003cem\u003eMotilimonas\u003c/em\u003e, \u003cem\u003eMuricauda\u003c/em\u003e, \u003cem\u003ePoseidonibacter\u003c/em\u003e, \u003cem\u003eProfundimonas, Pseudophaeobacter\u003c/em\u003e, \u003cem\u003ePsychrobium\u003c/em\u003e, \u003cem\u003ePsychromonas\u003c/em\u003e, \u003cem\u003eReichenbachiella\u003c/em\u003e, and \u003cem\u003eThalassotalea\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Table S6). Using dedicated functional annotation of dozens of genomes available for ten representative genera (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e and S7), we suggest that \u003cem\u003eMotilimonas, Reichenbachiella, Halodesulfovibrio, Aureivirga\u003c/em\u003e and \u003cem\u003ePsychromonas\u003c/em\u003e are potential chitin degraders by means of hydrolysis (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e1\u003c/span\u003e and S7). \u003cem\u003eEpibacterium\u003c/em\u003e may have a role in chitin utilization/COSs degradation via hydrolysis. \u003cem\u003ePseudophaeobacter\u003c/em\u003e and \u003cem\u003ePoseidonibacter\u003c/em\u003e may have a role in chitin degradation via deacetylation and in GlcNAc consumption. Moreover, all genera examined, except \u003cem\u003eAureivirga\u003c/em\u003e, are classified as potential GlcNAc utilisers. Wright and colleagues [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] applied an artificial selection process on microbial communities from bulk marine debris (Devon, UK) using varying incubation times (e.g., 9 days and 4 days) over several transfers, observing a few enriched taxa in common with our study. These include well-known chitin degraders such as \u003cem\u003eVibrio\u003c/em\u003e, \u003cem\u003eAlteromonas\u003c/em\u003e and \u003cem\u003ePseudoalteromonas\u003c/em\u003e and other taxa less known for their role in chitin degradation such as \u003cem\u003eMuricauda\u003c/em\u003e and \u003cem\u003eThalassotalea\u003c/em\u003e. Genomes available for these two taxa were found, in our study, to possess endochitinase genes which is suggestive of a potential role for these organisms as chitin degraders by means of hydrolysis in multiple biotopes. These trends suggest that performing the artificial selection procedure on several marine biotopes, as it was done in this study, increases the chance of obtaining different taxa involved in chitin degradation. Moreover, Wright et al. (2019) suggested that successive transfers over short time periods (e.g., 4 days) favours the selection of chitin-degrading bacteria in the \u003cem\u003eGammaproteobacteria\u003c/em\u003e class while reducing the abundance of chitin utilizers / \u0026ldquo;grazers\u0026rdquo; of COSs, such as representative members of the \u003cem\u003eAlphaproteobacteria\u003c/em\u003e class. The seven-day incubation period employed in our study led to the promotion of relatively stable communities most likely composed by a mix of chitin degraders and utilizers over the course of the experiment (29 days from the pre-culture to culture C3). Taken together, our results suggest that a versatile and functionally convergent coding potential for chitin metabolism, involving the breakdown of chitin and COSs via endo and exochitinase-mediated hydrolysis, deacetylation into chitosan, and N-acetylglucosamine utilization features, was assembled in enrichment cultures via artificial selection from multiple marine biotopes. This indicates that cross-feeding among artificially-selected bacteria can act as a possible mechanism underlying the diversity of chitin degraders and utilizers in the enrichment cultures, as observed experimentally for combinations of specific, marine bacterial isolates [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEnrichment cultures from sediments were regarded and \u0026ldquo;good\u0026rdquo; or \u0026ldquo;efficient\u0026rdquo; chitin degraders, while those derived from host-associated (sponges and octocorals) communities classified as \u0026ldquo;moderate\u0026rdquo; and seawater-derived cultures varying considerably from \u0026ldquo;low\u0026rdquo; to \u0026ldquo;efficient\u0026rdquo;, with the taxonomic composition within the enrichment cultures being influenced by the source biotope, in spite of observed sample-to-sample variability.\u003c/p\u003e \u003c/div\u003e"},{"header":"5 Conclusion","content":"\u003cp\u003eIn this study, distinct bacterial consortia efficient at degrading chitin composed by known chitin degraders, known chitin utilizers and many taxa not yet known or only poorly studied for their role(s) in chitin degradation were selected from several marine biotopes. The latter taxa (e.g., \u003cem\u003eMotilimonas\u003c/em\u003e, \u003cem\u003eMuricauda\u003c/em\u003e, \u003cem\u003eHalodesulfovibrio\u003c/em\u003e, \u003cem\u003ePsychromonas\u003c/em\u003e, \u003cem\u003eReichenbachiella\u003c/em\u003e, among others) are potential key players in marine chitin degradation revealed in this study by means of artificial selection. Building upon these enriched prokaryotic communities, future investigation can employ both top-down and bottom-up approaches. Top-down methods may involve isolating strains from the communities, studying the chitin degradation abilities of these isolated strains through commercially available chitinase assays and/or chitin degradation activity screenings on colloidal chitin agar plates, and reconstructing even simpler communities. In addition, bottom-up techniques may include diluting the communities to specifically select the most active chitin degraders and utilizers. These combined approaches hold potential to find optimal blends of bacteria successful at degrading chitin. Recently, DNA-Stable Isotope Probing (DNA-SIP) has been implemented to monitor the incorporation of \u003csup\u003e13\u003c/sup\u003eC labelled chitin by natural microbial communities [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Such an approach holds promise in unveiling chitin degraders, utilizers and scavengers (those not directly acting on chitin or COSs but feeding on metabolic by-products of chitin degraders and utilizers \u0026ndash; see e.g., [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]) in future artificial selection experiments, possibly strengthening cross-feeding hypotheses often raised to explain the co-existence of chitin-transforming microorganisms in natural and artificial settings.\u003c/p\u003e \u003cp\u003eAs an outlook, efforts are being made in our laboratory to i) isolate the prevailing taxa enriched from the different enriched cultures, ii) test for their ability to degrade chitin and iii) sequence their genomes and search for genes involved in chitin degradation to more specifically determine their chitin degradation and/or utilization capacities. In parallel, metagenomic sequencing of the chitin-degrading consortia is also being performed by our team to investigate the role(s) of each taxon in the consortia and to discover novel chitinolytic enzymes from the marine environment.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by a PhD grant to L. Meunier from the Fonds de la recherche dans l’Industrie et l’Agriculture (FRIA) at the Fonds de la Recherche Scientifique (FRS-FNRS). This work was also supported by the Portuguese Foundation for Science and Technology (FCT), through the research project EXPL/BIA-MIC/0286/2021 and projects UIDB/04565/2020 and UIDP/04565/2020 of iBB and LA/P/0140/2020 of i4HB. TKC is the recipient of an investigator contract (CEECIND/00788/2017) conceded by the FCT.\u0026nbsp;\u003cem\u003eMM acknowledges a doctoral grant (SFRH/BD/151376/2021) from the MIT Portugal program, financed through FCT.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eWe are grateful to Adela Belackova and the 'Fisheries, Biodiversity and Conservation' team from the Center of Marine Sciences (CCMAR), University of Algarve, for their precious help during sampling.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe amplicon data (Table S8) are available in the Sequence Read Archives (SRA) under the project accession number PRJNA999598, sample accession numbers SAMN36737297 to SAMN36737311, SAMN36737334 to SAMN36737348, SAMN36743901 to SAMN367433915 and SAMN36744262 to SAMN36744262 to SAMN36744276; run accession numbers from SRR25451171 to SRR25451185, SRR25451141 to SRR25451155, SRR25451652 to SRR25451666 and SRR25451336 to SRR25451350.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLM: conceptualization, investigation, visualization, formal analysis, methodology, writing-original draft. IG: conceptualization, resources, funding, supervision, writing-review\u0026amp;editing. RC: Conceptualization, resources, funding, supervision, writing-original draft, writing-review\u0026amp;editing. TKC: conceptualization, funding, supervision, investigation, writing-review\u0026amp;editing. DC: resources, supervision, writing-review\u0026amp;editing. JG: resources, investigation. ED: writing-review\u0026amp;editing. MM: investigation.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGooday GW. The Ecology of Chitin Degradation. In: Marshall KC, editor. Advances in Microbial Ecology. Boston, MA: Springer US; 1990. pp. 387\u0026ndash;430.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnston J. Conditions of life in the sea: a short account of quantitative marine biological research. University; 1908.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSouza CP, Almeida BC, Colwell RR, Rivera ING. 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Soil Biol Biochem. 2022;173:108786.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"prokaryotic communities, enrichment cultures, chitinase, marine sponge, octocoral, size exclusion chromatography","lastPublishedDoi":"10.21203/rs.3.rs-3456333/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3456333/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBiological chitin degradation is a major process in the ocean, governed primarily by the action of microorganisms. It is now known that the structure and taxonomic profile of chitin-degrading microbial communities change across marine biotopes, but efforts to harness the chitin turnover potential within these communities in the laboratory have seldom been attempted. In this study, we characterized the prokaryotic communities associated with the marine sponge \u003cem\u003eSarcotragus spinosulus\u003c/em\u003e, the octocoral \u003cem\u003eEunicella labiata\u003c/em\u003e, and their surrounding sediment and seawater and applied an artificial selection procedure to enrich bacterial consortia capable of degrading chitin from the abovementioned biotopes. Throughout the procedure, chitin degradation was monitored, and the taxonomic composition of four successive enrichment cultures from each biotope were followed.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe naturally occurring prokaryotic communities of the two host species were distinct from each other with specific taxa associated with each animal even though they were co-inhabiting the same geographic area. We found that members of the microbial rare biosphere were recruited in the enrichment cultures from all biotopes, while dominant bacterial symbionts likely to play a role in chitin degradation within marine sponges and octocorals remained \u0026ldquo;unculturable\u0026rdquo; under the conditions used in this study. Well-known chitin degraders such as \u003cem\u003eVibrio\u003c/em\u003e, \u003cem\u003ePseudoalteromonas\u003c/em\u003e and \u003cem\u003eAquimarina\u003c/em\u003e, as well as other taxa not known or yet poorly known for their role(s) in chitin degradation such as \u003cem\u003eAureivirga\u003c/em\u003e, \u003cem\u003eHalodesulfovibrio\u003c/em\u003e, \u003cem\u003eMotilimonas\u003c/em\u003e, \u003cem\u003eMuricauda\u003c/em\u003e, \u003cem\u003ePsychromonas\u003c/em\u003e, \u003cem\u003ePoseidonibacter\u003c/em\u003e, \u003cem\u003eReichenbachiella\u003c/em\u003e, and \u003cem\u003eThalassotalea\u003c/em\u003e, among others, were enriched using our artificial selection approach. Distinct chitin-degrading consortia were enriched from each marine biotope, highlighting the feasibility of this approach in fostering the discovery of novel microorganisms and enzymes involved in chitin degradation pathways of relevance in applied biotechnology.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this study, distinct bacterial consortia possessing moderate to high efficiencies at degrading chitin were unveiled. They were composed of a mix of known chitin degraders, known chitin utilizers and many taxa poorly or not yet known for their role(s) in chitin degradation such as \u003cem\u003eAureivirga\u003c/em\u003e, \u003cem\u003ePsychromonas, Motilimonas, Reichenbachiella, or Halodesulfovibrio\u003c/em\u003e. The latter taxa are potential key players in marine chitin degradation whose study could lead to the discovery of novel enzyme variants able to degrade chitin and its derivatives.\u003c/p\u003e","manuscriptTitle":"An artificial selection procedure enriches for known and suspected chitin degraders from the prokaryotic rare biosphere of multiple marine biotopes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-19 06:33:56","doi":"10.21203/rs.3.rs-3456333/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-02-07T18:58:52+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-20T16:17:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"185374153199239026110328378088158448395","date":"2024-11-13T15:39:23+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-09-18T15:43:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-08T12:59:33+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Microbiology","date":"2024-08-05T14:15:39+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-microbiology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mcro","sideBox":"Learn more about [BMC Microbiology](http://bmcmicrobiol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mcro","title":"BMC Microbiology","twitterHandle":"#bmcmicrobiology","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"358b892b-eb7c-4554-b515-31fc1b993605","owner":[],"postedDate":"February 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-01T15:59:01+00:00","versionOfRecord":{"articleIdentity":"rs-3456333","link":"https://doi.org/10.1186/s12866-025-04218-7","journal":{"identity":"bmc-microbiology","isVorOnly":false,"title":"BMC Microbiology"},"publishedOn":"2025-11-25 15:56:51","publishedOnDateReadable":"November 25th, 2025"},"versionCreatedAt":"2025-02-19 06:33:56","video":"","vorDoi":"10.1186/s12866-025-04218-7","vorDoiUrl":"https://doi.org/10.1186/s12866-025-04218-7","workflowStages":[]},"version":"v1","identity":"rs-3456333","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3456333","identity":"rs-3456333","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}